class CciSignal(CtaSignal):
"""CCI信号"""
# ----------------------------------------------------------------------
def __init__(self):
"""Constructor"""
super(CciSignal, self).__init__()
self.cciWindow = 10
self.cciLevel = 20
self.cciLong = self.cciLevel
self.cciShort = -self.cciLevel
self.cciValue = 0.0
self.bg = BarGenerator(self.onBar, 15, self.on15Bar)
self.am = ArrayManager()
# ----------------------------------------------------------------------
def onTick(self, tick):
"""Tick更新"""
self.bg.updateTick(tick)
# ----------------------------------------------------------------------
def onBar(self, bar):
"""K线更新"""
self.bg.updateBar(bar)
def on15Bar(self, bar):
self.am.updateBar(bar)
print bar.datetime
print "@cciSignal"
print "cci inited: ", self.am.inited
if not self.am.inited:
self.setSignalPos(0)
return
self.cciValue = self.am.cci(self.cciWindow)
print "cciValue: ", self.cciValue
if self.cciValue >= self.cciLong:
self.setSignalPos(1)
elif self.cciValue <= self.cciShort:
self.setSignalPos(-1)
else:
self.setSignalPos(0)
class AtrSignal(CtaSignal):
"""Atr信号"""
# ----------------------------------------------------------------------
def __init__(self):
"""Constructor"""
super(AtrSignal, self).__init__()
self.atrWindow = 30
self.bg = BarGenerator(self.onBar, 15, self.on15Bar)
self.am = ArrayManager()
self.atrValue = 0.0
# ----------------------------------------------------------------------
def onTick(self, tick):
"""Tick更新"""
self.bg.updateTick(tick)
# ----------------------------------------------------------------------
def onBar(self, bar):
"""K线更新"""
self.bg.updateBar(bar)
# ----------------------------------------------------------------------
def on15Bar(self, bar):
"""15分钟K线更新"""
self.am.updateBar(bar)
print bar.datetime
print "@atrSignal"
print "atr inited: ", self.am.inited
if not self.am.inited:
self.setSignalPos(0)
return
atrArray = self.am.atr(self.atrWindow, array=True)
self.atrValue = atrArray[-1]
atrMa = atrArray[-self.atrWindow:].mean()
print "atrValue: ", self.atrValue
# 趋势增强
if self.atrValue > atrMa:
self.setSignalPos(1)
else:
self.setSignalPos(0)
class MaSignal(CtaSignal):
"""双均线信号"""
# ----------------------------------------------------------------------
def __init__(self):
"""Constructor"""
super(MaSignal, self).__init__()
self.fastWindow = 5
self.slowWindow = 20
self.bg = BarGenerator(self.onBar, 5, self.onFiveBar)
self.am = ArrayManager()
# ----------------------------------------------------------------------
def onTick(self, tick):
"""Tick更新"""
self.bg.updateTick(tick)
# ----------------------------------------------------------------------
def onBar(self, bar):
"""K线更新"""
self.bg.updateBar(bar)
# ----------------------------------------------------------------------
def onFiveBar(self, bar):
"""5分钟K线更新"""
self.am.updateBar(bar)
if not self.am.inited:
self.setSignalPos(0)
fastMa = self.am.sma(self.fastWindow)
slowMa = self.am.sma(self.slowWindow)
if fastMa > slowMa:
self.setSignalPos(1)
elif fastMa < slowMa:
self.setSignalPos(-1)
else:
self.setSignalPos(0)
class MaSignal(CtaSignal):
"""双均线信号"""
#----------------------------------------------------------------------
def __init__(self):
"""Constructor"""
super(MaSignal, self).__init__()
self.fastWindow = 5
self.slowWindow = 20
self.bg = BarGenerator(self.onBar, 5, self.onFiveBar)
self.am = ArrayManager()
#----------------------------------------------------------------------
def onTick(self, tick):
"""Tick更新"""
self.bg.updateTick(tick)
#----------------------------------------------------------------------
def onBar(self, bar):
"""K线更新"""
self.bg.updateBar(bar)
#----------------------------------------------------------------------
def onFiveBar(self, bar):
"""5分钟K线更新"""
self.am.updateBar(bar)
if not self.am.inited:
self.setSignalPos(0)
fastMa = self.am.sma(self.fastWindow)
slowMa = self.am.sma(self.slowWindow)
if fastMa > slowMa:
self.setSignalPos(1)
elif fastMa < slowMa:
self.setSignalPos(-1)
else:
self.setSignalPos(0)
class BollSignal(CtaSignal):
"""布林带信号"""
# ----------------------------------------------------------------------
def __init__(self):
"""Constructor"""
super(BollSignal, self).__init__()
self.bollWindow = 18
self.bollDev = 5
# self.bollUp, self.bollDown = 0.0,0.0
self.bg = BarGenerator(self.onBar, 15, self.on15Bar)
self.am = ArrayManager()
# ----------------------------------------------------------------------
def onTick(self, tick):
"""Tick更新"""
self.bg.updateTick(tick)
# ----------------------------------------------------------------------
def onBar(self, bar):
"""K线更新"""
self.bg.updateBar(bar)
# ----------------------------------------------------------------------
def on15Bar(self, bar):
"""15分钟K线更新"""
self.am.updateBar(bar)
if not self.am.inited:
self.setSignalPos(0)
bollUp, bollDown = self.am.boll(self.bollWindow, self.bollDev)
if bar.close >= bollUp:
self.setSignalPos(1)
elif bar.close <= bollDown:
self.setSignalPos(-1)
else:
self.setSignalPos(0)
class CciSignal(CtaSignal):
"""CCI信号"""
#----------------------------------------------------------------------
def __init__(self):
"""Constructor"""
super(CciSignal, self).__init__()
self.cciWindow = 30
self.cciLevel = 10
self.cciLong = self.cciLevel
self.cciShort = -self.cciLevel
self.bg = BarGenerator(self.onBar)
self.am = ArrayManager()
#----------------------------------------------------------------------
def onTick(self, tick):
"""Tick更新"""
self.bg.updateTick(tick)
#----------------------------------------------------------------------
def onBar(self, bar):
"""K线更新"""
self.am.updateBar(bar)
if not self.am.inited:
self.setSignalPos(0)
cciValue = self.am.cci(self.cciWindow)
if cciValue >= self.cciLong:
self.setSignalPos(1)
elif cciValue <= self.cciShort:
self.setSignalPos(-1)
else:
self.setSignalPos(0)
class CciSignal(CtaSignal):
"""CCI信号"""
#----------------------------------------------------------------------
def __init__(self):
"""Constructor"""
super(CciSignal, self).__init__()
self.cciWindow = 30
self.cciLevel = 10
self.cciLong = self.cciLevel
self.cciShort = -self.cciLevel
self.bg = BarGenerator(self.onBar)
self.am = ArrayManager()
#----------------------------------------------------------------------
def onTick(self, tick):
"""Tick更新"""
self.bg.updateTick(tick)
#----------------------------------------------------------------------
def onBar(self, bar):
"""K线更新"""
self.am.updateBar(bar)
if not self.am.inited:
self.setSignalPos(0)
cciValue = self.am.cci(self.cciWindow)
if cciValue >= self.cciLong:
self.setSignalPos(1)
elif cciValue<= self.cciShort:
self.setSignalPos(-1)
else:
self.setSignalPos(0)
class RsiSignal(CtaSignal):
"""RSI信号"""
#----------------------------------------------------------------------
def __init__(self):
"""Constructor"""
super(RsiSignal, self).__init__()
self.rsiWindow = 14
self.rsiLevel = 20
self.rsiLong = 50 + self.rsiLevel
self.rsiShort = 50 - self.rsiLevel
self.bg = BarGenerator(self.onBar)
self.am = ArrayManager()
#----------------------------------------------------------------------
def onTick(self, tick):
"""Tick更新"""
self.bg.updateTick(tick)
#----------------------------------------------------------------------
def onBar(self, bar):
"""K线更新"""
self.am.updateBar(bar)
if not self.am.inited:
self.setSignalPos(0)
rsiValue = self.am.rsi(self.rsiWindow)
if rsiValue >= self.rsiLong:
self.setSignalPos(1)
elif rsiValue <= self.rsiShort:
self.setSignalPos(-1)
else:
self.setSignalPos(0)
class RsiSignal(CtaSignal):
"""RSI信号"""
# ----------------------------------------------------------------------
def __init__(self):
"""Constructor"""
super(RsiSignal, self).__init__()
self.rsiWindow = 14
self.rsiLevel = 20
self.rsiLong = 50 + self.rsiLevel
self.rsiShort = 50 - self.rsiLevel
self.bg = BarGenerator(self.onBar)
self.am = ArrayManager()
# ----------------------------------------------------------------------
def onTick(self, tick):
"""Tick更新"""
self.bg.updateTick(tick)
# ----------------------------------------------------------------------
def onBar(self, bar):
"""K线更新"""
self.am.updateBar(bar)
if not self.am.inited:
self.setSignalPos(0)
self.rsiValue = self.am.rsi(self.rsiWindow)
if self.rsiValue >= self.rsiLong:
self.setSignalPos(1)
elif self.rsiValue <= self.rsiShort:
self.setSignalPos(-1)
else:
self.setSignalPos(0)
class DualThrust_IntraDayStrategy(CtaTemplate):
"""DualThrust交易策略"""
className = 'DualThrust_IntraDayStrategy'
author = u'Leon Zhao'
# 策略参数
fixedSize = 2
k1 = 0.4
k2 = 0.4
initDays = 10 # original value is 10
rangeDays = 4
# 策略变量
barList = [] # K线对象的列表
dayOpen = 0
rangeHigh = 0
rangeLow = 0
rangeHighClose = 0
rangeLowClose = 0
range1 = 0
range2 = 0
range = 0
longEntry = 0
shortEntry = 0
exitTime = time(hour=15,
minute=20) #will not cover position when day close
longEntered = False
shortEntered = False
# 参数列表，保存了参数的名称
paramList = ['name', 'className', 'author', 'vtSymbol', 'k1', 'k2']
# 变量列表，保存了变量的名称
varList = [
'inited', 'trading', 'pos', 'range', 'longEntry', 'shortEntry',
'exitTime'
]
# 同步列表，保存了需要保存到数据库的变量名称
syncList = ['pos']
#----------------------------------------------------------------------
def __init__(self, ctaEngine, setting):
"""Constructor"""
super(DualThrust_IntraDayStrategy, self).__init__(ctaEngine, setting)
self.bg = BarGenerator(self.onBar, onDayBar=self.ondayBar)
self.am = ArrayManager()
self.barList = []
#----------------------------------------------------------------------
def onInit(self):
"""初始化策略（必须由用户继承实现）"""
self.writeCtaLog(u'%s策略初始化' % self.name)
# 载入历史数据，并采用回放计算的方式初始化策略数值
initData = self.loadBar(self.initDays)
for bar in initData:
self.onBar(bar)
self.putEvent()
#----------------------------------------------------------------------
def onStart(self):
"""启动策略（必须由用户继承实现）"""
self.writeCtaLog(u'%s策略启动' % self.name)
self.putEvent()
#----------------------------------------------------------------------
def onStop(self):
"""停止策略（必须由用户继承实现）"""
self.writeCtaLog(u'%s策略停止' % self.name)
self.putEvent()
#----------------------------------------------------------------------
def onTick(self, tick):
"""收到行情TICK推送（必须由用户继承实现）"""
self.bg.updateTick(tick)
#---------calcuate range for the last several days
def calcRange(self):
if self.am.count >= self.rangeDays:
self.rangeHigh = talib.MAX(self.am.high, self.rangeDays)[-1]
self.rangeLow = talib.MIN(self.am.low, self.rangeDays)[-1]
self.rangeHighClose = talib.MAX(self.am.close, self.rangeDays)[-1]
self.rangeLowClose = talib.MIN(self.am.close, self.rangeDays)[-1]
self.range1 = self.rangeHigh - self.rangeLowClose
self.range2 = self.rangeHighClose - self.rangeLow
if (self.range1 > self.range2):
calcRange = self.range1
else:
calcRange = self.range2
else:
calcRange = 0
return calcRange
#----------------------------------------------------------------------
def onBar(self, bar):
"""收到Bar推送（必须由用户继承实现）"""
# 撤销之前发出的尚未成交的委托（包括限价单和停止单）
self.cancelAll()
self.bg.updateBar(bar)
if self.am.count < self.rangeDays:
return
# 计算指标数值
self.barList.append(bar)
if len(self.barList) <= 2:
return
else:
self.barList.pop(0)
lastBar = self.barList[-2]
# 新的一天
#for commodity trade at night 9 also need because some day night is canncel due to holiday
if (lastBar.datetime.hour == 15 or
(lastBar.datetime.hour == 14 and lastBar.datetime.minute
== 59)) and ((bar.datetime.hour == 21 or bar.datetime.hour == 9)):
#for commodity not trade at night:
#if (lastBar.datetime.hour == 15 or lastBar.datetime.hour==14 and lastBar.datetime.minute==59) and ((bar.datetime.hour == 9) ):
# 如果已经初始化
self.range = self.calcRange()
self.dayOpen = bar.open
if self.range:
self.longEntry = bar.open + self.k1 * self.range
self.shortEntry = bar.open - self.k2 * self.range
#self.longEntered = False
#self.shortEntered = False
else:
pass
# 尚未到收盘
if not self.range:
self.range = self.calcRange()
self.dayOpen = bar.open
if self.range:
self.longEntry = bar.open + self.k1 * self.range
self.shortEntry = bar.open - self.k2 * self.range
if True: # Trade Time, no matter when, just send signal
if self.pos == 0:
self.longEntered = False
self.shortEntered = False
if bar.close > self.longEntry:
#if not self.longEntered:
#self.buy(self.longEntry + 2, self.fixedSize)
self.buy(bar.close + 2, self.fixedSize)
elif bar.close < self.shortEntry:
#if not self.shortEntered:
#self.short(self.shortEntry - 2, self.fixedSize)
self.short(bar.close - 2, self.fixedSize)
else:
pass
# 持有多头仓位
elif self.pos > 0:
self.longEntered = True
self.shortEntered = False
# 多头止损单
if bar.close < self.shortEntry:
#self.sell(self.shortEntry -2 , self.fixedSize)
self.sell(bar.close - 2, self.fixedSize)
# 空头开仓单
if not self.shortEntered:
#self.short(self.shortEntry -2 , self.fixedSize)
self.short(bar.close - 2, self.fixedSize)
# 持有空头仓位
elif self.pos < 0:
self.shortEntered = True
self.longEntered = False
# 空头止损单
if bar.close > self.longEntry:
#self.cover(self.longEntry + 2, self.fixedSize)
self.cover(bar.close + 2, self.fixedSize)
# 多头开仓单
if not self.longEntered:
#self.buy(self.longEntry + 2, self.fixedSize)
self.buy(bar.close + 2, self.fixedSize)
# 收盘平仓 This will not execute
else:
if self.pos > 0:
self.sell(bar.close * 0.99, abs(self.pos))
elif self.pos < 0:
self.cover(bar.close * 1.01, abs(self.pos))
# 发出状态更新事件
self.putEvent()
#update day chart
def ondayBar(self, dayBar):
"""收到日线推送（必须由用户继承实现）"""
self.am.updateBar(dayBar)
# 发出状态更新事件
self.putEvent()
#----------------------------------------------------------------------
def onOrder(self, order):
"""收到委托变化推送（必须由用户继承实现）"""
pass
#----------------------------------------------------------------------
def onTrade(self, trade):
# 发出状态更新事件
self.putEvent()
#----------------------------------------------------------------------
def onStopOrder(self, so):
"""停止单推送"""
pass
class AtrRsiStrategy(CtaTemplate):
"""结合ATR和RSI指标的一个分钟线交易策略"""
className = 'AtrRsiStrategy'
author = u'用Python的交易员'
# 策略参数
atrLength = 22 # 计算ATR指标的窗口数
atrMaLength = 10 # 计算ATR均线的窗口数
rsiLength = 5 # 计算RSI的窗口数
rsiEntry = 16 # RSI的开仓信号
trailingPercent = 0.8 # 百分比移动止损
initDays = 10 # 初始化数据所用的天数
fixedSize = 1 # 每次交易的数量
# 策略变量
atrValue = 0 # 最新的ATR指标数值
atrMa = 0 # ATR移动平均的数值
rsiValue = 0 # RSI指标的数值
rsiBuy = 0 # RSI买开阈值
rsiSell = 0 # RSI卖开阈值
intraTradeHigh = 0 # 移动止损用的持仓期内最高价
intraTradeLow = 0 # 移动止损用的持仓期内最低价
# 参数列表，保存了参数的名称
paramList = [
'name', 'className', 'author', 'vtSymbol', 'atrLength', 'atrMaLength',
'rsiLength', 'rsiEntry', 'trailingPercent'
]
# 变量列表，保存了变量的名称
varList = [
'inited', 'trading', 'pos', 'atrValue', 'atrMa', 'rsiValue', 'rsiBuy',
'rsiSell'
]
# 同步列表，保存了需要保存到数据库的变量名称
syncList = ['pos', 'intraTradeHigh', 'intraTradeLow']
#----------------------------------------------------------------------
def __init__(self, ctaEngine, setting):
"""Constructor"""
super(AtrRsiStrategy, self).__init__(ctaEngine, setting)
# 创建K线合成器对象
self.bg = BarGenerator(self.onBar)
self.am = ArrayManager()
# 注意策略类中的可变对象属性（通常是list和dict等），在策略初始化时需要重新创建，
# 否则会出现多个策略实例之间数据共享的情况，有可能导致潜在的策略逻辑错误风险，
# 策略类中的这些可变对象属性可以选择不写，全都放在__init__下面，写主要是为了阅读
# 策略时方便（更多是个编程习惯的选择）
#----------------------------------------------------------------------
def onInit(self):
"""初始化策略（必须由用户继承实现）"""
self.writeCtaLog(u'%s策略初始化' % self.name)
# 初始化RSI入场阈值
self.rsiBuy = 50 + self.rsiEntry
self.rsiSell = 50 - self.rsiEntry
# 载入历史数据，并采用回放计算的方式初始化策略数值
initData = self.loadBar(self.initDays)
for bar in initData:
self.onBar(bar)
self.putEvent()
#----------------------------------------------------------------------
def onStart(self):
"""启动策略（必须由用户继承实现）"""
self.writeCtaLog(u'%s策略启动' % self.name)
self.putEvent()
#----------------------------------------------------------------------
def onStop(self):
"""停止策略（必须由用户继承实现）"""
self.writeCtaLog(u'%s策略停止' % self.name)
self.putEvent()
#----------------------------------------------------------------------
def onTick(self, tick):
"""收到行情TICK推送（必须由用户继承实现）"""
self.bg.updateTick(tick)
#----------------------------------------------------------------------
def onBar(self, bar):
"""收到Bar推送（必须由用户继承实现）"""
self.cancelAll()
# 保存K线数据
am = self.am
am.updateBar(bar)
if not am.inited:
return
# 计算指标数值
atrArray = am.atr(self.atrLength, array=True)
self.atrValue = atrArray[-1]
self.atrMa = atrArray[-self.atrMaLength:].mean()
self.rsiValue = am.rsi(self.rsiLength)
# 判断是否要进行交易
# 当前无仓位
if self.pos == 0:
self.intraTradeHigh = bar.high
self.intraTradeLow = bar.low
# ATR数值上穿其移动平均线，说明行情短期内波动加大
# 即处于趋势的概率较大，适合CTA开仓
if self.atrValue > self.atrMa:
# 使用RSI指标的趋势行情时，会在超买超卖区钝化特征，作为开仓信号
if self.rsiValue > self.rsiBuy:
# 这里为了保证成交，选择超价5个整指数点下单
self.buy(bar.close + 5, self.fixedSize)
elif self.rsiValue < self.rsiSell:
self.short(bar.close - 5, self.fixedSize)
# 持有多头仓位
elif self.pos > 0:
# 计算多头持有期内的最高价，以及重置最低价
self.intraTradeHigh = max(self.intraTradeHigh, bar.high)
self.intraTradeLow = bar.low
# 计算多头移动止损
longStop = self.intraTradeHigh * (1 - self.trailingPercent / 100)
# 发出本地止损委托
self.sell(longStop, abs(self.pos), stop=True)
# 持有空头仓位
elif self.pos < 0:
self.intraTradeLow = min(self.intraTradeLow, bar.low)
self.intraTradeHigh = bar.high
shortStop = self.intraTradeLow * (1 + self.trailingPercent / 100)
self.cover(shortStop, abs(self.pos), stop=True)
# 同步数据到数据库
self.saveSyncData()
# 发出状态更新事件
self.putEvent()
#----------------------------------------------------------------------
def onOrder(self, order):
"""收到委托变化推送（必须由用户继承实现）"""
pass
#----------------------------------------------------------------------
def onTrade(self, trade):
# 发出状态更新事件
self.putEvent()
#----------------------------------------------------------------------
def onStopOrder(self, so):
"""停止单推送"""
pass
class DualThrustStrategy(CtaTemplate):
"""DualThrust交易策略"""
className = 'DualThrustStrategy'
author = u'用Python的交易员'
# 策略参数
fixedSize = 1
k1 = 0.6
k2 = 0.4
initDays = 10
# 策略变量
barList = [] # K线对象的列表
dayOpen = 0
dayHigh = 0
dayLow = 0
dayClose = 0
lastdayOpen = 0
lastdayHigh = 0
lastdayLow = 0
lastdayClose = 0
initialized = False
range = 0
longEntry = 0
shortEntry = 0
exitTime = time(hour=14, minute=55)
longEntered = False
shortEntered = False
# 策略参数
fastWindow = 10 # 快速均线参数
slowWindow = 60 # 慢速均线参数
# 策略变量
fastMa0 = EMPTY_FLOAT # 当前最新的快速EMA
fastMa1 = EMPTY_FLOAT # 上一根的快速EMA
slowMa0 = EMPTY_FLOAT
slowMa1 = EMPTY_FLOAT
# 参数列表，保存了参数的名称
paramList = ['name', 'className', 'author', 'vtSymbol', 'k1', 'k2']
# 变量列表，保存了变量的名称
varList = [
'inited', 'trading', 'pos', 'range', 'longEntry', 'shortEntry',
'exitTime'
]
# 同步列表，保存了需要保存到数据库的变量名称
syncList = ['pos']
#----------------------------------------------------------------------
def __init__(self, ctaEngine, setting):
"""Constructor"""
super(DualThrustStrategy, self).__init__(ctaEngine, setting)
self.bg = BarGenerator(self.onBar)
self.barList = []
self.am = ArrayManager()
self.baselinetime = None
#----------------------------------------------------------------------
def onInit(self):
"""初始化策略（必须由用户继承实现）"""
self.writeCtaLog(u'%s策略初始化' % self.name)
# 载入历史数据，并采用回放计算的方式初始化策略数值
initData = self.loadBar(self.initDays)
for bar in initData:
self.onBar(bar)
self.putEvent()
#----------------------------------------------------------------------
def onStart(self):
"""启动策略（必须由用户继承实现）"""
self.writeCtaLog(u'%s策略启动' % self.name)
self.putEvent()
#----------------------------------------------------------------------
def onStop(self):
"""停止策略（必须由用户继承实现）"""
self.writeCtaLog(u'%s策略停止' % self.name)
self.putEvent()
#----------------------------------------------------------------------
def onTick(self, tick):
"""收到行情TICK推送（必须由用户继承实现）"""
self.bg.updateTick(tick)
#----------------------------------------------------------------------
def onBar(self, bar):
"""收到Bar推送（必须由用户继承实现）"""
# 撤销之前发出的尚未成交的委托（包括限价单和停止单）
self.cancelAll()
am = self.am
am.updateBar(bar)
#if not am.inited:
# return
# 计算快慢均线
fastMa = am.sma(self.fastWindow, array=True)
self.fastMa0 = fastMa[-1]
self.fastMa1 = fastMa[-2]
slowMa = am.sma(self.slowWindow, array=True)
self.slowMa0 = slowMa[-1]
self.slowMa1 = slowMa[-2]
# 计算指标数值
self.barList.append(bar)
if len(self.barList) <= 2:
return
else:
self.barList.pop(0)
lastBar = self.barList[-2]
if self.baselinetime == None:
self.baselinetime = datetime.now() - timedelta(hours=20)
print(self.baselinetime)
# 新的一天
if lastBar.datetime.date() != bar.datetime.date(
) or self.initialized == False:
#if (bar.datetime - self.baselinetime).seconds >= 23*60*60 or self.initialized == False:
#print("%d" % (bar.datetime - self.baselinetime).seconds)
self.baselinetime = bar.datetime
if self.initialized == False:
self.lastdayHigh = float(bar.open) * 1.06
self.lastdayLow = float(bar.open) * 0.94
self.lastdayOpen = float(bar.open)
self.lastdayClose = float(bar.open)
self.range = max(self.lastdayHigh - self.lastdayClose,
self.lastdayClose - self.lastdayLow)
#self.range = self.lastdayHigh - self.lastdayLow
self.longEntry = float(bar.open) + self.range
self.shortEntry = float(bar.open) - 0.002
else:
self.lastdayHigh = self.dayHigh
self.lastdayLow = self.dayLow
self.lastdayOpen = self.dayOpen
self.lastdayClose = self.dayClose
# 如果已经初始化
self.range = max(self.lastdayHigh - self.lastdayClose,
self.lastdayClose - self.lastdayLow)
#self.range = self.lastdayHigh - self.lastdayLow
self.longEntry = float(bar.open) + self.k1 * self.range
self.shortEntry = float(bar.open) - self.k2 * self.range
print(
"range %f, range percent %f, open %f, long entry %f, short entry %f"
% (self.range, self.range / bar.open, bar.open, self.longEntry,
self.shortEntry))
print("time %s" % bar.datetime)
#self.coverp = self.longEntry
#self.sellp = self.shortEntry
self.dayOpen = float(bar.open)
self.dayHigh = float(bar.high)
self.dayLow = float(bar.low)
self.dayClose = float(bar.close)
self.longEntered = False
self.shortEntered = False
self.initialized = True
else:
self.dayHigh = max(self.dayHigh, float(bar.high))
self.dayLow = min(self.dayLow, float(bar.low))
if 0:
self.longstoptmp = max(self.longEntry, bar.high)
self.shortstoptmp = min(self.shortEntry, bar.low)
self.coverp = self.longEntry - (self.shortEntry -
self.shortstoptmp)
self.sellp = self.shortEntry + (self.longstoptmp -
self.longEntry)
'''
if self.range < max(bar.high - bar.close, bar.lose - bar.low):
self.range = max(bar.high - bar.close, bar.lose - bar.low)
self.longEntry = float(bar.open) + self.k1 * self.range
self.shortEntry = float(bar.open) + self.k2 * self.range
'''
# 尚未到收盘
if not self.range:
return
if self.pos == 0:
if float(bar.close) > self.dayOpen:
#if not self.longEntered:
if not self.longEntered and self.slowMa0 < self.fastMa0:
self.buy(self.longEntry, self.fixedSize, stop=True)
else:
#if not self.shortEntered:
if not self.shortEntered and self.slowMa0 > self.fastMa0:
self.short(self.shortEntry, self.fixedSize, stop=True)
# 持有多头仓位
elif self.pos > 0:
self.longEntered = True
# 多头止损单
self.sell(self.shortEntry, self.fixedSize, stop=True)
#self.sell(self.sellp, self.fixedSize, stop=True)
#self.sell(self.longEntry*0.99, self.fixedSize, stop=True)
# 空头开仓单
#if 1:
#if not self.shortEntered:
if not self.shortEntered and self.slowMa0 > self.fastMa0:
self.short(self.shortEntry, self.fixedSize, stop=True)
# 持有空头仓位
elif self.pos < 0:
self.shortEntered = True
# 空头止损单
self.cover(self.longEntry, self.fixedSize, stop=True)
#self.cover(self.coverp, self.fixedSize, stop=True)
#self.cover(self.shortEntry*1.01, self.fixedSize, stop=True)
# 多头开仓单
#if 1:
#if not self.longEntered:
if not self.longEntered and self.slowMa0 < self.fastMa0:
self.buy(self.longEntry, self.fixedSize, stop=True)
'''
if bar.datetime.time() < self.exitTime:
pass
# 收盘平仓
else:
if self.pos > 0:
self.sell(float(bar.close) * 0.99, abs(self.pos))
elif self.pos < 0:
self.cover(float(bar.close) * 1.01, abs(self.pos))
'''
# 发出状态更新事件
self.putEvent()
#----------------------------------------------------------------------
def onOrder(self, order):
"""收到委托变化推送（必须由用户继承实现）"""
pass
#----------------------------------------------------------------------
def onTrade(self, trade):
# 发出状态更新事件
self.putEvent()
#----------------------------------------------------------------------
def onStopOrder(self, so):
"""停止单推送"""
try:
if so.status == STOPORDER_CANCELLED:
pass
#print ("cancellling stop order orderid %s" % so.stopOrderID)
else:
pass
#print("sending stop order %s %f %s" % (so.orderType, so.price, so.stopOrderID))
#order.direction = so.direction
#order.offset = so.offset
#DIRECTION_LONG
#OFFSET_OPEN
except Exception, e:
print e
class DoubleMaStrategy(CtaTemplate):
"""双指数均线策略Demo"""
className = 'DoubleMaStrategy'
author = u'wxl'
# 策略参数
fastWindow = 2 # 快速均线参数
slowWindow = 5 # 慢速均线参数
initDays = 10 # 初始化数据所用的天数
# 策略变量
fastMa0 = EMPTY_FLOAT # 当前最新的快速EMA
fastMa1 = EMPTY_FLOAT # 上一根的快速EMA
slowMa0 = EMPTY_FLOAT
slowMa1 = EMPTY_FLOAT
# 参数列表，保存了参数的名称
paramList = [
'name', 'className', 'author', 'vtSymbol', 'fastWindow', 'slowWindow'
]
# 变量列表，保存了变量的名称
varList = [
'inited', 'trading', 'pos', 'fastMa0', 'fastMa1', 'slowMa0', 'slowMa1'
]
# 同步列表，保存了需要保存到数据库的变量名称
syncList = ['pos']
# ----------------------------------------------------------------------
def __init__(self, ctaEngine, setting):
"""Constructor"""
super(DoubleMaStrategy, self).__init__(ctaEngine, setting)
self.bg = BarGenerator(self.onBar)
self.am = ArrayManager()
# 注意策略类中的可变对象属性（通常是list和dict等），在策略初始化时需要重新创建，
# 否则会出现多个策略实例之间数据共享的情况，有可能导致潜在的策略逻辑错误风险，
# 策略类中的这些可变对象属性可以选择不写，全都放在__init__下面，写主要是为了阅读
# 策略时方便（更多是个编程习惯的选择）
# ----------------------------------------------------------------------
def onInit(self):
"""初始化策略（必须由用户继承实现）"""
self.writeCtaLog(u'双EMA演示策略初始化')
initData = self.loadBar(self.initDays)
for bar in initData:
self.onBar(bar)
self.putEvent()
# ----------------------------------------------------------------------
def onStart(self):
"""启动策略（必须由用户继承实现）"""
self.writeCtaLog(u'双EMA演示策略启动')
self.putEvent()
# ----------------------------------------------------------------------
def onStop(self):
"""停止策略（必须由用户继承实现）"""
self.writeCtaLog(u'双EMA演示策略停止')
self.putEvent()
# ----------------------------------------------------------------------
def onTick(self, tick):
"""收到行情TICK推送（必须由用户继承实现）"""
self.bg.updateTick(tick)
# ----------------------------------------------------------------------
def onBar(self, bar):
"""收到Bar推送（必须由用户继承实现）"""
am = self.am
am.updateBar(bar)
if not am.inited:
return
# 计算快慢均线
fastMa = am.sma(self.fastWindow, array=True)
self.fastMa0 = fastMa[-1]
self.fastMa1 = fastMa[-2]
slowMa = am.sma(self.slowWindow, array=True)
self.slowMa0 = slowMa[-1]
self.slowMa1 = slowMa[-2]
# 判断买卖
crossOver = self.fastMa0 > self.slowMa0 and self.fastMa1 < self.slowMa1 # 金叉上穿
crossBelow = self.fastMa0 < self.slowMa0 and self.fastMa1 > self.slowMa1 # 死叉下穿
# 金叉和死叉的条件是互斥
# 所有的委托均以K线收盘价委托（这里有一个实盘中无法成交的风险，考虑添加对模拟市价单类型的支持）
if crossOver:
# 如果金叉时手头没有持仓，则直接做多
if self.pos == 0:
self.buy(bar.close, 1)
# 如果有空头持仓，则先平空，再做多
elif self.pos < 0:
self.cover(bar.close, 1)
self.buy(bar.close, 1)
# 死叉和金叉相反
elif crossBelow:
if self.pos == 0:
self.short(bar.close, 1)
elif self.pos > 0:
self.sell(bar.close, 1)
self.short(bar.close, 1)
# 发出状态更新事件
self.putEvent()
# ----------------------------------------------------------------------
def onOrder(self, order):
"""收到委托变化推送（必须由用户继承实现）"""
# 对于无需做细粒度委托控制的策略，可以忽略onOrder
pass
# ----------------------------------------------------------------------
def onTrade(self, trade):
"""收到成交推送（必须由用户继承实现）"""
# 对于无需做细粒度委托控制的策略，可以忽略onOrder
pass
# ----------------------------------------------------------------------
def onStopOrder(self, so):
"""停止单推送"""
pass
def atr_cond(self):
import tushare as ts
import numpy as np
import talib as tl
start_date = datetime.datetime.now() - datetime.timedelta(30)
data = ts.bar(self.vtSymbol,
conn=ts.get_apis(),
start_date=start_date,
asset='X').sort_index()
C = np.array(data['close'])
H = np.array(data['high'])
L = np.array(data['low'])
TR = tl.ATR(H, L, C, timeperiod=1) / C[-2]
ATR10 = tl.ATR(H, L, C, timeperiod=10) / C[-2]
return TR[-2] < ATR10[-2] and ATR10[-2] > 0.02
class AtrRsiStrategy(CtaTemplate):
"""结合ATR和RSI指标的一个分钟线交易策略"""
className = 'AtrRsiStrategy'
author = u'用Python的交易员'
# 策略参数
atrLength = 22 # 计算ATR指标的窗口数
atrMaLength = 10 # 计算ATR均线的窗口数
rsiLength = 5 # 计算RSI的窗口数
rsiEntry = 16 # RSI的开仓信号
trailingPercent = 0.8 # 百分比移动止损
initDays = 10 # 初始化数据所用的天数
fixedSize = 1 # 每次交易的数量
# 策略变量
atrValue = 0 # 最新的ATR指标数值
atrMa = 0 # ATR移动平均的数值
rsiValue = 0 # RSI指标的数值
rsiBuy = 0 # RSI买开阈值
rsiSell = 0 # RSI卖开阈值
intraTradeHigh = 0 # 移动止损用的持仓期内最高价
intraTradeLow = 0 # 移动止损用的持仓期内最低价
# 参数列表，保存了参数的名称
paramList = ['name',
'className',
'author',
'vtSymbol',
'atrLength',
'atrMaLength',
'rsiLength',
'rsiEntry',
'trailingPercent']
# 变量列表，保存了变量的名称
varList = ['inited',
'trading',
'pos',
'atrValue',
'atrMa',
'rsiValue',
'rsiBuy',
'rsiSell']
# 同步列表，保存了需要保存到数据库的变量名称
syncList = ['pos',
'intraTradeHigh',
'intraTradeLow']
#----------------------------------------------------------------------
def __init__(self, ctaEngine, setting):
"""Constructor"""
super(AtrRsiStrategy, self).__init__(ctaEngine, setting)
# 创建K线合成器对象
self.bg = BarGenerator(self.onBar)
self.am = ArrayManager()
# 注意策略类中的可变对象属性（通常是list和dict等），在策略初始化时需要重新创建，
# 否则会出现多个策略实例之间数据共享的情况，有可能导致潜在的策略逻辑错误风险，
# 策略类中的这些可变对象属性可以选择不写，全都放在__init__下面，写主要是为了阅读
# 策略时方便（更多是个编程习惯的选择）
#----------------------------------------------------------------------
def onInit(self):
"""初始化策略（必须由用户继承实现）"""
self.writeCtaLog(u'%s策略初始化' %self.name)
# 初始化RSI入场阈值
self.rsiBuy = 50 + self.rsiEntry
self.rsiSell = 50 - self.rsiEntry
# 载入历史数据，并采用回放计算的方式初始化策略数值
initData = self.loadBar(self.initDays)
for bar in initData:
self.onBar(bar)
self.putEvent()
#----------------------------------------------------------------------
def onStart(self):
"""启动策略（必须由用户继承实现）"""
self.writeCtaLog(u'%s策略启动' %self.name)
self.putEvent()
#----------------------------------------------------------------------
def onStop(self):
"""停止策略（必须由用户继承实现）"""
self.writeCtaLog(u'%s策略停止' %self.name)
self.putEvent()
#----------------------------------------------------------------------
def onTick(self, tick):
"""收到行情TICK推送（必须由用户继承实现）"""
self.bg.updateTick(tick)
#----------------------------------------------------------------------
def onBar(self, bar):
"""收到Bar推送（必须由用户继承实现）"""
self.cancelAll()
# 保存K线数据
am = self.am
am.updateBar(bar)
if not am.inited:
return
# 计算指标数值
atrArray = am.atr(self.atrLength, array=True)
self.atrValue = atrArray[-1]
self.atrMa = atrArray[-self.atrMaLength:].mean()
self.rsiValue = am.rsi(self.rsiLength)
# 判断是否要进行交易
# 当前无仓位
if self.pos == 0:
self.intraTradeHigh = bar.high
self.intraTradeLow = bar.low
# ATR数值上穿其移动平均线，说明行情短期内波动加大
# 即处于趋势的概率较大，适合CTA开仓
if self.atrValue > self.atrMa:
# 使用RSI指标的趋势行情时，会在超买超卖区钝化特征，作为开仓信号
if self.rsiValue > self.rsiBuy:
# 这里为了保证成交，选择超价5个整指数点下单
self.buy(bar.close+5, self.fixedSize)
elif self.rsiValue < self.rsiSell:
self.short(bar.close-5, self.fixedSize)
# 持有多头仓位
elif self.pos > 0:
# 计算多头持有期内的最高价，以及重置最低价
self.intraTradeHigh = max(self.intraTradeHigh, bar.high)
self.intraTradeLow = bar.low
# 计算多头移动止损
longStop = self.intraTradeHigh * (1-self.trailingPercent/100)
# 发出本地止损委托
self.sell(longStop, abs(self.pos), stop=True)
# 持有空头仓位
elif self.pos < 0:
self.intraTradeLow = min(self.intraTradeLow, bar.low)
self.intraTradeHigh = bar.high
shortStop = self.intraTradeLow * (1+self.trailingPercent/100)
self.cover(shortStop, abs(self.pos), stop=True)
# 同步数据到数据库
self.saveSyncData()
# 发出状态更新事件
self.putEvent()
#----------------------------------------------------------------------
def onOrder(self, order):
"""收到委托变化推送（必须由用户继承实现）"""
pass
#----------------------------------------------------------------------
def onTrade(self, trade):
# 发出状态更新事件
self.putEvent()
#----------------------------------------------------------------------
def onStopOrder(self, so):
"""停止单推送"""
pass
class KkStrategy(CtaTemplate):
"""基于King Keltner通道的交易策略"""
className = 'KkStrategy'
author = u'张老师'
# 策略参数
kkLength = 11 # 计算通道中值的窗口数
kkDev = 1.6 # 计算通道宽度的偏差
trailingPrcnt = 0.8 # 移动止损
initDays = 10 # 初始化数据所用的天数
fixedSize = 1 # 每次交易的数量
# 策略变量
kkUp = 0 # KK通道上轨
kkDown = 0 # KK通道下轨
intraTradeHigh = 0 # 持仓期内的最高点
intraTradeLow = 0 # 持仓期内的最低点
buyOrderIDList = [] # OCO委托买入开仓的委托号
shortOrderIDList = [] # OCO委托卖出开仓的委托号
orderList = [] # 保存委托代码的列表
# 参数列表，保存了参数的名称
paramList = [
'name', 'className', 'author', 'vtSymbol', 'kkLength', 'kkDev'
]
# 变量列表，保存了变量的名称
varList = ['inited', 'trading', 'pos', 'kkUp', 'kkDown']
# 同步列表，保存了需要保存到数据库的变量名称
syncList = ['pos', 'intraTradeHigh', 'intraTradeLow']
#----------------------------------------------------------------------
def __init__(self, ctaEngine, setting):
"""Constructor"""
super(KkStrategy, self).__init__(ctaEngine, setting)
self.bg = BarGenerator(self.onBar, 5, self.onFiveBar) # 创建K线合成器对象
self.am = ArrayManager()
self.buyOrderIDList = []
self.shortOrderIDList = []
self.orderList = []
#----------------------------------------------------------------------
def onInit(self):
"""初始化策略（必须由用户继承实现）"""
self.writeCtaLog(u'%s策略初始化' % self.name)
# 载入历史数据，并采用回放计算的方式初始化策略数值
initData = self.loadBar(self.initDays)
for bar in initData:
self.onBar(bar)
self.putEvent()
#----------------------------------------------------------------------
def onStart(self):
"""启动策略（必须由用户继承实现）"""
self.writeCtaLog(u'%s策略启动' % self.name)
self.putEvent()
#----------------------------------------------------------------------
def onStop(self):
"""停止策略（必须由用户继承实现）"""
self.writeCtaLog(u'%s策略停止' % self.name)
self.putEvent()
#----------------------------------------------------------------------
def onTick(self, tick):
"""收到行情TICK推送（必须由用户继承实现）"""
self.bg.updateTick(tick)
#----------------------------------------------------------------------
def onBar(self, bar):
"""收到Bar推送（必须由用户继承实现）"""
self.bg.updateBar(bar)
#----------------------------------------------------------------------
def onFiveBar(self, bar):
"""收到5分钟K线"""
# 撤销之前发出的尚未成交的委托（包括限价单和停止单）
for orderID in self.orderList:
self.cancelOrder(orderID)
self.orderList = []
# 保存K线数据
am = self.am
am.updateBar(bar)
if not am.inited:
return
# 计算指标数值
self.kkUp, self.kkDown = am.keltner(self.kkLength, self.kkDev)
# 判断是否要进行交易
# 当前无仓位，发送OCO开仓委托
if self.pos == 0:
self.intraTradeHigh = bar.high
self.intraTradeLow = bar.low
self.sendOcoOrder(self.kkUp, self.kkDown, self.fixedSize)
# 持有多头仓位
elif self.pos > 0:
self.intraTradeHigh = max(self.intraTradeHigh, bar.high)
self.intraTradeLow = bar.low
l = self.sell(self.intraTradeHigh * (1 - self.trailingPrcnt / 100),
abs(self.pos), True)
self.orderList.extend(l)
# 持有空头仓位
elif self.pos < 0:
self.intraTradeHigh = bar.high
self.intraTradeLow = min(self.intraTradeLow, bar.low)
l = self.cover(self.intraTradeLow * (1 + self.trailingPrcnt / 100),
abs(self.pos), True)
self.orderList.extend(l)
# 同步数据到数据库
self.saveSyncData()
# 发出状态更新事件
self.putEvent()
#----------------------------------------------------------------------
def onOrder(self, order):
"""收到委托变化推送（必须由用户继承实现）"""
pass
#----------------------------------------------------------------------
def onTrade(self, trade):
if self.pos != 0:
# 多头开仓成交后，撤消空头委托
if self.pos > 0:
for shortOrderID in self.shortOrderIDList:
self.cancelOrder(shortOrderID)
# 反之同样
elif self.pos < 0:
for buyOrderID in self.buyOrderIDList:
self.cancelOrder(buyOrderID)
# 移除委托号
for orderID in (self.buyOrderIDList + self.shortOrderIDList):
if orderID in self.orderList:
self.orderList.remove(orderID)
# 发出状态更新事件
self.putEvent()
#----------------------------------------------------------------------
def sendOcoOrder(self, buyPrice, shortPrice, volume):
"""
发送OCO委托
OCO(One Cancel Other)委托：
1. 主要用于实现区间突破入场
2. 包含两个方向相反的停止单
3. 一个方向的停止单成交后会立即撤消另一个方向的
"""
# 发送双边的停止单委托，并记录委托号
self.buyOrderIDList = self.buy(buyPrice, volume, True)
self.shortOrderIDList = self.short(shortPrice, volume, True)
# 将委托号记录到列表中
self.orderList.extend(self.buyOrderIDList)
self.orderList.extend(self.shortOrderIDList)
#----------------------------------------------------------------------
def onStopOrder(self, so):
"""停止单推送"""
pass
class ZeroStrategy(CtaTemplate):
"""基于布林通道的交易策略"""
className = 'ZeroStrategy'
author = u'用Python的交易员'
initDays = 4 # 初始化数据所用的天数
fixedSize = 1 # 每次交易的数量
# 参数列表，保存了参数的名称
paramList = [
'name', 'className', 'author', 'vtSymbol', 'initDays', 'fixedSize'
]
# 变量列表，保存了变量的名称
varList = ['inited', 'trading', 'pos']
# 同步列表，保存了需要保存到数据库的变量名称
syncList = ['pos']
#----------------------------------------------------------------------
def __init__(self, ctaEngine, setting):
"""Constructor"""
super(ZeroStrategy, self).__init__(ctaEngine, setting)
self.bg = BarGenerator(self.onBar, 30, self.on30minBar) # 创建K线合成器对象
self.am = ArrayManager()
#最小价差变动
self.tickadd = 1
#有无夜盘和 相关的时间
self.yepan = True
self.yepanhour = 23
self.yepanminute = 00
self.stopcount = 0
#断网变量相关
self.lastbardatetime = None
self.didinited = False
#仓位相关
self.posdetail = None
#订单相关
self.shortOrder = None
self.buyOrder = None
self.sellOrder = None
self.coverOrder = None
#撤单后跟单相关
self.genOrder = None
#tick策略相关全局函数
#交易那一分钟
self.tradeMinute = False
#order那一分钟
self.orderMinute = False
#----------------------------------------------------------------------
def on30minBar(self, bar):
""""""
#----------------------------------------------------------------------
def onInit(self):
"""初始化策略（必须由用户继承实现）"""
self.writeCtaLog(u'%s策略初始化' % self.name)
self.getPosDetail()
# 载入历史数据，并采用回放计算的方式初始化策略数值
initData = self.loadBar(self.initDays)
for bar in initData:
self.onBar(bar)
self.didinited = True
self.putEvent()
#----------------------------------------------------------------------
def onStart(self):
"""启动策略（必须由用户继承实现）"""
self.writeCtaLog(u'%s策略启动' % self.name)
self.putEvent()
#----------------------------------------------------------------------
def onStop(self):
"""停止策略（必须由用户继承实现）"""
self.writeCtaLog(u'%s策略停止' % self.name)
self.putEvent()
def cancelVtOrder(self, order, yuanyin, fangxiang, price=None):
self.writeCtaLog(yuanyin + 'cancle')
self.cancelOrder(order)
if fangxiang == 'buy':
self.buyOrder = None
elif fangxiang == 'short':
self.shortOrder = None
elif fangxiang == 'sell':
self.sellOrder == None
elif fangxiang == 'cover':
self.coverOrder = None
else:
self.writeCtaLog('ohmyghoa')
if price is not None:
self.genOrder = price
#----------------------------------------------------------------------
def buyTickCelve(self, tick):
am = self.am
fangxiang = None
price = None
if tick.datetime.second > 51:
if am.diff > 0 and am.macd < 0 and am.lastmacd > 0:
fangxiang = duo
price = tick.bidPrice1
elif am.macd > 0 and am.lastmacd < 0:
fangxiang = duoping
price = tick.askPrice1
self.chulikaipingcang(fangxiang, price)
# 处理错误开仓（但市场方向正确的仓），在收阳时平掉
if self.posdetail.longPos > 0 and am.macd > 0 and am.lastmacd > 0 and self.bg.bar.open > tick.lastPrice and not self.tradeMinute:
fangxiang = duoping
price = tick.askPrice1
self.chulikaipingcang(fangxiang, price)
#----------------------------------------------------------------------
def shortTickCelve(self, tick):
am = self.am
fangxiang = None
price = None
if tick.datetime.second > 51:
if am.diff < 0 and am.macd > 0 and am.lastmacd < 0:
fangxiang = kong
price = tick.askPrice1
elif am.macd < 0 and am.lastmacd > 0:
fangxiang = kongping
price = tick.bidPrice1
self.chulikaipingcang(fangxiang, price)
#处理错误开仓（但市场方向正确的仓），在收阳时平掉
if self.posdetail.shortPos > 0 and am.macd < 0 and am.lastmacd < 0 and self.bg.bar.open < tick.lastPrice and not self.tradeMinute:
fangxiang = kongping
price = tick.bidPrice1
self.chulikaipingcang(fangxiang, price)
#----------------------------------------------------------------------
def onTick(self, tick):
"""收到行情TICK推送（必须由用户继承实现）"""
self.bg.updateTick(tick)
self.am.updateTick(tick)
if not self.stopcount:
self.buyTickCelve(tick)
self.shortTickCelve(tick)
if tick.datetime.second == 59:
self.checkFalseSignal(tick)
def checkPingcang(self, bar):
if self.didinited:
am = self.am
fangxiang = None
price = None
if self.posdetail.longPos > 0 and self.sellOrder is not None and am.lastmacd > 0 and am.mj < 0:
price = am.tick.bidPrice1
self.cancelVtOrder(self.sellOrder, u'必须平多', 'sell', price)
elif self.posdetail.shortPos > 0 and self.coverOrder is not None and am.lastmacd < 0 and am.mj > 0:
price = am.tick.askPrice1
self.cancelVtOrder(self.coverOrder, u'必须平空', 'cover', price)
#----------------------------------------------------------------------
def getPosDetail(self):
self.posdetail = self.ctaEngine.mainEngine.getPositionDetail(
self.vtSymbol)
def onBar(self, bar):
"""收到Bar推送（必须由用户继承实现）"""
#检查是否有效的交易时间
if self.notintradingTime(bar):
print('not')
runDataCleaning()
return
detail = self.posdetail
# if not self.didinited:
# posdetial = self.posdetail
#print( detail.longPos,'long and short ',detail.shortPos )
if not self.lastbardatetime == bar.datetime:
self.bg.updateBar(bar)
self.am.updateBar(bar)
am = self.am
self.barCelve(bar)
#tick策略数据还原
self.tradeMinute = False
self.orderMinute = False
print('zhibiao', 'macd', am.macd, 'diff', am.diff, 'mj', am.mj, 'time',
bar.datetime, 'end')
#检查是否断网
self.lastbardatetime = bar.datetime
self.am.endBar()
#----------------------------------------------------------------------
def barCelve(self, bar):
self.checkCancelOrder()
self.checkIfConnecting(bar)
self.checkPingcang(bar)
#----------------------------------------------------------------------
def onOrder(self, order):
"""收到委托变化推送（必须由用户继承实现）"""
#orderminute
self.orderMinute = True
#对相应订单编号进行管理
if order.status == STATUS_NOTTRADED:
self.reactOrder(order, order.vtOrderID)
elif order.status == STATUS_ALLTRADED or order.status == STATUS_CANCELLED:
self.reactOrder(order, None)
elif order.status == STATUS_REJECTED:
self.writeCtaLog(STATUS_REJECTED + order.offset + order.direction)
print('time', self.am.tick.datetime, order.orderTime, order.price,
self.genOrder)
#检查需不需要跟单
if order.status == STATUS_CANCELLED and self.genOrder is not None:
self.writeCtaLog('ongendan' + order.offset + order.direction)
print(self.genOrder)
if order.offset == OFFSET_OPEN and order.direction == DIRECTION_LONG:
self.orderBuy(self.genOrder)
self.genOrder = None
elif order.offset == OFFSET_OPEN and order.direction == DIRECTION_SHORT:
self.orderShort(self.genOrder)
self.genOrder = None
elif (order.offset == OFFSET_CLOSE or order.offset
== OFFSET_CLOSETODAY or order.offset == OFFSET_CLOSEYESTERDAY
) and order.direction == DIRECTION_LONG:
self.orderCover(self.genOrder)
self.genOrder = None
elif (order.offset == OFFSET_CLOSE or order.offset
== OFFSET_CLOSETODAY or order.offset == OFFSET_CLOSEYESTERDAY
) and order.direction == DIRECTION_SHORT:
self.orderSell(self.genOrder)
self.genOrder = None
print 'order', order.price, order.direction, order.offset, order.status, order.vtOrderID, order.orderTime, self.pos, self.am.tick.datetime
#----------------------------------------------------------------------
def reactOrder(self, order, vtOrderID):
print 'react', order.direction, order.offset
if (order.direction == DIRECTION_LONG and order.offset == OFFSET_OPEN):
print 'enterlong'
self.buyOrder = vtOrderID
elif (
order.direction == DIRECTION_SHORT and
(order.offset == OFFSET_CLOSE or order.offset == OFFSET_CLOSETODAY
or order.offset == OFFSET_CLOSEYESTERDAY)):
print('entersell')
self.sellOrder = vtOrderID
elif (order.direction == DIRECTION_SHORT
and order.offset == OFFSET_OPEN):
print 'entershort'
self.shortOrder = vtOrderID
elif (
order.direction == DIRECTION_LONG and
(order.offset == OFFSET_CLOSE or order.offset == OFFSET_CLOSETODAY
or order.offset == OFFSET_CLOSEYESTERDAY)):
print('enter coveer')
self.coverOrder = vtOrderID
else:
print('enteranother')
def onTrade(self, trade):
# 发出状态更新事件
self.reactOrder(trade, None)
#处理tick策略
self.tradeMinute = True
print 'trade', trade.price, trade.direction, trade.offset, trade.tradeTime
self.putEvent()
#----------------------------------------------------------------------
def onStopOrder(self, so):
"""停止单推送"""
pass
#----------------------------------------------------------------------
'''仓位函数'''
def chulikaipingcang(self, fangxiang, price):
if self.didinited:
if fangxiang == duo:
if self.posdetail.longPos == 0:
print 'buybuy'
self.orderBuy(price, 1)
elif fangxiang == kong:
if self.posdetail.shortPos == 0:
self.orderShort(price, 1)
elif fangxiang == duoping:
if self.posdetail.longPos > 0:
self.orderSell(price, 1)
if self.buyOrder is not None:
self.cancelVtOrder(self.buyOrder, u'平多时候', 'buy')
elif fangxiang == kongping:
if self.posdetail.shortPos > 0:
self.orderCover(price, 1)
if self.shortOrder is not None:
self.cancelVtOrder(self.shortOrder, u'平空时候', 'short')
#-------------------------------------------------------
'''订单管理类'''
def orderBuy(self, price, volume=1, stop=False):
if self.buyOrder is None:
print 'buyorder'
self.buyOrder = 0
self.buy(price, volume, stop)
def orderSell(self, price, volume=1, stop=False):
if self.sellOrder is None:
self.sellOrder = 0
self.sell(price, volume, stop)
def orderShort(self, price, volume=1, stop=False):
if self.shortOrder is None:
self.shortOrder = 0
self.short(price, volume, stop)
def orderCover(self, price, volume=1, stop=False):
if self.coverOrder is None:
self.coverOrder = 0
self.cover(price, volume, stop)
# ----------------------------------------------------------------------
'''断网判断及处理函数'''
'''目前的逻辑是根据两个bar的时间间隔来判断是否断网，一个可能的风险当市场上两笔交易的间隔长于两分钟时，会错认为也是断网了，这个在不活跃品种也较容易出现。不过一般出现这种情况较少。'''
def closeAllPosistion(self, price):
'''出意外如断网时平仓'''
self.cancelAll()
print('--closeallpos--')
if self.pos > 0:
self.short(price - self.tickadd, abs(self.pos))
elif self.pos < 0:
self.cover(price + self.tickadd, abs(self.pos))
# ----------------------------------------------------------------------
# ----------------------------------------------------------------------
def iscontinueTime(self, firstdatetime, seconddatetime):
'''判断是否为连续的时间'''
if (firstdatetime.hour == seconddatetime.hour and firstdatetime.minute + 1 == seconddatetime.minute) \
or (
firstdatetime.hour == seconddatetime.hour - 1 and firstdatetime.minute == 59 and seconddatetime.minute == 0):
return True
# ----------------------------------------------------------------------
def isTradeContinueTime(self, firstdatetime, seconddatetime):
'''判断是否为连续的交易时间'''
if self.iscontinueTime(firstdatetime, seconddatetime):
return True
elif firstdatetime.hour == 10 and (
firstdatetime.minute == 15 or firstdatetime.minute == 14
) and seconddatetime.hour == 10 and (seconddatetime.minute == 30
or seconddatetime.minute == 31):
return True
elif firstdatetime.hour == 11 and (
firstdatetime.minute == 29 or firstdatetime.minute == 30
) and seconddatetime.hour == 13 and (seconddatetime.minute == 30
or seconddatetime.minute == 31
or seconddatetime.minute == 29):
return True
elif self.yepan and (seconddatetime.hour == 9 or
(seconddatetime.hour == 8
and seconddatetime.minute == 59)) and (
firstdatetime.hour == self.yepanhour or
(firstdatetime.hour == self.yepanhour - 1
and firstdatetime.minute == 59)):
return True
elif (firstdatetime.hour == 15 or
(firstdatetime.hour == 14 and firstdatetime.minute == 59)) and (
(seconddatetime.hour == 9 and seconddatetime.minute == 0) or
(seconddatetime.hour == 8 and seconddatetime.minute == 59)):
return True
elif ((firstdatetime.hour == 14 and firstdatetime.minute == 59)
or firstdatetime.hour == 15) and (
seconddatetime.hour == 21 or
(seconddatetime.hour == 20 and seconddatetime.minute == 59)):
return True
elif ((firstdatetime.hour == 23 and firstdatetime.minute == 59) and
(seconddatetime.hour == 0 and seconddatetime.minute == 0)) or (
(firstdatetime.hour == 0 and firstdatetime.minute == 59) and
((seconddatetime.hour == 9 and seconddatetime.minute == 0))):
return True
else:
print('dus conne', firstdatetime, seconddatetime)
return False
# ----------------------------------------------------------------------
def handleDisConnected(self, price):
print('DISCONNECTED', self.lastbardatetime, self.am.datetime)
self.reSetOrder()
self.stopcount = 15
def notintradingTime(self, bar):
dt = bar.datetime.time()
if ((MORNING_START <= dt < MORNING_REST)
or (MORNING_RESTART <= dt < MORNING_END)
or (AFTERNOON_START <= dt < AFTERNOON_END)
or (dt >= NIGHT_START) or (dt < NIGHT_END)):
return False
else:
return True
def checkIfConnecting(self, bar):
if self.lastbardatetime is None:
self.lastbardatetime = bar.datetime
elif self.lastbardatetime == bar.datetime:
pass
else:
if not self.isTradeContinueTime(self.lastbardatetime,
bar.datetime):
# 断网了，需要处理断网状态
self.handleDisConnected(bar.close)
# 没有断网
else:
if self.stopcount > 0:
self.stopcount -= 1
def checkCancelOrder(self):
if self.orderMinute:
print('orderminute', self.buyOrder, self.shortOrder,
self.sellOrder, self.coverOrder)
if self.buyOrder:
if self.am.macd > 0:
self.cancelVtOrder(self.buyOrder, u"没进入绿浪", 'buy')
if self.shortOrder:
if self.am.macd < 0:
self.cancelVtOrder(self.shortOrder, u"没进入红狼", 'short')
if self.sellOrder:
if self.am.macd < 0:
self.cancelVtOrder(self.sellOrder, u'没进入红浪', 'sell')
if self.coverOrder:
if self.am.macd > 0:
self.cancelVtOrder(self.coverOrder, u'没进入绿琅', 'cover')
def checkFalseSignal(self, tick):
if self.tradeMinute:
if self.posdetail.longPos > 0:
if self.am.macd > 0:
self.sellFok(tick.askPrice1, 1)
elif self.posdetail.shortPos > 0:
if self.am.macd < 0:
self.coverFok(tick.bidPrice1, 1)
#回测用
def barkaicang(self, bar):
am = self.am
if not self.stopcount:
fangxiang = None
price = bar.close
if am.diff > 0 and am.macd < 0 and am.lastmacd > 0:
fangxiang = duo
elif am.macd > 0 and am.lastmacd < 0:
fangxiang = duoping
elif am.diff < 0 and am.macd > 0 and am.lastmacd < 0:
fangxiang = kong
elif am.macd < 0 and am.lastmacd > 0:
fangxiang = kongping
self.chulikaipingcang(fangxiang, price)
def reSetOrder(self):
print '---------------------reset--------------'
self.shortOrder = None
self.coverOrder = None
self.buyOrder = None
self.sellOrder = None
class DoubleMaStrategy(CtaTemplate):
"""双指数均线策略Demo"""
className = 'DoubleMaStrategy'
author = u'用Python的交易员'
# 策略参数
fastWindow = 10 # 快速均线参数
slowWindow = 60 # 慢速均线参数
initDays = 10 # 初始化数据所用的天数
# 策略变量
fastMa0 = EMPTY_FLOAT # 当前最新的快速EMA
fastMa1 = EMPTY_FLOAT # 上一根的快速EMA
slowMa0 = EMPTY_FLOAT
slowMa1 = EMPTY_FLOAT
# 参数列表，保存了参数的名称
paramList = ['name',
'className',
'author',
'vtSymbol',
'fastWindow',
'slowWindow']
# 变量列表，保存了变量的名称
varList = ['inited',
'trading',
'pos',
'fastMa0',
'fastMa1',
'slowMa0',
'slowMa1']
# 同步列表，保存了需要保存到数据库的变量名称
syncList = ['pos']
#----------------------------------------------------------------------
def __init__(self, ctaEngine, setting):
"""Constructor"""
super(DoubleMaStrategy, self).__init__(ctaEngine, setting)
self.bg = BarGenerator(self.onBar)
self.am = ArrayManager()
# 注意策略类中的可变对象属性（通常是list和dict等），在策略初始化时需要重新创建，
# 否则会出现多个策略实例之间数据共享的情况，有可能导致潜在的策略逻辑错误风险，
# 策略类中的这些可变对象属性可以选择不写，全都放在__init__下面，写主要是为了阅读
# 策略时方便（更多是个编程习惯的选择）
#----------------------------------------------------------------------
def onInit(self):
"""初始化策略（必须由用户继承实现）"""
self.writeCtaLog(u'双EMA演示策略初始化')
initData = self.loadBar(self.initDays)
for bar in initData:
self.onBar(bar)
self.putEvent()
#----------------------------------------------------------------------
def onStart(self):
"""启动策略（必须由用户继承实现）"""
self.writeCtaLog(u'双EMA演示策略启动')
self.putEvent()
#----------------------------------------------------------------------
def onStop(self):
"""停止策略（必须由用户继承实现）"""
self.writeCtaLog(u'双EMA演示策略停止')
self.putEvent()
#----------------------------------------------------------------------
def onTick(self, tick):
"""收到行情TICK推送（必须由用户继承实现）"""
self.bg.updateTick(tick)
#----------------------------------------------------------------------
def onBar(self, bar):
"""收到Bar推送（必须由用户继承实现）"""
am = self.am
am.updateBar(bar)
if not am.inited:
return
# 计算快慢均线
fastMa = am.sma(self.fastWindow, array=True)
self.fastMa0 = fastMa[-1]
self.fastMa1 = fastMa[-2]
slowMa = am.sma(self.slowWindow, array=True)
self.slowMa0 = slowMa[-1]
self.slowMa1 = slowMa[-2]
# 判断买卖
crossOver = self.fastMa0>self.slowMa0 and self.fastMa1<self.slowMa1 # 金叉上穿
crossBelow = self.fastMa0<self.slowMa0 and self.fastMa1>self.slowMa1 # 死叉下穿
# 金叉和死叉的条件是互斥
# 所有的委托均以K线收盘价委托（这里有一个实盘中无法成交的风险，考虑添加对模拟市价单类型的支持）
if crossOver:
# 如果金叉时手头没有持仓，则直接做多
if self.pos == 0:
self.buy(bar.close, 1)
# 如果有空头持仓，则先平空，再做多
elif self.pos < 0:
self.cover(bar.close, 1)
self.buy(bar.close, 1)
# 死叉和金叉相反
elif crossBelow:
if self.pos == 0:
self.short(bar.close, 1)
elif self.pos > 0:
self.sell(bar.close, 1)
self.short(bar.close, 1)
# 发出状态更新事件
self.putEvent()
#----------------------------------------------------------------------
def onOrder(self, order):
"""收到委托变化推送（必须由用户继承实现）"""
# 对于无需做细粒度委托控制的策略，可以忽略onOrder
pass
#----------------------------------------------------------------------
def onTrade(self, trade):
"""收到成交推送（必须由用户继承实现）"""
# 对于无需做细粒度委托控制的策略，可以忽略onOrder
pass
#----------------------------------------------------------------------
def onStopOrder(self, so):
"""停止单推送"""
pass
class BollChannelStrategy(CtaTemplate):
"""基于布林通道的交易策略"""
className = 'BollChannelStrategy'
author = u'用Python的交易员'
# 策略参数
bollWindow = 18 # 布林通道窗口数
bollDev = 3.4 # 布林通道的偏差
cciWindow = 10 # CCI窗口数
atrWindow = 30 # ATR窗口数
slMultiplier = 5.2 # 计算止损距离的乘数
initDays = 10 # 初始化数据所用的天数
fixedSize = 1 # 每次交易的数量
# 策略变量
bollUp = 0 # 布林通道上轨
bollDown = 0 # 布林通道下轨
cciValue = 0 # CCI指标数值
atrValue = 0 # ATR指标数值
intraTradeHigh = 0 # 持仓期内的最高点
intraTradeLow = 0 # 持仓期内的最低点
longStop = 0 # 多头止损
shortStop = 0 # 空头止损
# 参数列表，保存了参数的名称
paramList = ['name',
'className',
'author',
'vtSymbol',
'bollWindow',
'bollDev',
'cciWindow',
'atrWindow',
'slMultiplier',
'initDays',
'fixedSize']
# 变量列表，保存了变量的名称
varList = ['inited',
'trading',
'pos',
'bollUp',
'bollDown',
'cciValue',
'atrValue',
'intraTradeHigh',
'intraTradeLow',
'longStop',
'shortStop']
# 同步列表，保存了需要保存到数据库的变量名称
syncList = ['pos',
'intraTradeHigh',
'intraTradeLow']
#----------------------------------------------------------------------
def __init__(self, ctaEngine, setting):
"""Constructor"""
super(BollChannelStrategy, self).__init__(ctaEngine, setting)
self.bg = BarGenerator(self.onBar, 15, self.onXminBar) # 创建K线合成器对象
self.bg30 = BarGenerator(self.onBar, 30, self.on30minBar)
self.am = ArrayManager()
#----------------------------------------------------------------------
def on30minBar(self, bar):
""""""
#----------------------------------------------------------------------
def onInit(self):
"""初始化策略（必须由用户继承实现）"""
self.writeCtaLog(u'%s策略初始化' %self.name)
# 载入历史数据，并采用回放计算的方式初始化策略数值
initData = self.loadBar(self.initDays)
for bar in initData:
self.onBar(bar)
self.putEvent()
#----------------------------------------------------------------------
def onStart(self):
"""启动策略（必须由用户继承实现）"""
self.writeCtaLog(u'%s策略启动' %self.name)
self.putEvent()
#----------------------------------------------------------------------
def onStop(self):
"""停止策略（必须由用户继承实现）"""
self.writeCtaLog(u'%s策略停止' %self.name)
self.putEvent()
#----------------------------------------------------------------------
def onTick(self, tick):
"""收到行情TICK推送（必须由用户继承实现）"""
self.bg.updateTick(tick)
#----------------------------------------------------------------------
def onBar(self, bar):
"""收到Bar推送（必须由用户继承实现）"""
self.bg.updateBar(bar)
#----------------------------------------------------------------------
def onXminBar(self, bar):
"""收到X分钟K线"""
# 全撤之前发出的委托
self.cancelAll()
# 保存K线数据
am = self.am
am.updateBar(bar)
if not am.inited:
return
# 计算指标数值
self.bollUp, self.bollDown = am.boll(self.bollWindow, self.bollDev)
self.cciValue = am.cci(self.cciWindow)
self.atrValue = am.atr(self.atrWindow)
# 判断是否要进行交易
# 当前无仓位，发送开仓委托
if self.pos == 0:
self.intraTradeHigh = bar.high
self.intraTradeLow = bar.low
if self.cciValue > 0:
self.buy(self.bollUp, self.fixedSize, True)
elif self.cciValue < 0:
self.short(self.bollDown, self.fixedSize, True)
# 持有多头仓位
elif self.pos > 0:
self.intraTradeHigh = max(self.intraTradeHigh, bar.high)
self.intraTradeLow = bar.low
self.longStop = self.intraTradeHigh - self.atrValue * self.slMultiplier
self.sell(self.longStop, abs(self.pos), True)
# 持有空头仓位
elif self.pos < 0:
self.intraTradeHigh = bar.high
self.intraTradeLow = min(self.intraTradeLow, bar.low)
self.shortStop = self.intraTradeLow + self.atrValue * self.slMultiplier
self.cover(self.shortStop, abs(self.pos), True)
# 同步数据到数据库
self.saveSyncData()
# 发出状态更新事件
self.putEvent()
#----------------------------------------------------------------------
def onOrder(self, order):
"""收到委托变化推送（必须由用户继承实现）"""
pass
#----------------------------------------------------------------------
def onTrade(self, trade):
# 发出状态更新事件
self.putEvent()
#----------------------------------------------------------------------
def onStopOrder(self, so):
"""停止单推送"""
pass
class BollChannelStrategy01(CtaTemplate):
"""基于布林通道的交易策略"""
className = 'BollChannelStrategy01'
author = 'Y.Raul'
# 策略参数
bollWindow = 18 # 布林通道窗口数
bollDev = 5 # 布林通道的偏差
cciWindow = 10 # CCI窗口数
atrWindow = 30 # ATR窗口数
slMultiplier = 5 # 计算止损距离的乘数
initDays = 10 # 初始化数据所用的天数
fixedSize = 1 # 每次交易的数量
# 策略变量
bollUp = 0 # 布林通道上轨
bollDown = 0 # 布林通道下轨
cciValue = 0 # CCI指标数值
atrValue = 0 # ATR指标数值
filterTime = True #是否过滤9点开盘后头五分钟，15点收盘前五分钟
intraTradeHigh = 0 # 持仓期内的最高点
intraTradeLow = 0 # 持仓期内的最低点
longStop = 0 # 多头止损
shortStop = 0 # 空头止损
avgEntryPrice = 0 #平均入场价
avgExitPrice = 0 #平均出场价
buySig = False
shortSig = False
exitOnLossStop = 2
miniDiff = 1
# 参数列表，保存了参数的名称
paramList = [
'name', 'className', 'author', 'vtSymbol', 'bollWindow', 'bollDev',
'cciWindow', 'atrWindow', 'slMultiplier', 'initDays', 'fixedSize'
]
# 变量列表，保存了变量的名称
varList = [
'inited', 'trading', 'pos', 'bollUp', 'bollDown', 'cciValue',
'atrValue', 'intraTradeHigh', 'intraTradeLow', 'longStop', 'shortStop'
]
# 同步列表，保存了需要保存到数据库的变量名称
syncList = ['pos', 'intraTradeHigh', 'intraTradeLow']
#----------------------------------------------------------------------
def __init__(self, ctaEngine, setting):
"""Constructor"""
super(BollChannelStrategy01, self).__init__(ctaEngine, setting)
self.bm = BarGenerator(self.onBar, 15, self.on5minBar) # 创建K线合成器对象
self.am = ArrayManager()
self.entryPriceList = []
self.orderList = []
#----------------------------------------------------------------------
def onInit(self):
"""初始化策略（必须由用户继承实现）"""
self.writeCtaLog(u'%s策略初始化' % self.name)
# 载入历史数据，并采用回放计算的方式初始化策略数值
initData = self.loadBar(self.initDays)
for bar in initData:
self.onBar(bar)
self.putEvent()
#----------------------------------------------------------------------
def onStart(self):
"""启动策略（必须由用户继承实现）"""
self.writeCtaLog(u'%s策略启动' % self.name)
self.putEvent()
#----------------------------------------------------------------------
def onStop(self):
"""停止策略（必须由用户继承实现）"""
self.writeCtaLog(u'%s策略停止' % self.name)
self.putEvent()
#----------------------------------------------------------------------
def onTick(self, tick):
"""收到行情TICK推送（必须由用户继承实现）"""
self.bm.updateTick(tick)
#----------------------------------------------------------------------
def onBar(self, bar):
self.bm.updateBar(bar)
if not self.trading:
# 记录log
log = "-----" * 10 + "\n@onBar\n" + \
"trading: {0}\n".format(self.trading)+\
"bar.datetime: {0}; pos: {1} \n".format(bar.datetime, self.pos) + \
"buySig: {0}; shortSig: {1}\n".format(self.buySig, self.shortSig)
self.writeCtaLog(log)
print log
self.buySig = False
self.shortSig = False
return
# 检查开仓信号
if self.buySig:
res = self.buy(self.bollUp, self.fixedSize)
self.orderList.extend(res)
# 记录log
log = "-----" * 10 + "\n@onBar\n" + \
"bar.datetime: {0}; pos: {1} \n".format(bar.datetime, self.pos) + \
"buySig: {0}; shortSig: {1}\n".format(self.buySig, self.shortSig)
self.writeCtaLog(log)
log = "\n Trading: {0}\n".format(self.trading) + \
"{0} Buy : bar.close: {1};\n".format(bar.datetime, bar.close) + \
" entryUp:{0}; cci:{1};\n".format(self.bollUp, self.cciValue)
self.writeCtaLog(log)
self.buySig = False
print log
if self.shortSig:
res = self.short(self.bollDown, self.fixedSize)
self.orderList.extend(res)
# 记录log
log = "-----" * 10 + "\n@onBar\n" + \
"bar.datetime: {0}; pos: {1} \n".format(bar.datetime, self.pos) + \
"buySig: {0}; shortSig: {1}\n".format(self.buySig, self.shortSig)
self.writeCtaLog(log)
log = "\n Trading: {0}\n".format(self.trading) + \
"{0} Short : bar.close: {1};\n".format(bar.datetime, bar.close) + \
" entryDown:{0}; cci:{1};\n".format(self.bollDown, self.cciValue)
self.writeCtaLog(log)
self.shortSig = False
print log
self.putEvent()
#----------------------------------------------------------------------
def on5minBar(self, bar):
"""收到X分钟K线"""
# 全撤之前发出的委托
self.cancelAll()
# 保存K线数据
am = self.am
am.updateBar(bar)
if not am.inited:
return
# 计算指标数值
self.bollUp, self.bollDown = am.boll(self.bollWindow, self.bollDev)
self.cciValue = am.cci(self.cciWindow)
atrArray = am.atr(self.atrWindow, array=True)
self.atrValue = atrArray[-1]
self.atrMa = atrArray[-self.atrWindow:].mean()
# 判断是否要进行交易
# 当前无仓位，发送开仓委托，限价单
if self.pos == 0:
self.intraTradeHigh = bar.high
self.intraTradeLow = bar.low
self.entryPriceList = []
self.orderList = []
self.avgEntryPrice = []
import datetime
timeWindow = True
if self.filterTime:
timeWindow = bar.datetime.time() > datetime.time(
9) and bar.datetime.time() < datetime.time(14, 55)
if timeWindow:
if self.cciValue > 0 and self.atrValue > self.atrMa:
# if self.cciValue > 0 :
self.buySig = True
elif self.cciValue < 0 and self.atrValue < self.atrMa:
# elif self.cciValue < 0:
self.shortSig = True
# 记录log
log = "-----" * 10 + "\n@on5minBar\n" + \
"timeWidow: {0}\n".format(timeWindow) +\
"bar.datetime: {0}; pos: {1} ; close: {2}\n".format(bar.datetime, self.pos, bar.close) + \
"buySig: {0}; shortSig: {1}\n".format(self.buySig, self.shortSig) + \
"intraTradeHigh: {0}\n".format(self.intraTradeHigh) + \
"intraTradeLow: {0}\n".format(self.intraTradeLow)
self.writeCtaLog(log)
print log
# 当前有仓位，以本地停止单止损
# 持有多头仓位
elif self.pos > 0:
self.intraTradeHigh = max(self.intraTradeHigh, bar.high)
self.intraTradeLow = bar.low
self.longStop = self.intraTradeHigh - self.atrValue * self.slMultiplier
# if bar.close < self.stopExit:
# 固定止损
# self.sell(bar.close, abs(self.pos), True)
# else:
# 跟随止损
# self.sell(self.longStop, abs(self.pos), True)
self.sell(self.longStop, abs(self.pos), True)
# 记录log
log = "-----" * 10 + "\n@on5minBar\n" + \
"bar.datetime: {0}; pos: {1} ; close: {2}\n".format(bar.datetime, self.pos, bar.close) + \
"intraTradeHigh: {0}\n".format(self.intraTradeHigh) + \
"intraTradeLow: {0}\n".format(self.intraTradeLow)
"avgEntryPrice: {0}\n".format(self.avgEntryPrice) + \
"longStop: {0}\n".format(self.longStop) + \
"stopExit:{0}\n".format(self.stopExit)
self.writeCtaLog(log)
print log
# 持有空头仓位
elif self.pos < 0:
self.intraTradeHigh = bar.high
self.intraTradeLow = min(self.intraTradeLow, bar.low)
self.shortStop = self.intraTradeLow + self.atrValue * self.slMultiplier
# if bar.close > self.stopExit:
# 固定止损
# self.cover(bar.close, abs(self.pos), True)
# else:
# 跟随止损
# self.cover(self.shortStop, abs(self.pos), True)
self.cover(self.shortStop, abs(self.pos), True)
# 记录log
log = "-----" * 10 + "\n@on5minBar\n" + \
"bar.datetime: {0}; pos: {1} ; close: {2}\n".format(bar.datetime, self.pos, bar.close) + \
"intraTradeHigh: {0}\n".format(self.intraTradeHigh) + \
"intraTradeLow: {0}\n".format(self.intraTradeLow) +\
"avgEntryPrice: {0}\n".format(self.avgEntryPrice) + \
"shortStop: {0}\n".format(self.longStop) + \
"stopExit:{0}\n".format(self.stopExit)
self.writeCtaLog(log)
print log
# 同步数据到数据库
self.saveSyncData()
# 发出状态更新事件
self.putEvent()
#----------------------------------------------------------------------
def onOrder(self, order):
'''
处理order更新
:param order:
:return:
'''
# 记录log
log = "-----" * 10 + "\n@onOrder\n" + \
"orderTime: {0}; pos: {1} \n".format(order.orderTime, order.totalVolume) + \
u"status {0}; vtOrderID: {1}\n".format(order.status, order.vtOrderID)+ \
u"direction:{0}\n".format(order.direction)
self.writeCtaLog(log)
print log
# 对于开仓，记录相关价格
if order.direction == DIRECTION_LONG and order.offset == OFFSET_OPEN:
if order.totalVolume == order.tradedVolume:
# 更新入场价列表，更新平均入场价
self.entryPriceList.append(order.price)
self.avgEntryPrice = sum(self.entryPriceList) / len(
self.entryPriceList)
self.stopExit = round(self.avgEntryPrice *
(100 - self.exitOnLossStop) /
100) # 固定止损价
elif order.direction == DIRECTION_SHORT and order.offset == OFFSET_OPEN:
# 更新入场价列表，更新平均入场价
if order.totalVolume == order.tradedVolume:
# 更新入场价列表，更新平均入场价
self.entryPriceList.append(order.price)
self.avgEntryPrice = sum(self.entryPriceList) / len(
self.entryPriceList)
self.stopExit = round(self.avgEntryPrice *
(1 + self.exitOnLossStop) / 100) # 固定止损价
self.putEvent()
#----------------------------------------------------------------------
def onTrade(self, trade):
# 发出状态更新事件
self.putEvent()
#----------------------------------------------------------------------
def onStopOrder(self, so):
"""停止单推送"""
pass
class ShortTermStrategy(CtaTemplate):
"""短期市场结构策略"""
className = 'ShortTermStrategy'
author = u'任建军'
# 策略参数
A_WEIGHT = 10 #{每手吨数 }
A_BZJ = 0.14 #{保证金参数 }
#--------------以下是可以优化的策略----------------------------
# 策略变量
initDays = 1 # 初始化数据所用的天数
# 策略启动日期位置（即前面的数据用于初始化），int值
# 注意：这个值决定了回测开始时刻的index值,
# 多参数优化时根据F:\uiKLine\json\uiKLine_startpara中的STARTPOS值直接修改该值
# 直接回测时候也需要直接修改该值
# 同时修改__init__中的这个值
#strategyStartpos=1890
#strategyEndpos=2340
strategyStartpos = 1 # 20141010
strategyEndpos = 2353 # 20160927
# 策略 做多策略还是做空策略，BOOL值 True=Long False=Short
# 注意：多参数优化时直接修改该值
# 直接回测时候也需要直接修改该值
LongOrShort = False
all_bar = [] # 存放所以bar
####--20170103优化参数(strategyStartpos = 1890 20170103)开多------#####
A_LOSS_SP_ALL = 0.16 # 保证金亏损幅度 #
A_FLAOT_PROFIT_ALL = 1900 # 最佳浮盈 #
A_MIN_UP_ALL = 0.9 # close超过short_term_last_two_high_all_index[1]幅度#
E_LONG_ALL = 34
###--20090327优化参数(strategyStartpos = 1890 20170103)开空-----#####
SK_A_LOSS_SP_ALL = 0.37 # 保证金亏损幅度 #
SK_A_FLAOT_PROFIT_ALL = 1450 # 最佳浮盈 #
SK_E_LONG_ALL = 34
A_MIN_DOWN_ALL = 0.9 # close超过short_term_last_two_low_all_index[1]幅度 #
###---------------------------------------------------#####
BKPRICE = EMPTY_FLOAT_WH
SKPRICE = EMPTY_FLOAT_WH
# 参数列表，保存了参数的名称
paramList = [
'name',
'className',
'author',
'vtSymbol',
'A_LOSS_SP_FIRST',
'A_FLAOT_PROFIT_FIRST ',
'E_LONG_FIRST',
'A_LOSS_SP_ALL',
'A_FLAOT_PROFIT_ALL',
'A_MIN_UP_ALL',
'A_MIN_DOWN_ALL',
'SK_A_LOSS_SP_ALL',
'SK_A_FLAOT_PROFIT_ALL',
'SK_E_LONG',
'LongOrShort',
]
# 变量列表，保存了变量的名称
varList = ['inited', 'trading', 'pos']
# 同步列表，保存了需要保存到数据库的变量名称
syncList = ['pos']
#----------------------------------------------------------------------
def __init__(self, ctaEngine, setting):
"""Constructor"""
super(ShortTermStrategy, self).__init__(ctaEngine, setting)
# 注意策略类中的可变对象属性（通常是list和dict等），在策略初始化时需要重新创建，
# 否则会出现多个策略实例之间数据共享的情况，有可能导致潜在的策略逻辑错误风险，
# 策略类中的这些可变对象属性可以选择不写，全都放在__init__下面，写主要是为了阅读
# 策略时方便（更多是个编程习惯的选择）
self.short_term_list_first = []
self.short_term_list_all = []
self.short_term_last_three_first_index = []
self.short_term_last_two_low_all_index = []
self.short_term_last_two_high_all_index = []
self.short_term_open_last_three_first_index = []
self.short_term_open_last_two_all_index = []
self.all_bar = []
self.BK_style = EMPTY_INT_WH # 2-->所有的低点 21利用低点 22利用高点
self.SK_style = EMPTY_INT_WH # 2-->所有的高点 21利用高点 22利用低点
self.BKPRICE = EMPTY_FLOAT_WH
self.SKPRICE = EMPTY_FLOAT_WH
self.initDays = self.E_LONG_ALL if self.LongOrShort == True else self.SK_E_LONG_ALL
self.MAXCLOSE_AFTER_OPEN = EMPTY_FLOAT_WH #建仓后close的最大值
self.strategyStartpos = 1343
self.strategyEndpos = 1826
self.SP_style = 0000
self.tradeday = 0
self.bg = BarGenerator(self.onBar)
self.am = ArrayManager(self.initDays)
#----------------------------------------------------------------------
def onInit(self):
"""初始化策略（必须由用户继承实现）"""
self.writeCtaLog(u'短期市场结构策略初始化')
index_settings = self.load_All_Index_Setting()
if len(index_settings) == 0:
print("检查F:\uiKLine\json\uiKLine_all_index.json路径是否正确")
return
for setting in index_settings:
self.short_term_list_all = setting[u'SHORT_TERM_INDEX']
if len(self.short_term_list_all) == 0:
print("short term数据为空")
return
initData = self.loadBar(self.initDays)
for bar in initData:
self.ctaEngine.updateDailyClose(bar.datetime, bar.close)
self.onBar(bar)
self.putEvent()
#----------------------------------------------------------------------
def onStart(self):
"""启动策略（必须由用户继承实现）"""
self.writeCtaLog(u'短期市场结构策略启动')
self.putEvent()
#----------------------------------------------------------------------
def onStop(self):
"""停止策略（必须由用户继承实现）"""
self.writeCtaLog(u'短期市场结构策略停止')
self.putEvent()
#----------------------------------------------------------------------
def onTick(self, tick):
"""收到行情TICK推送（必须由用户继承实现）"""
self.bg.updateTick(tick)
#----------------------------------------------------------------------
def short_term_all_index(self, bar, am):
"""
利用short term(all)作为策略进行交易
1、做多买开：
1-1、2个连续的低点呈现上升趋势买开
1-2、2个连续的高点呈现上升趋势，且当日的close高于第二个高点的最高值A_MIN_UP_ALL%买开
2、做多卖平
2-1、保证金亏损幅度
2-2、最佳浮盈
2-3、对于1-1 closed低于用于开仓的第二个低点日的low值
2-4、对于1-2 closed低于用于开仓的第一个高点日的high值
"""
########################################################################################
# 更新最近两次短期列表的值 低1 < 低1 -->做多买入
if len(self.short_term_last_two_low_all_index) < 2:
if (self.short_term_list_all[len(self.all_bar) - 1] != 0
and self.short_term_list_all[len(self.all_bar) - 1] != 2):
self.short_term_last_two_low_all_index.append(
len(self.all_bar) - 1)
return
else:
if (self.short_term_list_all[len(self.all_bar) - 1] != 0
and self.short_term_list_all[len(self.all_bar) - 1] != 2):
del self.short_term_last_two_low_all_index[0]
self.short_term_last_two_low_all_index.append(
len(self.all_bar) - 1)
# 更新最近两次短期列表的值 高2 < 高2 -->做多买入 , 高2 > 高2 -->做多卖平
if len(self.short_term_last_two_high_all_index) < 2:
if (self.short_term_list_all[len(self.all_bar) - 1] != 0
and self.short_term_list_all[len(self.all_bar) - 1] != 1):
self.short_term_last_two_high_all_index.append(
len(self.all_bar) - 1)
return
else:
if (self.short_term_list_all[len(self.all_bar) - 1] != 0
and self.short_term_list_all[len(self.all_bar) - 1] != 1):
del self.short_term_last_two_high_all_index[0]
self.short_term_last_two_high_all_index.append(
len(self.all_bar) - 1)
if len(self.all_bar) < self.strategyStartpos:
return
if self.tradeday > 0:
self.tradeday = self.tradeday + 1
#if bar.date=='20190529':
# print bar.date
########################################################################################
#------------------------ 1 、 做多买开条件-----------------------------------------------
# 条件1：短期市场结构是否满足要求 满足为TRUE 不满足为FALSE
BK_Condition_1 = False
# 首先：满足做多的基本要求形态-->低1 < 低1
if self.short_term_list_all[self.short_term_last_two_low_all_index[0]] == 1 and \
self.short_term_list_all[self.short_term_last_two_low_all_index[1]] == 1 :
# 其次：低点是上升的形态 后面的低点高于前面的低点 并且 最后面的低1的那个k日线全部走完（确定一个高、低点需要3个K线）
if (self.all_bar[self.short_term_last_two_low_all_index[0]].low < self.all_bar[self.short_term_last_two_low_all_index[1]].low) and \
(len(self.all_bar) == self.short_term_last_two_low_all_index[1]+2) :
# 最后： 如果指标没有被使用过
if cmp(self.short_term_open_last_two_all_index,
self.short_term_last_two_low_all_index) != 0:
BK_Condition_1 = True
# 条件2：短期市场结构是否满足要求 满足为TRUE 不满足为FALSE
BK_Condition_2 = False
# 首先：满足做多的基本要求形态-->高2 < 高2
if self.short_term_list_all[self.short_term_last_two_high_all_index[0]] == 2 and \
self.short_term_list_all[self.short_term_last_two_high_all_index[1]] == 2 :
# 其次：高点是上升的形态 后面的高点高于前面的高点 并且 最后面的高2的那个k日线全部走完（确定一个高、低点需要3个K线）
if (self.all_bar[self.short_term_last_two_high_all_index[0]].high < self.all_bar[self.short_term_last_two_high_all_index[1]].high) and \
(len(self.all_bar) >= self.short_term_last_two_high_all_index[1]+2) :
# 然后：高2后面的某个交易日的close高于第二个高点的最高值一定百分比
if bar.close > self.all_bar[
self.short_term_last_two_high_all_index[1]].high * (
1 + self.A_MIN_UP_ALL / 100.0):
# 最后： 如果指标没有被使用过
if cmp(self.short_term_open_last_two_all_index,
self.short_term_last_two_high_all_index) != 0:
BK_Condition_2 = True
#--------------------------2 、做多卖平条件-----------------------------------------------
self.SP_style = 0000
#条件1：保证金亏损幅度
SP_Condition_1 = False
if self.pos == 1:
A_PRICE_SP = self.BKPRICE * self.A_WEIGHT * self.A_BZJ #{最近买开价位总费用}
SP_Condition_1 = (self.BKPRICE - bar.close) * self.A_WEIGHT > (
A_PRICE_SP * self.A_LOSS_SP_ALL)
if SP_Condition_1:
self.SP_style = self.SP_style | 8 #1000
#条件2：最佳浮盈
SP_Condition_2 = False
if self.pos == 1:
SP_Condition_2 = (bar.close - self.BKPRICE
) * self.A_WEIGHT >= self.A_FLAOT_PROFIT_ALL
if SP_Condition_2:
self.SP_style = self.SP_style | 4 #1000
#条件3：closed低于用于开仓的第二个低点日的low值
SP_Condition_3 = False
if self.pos == 1 and self.BK_style == 21:
SP_Condition_3 = bar.close < self.all_bar[
self.short_term_open_last_two_all_index[1]].low
if SP_Condition_3:
self.SP_style = self.SP_style | 2 #0010
#条件4：closed低于用于开仓的第一个高点日的high值
SP_Condition_4 = False
if self.pos == 1 and self.BK_style == 22:
SP_Condition_4 = bar.close < self.all_bar[
self.short_term_open_last_two_all_index[0]].high
if SP_Condition_4:
self.SP_style = self.SP_style | 1 #0001
#-------------------------3 、 做多执行交易---------------------------------------------------
if BK_Condition_1 and self.pos == 0 and self.BK_style == EMPTY_INT_WH and self.LongOrShort == True:
self.buy(bar.close, 1)
self.short_term_open_last_two_all_index = []
self.short_term_open_last_two_all_index = copy.deepcopy(
self.short_term_last_two_low_all_index)
self.BK_style = 21
self.tradeday = 1
elif BK_Condition_2 and self.pos == 0 and self.BK_style == EMPTY_INT_WH and self.LongOrShort == True:
self.buy(bar.close, 1)
self.short_term_open_last_two_all_index = []
self.short_term_open_last_two_all_index = copy.deepcopy(
self.short_term_last_two_high_all_index)
self.BK_style = 22
self.tradeday = 1
if (SP_Condition_1 or SP_Condition_2
or SP_Condition_3) and self.pos == 1 and self.BK_style == 21:
self.sell(bar.close, 1)
self.BK_style = EMPTY_INT_WH
elif (SP_Condition_1 or SP_Condition_2
or SP_Condition_4) and self.pos == 1 and self.BK_style == 22:
self.sell(bar.close, 1)
self.BK_style = EMPTY_INT_WH
#################################################################################################
#------------------------ 4 、 做空卖开条件-----------------------------------------------
# 条件1：短期市场结构是否满足要求 满足为TRUE 不满足为FALSE
SK_Condition_1 = False
# 首先：满足做空的基本要求形态-->高2 > 高2
if self.short_term_list_all[self.short_term_last_two_high_all_index[0]] == 2 and \
self.short_term_list_all[self.short_term_last_two_high_all_index[1]] == 2 :
# 其次：高点是下降的形态 后面的高点点低于前面的高点 最后面的高2全部走完（确定一个高、低点需要3个K线）
if (self.all_bar[self.short_term_last_two_high_all_index[0]].high > self.all_bar[self.short_term_last_two_high_all_index[1]].high) and \
(len(self.all_bar) == self.short_term_last_two_high_all_index[1]+2) :
# 最后： 如果指标没有被使用过
if cmp(self.short_term_open_last_two_all_index,
self.short_term_last_two_high_all_index) != 0:
SK_Condition_1 = True
# 条件2：短期市场结构是否满足要求 满足为TRUE 不满足为FALSE
SK_Condition_2 = False
# 首先：满足做空的基本要求形态-->低1 > 低1
if self.short_term_list_all[self.short_term_last_two_low_all_index[0]] == 1 and \
self.short_term_list_all[self.short_term_last_two_low_all_index[1]] == 1 :
# 其次：低点是下降的形态 后面的低点低于前面的低点 最后面的低1全部走完（确定一个高、低点需要3个K线）
if (self.all_bar[self.short_term_last_two_low_all_index[0]].low > self.all_bar[self.short_term_last_two_low_all_index[1]].low) and \
(len(self.all_bar) >= self.short_term_last_two_low_all_index[1]+2) :
# 然后：当日的close低于第二个低点的最低值
if bar.close < self.all_bar[
self.short_term_last_two_low_all_index[1]].low * (
1 - self.A_MIN_DOWN_ALL / 100.0):
# 最后： 如果指标没有被使用过
if cmp(self.short_term_open_last_two_all_index,
self.short_term_last_two_low_all_index) != 0:
SK_Condition_2 = True
#--------------------------5 、做空买平条件-----------------------------------------------
#条件1：保证金亏损幅度
BP_Condition_1 = False
if self.pos == -1:
A_PRICE_SP = self.SKPRICE * self.A_WEIGHT * self.A_BZJ #{最近买开价位总费用}
BP_Condition_1 = (bar.close - self.SKPRICE) * self.A_WEIGHT > (
A_PRICE_SP * self.SK_A_LOSS_SP_ALL)
#条件2：最佳浮盈
BP_Condition_2 = False
if self.pos == -1:
BP_Condition_2 = (self.SKPRICE - bar.close
) * self.A_WEIGHT >= self.SK_A_FLAOT_PROFIT_ALL
#条件3：closed高于用于开仓的第二个高点日的high值
BP_Condition_3 = False
if self.pos == -1 and self.SK_style == 21:
BP_Condition_3 = bar.close > self.all_bar[
self.short_term_open_last_two_all_index[1]].high
#条件4：closed高于用于开仓的第一个低点日的low值
BP_Condition_4 = False
if self.pos == -1 and self.SK_style == 22:
BP_Condition_4 = bar.close > self.all_bar[
self.short_term_open_last_two_all_index[0]].low
#-------------------------6 、 做空执行交易-----------------------------------------------
if SK_Condition_1 and self.pos == 0 and self.SK_style == EMPTY_INT_WH and self.LongOrShort == False:
self.short(bar.close, 1)
self.short_term_open_last_two_all_index = []
self.short_term_open_last_two_all_index = copy.deepcopy(
self.short_term_last_two_high_all_index)
self.SK_style = 21
elif SK_Condition_2 and self.pos == 0 and self.SK_style == EMPTY_INT_WH and self.LongOrShort == False:
self.short(bar.close, 1)
self.short_term_open_last_two_all_index = []
self.short_term_open_last_two_all_index = copy.deepcopy(
self.short_term_last_two_low_all_index)
self.SK_style = 22
if (BP_Condition_1 or BP_Condition_2
or BP_Condition_3) and self.pos == -1 and self.SK_style == 21:
self.cover(bar.close, 1)
self.SK_style = EMPTY_INT_WH
elif (BP_Condition_1 or BP_Condition_2
or BP_Condition_4) and self.pos == -1 and self.SK_style == 22:
self.cover(bar.close, 1)
self.SK_style = EMPTY_INT_WH
self.putEvent()
#----------------------------------------------------------------------
def onBar(self, bar):
"""收到Bar推送（必须由用户继承实现）"""
self.all_bar.append(bar)
am = self.am
am.updateBar(bar)
if not am.inited:
return
if len(self.all_bar) > self.strategyEndpos + 1:
'''
if self.pos > 0:
self.sell(bar.close, self.pos)
self.putEvent()
if self.pos < 0:
self.cover(bar.close, abs(self.pos))
self.putEvent()
'''
return
self.short_term_all_index(bar, am)
# 发出状态更新事件
self.putEvent()
#----------------------------------------------------------------------
def onOrder(self, order):
"""收到委托变化推送（必须由用户继承实现）"""
pass
#----------------------------------------------------------------------
def onTrade(self, trade):
"""收到成交推送（必须由用户继承实现）"""
# 对于无需做细粒度委托控制的策略，可以忽略onOrder
if trade.direction == DIRECTION_LONG and trade.offset == OFFSET_OPEN: #做多买开
print 'STRB BUY :', ',', trade.tradeTime, ',', trade.price, ',', ',', self.BK_style
self.BKPRICE = trade.price
if trade.direction == DIRECTION_SHORT and trade.offset == OFFSET_CLOSE: #做多卖平
print 'STRB SELL:', ',', trade.tradeTime, ',', trade.price, ',', (
trade.price -
self.BKPRICE) * self.A_WEIGHT, ',', '{:08b}'.format(
self.SP_style)[-4:], ',', self.tradeday
self.BKPRICE = EMPTY_FLOAT_WH
self.tradeday = 0
if trade.direction == DIRECTION_SHORT and trade.offset == OFFSET_OPEN: #做空卖开
print 'STRB SELL :', ',', trade.tradeTime, ',', trade.price, ',', self.SK_style
self.SKPRICE = trade.price
if trade.direction == DIRECTION_LONG and trade.offset == OFFSET_CLOSE: #做空买平
print 'STRB COVER:', ',', trade.tradeTime, ',', trade.price, ',', (
self.SKPRICE - trade.price) * self.A_WEIGHT
self.SKPRICE = EMPTY_FLOAT_WH
#----------------------------------------------------------------------
def onStopOrder(self, so):
"""停止单推送"""
pass
#----------------------------------------------------------------------
def load_All_Index_Setting(self):
"""把相关指标从json文件读取"""
try:
with open(u'F:\\uiKLine\\json\\uiKLine_all_index.json') as f:
index_settings = json.load(f)
f.close()
except:
print("读取失败，检查F:\\uiKLine\\json\\uiKLine_all_index.json路径是否正确")
return {}
return index_settings
class EMAC_IntraDayCommonStrategy(CtaTemplate):
"""DualThrust交易策略"""
className = 'EMAC_IntraDayCommonStrategy'
author = u'Leon Zhao'
# 策略参数
fixedSize = 1
fast1 = 5
slow1 = 21
fast2 = 8
slow2 = 34
fast3 = 13
slow3 = 55
dbpath = "./sr.csv"
cumrange = 0
shreshhold = 0.3
atrDays = 20
atrValue = 0
initDays = 35
# 策略变量
barList = [] # K线对象的列表
longEntry = 0
shortEntry = 0
exitTime = time(hour=15,
minute=20) #will not cover position when day close
longEntered = False
shortEntered = False
# 参数列表，保存了参数的名称
paramList = ['name', 'className', 'author', 'vtSymbol']
# 变量列表，保存了变量的名称
varList = [
'inited', 'trading', 'pos', 'cumrange', 'longEntry', 'shortEntry',
'exitTime'
]
range = 0
longEntry1 = 0
shortEntry1 = 0
# 同步列表，保存了需要保存到数据库的变量名称
syncList = ['pos', 'range', 'longEntry1', 'shortEntry1']
#----------------------------------------------------------------------
def __init__(self, ctaEngine, setting):
"""Constructor"""
super(EMAC_IntraDayCommonStrategy, self).__init__(ctaEngine, setting)
self.bg = BarGenerator(self.onBar,
onDayBar=self.ondayBar,
vtSymbol=self.vtSymbol)
self.am = ArrayManager()
self.indexam = ArrayManager()
self.barList = []
self.longEntry1 = 0
self.shortEntry1 = 0
# Read Parameters from Setting files
if 'strParams' in setting:
self.params = setting['strParams']
if len(self.params) >= 3:
for p in self.params:
if p[0] == 'unit':
self.fixedSize = p[1]
if p[0] == 'p1':
self.fast1 = p[1]
if p[0] == 'p2':
self.slow1 = p[1]
if p[0] == 'p3':
self.fast2 = p[1]
if p[0] == 'p4':
self.slow2 = p[1]
if p[0] == 'p5':
self.fast3 = p[1]
if p[0] == 'p6':
self.slow3 = p[1]
if p[0] == 'p7':
self.dbpath = p[1]
else:
# 策略参数
self.fast1 = 5
self.slow1 = 21
self.fast2 = 8
self.slow2 = 34
self.fast3 = 13
self.slow3 = 55
self.dbpath = "./sr.csv"
#print(self.fixedSize,self.k1,self.k2,self.rangeDays,self.initDays)
self.cumrange = 0
self.shreshhold = 0.3
self.atrDays = 20
self.atrValue = 0
self.initDays = 100
self.longEntry = 0
self.shortEntry = 0
self.exitTime = time(
hour=15, minute=20) #will not cover position when day close
self.longEntered = False
self.shortEntered = False
self.emac_kpi = 0
self.emac1scalar = 7.5
self.emac2scalar = 5.3
self.emac3scalar = 3.7
self.pcstd = 0
self.weights = [0.35, 0.3, 0.35]
def loadIndexBar(self, dbpath):
csvfile = "../TdxData/bar_data/" + dbpath
#print(csvfile)
dfindex = pd.read_csv(csvfile, parse_dates=True, index_col=0)
#print(dbpath)
dfindex["pc"] = dfindex["close"] - dfindex["close"].shift(-1)
#dfordered = dfindex.sort_index( ascending=False)
daybar = VtBarData()
dt = datetime.now()
for idx, indexbar in dfindex.iterrows():
#print(idx)
daybar.vtSymbol = self.vtSymbol
daybar.symbol = self.vtSymbol
daybar.exchange = ""
daybar.open = indexbar["open"]
daybar.high = indexbar["high"]
daybar.low = indexbar["low"]
daybar.close = indexbar["close"]
#dt = datetime.strptime(str(indexbar["trade_date"]),"%Y%m%d")
#change bar Date to next day if time is night
#nextDay =
daybar.datetime = idx # 以第一根分钟K线的开始时间戳作为X分钟线的时间戳
daybar.date = daybar.datetime.strftime('%Y%m%d')
daybar.time = daybar.datetime.strftime('%H:%M:%S.%f')
#print(daybar.datetime,daybar.close)
self.indexam.updateBar(daybar)
temp = dfindex["pc"].rolling(20, min_periods=20).std()
temp = temp.dropna()
self.pcstd = temp.iloc[-1]
#----------------------------------------------------------------------
def onInit(self):
"""初始化策略（必须由用户继承实现）"""
self.writeCtaLog(u'%s策略初始化' % self.name)
# 载入历史数据，并采用回放计算的方式初始化策略数值
initData = self.loadBar(self.initDays)
#dbpath = ""
self.loadIndexBar(self.dbpath)
for bar in initData:
self.onBar(bar)
self.putEvent()
#----------------------------------------------------------------------
def onStart(self):
"""启动策略（必须由用户继承实现）"""
self.writeCtaLog(u'%s策略启动' % self.name)
self.putEvent()
#----------------------------------------------------------------------
def onStop(self):
"""停止策略（必须由用户继承实现）"""
self.writeCtaLog(u'%s策略停止' % self.name)
self.putEvent()
#----------------------------------------------------------------------
def onTick(self, tick):
"""收到行情TICK推送（必须由用户继承实现）"""
#ignore data before real open
if (tick.datetime.hour == 8 or tick.datetime.hour == 20):
return
self.bg.updateTick(tick)
def calcUnitNo(self, atr, fixSize):
dtCap = 0.0
defaultCap = 0.0
unitNo = 0
cust = []
var_sizelist = CtaTemplate.vol_Size
var_size = 0.0
var_Symbol = ""
if len(var_sizelist) == 0:
return fixSize
else:
var_Symbol = var_Symbol.join(
list(filter(lambda x: x.isalpha(), self.vtSymbol)))
var_size = float(var_sizelist[var_Symbol][0])
if var_size - 0 < 0.01:
return fixSize
var_temp = 0.0
if len(CtaTemplate.cust_Setting) > 0:
cust = CtaTemplate.cust_Setting
for cs in cust:
if cs["StrategyGroup"] == "DT" and cs["Status"] == 'True':
dtCap = cs["CaptialAmt"]
break
if cs["StrategyGroup"] == "Default" and cs["Status"] == 'True':
defaultCap = cs["CaptialAmt"]
if dtCap > 0:
self.capConfig = float(dtCap)
elif defaultCap > 0:
self.capConfig = float(defaultCap)
else:
self.capConfig = 0.0
unitNo = 0
if self.capConfig - 0 < 0.0001:
unitNo = fixSize
elif var_size - 0 < 0.001:
unitNo = fixSize
else:
unitNo = int(self.capConfig * 0.0088 / (atr * var_size))
if unitNo < 1:
unitNo = 1
return unitNo
#---------calcuate range for the last several days
def getUnitNo(self):
if self.am.count >= self.atrDays + 1:
self.atrValue = self.am.atr(self.atrDays, False)
if self.atrValue > 0:
self.fixedSize = self.calcUnitNo(self.atrValue, self.fixedSize)
else:
pass
def CalcKPI(self):
#pass
emafast1 = self.indexam.ema(self.fast1)
emaslow1 = self.indexam.ema(self.slow1)
emafast2 = self.indexam.ema(self.fast2)
emaslow2 = self.indexam.ema(self.slow2)
emafast3 = self.indexam.ema(self.fast3)
emaslow3 = self.indexam.ema(self.slow3)
kpi = self.emac1scalar * (
emafast1 -
emaslow1) * self.weights[0] / self.pcstd + self.emac2scalar * (
emafast2 -
emaslow2) * self.weights[1] / self.pcstd + self.emac3scalar * (
emafast3 - emaslow3) * self.weights[2] / self.pcstd
return kpi
#indexvol = self.indexam
#----------------------------------------------------------------------
def onBar(self, bar):
"""收到Bar推送（必须由用户继承实现）"""
if self.reduceCountdown() > 0:
return
# 撤销之前发出的尚未成交的委托（包括限价单和停止单）
self.cancelAll()
self.bg.updateBar(bar)
barLength = 0
barLength = self.atrDays + 1
if self.am.count < barLength:
return
# 计算指标数值
self.barList.append(bar)
if len(self.barList) <= 2:
return
else:
self.barList.pop(0)
lastBar = self.barList[-2]
self.getUnitNo()
self.emac_kpi = self.CalcKPI()
#print(self.emac_kpi,bar.close)
pos_multiple = 1
if abs(self.emac_kpi) > 30:
pos_multiple = 2
else:
pos_multiple = 1
#print(self.emac_kpi)
if True: # Trade Time, no matter when, just send signal
if self.pos == 0:
self.longEntered = False
self.shortEntered = False
if self.emac_kpi > 1:
self.buy(bar.close, self.fixedSize * pos_multiple)
elif self.emac_kpi < -1:
self.short(bar.close, self.fixedSize * pos_multiple)
else:
pass
# 持有多头仓位
elif self.pos > 0:
self.longEntered = True
self.shortEntered = False
# 多头止损单
if self.emac_kpi < 1 and self.emac_kpi > -1:
#self.sell(self.shortEntry -2 , self.fixedSize)
self.sell(bar.close, abs(self.pos))
# 空头开仓单
elif self.emac_kpi < -1:
self.sell(bar.close,
abs(self.pos)) # close first then open new
if not self.shortEntered:
#self.short(self.shortEntry -2 , self.fixedSize)
self.short(bar.close, self.fixedSize * pos_multiple)
# 持有空头仓位
elif self.pos < 0:
self.shortEntered = True
self.longEntered = False
# 空头止损单
if self.emac_kpi > -1 and self.emac_kpi < 1:
#self.cover(self.longEntry + 2, self.fixedSize)
self.cover(bar.close, abs(self.pos))
# 多头开仓单
elif self.emac_kpi > 1:
self.cover(bar.close,
abs(self.pos)) # close first then open new
if not self.longEntered:
#self.buy(self.longEntry + 2, self.fixedSize)
self.buy(bar.close, self.fixedSize)
# 收盘平仓 This will not execute
else:
if self.pos > 0:
self.sell(bar.close * 0.99, abs(self.pos))
elif self.pos < 0:
self.cover(bar.close * 1.01, abs(self.pos))
# 发出状态更新事件
self.putEvent()
#update day chart
def ondayBar(self, dayBar):
"""收到日线推送（必须由用户继承实现）"""
self.am.updateBar(dayBar)
self.range = None
self.dayOpen = 0
# 发出状态更新事件
self.putEvent()
#----------------------------------------------------------------------
def onOrder(self, order):
"""收到委托变化推送（必须由用户继承实现）"""
pass
#----------------------------------------------------------------------
def onTrade(self, trade):
# 发出状态更新事件
persisttrade(self.vtSymbol, self.className, trade)
self.putEvent()
#----------------------------------------------------------------------
def onStopOrder(self, so):
"""停止单推送"""
pass
class HgStrategy(CtaTemplate):
"""Demo"""
className = 'haigui'
author = u'zhice'
priceTpye = PRICETYPE_MARKETPRICE # 设置为市价单
# 参数列表，保存了参数的名称
paramList = ['name',
'className',
'author',
'vtSymbol',
'productID',
'shortWindow',
'middleWindow',
'longWindow',
# 交易的实例名信息，一个实例包含一组策略实例
'instanceName',
'instanceId',
'instanceAccount']
# 保存了要用pickle恢复的参数列表
pickleParamList = []
# 同步列表，保存了需要保存到数据库的变量名称
syncList = ['pos']
#----------------------------------------------------------------------
def __init__(self, ctaEngine, setting):
"""Constructor"""
super(HgStrategy, self).__init__(ctaEngine, setting)
self.GOON = False
# 每次启动要重建的参数
self.bg = BarGenerator(self.onBar)
self.cacheDays = max(self.longWindow, (2 * self.middleWindow) + 1)
self.am = ArrayManager(self.cacheDays)
self.myDb = mydb # 数据库引擎
self.hgDbEngine = hgDbEngine(mydb) # cta 数据库操作的一些封装
self.hgReport = hgReport(self.hgDbEngine)
self.monitor = {} # 合约当天的 10日线高低、20日线高低、55日线和ART信息
self.contracts = self.hgDbEngine.getAllContract() # 最新的合约信息
self.sessionID = None # 本地交易
self.frontID = None # 本次交易的
self.logLevel = LOG_INFO # 设置日志输出级别
self.bGenImg = True # 是否生成图像标志位
# self.sessionid = uuid.uuid1() # 本次唯一id
# 关于生成图片与展示html的两个关键变量
self.imgHtmlRootDir = '' # 图片和展示html的根路径
if os.path.exists('/home/ubuntu/vnpy/vnpy-1.8/'):
self.imgHtmlRootDir = '/home/ubuntu/'
print('sys.path.append - /home/ubuntu/vnpy/vnpy-1.8/')
elif os.path.exists('/srv/vnpy18'):
self.imgHtmlRootDir = '/srv/img_html/'
print('sys.path.append - /srv/vnpy18')
# 【重要】所有要pickle存储的数据都要记录在变量中
# True 代表用pickle存储，False代表用正常方式存储
self.pickleItemDict = {"orderList": True,
"tradeList": True,
"hgCellList": True,
"plan_add_price": False,
"atr": False,
"cell_num": False,
"s_or_b": False,
"offsetProfit": False,
"floatProfit": False,
"max_cell_num": False,
"health": False,
"MaxInstanceTotalCellNum": False,
"totalRealUnit": False,
"vtSymbol": False,
"symbolName": False}
# 每次启动要用pickle恢复的数据
#self.hgPosition = {} # 持仓信息
self.orderList = [] # 报单列表
self.tradeList = [] # 成交列表
self.hgCellList = [] # 持仓列表，元素为HgCell
self.plan_add_price = -1 # 加仓价格
self.atr = -1
self.cell_num = 0 # 持仓量
self.s_or_b = '' # 买卖方向
self.offsetProfit = -1 # 平仓盈亏
self.floatProfit = -1 # 浮动盈亏
self.max_cell_num = 3 # 最大持仓量
self.health = True # 交易状态是否健康
self.MaxInstanceTotalCellNum = 12 # 相同实例下单方向的总持仓上限
self.totalRealUnit = 0 # 真实总持仓
self.vtSymbol = ''
self.symbolName = '' # 合约中文名字
fileProductID = self.productID
# TODO通过pickle进行数据恢复
self.hgDbEngine.recoveryFromDb(self)
# 数据库恢复的 productID 与 配置文件中的不一致，属于异常情况，停止交易
if fileProductID <> self.productID:
self.stopTrading()
self.myPrint(LOG_ERROR, '__init__', '文件与数据库中productID不一致，停止交易。')
# 海龟交易主力合约，配置时 symbol 配置的是品种名称，进行翻译。
ret = self.hgDbEngine.getDominantByProductID(self.productID)
# 判断是否需要进行手工移仓
# TODO 目前出现移仓情况需要手动处理
if ret is not None and self.vtSymbol != "" and self.vtSymbol != ret:
self.stopTrading() # 需要进行手工移仓
self.myPrint(LOG_ERROR, '__init__', '需要进行手工移仓。')
if ret is not None and self.vtSymbol == "" :
self.vtSymbol = ret
if ret is None:
self.stopTrading()
self.myPrint(LOG_ERROR, '__init__', '获取主力合约失败。')
self.symbolName = self.contracts[self.vtSymbol]['name'] # 获取合约中文名字
# 只在第一个实例中发送报告
if self.instanceId.endswith('_01'):
self.myPrint(LOG_INFO, 'onInit', '发送报告: ' + self.instanceName)
self.hgReport.sendReport(self.instanceName, self.pickleItemDict)
if self.health:
self.myPrint(LOG_INFO, '__init__', '初始化完成。')
else:
self.myPrint(LOG_ERROR, '__init__', '初始化失败。')
def stopTrading(self, info = ""):
self.myPrint(LOG_ERROR, 'stopTrading', info)
self.health = False
#----------------------------------------------------------------------
def onInit(self):
"""初始化策略（必须由用户继承实现）"""
self.myPrint(LOG_INFO, 'onInit', '海龟交易法则策略开始初始化。')
# 初始化合约信息
#self.contracts = self.hgDbEngine.getAllContract()
initData = self.hgDbEngine.loadDayBar(self.vtSymbol, self.cacheDays)
if len(initData) != self.cacheDays:
self.myPrint(LOG_ERROR, 'onInit', u'【ERROR】【hg】%s 合约初始化数据不足，需要长度为%d ,实际长度为 %d' % (self.vtSymbol, self.longWindow, len(initData)))
self.stopTrading()
return
for bar in initData:
self.am.updateBar(bar)
shortWindowHighBreak = self.am.high[-self.shortWindow:].max()
shortWindowLowBreak = self.am.low[-self.shortWindow:].min()
middleWindowHighBreak = self.am.high[-self.middleWindow:].max()
middleWindowLowBreak = self.am.low[-self.middleWindow:].min()
longWindowHighBreak = self.am.high[-self.longWindow:].max()
longWindowLowBreak = self.am.low[-self.longWindow:].min()
atr = self.am.atr(20, False)
# 如果记录过atr，则使用开仓时候的 atr
if self.atr != -1 and self.cell_num > 0:
atr = self.atr
unit = int(self.instanceAccount * 0.01 / (atr * self.contracts[self.vtSymbol]['size']))
self.monitor = {
'shortWindowHighBreak': shortWindowHighBreak,
'shortWindowLowBreak': shortWindowLowBreak,
'middleWindowHighBreak': middleWindowHighBreak,
'middleWindowLowBreak': middleWindowLowBreak,
'longWindowHighBreak': longWindowHighBreak,
'longWindowLowBreak': longWindowLowBreak,
'atr': atr,
'unit': unit
}
# 增加一个校验，但凡有一个为零，认为初始化不成功，停止交易
if 0 in [shortWindowHighBreak, shortWindowLowBreak, middleWindowHighBreak
, middleWindowLowBreak, longWindowHighBreak, longWindowLowBreak, atr, unit]:
self.myPrint(LOG_ERROR, 'onInit', u'%s合约初始化失败，信息为%s' % (self.vtSymbol, self.monitor))
self.stopTrading()
self.myPrint(LOG_INFO, 'onInit', u'%s合约初始化，信息为%s' % (self.vtSymbol,self.monitor))
# 报单查询测试
gateway = self.ctaEngine.mainEngine.getGateway('CTP')
# 拿到本次交易的 sessionID 和 frontID，可以抽象到上层
self.sessionID = gateway.tdApi.sessionID # 本地交易
self.frontID = gateway.tdApi.frontID # 本次交易的
self.myPrint(LOG_INFO, 'onInit', u'初始化，sessionID = %s; frontID = %s' % (self.sessionID, self.frontID))
self.myPrint(LOG_INFO, 'onInit', '海龟交易法则策略初始化完成。')
# TODO 每次重新登录如果有历史报单，对历史报单的处理
# 前几个函数测试使用
#self.health = False
#self.myPrint(LOG_INFO, 'onInit', '未测试，先关闭真正的交易。')
#self.stopTrading()
#gateway.tdApi.qryTest()
# ----------------------------------------------------------------------
# 生成图像的封装函数
def genImg(self, size, closePrice):
# 每月的图片放在一个文件夹
# 文件用时间命名
strTime = datetime.now().strftime('%Y%m%d-%H%M%S-%f')
strMonth = strTime[0:6]
filePath = self.imgHtmlRootDir + 'img/' + strMonth
if not os.path.exists(filePath):
os.makedirs(filePath)
fileNamePath = filePath + '/' + strTime + '.jpg'
title = self.vtSymbol + " " + strTime
s_h, s_l = self.am.donchian(self.shortWindow, array=True)
m_h, m_l = self.am.donchian(self.middleWindow, array=True)
l_h, l_l = self.am.donchian(self.longWindow, array=True)
s_h = s_h[-size:]
s_l = s_l[-size:]
m_h = m_h[-size:]
m_l = m_l[-size:]
l_h = l_h[-size:]
l_l = l_l[-size:]
close = self.am.close[-size:]
s_h = np.hstack((s_h, s_h[-1]))
s_l = np.hstack((s_l, s_l[-1]))
m_h = np.hstack((m_h, m_h[-1]))
m_l = np.hstack((m_l, m_l[-1]))
l_h = np.hstack((l_h, l_h[-1]))
l_l = np.hstack((l_l, l_l[-1]))
close = np.hstack((close, closePrice))
saveImg(self,fileNamePath, title,s_h, s_l, m_h, m_l, l_h, l_l, close, size+1)
# ----------------------------------------------------------------------
#----------------------------------------------------------------------
def onStart(self):
"""启动策略（必须由用户继承实现）"""
self.myPrint(LOG_INFO, 'onStart', u'海龟交易法则策略启动')
self.putEvent()
#----------------------------------------------------------------------
def onStop(self):
"""停止策略（必须由用户继承实现）"""
self.myPrint(LOG_INFO, 'onStop', u'海龟交易法则策略启动')
self.putEvent()
#----------------------------------------------------------------------
def onTick(self, tick):
"""收到行情TICK推送（必须由用户继承实现）"""
self.bg.updateTick(tick)
# TODO 将来可以添加校验，校验是否订阅的合约都有信号
#----------------------------------------------------------------------
def onBar(self, bar):
"""收到Bar推送（必须由用户继承实现）"""
# TODO 对涨跌停的处理
# TODO 异常值的处理
# TODO 如果委托了，一直不成交怎么办
#strategy.trading = False
#strategy.inited = False
print(bar.__dict__)
self.myPrint(LOG_DEBUG, 'onBar', '进入onBar.')
self.myPrint(LOG_DEBUG, 'onBar', bar.__dict__)
if not self.trading :
self.myPrint(LOG_INFO, 'onBar', 'self.trading is false')
return
if not self.health:
self.myPrint(LOG_ERROR, 'onBar', 'self.health is false')
return
# 是否生成图像处理
if self.bGenImg:
# 生成图像
self.genImg(20, bar.close)
# 生成展示html
genHtmls(self.imgHtmlRootDir)
self.bGenImg = False
#self.buy(3750, 1)
#return
# 测试
#self.monitor['middleWindowHighBreak'] = 3575
# 测试结束
vtSymbol = bar.vtSymbol
# 如果发现有合约初始化未完成，直接返回
if not self.am.inited:
self.myPrint(LOG_ERROR, 'onBar', u'【ERROR】【hg】合约未能正常初始化' % (vtSymbol))
return
# 账户金额有限，如果加仓单位还不到1，则直接返回
if self.monitor['unit'] == 0:
self.myPrint(LOG_ERROR, 'onBar', u'self.monitor[unit] == 0')
return
# 5、如果存在不问稳定的订单状态直接返回
if not self.is_all_cell_stable():
# self.printCells("not self.is_all_cell_stable()")
self.myPrint(LOG_INFO, 'onBar', "not self.is_all_cell_stable()")
return
# TODO 这里可以优化， hand_cell 和 saveIntoDB 重复了。
# 6、如果真实持仓未达到目标状态，下单，更新数据库，并返回
if not self.is_all_cell_get_target_unit():
self.myPrint(LOG_IMPORTANT, 'onBar', "当前订单稳定了，但是 没有达到目标仓位，则继续交易。")
for hgcell in self.hgCellList:
hgcell.hand_cell(self, bar.close)
# 记录在数据库中
self.hgDbEngine.saveIntoDB(self)
return
if not self.calCellNumAndTotalRealUnit() and len(self.hgCellList) > 0:
self.myPrint(LOG_ERROR, 'onBar', 'not self.calCellNumAndTotalRealUnit() and len(self.hgCellList) > 0')
self.stopTrading()
return
if self.cell_num >= 1:
# 更新加仓价格
cell = self.hgCellList[self.cell_num - 1] # 取最后一个持仓
if cell.is_all_order_stable(self) and cell.real_unit == cell.target_unit:
# 订单都稳定了，并且达到了目标持仓，更新加仓价格
if cell.open_direction == 'b':
self.plan_add_price = cell.real_in_price + (cell.N / 2)
if cell.open_direction == 's':
self.plan_add_price = cell.real_in_price - (cell.N / 2)
else:
self.myPrint(LOG_ERROR, 'onBar', '不应该出现这种情况，存在订单不稳定或者 目标真实持仓不一致的情况')
self.stopTrading()
return
# 更新退出价格信息
self.update_plan_stop_price()
# 进行一次数据库写入
self.hgDbEngine.saveIntoDB(self)
# 当前持仓大于最大持仓要求
if self.cell_num >= self.max_cell_num:
self.myPrint(LOG_INFO, 'onBar', u'已达到最大持仓 %d / %d' % (self.cell_num, self.max_cell_num))
return
# 单方向是否达到了最大值
tmpInstanceTotalCellNum = self.hgDbEngine.getInstanceTotalCellNum(self.instanceName, self.s_or_b)
if self.s_or_b and tmpInstanceTotalCellNum >= self.MaxInstanceTotalCellNum:
self.myPrint(LOG_INFO, 'onBar', "tmpInstanceTotalCellNum >= self.MaxInstanceTotalCellNum ,"
"the value is %d / %d " % (
tmpInstanceTotalCellNum, self.MaxInstanceTotalCellNum))
return
# TODO 当前持仓是否满足 6 规则
# TODO 撤销所有的合约
# cell 是否发生变化，如果有发生变化，就不再进行下面的逻辑
isCellChange = False
# 如果未持有合约，判断是否有突破
if self.cell_num == 0:
if bar.close > self.monitor['middleWindowHighBreak']:
# 有向上突破
isCellChange = True
self.s_or_b = 'b'
a_cell = HgCell(vtSymbol, self.s_or_b, self.monitor['unit'],
self.monitor['middleWindowHighBreak'], BREAK_MIDDLEWINDOW, self.monitor['atr'])
self.myPrint(LOG_IMPORTANT, 'onBar', "发现向上突破，开仓信息如下"
"vtSymbol = %s, "
"s_or_b = %s, "
"unit = %d, "
"middleWindowHighBreak = %d, "
"type = %s, "
"atr = %d " % (vtSymbol, self.s_or_b, self.monitor['unit'],
self.monitor['middleWindowHighBreak'], BREAK_MIDDLEWINDOW, self.monitor['atr']))
self.addCell(a_cell)
elif bar.close < self.monitor['middleWindowLowBreak']:
# 有向下突破
isCellChange = True
self.s_or_b = 's'
a_cell = HgCell(vtSymbol, self.s_or_b, self.monitor['unit'],
self.monitor['middleWindowLowBreak'], BREAK_MIDDLEWINDOW, self.monitor['atr'])
self.myPrint(LOG_IMPORTANT, 'onBar', "发现向下突破，开仓信息如下"
"vtSymbol = %s, "
"s_or_b = %s, "
"unit = %d, "
"middleWindowLowBreak = %d, "
"type = %s, "
"atr = %d " % (vtSymbol, self.s_or_b, self.monitor['unit'],
self.monitor['middleWindowLowBreak'],
BREAK_MIDDLEWINDOW, self.monitor['atr']))
self.addCell(a_cell)
# 初始持仓为0，并出现成交，说明开仓了，记录开仓时候的art
if isCellChange == True:
self.atr = self.monitor['atr']
self.myPrint(LOG_IMPORTANT, 'onBar', "开仓atr = %d" % (self.atr))
# TODO 清仓完毕后需要重置一些属性，尤其是ATR
if self.cell_num == 0:
# 下面的操作只有有持仓时才操作
self.myPrint(LOG_DEBUG, 'onBar', "self.cell_num == 0")
return
if not isCellChange:
# 如果持有合约，判断是否触及退出
# 10日线退出法则, 多头头寸，价格低于最近10日最低点时退出
if self.s_or_b == 'b' and bar.close < self.monitor['shortWindowLowBreak']:
self.myPrint(LOG_IMPORTANT, 'onBar', "10日线退出法则, 多头头寸，价格低于最近10日最低点时退出。"
"s_or_b = %s, "
"bar.close = %d,"
"shortWindowLowBreak = %d " % (self.s_or_b, bar.close, self.monitor['shortWindowLowBreak']))
self.quitAllOrders()
isCellChange = True
# 10日线退出法则, 空头头寸，价格高于最近10日最高点时退出
if self.s_or_b == 's' and bar.close > self.monitor['shortWindowHighBreak']:
self.myPrint(LOG_IMPORTANT, 'onBar', "10日线退出法则,空头头寸，价格高于最近10日最高点时退出。"
"s_or_b = %s, "
"bar.close = %d,"
"shortWindowHighBreak = %d " % (
self.s_or_b, bar.close, self.monitor['shortWindowHighBreak']))
self.quitAllOrders()
isCellChange = True
# 如果持有合约，判断是否触及止损
# TODO 涨跌停的处理
if not isCellChange:
isCellChange = self.check_stop_condition(bar.close)
if isCellChange:
self.myPrint(LOG_IMPORTANT, 'onBar', "触及止损。")
# 如果持有合约，判断是否触及加仓，同时判断仓位是否超过限制
if not isCellChange:
isCellChange = self.check_add_condition(bar.close)
if isCellChange:
self.myPrint(LOG_IMPORTANT, 'onBar', "触及加仓。")
# 处理每个cell
if isCellChange:
self.myPrint(LOG_IMPORTANT, 'onBar', "处理cell变动，并记录在数据库中。")
for hgcell in self.hgCellList:
hgcell.hand_cell(self, bar.close)
# 记录在数据库中
self.hgDbEngine.saveIntoDB(self)
# 判断是否所有cell的订单都是稳定的
def is_all_cell_stable(self):
ret = True
for hgcell in self.hgCellList:
ret = hgcell.is_all_order_stable(self) and ret
return ret
# 判断是否所有cell都达到目标订单了
def is_all_cell_get_target_unit(self):
ret = True
for hgcell in self.hgCellList:
ret = (hgcell.target_unit == hgcell.real_unit) and ret
return ret
#----------------------------------------------------------------------
def onOrder(self, order):
"""收到委托变化推送（必须由用户继承实现）"""
# 对于无需做细粒度委托控制的策略，可以忽略onOrder
self.myPrint(LOG_DEBUG, 'onOrder', 'IN')
self.myPrint(LOG_INFO, 'onOrder', str(order.__dict__).decode('unicode-escape'))
self.printCells("*" * 20 + " in onorder")
self.orderList.append(order)
# onOrder -133888101.1.CTP.4
# 更新 cell 中 in_orderId_dict out_orderId_dict 中的订单信息
is_update = False
for hgcell in self.hgCellList:
is_update = (hgcell.updateOrder(order) or is_update)
if is_update:
self.myPrint(LOG_IMPORTANT, 'onOrder', '成功更新 cell orders。')
else:
self.myPrint(LOG_ERROR, 'onOrder', '更新 cell orders 失败。')
self.stopTrading()
# TODO 更新持仓数量信息
# 记录在数据库中
self.hgDbEngine.saveIntoDB(self)
self.printCells("*" * 20 + " out onorder")
#----------------------------------------------------------------------
def onTrade(self, trade):
"""收到成交推送（必须由用户继承实现）"""
# 对于无需做细粒度委托控制的策略，可以忽略onOrder
# 打印过trader信息，里面没有session信息
self.myPrint(LOG_DEBUG, 'onTrade', '')
self.myPrint(LOG_INFO, 'onTrade', str(trade.__dict__).decode('unicode-escape'))
self.tradeList.append(trade)
self.printCells("*"*20 + " in onTrade")
is_update = False
orderid = trade.vtOrderID
# 如果 sessionID 和 frontID 维护了
if self.sessionID is not None and self.frontID is not None:
orderid = self.sessionID + '.' + self.frontID + '.' + orderid
# 把 Trade 更新到 cell 中， 更新完之后，会自动计算当前cell持仓 和 真实价格
for hgcell in self.hgCellList:
is_update = (hgcell.updateTrade(orderid, trade) or is_update)
if is_update:
self.myPrint(LOG_IMPORTANT, 'onTrade', '成功更新 cell trades。')
else:
self.myPrint(LOG_ERROR, 'onTrade', '更新 cell trades 失败。')
self.stopTrading()
# 接收到成交之后打印一下自己
for hgcell in self.hgCellList:
hgcell.print_self()
# 记录在数据库中
self.hgDbEngine.saveIntoDB(self)
# TODO 发送下报告，这里报告中有些字段还没更新，其实不是最佳时机
self.myPrint(LOG_INFO, 'onTrade', '发送报告: ' + self.instanceName)
self.hgReport.sendReport(self.instanceName, self.pickleItemDict)
self.printCells("*" * 20 + " out onTrade")
#----------------------------------------------------------------------
def onStopOrder(self, so):
"""停止单推送"""
self.myPrint("onStopOrder", so.__dict__)
pass
# ----------------------------------------------------------------------
def myPrint(self, funName, date):
print("%s strategyHg funName = %s , date = %s " % (datetime.now(), funName, date))
# 自定义日志级别输出函数
def myPrint(self, level, funName, data):
info = ""
if level == LOG_INFO:
info = '【INFO】'
if level == LOG_DEBUG:
info = '【DEBUG】'
if level == LOG_IMPORTANT:
info = '【IMPORTANT】'
if level == LOG_ERROR:
info = '【ERROR】'
# 添加策略实例标识
info = info + self.instanceName + ' ' + self.instanceId + ' '
if level >= self.logLevel:
info = info + " %s strategyHg funName = %s , data = %s " % (datetime.now(), funName, data)
#print(info) # 输出在文件中
self.writeCtaLog(info) # 输出在数据库中
# 计算真实cell持仓,和 总单位持仓，调用前提是订单已经稳定，订单列表肯定不能为空
def calCellNumAndTotalRealUnit(self):
self.myPrint(LOG_DEBUG, 'calCellNumAndTotalRealUnit', 'IN')
positionCellNum = 0 # 处于已持仓的cell数量
totalRealUnit = 0
ret = True # 返回默认为正常
# 倒叙遍历cell
for cell in list(reversed(self.hgCellList)):
real = cell.real_unit
target = cell.target_unit
totalRealUnit = totalRealUnit + real
# 进入此函数，cell 一定经过了执行 hand_cell in_orderId_dict 不可能为空
if not cell.in_orderId_dict:
self.myPrint(LOG_ERROR, 'calRealCellAndUnitNum', 'not cell.in_orderId_dict')
self.stopTrading()
ret = False
# 订单处于稳定状态，只有一种情况 target == real
if target > 0 and target == real:
positionCellNum = positionCellNum + 1
elif target == 0 and target == real:
self.myPrint(LOG_IMPORTANT, 'calRealCellAndUnitNum', 'cell 清空完毕,将cell删除。')
self.hgCellList.remove(cell)
else:
# 其他情况均为不正常状态
self.myPrint(LOG_ERROR, 'calRealCellAndUnitNum', '其他情况均为不正常状态'
'target = %d, real = %d ' % (target, real))
self.stopTrading()
ret = False
self.cell_num = len(self.hgCellList) # cell数量
self.totalRealUnit = totalRealUnit # 真实总持仓情况
return ret
# ----------------------------------------------------------------------
def addCell(self, cell):
# 增加一个持仓单位
# 当前持仓大于最大持仓要求
if self.cell_num >= self.max_cell_num:
self.myPrint(LOG_IMPORTANT, 'addCell', u'已达到最大持仓 %d / %d' % (self.cell_num, self.max_cell_num))
return
# 单方向是否达到了最大值
tmpInstanceTotalCellNum = self.hgDbEngine.getInstanceTotalCellNum(self.instanceName, self.s_or_b)
if tmpInstanceTotalCellNum >= self.MaxInstanceTotalCellNum:
self.myPrint(LOG_IMPORTANT, 'addCell', "tmpInstanceTotalCellNum >= self.MaxInstanceTotalCellNum ,"
"the value is %d / %d " % (
tmpInstanceTotalCellNum, self.MaxInstanceTotalCellNum))
return
self.cell_num = self.cell_num + 1 # 持仓计数加1
self.hgCellList.append(cell) # 添加在持仓列表中
# ----------------------------------------------------------------------
def quitAllOrders(self):
# 设定所有持仓的目标仓位为0
for cell in self.hgCellList:
cell.target_unit = 0
def check_stop_condition(self, price):
""" 检验是否触发止损条件"""
ret = False # 默认返回True
if self.s_or_b == 'b':
# 多头持仓
for cell in self.hgCellList:
if cell.plan_stop_price is not None:
if price <= cell.plan_stop_price:
# 当前价格小于等于止损价格时，设定目标仓位为0
cell.target_unit = 0
ret = True
else:
self.myPrint(LOG_ERROR, 'check_stop_condition', "check_stop_condition,cell.plan_stop_price is None")
if self.s_or_b == 's':
# 空头持仓
for cell in self.hgCellList:
if cell.plan_stop_price is not None:
if price >= cell.plan_stop_price:
# 当前价格大于等于止损价格时，设定目标仓位为0
cell.target_unit = 0
ret = True
else:
self.myPrint(LOG_ERROR, 'check_stop_condition', "check_stop_condition,cell.plan_stop_price is None")
return ret
# ----------------------------------------------------------------------
def check_add_condition(self, price):
"""检验是否触及加仓条件"""
# 之前已有校验，能进入这个函数说明未达到最大持仓，单方向也满足要求
ret = False
cell = self.hgCellList[len(self.hgCellList) - 1] # 取最后一个持仓
if self.s_or_b == 'b':
# 多头持仓，并且当前价格大约加仓价
if price >= self.plan_add_price:
a_cell = HgCell(self.vtSymbol, self.s_or_b, self.monitor['unit'],
self.plan_add_price, HALF_N, cell.N)
self.myPrint(LOG_IMPORTANT, 'check_add_condition', "触发加仓，信息如下"
"vtSymbol = %s, "
"s_or_b = %s, "
"unit = %d, "
"plan_add_price = %d, "
"type = %s, "
"N = %d " % (self.vtSymbol, self.s_or_b, self.monitor['unit'],
self.plan_add_price,
HALF_N, cell.N))
self.addCell(a_cell)
ret = True
if self.s_or_b == 's':
# 空头持仓，并且当前价格小于加仓价
if price <= self.plan_add_price:
a_cell = HgCell(self.vtSymbol, self.s_or_b, self.monitor['unit'],
self.plan_add_price, HALF_N, cell.N)
self.myPrint(LOG_IMPORTANT, 'check_add_condition', "触发加仓，信息如下"
"vtSymbol = %s, "
"s_or_b = %s, "
"unit = %d, "
"plan_add_price = %d, "
"type = %s, "
"N = %d " % (
self.vtSymbol, self.s_or_b, self.monitor['unit'],
self.plan_add_price,
HALF_N, cell.N))
self.addCell(a_cell)
ret = True
return ret
# ----------------------------------------------------------------------
# 更新 self.plan_stop_price
# 从最后一个仓位开始，计算每个仓位的退出值
def update_plan_stop_price(self):
last_real_in_price = None # 记录上一个价格
last_plan_stop_price = None # 记录上一个止损价格
for cell in list(reversed(self.hgCellList)):
self.real_unit = 0 # 真实持仓单位
self.real_in_price = 0 # 平均入场价格
if cell.real_unit == 0 or cell.real_in_price == 0:
self.myPrint(LOG_ERROR, 'update_plan_stop_price', "cell.real_unit == 0 or cell.real_in_price == 0")
self.stopTrading()
break
tmp_plan_stop_price = None
if self.s_or_b == 'b':
tmp_plan_stop_price = cell.real_in_price - 2 * cell.N
elif self.s_or_b == 's':
tmp_plan_stop_price = cell.real_in_price + 2 * cell.N
# 如果处理的是最后一个cell，直接更新
if last_real_in_price == None:
cell.plan_stop_price = tmp_plan_stop_price
elif 0.8 < float(last_real_in_price)/cell.real_in_price < 1.2:
cell.plan_stop_price = last_plan_stop_price
else:
cell.plan_stop_price = tmp_plan_stop_price
last_real_in_price = cell.real_in_price
last_plan_stop_price = cell.plan_stop_price
# 获取当前实例s_or_b 方向的总持仓数
"""
def getInstanceTotalCellNum(self):
TotalCellNum = 0
d = [
{'$match': {"instanceName": self.instanceName ,"s_or_b" : self.s_or_b}},
{'$group': {'_id': "$instanceName", 'total': {'$sum': "$cell_num"}}}
]
ret = mydb.dbAggregateSum(MAIN_DB_NAME, TB_HG_MAIN, d)
for tmp in ret:
TotalCellNum = int(tmp['total'])
break
print("instanceName:%s %s 方向的总持仓为: %d" % (self.instanceName, self.s_or_b, TotalCellNum))
return TotalCellNum
"""
def printCells(self,info=""):
print(info)
print("start printself")
gt200 = {key: value for key, value in self.__dict__.items() if key not in ['contracts','orderList','tradeList','hgCellList']}
print(str(gt200).decode('unicode-escape'))
print("end printsefl")
print("start printcells")
for cell in self.hgCellList:
cell.print_self()
print("end printcells")
class BollChannelStrategy(CtaTemplate):
"""基于布林通道的交易策略"""
className = 'BollChannelStrategy'
author = u'用Python的交易员'
# 策略参数
bollWindow = 18 # 布林通道窗口数
bollDev = 3.4 # 布林通道的偏差
cciWindow = 10 # CCI窗口数
atrWindow = 30 # ATR窗口数
slMultiplier = 5.2 # 计算止损距离的乘数
initDays = 10 # 初始化数据所用的天数
fixedSize = 1 # 每次交易的数量
# 策略变量
bollUp = 0 # 布林通道上轨
bollDown = 0 # 布林通道下轨
cciValue = 0 # CCI指标数值
atrValue = 0 # ATR指标数值
intraTradeHigh = 0 # 持仓期内的最高点
intraTradeLow = 0 # 持仓期内的最低点
longStop = 0 # 多头止损
shortStop = 0 # 空头止损
# 参数列表，保存了参数的名称
paramList = [
'name', 'className', 'author', 'vtSymbol', 'bollWindow', 'bollDev',
'cciWindow', 'atrWindow', 'slMultiplier', 'initDays', 'fixedSize'
]
# 变量列表，保存了变量的名称
varList = [
'inited', 'trading', 'pos', 'bollUp', 'bollDown', 'cciValue',
'atrValue', 'intraTradeHigh', 'intraTradeLow', 'longStop', 'shortStop'
]
# 同步列表，保存了需要保存到数据库的变量名称
syncList = ['pos', 'intraTradeHigh', 'intraTradeLow']
#----------------------------------------------------------------------
def __init__(self, ctaEngine, setting):
"""Constructor"""
super(BollChannelStrategy, self).__init__(ctaEngine, setting)
self.bg = BarGenerator(self.onBar, 15, self.onXminBar) # 创建K线合成器对象
self.bg30 = BarGenerator(self.onBar, 30, self.on30minBar)
self.am = ArrayManager()
#----------------------------------------------------------------------
def on30minBar(self, bar):
""""""
#----------------------------------------------------------------------
def onInit(self):
"""初始化策略（必须由用户继承实现）"""
self.writeCtaLog(u'%s策略初始化' % self.name)
# 载入历史数据，并采用回放计算的方式初始化策略数值
initData = self.loadBar(self.initDays)
for bar in initData:
self.onBar(bar)
self.putEvent()
#----------------------------------------------------------------------
def onStart(self):
"""启动策略（必须由用户继承实现）"""
self.writeCtaLog(u'%s策略启动' % self.name)
self.putEvent()
#----------------------------------------------------------------------
def onStop(self):
"""停止策略（必须由用户继承实现）"""
self.writeCtaLog(u'%s策略停止' % self.name)
self.putEvent()
#----------------------------------------------------------------------
def onTick(self, tick):
"""收到行情TICK推送（必须由用户继承实现）"""
self.bg.updateTick(tick)
#----------------------------------------------------------------------
def onBar(self, bar):
"""收到Bar推送（必须由用户继承实现）"""
self.bg.updateBar(bar)
#----------------------------------------------------------------------
def onXminBar(self, bar):
"""收到X分钟K线"""
# 全撤之前发出的委托
self.cancelAll()
# 保存K线数据
am = self.am
am.updateBar(bar)
if not am.inited:
return
# 计算指标数值
self.bollUp, self.bollDown = am.boll(self.bollWindow, self.bollDev)
self.cciValue = am.cci(self.cciWindow)
self.atrValue = am.atr(self.atrWindow)
# 判断是否要进行交易
# 当前无仓位，发送开仓委托
if self.pos == 0:
self.intraTradeHigh = bar.high
self.intraTradeLow = bar.low
if self.cciValue > 0:
self.buy(self.bollUp, self.fixedSize, True)
elif self.cciValue < 0:
self.short(self.bollDown, self.fixedSize, True)
# 持有多头仓位
elif self.pos > 0:
self.intraTradeHigh = max(self.intraTradeHigh, bar.high)
self.intraTradeLow = bar.low
self.longStop = self.intraTradeHigh - self.atrValue * self.slMultiplier
self.sell(self.longStop, abs(self.pos), True)
# 持有空头仓位
elif self.pos < 0:
self.intraTradeHigh = bar.high
self.intraTradeLow = min(self.intraTradeLow, bar.low)
self.shortStop = self.intraTradeLow + self.atrValue * self.slMultiplier
self.cover(self.shortStop, abs(self.pos), True)
# 同步数据到数据库
self.saveSyncData()
# 发出状态更新事件
self.putEvent()
#----------------------------------------------------------------------
def onOrder(self, order):
"""收到委托变化推送（必须由用户继承实现）"""
pass
#----------------------------------------------------------------------
def onTrade(self, trade):
# 发出状态更新事件
self.putEvent()
#----------------------------------------------------------------------
def onStopOrder(self, so):
"""停止单推送"""
pass
class TripleMAStrategy04(CtaTemplate):
"""基于三均线的交易策略"""
className = 'TripleMAStrategy04'
author = 'Y.Raul'
# 策略参数
initDays = 10 # 初始化数据所用的天数
addPos = True # 加仓开关
windowCheck = True #交易窗口开关
openWindowSize = 5 #开盘观察窗口，单位分钟
closeWindowSize = 10 #收盘平仓窗口，单位分钟
minDiff = 1 #最小变动单位
# 策略变量
# 仓位设置
stepPos = 1 # 每次交易的数量
maxPos = 4 # 仓位上限
addPosRatio = 3
# 均线设置
maWindow1 = 10
maWindow2 = 20
maWindow3 = 120
maWindow4 = 5
atrWindow = 30 # ATR窗口数
# 出场设置
exitOnTrailingStop = 2 # Trailing Stop 距离
exitOnLossStop = 3 # Loss Stop 距离
# 价格相关变量
intraTradeHigh = 0 # 持仓期内的最高点
intraTradeLow = 0 # 持仓期内的最低点
longStop = 0 # 多头止损
shortStop = 0 # 空头止损
longEntry = 0 # 多头开仓
shortEntry = 0
avgEntryPrice = 0
# 指标相关变量
# ma次新值
ma10 = 0
ma20 = 0
ma30 = 0
# ma最新值
ma11 = 0
ma21 = 0
ma31 = 0
atrValue = 0 # ATR指标数值
orderList = [] # 保存委托代码的列表
# 参数列表，保存了参数的名称
paramList = ['name',
'className',
'author',
'vtSymbol',
'maWindow1',
'maWindow2',
'maWindow3',
'maWindow4'
'initDays',
'addPos',
'stepPos',
'maxPos',
'exitOnTrailingStop',
'exitOnLossStop',
]
# 变量列表，保存了变量的名称
varList = ['inited',
'trading',
'pos',
'ma10',
'ma11',
'ma20',
'ma21',
'ma30',
'ma31',
'atrValue',
'avgPrice']
# 同步列表
syncList = ['pos']
# ----------------------------------------------------------------------
def __init__(self, ctaEngine, setting):
"""Constructor"""
super(TripleMAStrategy04, self).__init__(ctaEngine, setting)
self.EntryPriceList = []
self.bm = BarGenerator(self.onBar, 5, self.onFiveBar)
self.am = ArrayManager(size= self.maWindow3 + 30)
# ----------------------------------------------------------------------
def onInit(self):
"""初始化策略（必须由用户继承实现）"""
self.writeCtaLog(u'%s策略初始化' % self.name)
# 载入历史数据，并采用回放计算的方式初始化策略数值
initData = self.loadBar(self.initDays)
for bar in initData:
self.onBar(bar)
self.putEvent()
# ----------------------------------------------------------------------
def onStart(self):
"""启动策略（必须由用户继承实现）"""
self.writeCtaLog(u'%s策略启动' % self.name)
self.putEvent()
# ----------------------------------------------------------------------
def onStop(self):
"""停止策略（必须由用户继承实现）"""
self.writeCtaLog(u'%s策略停止' % self.name)
self.putEvent()
# ----------------------------------------------------------------------
def onTick(self, tick):
"""收到行情TICK推送（必须由用户继承实现）"""
self.curDateTime = tick.datetime
# 计算交易时间和平仓时间
if self.windowCheck == True:
self.__timeWindow(tick.datetime)
else:
self.tradeWindow = True
self.bm.updateTick(tick)
# ----------------------------------------------------------------------
def onBar(self, bar):
"""收到Bar推送（必须由用户继承实现）"""
# 更新策略执行的时间（用于回测时记录发生的时间）
# 回测数据传送的bar.datetime，为bar的结束时间
self.curDateTime = bar.datetime
# 计算交易时间和平仓时间
if self.windowCheck == True:
self.__timeWindow(bar.datetime)
else:
self.tradeWindow = True
self.bm.updateBar(bar)
# ----------------------------------------------------------------------
def onFiveBar(self, bar):
"""收到5分钟K线"""
# 保存K线数据
self.am.updateBar(bar)
if not self.am.inited:
return
# print bar.datetime
# 撤销之前发出的尚未成交的委托（包括限价单和停止单）
self.cancelAll()
import talib
# 计算指标数值
ma3Array = self.am.sma(self.maWindow3, True)
self.ma30 = round(ma3Array[-2])
self.ma31 = round(ma3Array[-1])
ma3_ma5 = round(talib.SMA(ma3Array, self.maWindow4)[-1])
ma1Array = self.am.sma(self.maWindow1, True)
self.ma10 = round(ma1Array[-2])
self.ma11 = round(ma1Array[-1])
ma1_ma5 = talib.SMA(ma1Array, self.maWindow4)[-1]
ma2Array = self.am.sma(self.maWindow2, True)
self.ma20 = round(ma2Array[-2])
self.ma21 = round(ma2Array[-1])
self.atrValue = round(self.am.atr(self.atrWindow))
# 判断是否要进行交易
# 当前无仓位，发送OCO开仓委托
if self.pos == 0 :
self.intraTradeHigh = bar.high
self.intraTradeLow = bar.low
if self.tradeWindow:
# 开多, bar.close > MA120,MA10 > MA120,MA10 上穿MA20，MA10、MA120向上
if bar.close > self.ma31 and self.ma11 > self.ma31 \
and self.ma10 < self.ma20 and self.ma11 > self.ma21\
and self.ma31 > ma3_ma5 and self.ma11 > ma1_ma5:
self.longEntry = bar.close
self.buy(self.longEntry, self.stepPos, True)
# lastEntryPrice = self.longEntry
self.LossStopPrice = round(self.longEntry * (100.0 -self.exitOnLossStop)/100)
self.EntryPriceList.append(self.longEntry)
# 记录log
log = "\n Trading: {0}\n".format(self.trading)+\
"{0} Buy : bar.close: {1};\n".format(bar.datetime, bar.close) + \
" ma10:{0}; ma11:{1}; ma20:{2}; ma21:{3}; ma30:{4};ma31:{5}\n".format(self.ma10,self.ma11,self.ma20,self.ma21,self.ma30,self.ma31) + \
"ma1_ma5:{0}; ma3_ma5:{1}\n".format(ma1_ma5,ma3_ma5)+\
"LossStopPrice:{0}\n".format(self.LossStopPrice)
self.writeCtaLog(log)
# 开空, bar.close < MA120,MA10 < MA120,MA10 下穿MA20, MA10,MA120向下
elif bar.close < self.ma31 and self.ma11 < self.ma31 \
and self.ma10 > self.ma20 and self.ma11 < self.ma21\
and self.ma31 < ma3_ma5 and self.ma11 < ma1_ma5:
self.shortEntry = bar.close
self.short(self.shortEntry, self.stepPos, True)
# lastEntryPrice = self.shortEntry
self.LossStopPrice = round(self.shortEntry * (100.0 + self.exitOnLossStop)/100)
self.EntryPriceList.append(self.shortEntry)
# 记录log
log = "\n Trading: {0}\n".format(self.trading)+\
"{0} Short : bar.close: {1};\n".format(bar.datetime, bar.close) + \
" ma10:{0}; ma11:{1}; ma20:{2}; ma21:{3}; ma30:{4};ma31:{5}\n".format(self.ma10, self.ma11,
self.ma20, self.ma21,
self.ma30, self.ma31) + \
"ma1_ma5:{0}; ma3_ma5:{1}\n".format(ma1_ma5, ma3_ma5) + \
"LossStopPrice:{0}\n".format(self.LossStopPrice)
self.writeCtaLog(log)
# return
else:
if self.tradeWindow:
# Trailing Stop 跟随止损
if self.exitOnTrailingStop:
# 持有多头仓位
if self.pos > 0 and self.tradeWindow:
self.intraTradeHigh = max(self.intraTradeHigh, bar.high)
self.intraTradeLow = bar.low
self.longStop = round(self.intraTradeHigh - self.atrValue * self.exitOnTrailingStop)
if bar.close < self.longStop:
self.sell(bar.close, abs(self.pos), True)
# 记录log
log = "\n{0} Sell(Trailing Stop) : bar.close: {1};\n".format(bar.datetime, bar.close) + \
"intraTradeHigh:{0}; atrValue:{1}; dev: {2}\n".format(self.intraTradeHigh,self.atrValue,self.exitOnTrailingStop)+\
"LongStop:{0}\n".format(self.longStop)
self.writeCtaLog(log)
self.putEvent()
self.EntryPriceList = []
return
# 持有空头仓位
if self.pos < 0 and self.tradeWindow:
self.intraTradeHigh = bar.high
self.intraTradeLow = min(self.intraTradeLow, bar.low)
self.shortStop = round(self.intraTradeLow + self.atrValue * self.exitOnTrailingStop)
if bar.close > self.shortStop:
self.cover(bar.close, abs(self.pos), True)
# 记录log
log = "\n{0} Cover(Trailing Stop) : bar.close: {1};\n".format(bar.datetime, bar.close) + \
"intraTradeLow:{0}; atrValue:{1}; dev: {2}\n".format(self.intraTradeLow, self.atrValue,
self.exitOnTrailingStop) + \
"LongStop:{0}\n".format(self.longStop)
self.writeCtaLog(log)
self.putEvent()
self.EntryPriceList = []
return
# Loss Stop 固定止损
if self.exitOnLossStop:
# 持有多头仓位
if self.pos > 0 and bar.close < self.LossStopPrice:
# 记录log
log = "\n{0} Sell(Stop Loss) : bar.close: {1};\n".format(bar.datetime, bar.close) + \
"LossStopPrice:{0}\n".format(self.LossStopPrice) + \
"Ratio:{0}%\n".format((1 - bar.close/self.LossStopPrice)*100)
self.writeCtaLog(log)
self.sell(bar.close, abs(self.pos), True)
self.putEvent()
self.EntryPriceList = []
return
# 持有空头仓位
if self.pos < 0 and bar.close > self.LossStopPrice:
# 记录log
log = "\n{0} Cover(Stop Loss) : bar.close: {1};\n".format(bar.datetime, bar.close) + \
"LossStopPrice:{0}\n".format(self.LossStopPrice) +\
"Ratio:{0}%\n".format((1 - bar.close / self.LossStopPrice) * 100)
self.writeCtaLog(log)
self.cover(bar.close, abs(self.pos), True)
self.putEvent()
self.EntryPriceList = []
return
# 加仓
if self.addPos and (self.maxPos - abs(self.pos) > 0):
print self.pos, (self.maxPos - abs(self.pos) )
print self.EntryPriceList
lastEntryPrice = self.EntryPriceList[-1]
# 固定百分比加仓
addPosOnPips= round(lastEntryPrice* self.addPosRatio/100)
self.writeCtaLog(u'\n 加仓判断:{0}，当前仓位:{1}'.format(bar.datetime, self.pos))
# 加多仓
if self.pos > 0 \
and bar.close >= lastEntryPrice + addPosOnPips* self.minDiff:
# 记录log
self.writeCtaLog(u'\n {0},加仓多单{1}手,价格:{2}'.format(bar.datetime, self.stepPos, bar.close))
self.buy(bar.close, self.stepPos, True)
# 更新开仓价格
lastEntryPrice = bar.close
self.EntryPriceList.append(lastEntryPrice)
self.avgEntryPrice = sum(self.EntryPriceList)/len(self.EntryPriceList)
# 更新固定止损价
self.LossStopPrice = round( self.avgEntryPrice* (100.0 - self.exitOnLossStop) / 100)
self.writeCtaLog(u'\n 更新固定止损价:{0}，最新仓位:{1}'.format(self.LossStopPrice,self.pos))
return
# 加空仓
if self.pos < 0 \
and bar.close <= (lastEntryPrice + addPosOnPips*self.minDiff):
self.writeCtaLog(u'{0},加仓空单{1}手,价格:{2}'.format(bar.datetime, self.stepPos, bar.close))
self.short(bar.close, self.stepPos, True)
# 更新开仓价格
lastEntryPrice = bar.close
self.EntryPriceList.append(lastEntryPrice)
self.avgEntryPrice = (sum(self.EntryPriceList)) / len(self.EntryPriceList)
# 更新固定止损价
self.LossStopPrice = round(self.avgEntryPrice * (100.0 + self.exitOnLossStop) / 100)
self.writeCtaLog(u'\n 更新固定止损价:{0}，最新仓位:{1}'.format(self.LossStopPrice, self.pos))
return
# 执行收盘前平仓检查
# self.__dailyCloseCheck(bar)
# 发出状态更新事件
self.putEvent()
# ----------------------------------------------------------------------
def onOrder(self, order):
"""收到委托变化推送（必须由用户继承实现）"""
log = u'\n OnOrder()更新，orderID:{0},{1},totalVol:{2},tradedVol:{3},offset:{4},price:{5},direction:{6},status:{7},orderTime: {7}'\
.format(order.orderID, order.vtSymbol, order.totalVolume,order.tradedVolume,
order.offset, order.price, order.direction, order.status, order.orderTime)
self.writeCtaLog(log)
self.putEvent()
# ----------------------------------------------------------------------
def onTrade(self, trade):
log = u'\n OnTrade()更新，orderID:{0},{1},Vol:{2},price:{3},direction:{4},tradeTime:{5}' \
.format(trade.orderID, trade.vtSymbol, trade.volume,trade.price, trade.direction,trade.tradeTime)
self.writeCtaLog(log)
# 发出状态更新事件
self.putEvent()
# ----------------------------------------------------------------------
def onStopOrder(self, so):
"""停止单推送"""
log = u'\n OnStopOrder()停止单更新，stopOrderID:{0},Vol:{1},price:{2},direction:{3},status:{4}' \
.format(so.stopOrderID, so.volume,so.price, so.direction,so.status)
self.writeCtaLog(log)
def __timeWindow(self, dt):
"""交易与平仓窗口"""
# 螺纹钢交易窗口 避开早盘和夜盘的前5分钟，防止隔夜跳空。
# 日内平仓窗口
self.closeWindow = False
# 交易窗口
self.tradeWindow = False
# 开盘窗口
self.openWindow = False
# 开市期头5分钟波动较大
if (dt.hour == 9 or dt.hour == 21) and dt.minute < self.openWindowSize:
self.openWindow = False
return
# 日盘
if dt.hour == 9 and dt.minute >= 0:
self.tradeWindow = True
return
if dt.hour == 10:
if dt.minute <= 15 or dt.minute >= 30:
self.tradeWindow = True
return
if dt.hour == 11 and dt.minute <= 30:
self.tradeWindow = True
return
if dt.hour == 13 and dt.minute >= 30:
self.tradeWindow = True
return
if dt.hour == 14:
if dt.minute < 60 - self.closeWindowSize:
self.tradeWindow = True
return
else:
self.closeWindow = True
return
# 夜盘
if dt.hour == 21 and dt.minute >= 0:
self.tradeWindow = True
return
if dt.hour == 22 and dt.minute < 60 - self.closeWindowSize:
self.tradeWindow = True
return
else:
self.closeWindow = True
return
def __dailyCloseCheck(self, bar):
"""每天收盘前检查，如果是亏损单，则平掉"""
if self.pos == 0 :
return False
if not self.closeWindow:
return False
# 撤销未成交的订单
self.cancelAll()
log = u'{0},收盘前{1}分钟，撤单及平仓'.format(bar.datetime,self.closeWindowSize)
self.writeCtaLog(log)
self.avgEntryPrice = (sum(self.EntryPriceList)) / len(self.EntryPriceList)
# 记录log
log = "\n{0} __dailyCloseCheck : bar.close: {1};\n".format(bar.datetime, bar.close) + \
"avgPrice:{0}\n".format(self.avgEntryPrice)+\
"pos:{0}\n".format(self.pos)
self.writeCtaLog(log)
# 强制平仓
if self.pos > 0 and bar.close < self.avgEntryPrice:
self.writeCtaLog(u'强制日内平亏损多仓')
# 降低两个滑点
self.sell(bar.close-2*self.minDiff, abs(self.pos),True )
# 记录log
log = "\n{0} Sell(Force) : bar.close: {1};\n".format(bar.datetime, bar.close) + \
"entryPrice:{0}\n".format(bar.close - 2 * self.minDiff)
self.writeCtaLog(log)
return True
if self.pos < 0 and bar.close > self.avgEntryPrice:
self.writeCtaLog(u'强制日内平亏损空仓')
self.cover(bar.close+2*self.minDiff, abs(self.pos),True )
# 记录log
log = "\n{0} Cover(Force) : bar.close: {1};\n".format(bar.datetime, bar.close) + \
"forcePrice:{0}\n".format(bar.close - 2 * self.minDiff)
self.writeCtaLog(log)
return True
return True
class DT_ChengfaStrategy(CtaTemplate):
"""DualThrust交易策略"""
className = 'DT_ChengfaStrategy'
author = u'Leon Zhao'
# 策略参数
fixedSize = 1
k1 = 0.4
k2 = 0.4
rangeDays = 4
initDays = 30 # original value is 10
atrDays = 20
# 策略变量
barList = [] # K线对象的列表
dayOpen = 0
rangeHigh = 0
rangeLow = 0
rangeHighClose = 0
rangeLowClose = 0
range1 = 0
range2 = 0
range = 0
longEntry = 0
shortEntry = 0
exitTime = time(hour=15, minute=20) #will not cover position when day close
longEntered = False
shortEntered = False
# 参数列表，保存了参数的名称
paramList = ['name',
'className',
'author',
'vtSymbol',
'k1',
'k2']
# 变量列表，保存了变量的名称
varList = ['inited',
'trading',
'pos',
'range',
'longEntry',
'shortEntry',
'exitTime']
longEntry1 = 0
shortEntry1 = 0
# 同步列表，保存了需要保存到数据库的变量名称
syncList = ['pos','range','longEntry1','shortEntry1']
#----------------------------------------------------------------------
def __init__(self, ctaEngine, setting):
"""Constructor"""
super(DT_ChengfaStrategy, self).__init__(ctaEngine, setting)
self.bg = BarGenerator(self.onBar,onDayBar = self.ondayBar,vtSymbol =self.vtSymbol)
self.am = ArrayManager()
self.barList = []
self.longEntry1 = 0
self.shortEntry1 = 0
# Read Parameters from Setting files
if 'strParams' in setting:
self.params = setting['strParams']
if len(self.params)>=3:
for p in self.params:
if p[0] == 'unit':
self.fixedSize = p[1]
if p[0] == 'p1':
self.k1 = p[1]
if p[0] == 'p2':
self.k2 = p[1]
if p[0] == 'p3':
self.rangeDays = p[1]
if p[0] == 'p4':
self.atrDays = p[1]
if p[0] == 'p5':
self.initDays = p[1]
else:
# 策略参数
self.fixedSize = 1
self.k1 = 0.4
self.k2 = 0.4
self.rangeDays = 4
self.atrDays = 20
self.initDays = 55 # original value is 10
#print(self.fixedSize,self.k1,self.k2,self.rangeDays,self.initDays)
self.dayOpen = 0
self.rangeHigh = 0
self.rangeLow = 0
self.rangeHighClose = 0
self.rangeLowClose = 0
self.range1 = 0
self.range2 = 0
self.atrValue = 0
self.range = 0
self.longEntry = 0
self.shortEntry = 0
self.exitTime = time(hour=15, minute=20) #will not cover position when day close
self.longEntered = False
self.shortEntered = False
self.testflag = False
#----------------------------------------------------------------------
def onInit(self):
"""初始化策略（必须由用户继承实现）"""
self.writeCtaLog(u'%s策略初始化' %self.name)
# 载入历史数据，并采用回放计算的方式初始化策略数值
initData = self.loadBar(self.initDays)
for bar in initData:
self.onBar(bar)
self.putEvent()
#----------------------------------------------------------------------
def onStart(self):
"""启动策略（必须由用户继承实现）"""
self.writeCtaLog(u'%s策略启动' %self.name)
self.putEvent()
#----------------------------------------------------------------------
def onStop(self):
"""停止策略（必须由用户继承实现）"""
self.writeCtaLog(u'%s策略停止' %self.name)
self.putEvent()
#----------------------------------------------------------------------
def onTick(self, tick):
"""收到行情TICK推送（必须由用户继承实现）"""
#ignore data before real open
if (tick.datetime.hour == 8 or tick.datetime.hour ==20):
return
self.bg.updateTick(tick)
def calcUnitNo(self,atr,fixSize):
dtCap = 0.0
defaultCap = 0.0
unitNo = 0
cust = []
var_sizelist = CtaTemplate.vol_Size
var_size = 0.0
var_Symbol = ""
if len(var_sizelist) == 0:
return fixSize
else:
var_Symbol = var_Symbol.join(list(filter(lambda x: x.isalpha(),self.vtSymbol)))
var_size = float(var_sizelist[var_Symbol][0])
if var_size -0 < 0.01:
return fixSize
var_temp = 0.0
if len(CtaTemplate.cust_Setting) > 0:
cust = CtaTemplate.cust_Setting
for cs in cust:
if cs["StrategyGroup"] == "DT" and cs["Status"] == 'True':
dtCap = cs["CaptialAmt"]
break
if cs["StrategyGroup"] == "Default" and cs["Status"] == 'True':
defaultCap = cs["CaptialAmt"]
if dtCap > 0:
self.capConfig = float(dtCap)
elif defaultCap > 0 :
self.capConfig = float(defaultCap)
else:
self.capConfig = 0.0
unitNo = 0
if self.capConfig -0 < 0.0001:
unitNo = fixSize
elif var_size - 0 < 0.001:
unitNo = fixSize
else:
unitNo = int(self.capConfig * 0.0088 /(atr*var_size))
if unitNo < 1:
unitNo = 1
return unitNo
#---------calcuate range for the last several days
def calcRange(self):
if self.am.count >= self.atrDays + 1 :
self.atrValue = self.am.atr(self.atrDays,False)
if self.atrValue > 0 :
self.fixedSize = self.calcUnitNo(self.atrValue, self.fixedSize)
self.rangeHigh = talib.MAX(self.am.high,self.rangeDays)[-1]
self.rangeLow = talib.MIN(self.am.low,self.rangeDays)[-1]
self.rangeHighClose = talib.MAX(self.am.close,self.rangeDays)[-1]
self.rangeLowClose = talib.MIN(self.am.close,self.rangeDays)[-1]
self.range1 = self.rangeHigh-self.rangeLowClose
self.range2 = self.rangeHighClose -self.rangeLow
#print(self.rangeHigh,self.rangeLow)
if (self.range1 > self.range2) :
calcRange = self.range1
else:
calcRange = self.range2
else:
calcRange = 0
return calcRange
#----------------------------------------------------------------------
def onBar(self, bar):
"""收到Bar推送（必须由用户继承实现）"""
self.fixedSize = 1
if self.reduceCountdown() > 0:
return
# 撤销之前发出的尚未成交的委托（包括限价单和停止单）
self.cancelAll()
self.bg.updateBar(bar)
barLength = 0
# 计算指标数值
self.barList.append(bar)
if len(self.barList) <= 2:
return
else:
self.barList.pop(0)
lastBar = self.barList[-2]
print(bar.close)
if self.testflag:
return
if self.pos == 0:
self.buy(bar.close,self.fixedSize)
elif self.pos > 0:
self.sell(bar.close,abs(self.pos))
if not self.shortEntered:
#self.short(self.shortEntry -2 , self.fixedSize)
self.short(bar.close,self.fixedSize)
self.testflag = True
# 持有空头仓位
elif self.pos < 0:
self.cover(bar.close,abs(self.pos))
if not self.longEntered:
self.buy(bar.close,self.fixedSize)
self.testflag = True
# 发出状态更新事件
self.putEvent()
#update day chart
def ondayBar(self, dayBar):
"""收到日线推送（必须由用户继承实现）"""
self.am.updateBar(dayBar)
self.range = None
self.dayOpen = 0
# 发出状态更新事件
self.putEvent()
#----------------------------------------------------------------------
def onOrder(self, order):
"""收到委托变化推送（必须由用户继承实现）"""
pass
#----------------------------------------------------------------------
def onTrade(self, trade):
# 发出状态更新事件
persisttrade(self.vtSymbol,self.className ,trade)
self.putEvent()
#----------------------------------------------------------------------
def onStopOrder(self, so):
"""停止单推送"""
pass
class AtrRsiStrategy(CtaTemplate):
"""结合ATR和RSI指标的一个分钟线交易策略"""
className = 'AtrRsiStrategy'
author = u'Dingzh.Tobest'
# 策略参数
atrLength = 22 # 计算ATR指标的窗口数
atrMaLength = 10 # 计算ATR均线的窗口数
rsiLength = 5 # 计算RSI的窗口数
rsiEntry = 16 # RSI的开仓信号
trailingPercent = 0.8 # 百分比移动止损
initDays = 10 # 初始化数据所用的天数
fixedSize = 1 # 每次交易的数量
# 策略变量
atrValue = 0 # 最新的ATR指标数值
atrMa = 0 # ATR移动平均的数值
rsiValue = 0 # RSI指标的数值
rsiBuy = 0 # RSI买开阈值
rsiSell = 0 # RSI卖开阈值
intraTradeHigh = 0 # 移动止损用的持仓期内最高价
intraTradeLow = 0 # 移动止损用的持仓期内最低价
# 参数列表，保存了参数的名称
paramList = [
'name', 'className', 'author', 'vtSymbol', 'atrLength', 'atrMaLength',
'rsiLength', 'rsiEntry', 'trailingPercent'
]
# 变量列表，保存了变量的名称
varList = [
'inited', 'trading', 'pos', 'atrValue', 'atrMa', 'rsiValue', 'rsiBuy',
'rsiSell'
]
# 同步列表，保存了需要保存到数据库的变量名称
syncList = ['pos', 'intraTradeHigh', 'intraTradeLow']
#----------------------------------------------------------------------
def __init__(self, ctaEngine, setting):
"""Constructor"""
super(AtrRsiStrategy, self).__init__(ctaEngine, setting)
# 创建K线合成器对象
self.bg = BarGenerator(self.onBar)
self.am = ArrayManager()
# 注意策略类中的可变对象属性（通常是list和dict等），在策略初始化时需要重新创建，
# 否则会出现多个策略实例之间数据共享的情况，有可能导致潜在的策略逻辑错误风险，
# 策略类中的这些可变对象属性可以选择不写，全都放在__init__下面，写主要是为了阅读
# 策略时方便（更多是个编程习惯的选择）
#----------------------------------------------------------------------
def onInit(self):
"""初始化策略（必须由用户继承实现）"""
self.writeCtaLog(u'%s策略初始化' % self.name)
self.writeCtaLog(u'测试')
# 获取当前日期
self.today = str(self.ctaEngine.today)[0:10]
print(self.today)
# 初始化RSI入场阈值
self.rsiBuy = 50 + self.rsiEntry
self.rsiSell = 50 - self.rsiEntry
# 载入历史数据，并采用回放计算的方式初始化策略数值
# initData = self.loadBar(self.initDays)
# jqdata登陆
jqdatasdk.auth(u'XXXXXXXX', u'XXXXXXX')
initData = []
trade_days_list = jqdatasdk.get_trade_days(end_date=self.today,
count=self.initDays)
# 获取前多日如数，按倒叙排序
minute_df = jqdatasdk.get_price('IC1808.CCFX',
start_date=trade_days_list[0],
end_date=self.today,
frequency='minute') # Fix
# 将数据转换为loadCsv中处理的数据类型，方便处理
del minute_df['money']
minute_df = minute_df.reset_index()
minute_df.rename(columns={
'index': 'trade_date',
'open': 'Open',
'close': 'Close',
'high': 'High',
'low': 'Low',
'volume': 'TotalVolume'
},
inplace=True)
minute_df["Date"] = minute_df["trade_date"].map(lambda x: str(x)[0:10])
minute_df["Time"] = minute_df["trade_date"].map(lambda x: str(x)[11:])
del minute_df['trade_date']
# 将数据传入到数据队列当中
for index, row in minute_df.iterrows():
bar = VtBarData()
bar.vtSymbol = "IC1808" # Fix
bar.symbol = "IC1808" # Fix
bar.open = float(row['Open'])
bar.high = float(row['High'])
bar.low = float(row['Low'])
bar.close = float(row['Close'])
bar.date = datetime.strptime(row['Date'],
'%Y-%m-%d').strftime('%Y%m%d')
bar.time = row['Time']
bar.datetime = datetime.strptime(bar.date + ' ' + bar.time,
'%Y%m%d %H:%M:%S')
bar.volume = row['TotalVolume']
initData.append(bar)
print bar.date, bar.time
for bar in initData:
self.onBar(bar)
self.putEvent()
self.writeCtaLog(u'策略初始化成功')
#----------------------------------------------------------------------
def onStart(self):
"""启动策略（必须由用户继承实现）"""
self.writeCtaLog(u'%s策略启动' % self.name)
self.putEvent()
#----------------------------------------------------------------------
def onStop(self):
"""停止策略（必须由用户继承实现）"""
self.writeCtaLog(u'%s策略停止' % self.name)
self.putEvent()
#----------------------------------------------------------------------
def onTick(self, tick):
"""收到行情TICK推送（必须由用户继承实现）"""
self.bg.updateTick(tick)
#----------------------------------------------------------------------
def onBar(self, bar):
"""收到Bar推送（必须由用户继承实现）"""
self.cancelAll()
# 保存K线数据
am = self.am
am.updateBar(bar)
if not am.inited:
return
# 计算指标数值
atrArray = am.atr(self.atrLength, array=True)
self.atrValue = atrArray[-1]
self.atrMa = atrArray[-self.atrMaLength:].mean()
self.rsiValue = am.rsi(self.rsiLength)
# 判断是否要进行交易
# 当前无仓位
if self.pos == 0:
self.intraTradeHigh = bar.high
self.intraTradeLow = bar.low
# ATR数值上穿其移动平均线，说明行情短期内波动加大
# 即处于趋势的概率较大，适合CTA开仓
if self.atrValue > self.atrMa:
# 使用RSI指标的趋势行情时，会在超买超卖区钝化特征，作为开仓信号
if self.rsiValue > self.rsiBuy:
# 这里为了保证成交，选择超价5个整指数点下单
self.buy(bar.close + 5, self.fixedSize)
elif self.rsiValue < self.rsiSell:
self.short(bar.close - 5, self.fixedSize)
# 持有多头仓位
elif self.pos > 0:
# 计算多头持有期内的最高价，以及重置最低价
self.intraTradeHigh = max(self.intraTradeHigh, bar.high)
self.intraTradeLow = bar.low
# 计算多头移动止损
longStop = self.intraTradeHigh * (1 - self.trailingPercent / 100)
# 发出本地止损委托
self.sell(longStop, abs(self.pos), stop=True)
# 持有空头仓位
elif self.pos < 0:
self.intraTradeLow = min(self.intraTradeLow, bar.low)
self.intraTradeHigh = bar.high
shortStop = self.intraTradeLow * (1 + self.trailingPercent / 100)
self.cover(shortStop, abs(self.pos), stop=True)
# 同步数据到数据库
self.saveSyncData()
# 发出状态更新事件
self.putEvent()
#----------------------------------------------------------------------
def onOrder(self, order):
"""收到委托变化推送（必须由用户继承实现）"""
pass
#----------------------------------------------------------------------
def onTrade(self, trade):
# 发出状态更新事件
self.putEvent()
#----------------------------------------------------------------------
def onStopOrder(self, so):
"""停止单推送"""
pass
class TurtleTradingStrategy(CtaTemplate):
"""海龟交易策略"""
className = 'TurtleTradingStrategy'
author = u'用Python的交易员'
# 策略参数
entryWindow = 55 # 入场通道窗口
exitWindow = 20 # 出场通道窗口
atrWindow = 20 # 计算ATR波动率的窗口
initDays = 10 # 初始化数据所用的天数
fixedSize = 1 # 每次交易的数量
# 策略变量
entryUp = 0 # 入场通道上轨
entryDown = 0 # 入场通道下轨
exitUp = 0 # 出场通道上轨
exitDown = 0 # 出场通道下轨
atrVolatility = 0 # ATR波动率
longEntry = 0 # 多头入场价格
shortEntry = 0 # 空头入场价格
longStop = 0 # 多头止损价格
shortStop = 0 # 空头止损价格
# 参数列表，保存了参数的名称
paramList = ['name',
'className',
'author',
'vtSymbol',
'entryWindow',
'exitWindow',
'atrWindow',
'initDays',
'fixedSize']
# 变量列表，保存了变量的名称
varList = ['inited',
'trading',
'pos',
'entryUp',
'entryDown',
'exitUp',
'exitDown',
'longEntry',
'shortEntry',
'longStop',
'shortStop']
# 同步列表，保存了需要保存到数据库的变量名称
syncList = ['pos']
#----------------------------------------------------------------------
def __init__(self, ctaEngine, setting):
"""Constructor"""
super(TurtleTradingStrategy, self).__init__(ctaEngine, setting)
self.bg = BarGenerator(self.onBar)
self.am = ArrayManager()
#----------------------------------------------------------------------
def onInit(self):
"""初始化策略（必须由用户继承实现）"""
self.writeCtaLog(u'%s策略初始化' %self.name)
# 载入历史数据，并采用回放计算的方式初始化策略数值
initData = self.loadBar(self.initDays)
for bar in initData:
self.onBar(bar)
self.putEvent()
#----------------------------------------------------------------------
def onStart(self):
"""启动策略（必须由用户继承实现）"""
self.writeCtaLog(u'%s策略启动' %self.name)
self.putEvent()
#----------------------------------------------------------------------
def onStop(self):
"""停止策略（必须由用户继承实现）"""
self.writeCtaLog(u'%s策略停止' %self.name)
self.putEvent()
#----------------------------------------------------------------------
def onTick(self, tick):
"""收到行情TICK推送（必须由用户继承实现）"""
self.bg.updateTick(tick)
#----------------------------------------------------------------------
def onBar(self, bar):
"""收到Bar推送（必须由用户继承实现）"""
self.cancelAll()
# 保存K线数据
self.am.updateBar(bar)
if not self.am.inited:
return
# 计算指标数值
self.entryUp, self.entryDown = self.am.donchian(self.entryWindow)
self.exitUp, self.exitDown = self.am.donchian(self.exitWindow)
if not self.pos:
self.atrVolatility = self.am.atr(self.atrWindow)
# 判断是否要进行交易
if self.pos == 0:
self.longEntry = 0
self.shortEntry = 0
self.longStop = 0
self.shortStop = 0
self.sendBuyOrders(self.entryUp)
self.sendShortOrders(self.entryDown)
elif self.pos > 0:
# 加仓逻辑
self.sendBuyOrders(self.longEntry)
# 止损逻辑
sellPrice = max(self.longStop, self.exitDown)
self.sell(sellPrice, abs(self.pos), True)
elif self.pos < 0:
# 加仓逻辑
self.sendShortOrders(self.shortEntry)
# 止损逻辑
coverPrice = min(self.shortStop, self.exitUp)
self.cover(coverPrice, abs(self.pos), True)
# 同步数据到数据库
self.saveSyncData()
# 发出状态更新事件
self.putEvent()
#----------------------------------------------------------------------
def onOrder(self, order):
"""收到委托变化推送（必须由用户继承实现）"""
pass
#----------------------------------------------------------------------
def onTrade(self, trade):
"""成交推送"""
if trade.direction == DIRECTION_LONG:
self.longEntry = trade.price
self.longStop = self.longEntry - self.atrVolatility * 2
else:
self.shortEntry = trade.price
self.shortStop = self.shortEntry + self.atrVolatility * 2
# 发出状态更新事件
self.putEvent()
#----------------------------------------------------------------------
def onStopOrder(self, so):
"""停止单推送"""
pass
#----------------------------------------------------------------------
def sendBuyOrders(self, price):
"""发出一系列的买入停止单"""
t = self.pos / self.fixedSize
if t < 1:
self.buy(price, self.fixedSize, True)
if t < 2:
self.buy(price + self.atrVolatility*0.5, self.fixedSize, True)
if t < 3:
self.buy(price + self.atrVolatility, self.fixedSize, True)
if t < 4:
self.buy(price + self.atrVolatility*1.5, self.fixedSize, True)
#----------------------------------------------------------------------
def sendShortOrders(self, price):
""""""
t = self.pos / self.fixedSize
if t > -1:
self.short(price, self.fixedSize, True)
if t > -2:
self.short(price - self.atrVolatility*0.5, self.fixedSize, True)
if t > -3:
self.short(price - self.atrVolatility, self.fixedSize, True)
if t > -4:
self.short(price - self.atrVolatility*1.5, self.fixedSize, True)
class DoubleMaPosStrategy(TargetPosTemplate):
"""双指数均线策略Demo"""
className = 'DoubleMaPosStrategy'
author = u'用Python的交易员'
# 策略参数
fastWindow = 10 # 快速均线参数
slowWindow = 60 # 慢速均线参数
initDays = 10 # 初始化数据所用的天数
# 策略变量
fastMa0 = EMPTY_FLOAT # 当前最新的快速EMA
fastMa1 = EMPTY_FLOAT # 上一根的快速EMA
slowMa0 = EMPTY_FLOAT
slowMa1 = EMPTY_FLOAT
curCapital = 0 #当前可用现金
capital = 0 #初始资金
# 参数列表，保存了参数的名称
paramList = [
'name', 'className', 'author', 'vtSymbol', 'fastWindow', 'slowWindow'
]
# 变量列表，保存了变量的名称
varList = [
'inited', 'trading', 'pos', 'fastMa0', 'fastMa1', 'slowMa0', 'slowMa1'
]
# 同步列表，保存了需要保存到数据库的变量名称
syncList = ['pos']
#----------------------------------------------------------------------
def __init__(self, ctaEngine, setting):
"""Constructor"""
super(DoubleMaPosStrategy, self).__init__(ctaEngine, setting)
self.bg = BarGenerator(self.onBar)
self.am = ArrayManager()
# 注意策略类中的可变对象属性（通常是list和dict等），在策略初始化时需要重新创建，
# 否则会出现多个策略实例之间数据共享的情况，有可能导致潜在的策略逻辑错误风险，
# 策略类中的这些可变对象属性可以选择不写，全都放在__init__下面，写主要是为了阅读
# 策略时方便（更多是个编程习惯的选择）
#----------------------------------------------------------------------
def onInit(self):
"""初始化策略（必须由用户继承实现）"""
self.writeCtaLog(u'双EMA演示策略初始化')
# initData = self.loadBar(self.initDays)
# for bar in initData:
# self.onBar(bar)
self.putEvent()
#----------------------------------------------------------------------
def onStart(self):
"""启动策略（必须由用户继承实现）"""
self.writeCtaLog(u'双EMA演示策略启动')
self.putEvent()
#----------------------------------------------------------------------
def onStop(self):
"""停止策略（必须由用户继承实现）"""
self.writeCtaLog(u'双EMA演示策略停止')
self.putEvent()
#----------------------------------------------------------------------
def onTick(self, tick):
"""收到行情TICK推送（必须由用户继承实现）"""
super(DoubleMaPosStrategy, self).onTick(tick)
self.bg.updateTick(tick)
#----------------------------------------------------------------------
def onBar(self, bar):
"""收到Bar推送（必须由用户继承实现）"""
super(DoubleMaPosStrategy, self).onBar(bar)
am = self.am
am.updateBar(bar)
if not am.inited:
return
# 计算快慢均线
fastMa = am.sma(self.fastWindow, array=True)
self.fastMa0 = fastMa[-1]
self.fastMa1 = fastMa[-2]
slowMa = am.sma(self.slowWindow, array=True)
self.slowMa0 = slowMa[-1]
self.slowMa1 = slowMa[-2]
# 判断买卖
# crossOver = self.fastMa0>self.slowMa0 and self.fastMa1<self.slowMa1 # 金叉上穿
# crossBelow = self.fastMa0<self.slowMa0 and self.fastMa1>self.slowMa1 # 死叉下穿
# 判断买卖
crossOver = self.fastMa0 > self.slowMa0 and self.pos <= 0 # 金叉上穿
crossBelow = self.fastMa0 < self.slowMa0 and self.pos >= 0 # 死叉下穿
# 金叉和死叉的条件是互斥
# 所有的委托均以K线收盘价委托（这里有一个实盘中无法成交的风险，考虑添加对模拟市价单类型的支持）
maxPos = max(int(self.curCapital / self.marginRatio / 1.1 / bar.close),
0)
if maxPos < 20:
maxPos = 0
if self.pos == 0:
if crossOver:
self.setTargetPos(maxPos)
elif crossBelow:
self.setTargetPos(-maxPos)
# 持有多头仓位
elif self.pos > 0:
if crossOver:
self.buy(bar.close, maxPos)
elif crossBelow:
self.setTargetPos(0)
# 持有空头仓位
elif self.pos < 0:
if crossOver:
self.setTargetPos(0)
elif crossBelow:
self.short(bar.close, maxPos)
# 发出状态更新事件
self.putEvent()
#----------------------------------------------------------------------
def onOrder(self, order):
"""收到委托变化推送（必须由用户继承实现）"""
super(DoubleMaPosStrategy, self).onOrder(order)
from vnpy.trader.vtConstant import DIRECTION_LONG, DIRECTION_SHORT, OFFSET_OPEN, OFFSET_CLOSE, PRICETYPE_LIMITPRICE
# 对于无需做细粒度委托控制的策略，可以忽略onOrder
pass
#----------------------------------------------------------------------
def onTrade(self, trade):
"""收到成交推送（必须由用户继承实现）"""
super(DoubleMaPosStrategy, self).onTrade(trade)
pass
#----------------------------------------------------------------------
def onStopOrder(self, so):
"""停止单推送"""
pass
class DoubleMaStrategy(CtaTemplate):
"""双指数均线策略Demo"""
className = 'DoubleMaStrategy'
author = u'张老师'
# 策略参数
fastWindow = 10 # 快速均线参数
slowWindow = 60 # 慢速均线参数
initDays = 10 # 初始化数据所用的天数
fixedSize = 1
# 策略变量
fastMa0 = EMPTY_FLOAT # 当前最新的快速EMA
fastMa1 = EMPTY_FLOAT # 上一根的快速EMA
slowMa0 = EMPTY_FLOAT
slowMa1 = EMPTY_FLOAT
# 参数列表，保存了参数的名称
paramList = [
'name', 'className', 'author', 'vtSymbol', 'fastWindow', 'slowWindow'
]
# 变量列表，保存了变量的名称
varList = [
'inited', 'trading', 'pos', 'fastMa0', 'fastMa1', 'slowMa0', 'slowMa1'
]
# 同步列表，保存了需要保存到数据库的变量名称
syncList = ['pos']
#----------------------------------------------------------------------
def __init__(self, ctaEngine, setting):
"""Constructor"""
super(DoubleMaStrategy, self).__init__(ctaEngine, setting)
self.bg = BarGenerator(self.onBar)
self.am = ArrayManager()
# 注意策略类中的可变对象属性（通常是list和dict等），在策略初始化时需要重新创建，
# 否则会出现多个策略实例之间数据共享的情况，有可能导致潜在的策略逻辑错误风险，
# 策略类中的这些可变对象属性可以选择不写，全都放在__init__下面，写主要是为了阅读
# 策略时方便（更多是个编程习惯的选择）
#----------------------------------------------------------------------
def onInit(self):
"""初始化策略（必须由用户继承实现）"""
self.writeCtaLog(u'双EMA演示策略初始化')
initData = self.loadBar(self.initDays)
for bar in initData:
self.onBar(bar)
self.putEvent()
#----------------------------------------------------------------------
def onStart(self):
"""启动策略（必须由用户继承实现）"""
self.writeCtaLog(u'双EMA演示策略启动')
self.putEvent()
#----------------------------------------------------------------------
def onStop(self):
"""停止策略（必须由用户继承实现）"""
self.writeCtaLog(u'双EMA演示策略停止')
self.putEvent()
#----------------------------------------------------------------------
def onTick(self, tick):
"""收到行情TICK推送（必须由用户继承实现）"""
self.bg.updateTick(tick)
#----------------------------------------------------------------------
def onBar(self, bar):
"""收到Bar推送（必须由用户继承实现）"""
am = self.am
am.updateBar(bar)
if not am.inited:
return
# 计算快慢均线
fastMa = am.sma(self.fastWindow, array=True)
self.fastMa0 = fastMa[-1]
self.fastMa1 = fastMa[-2]
slowMa = am.sma(self.slowWindow, array=True)
self.slowMa0 = slowMa[-1]
self.slowMa1 = slowMa[-2]
# 判断买卖
crossOver = self.fastMa0 > self.slowMa0 and self.fastMa1 < self.slowMa1 # 金叉上穿
crossBelow = self.fastMa0 < self.slowMa0 and self.fastMa1 > self.slowMa1 # 死叉下穿
# 金叉和死叉的条件是互斥
# 所有的委托均以K线收盘价委托（这里有一个实盘中无法成交的风险，考虑添加对模拟市价单类型的支持）
if crossOver:
# 如果金叉时手头没有持仓，则直接做多
if self.pos == 0:
self.buy(bar.close, fixedSize)
# 如果有空头持仓，则先平空，再做多
elif self.pos < 0:
self.cover(bar.close, fixedSize)
self.buy(bar.close, fixedSize)
# 死叉和金叉相反
elif crossBelow:
if self.pos == 0:
self.short(bar.close, fixedSize)
elif self.pos > 0:
self.sell(bar.close, fixedSize)
self.short(bar.close, fixedSize)
# 发出状态更新事件
self.putEvent()
#----------------------------------------------------------------------
def onOrder(self, order):
"""收到委托变化推送（必须由用户继承实现）"""
# 对于无需做细粒度委托控制的策略，可以忽略onOrder
pass
#----------------------------------------------------------------------
def onTrade(self, trade):
"""收到成交推送（必须由用户继承实现）"""
# 对于无需做细粒度委托控制的策略，可以忽略onOrder
pass
#----------------------------------------------------------------------
def onStopOrder(self, so):
"""停止单推送"""
pass
class DoubleMaStrategy(CtaTemplate):
"""双指数均线策略Demo"""
className = 'DoubleMaStrategy'
author = u'用Python的交易员'
# 策略参数
fastWindow = 10 # 快速均线参数
slowWindow = 40 # 慢速均线参数
initDays = 10 # 初始化数据所用的天数
# 策略变量
fastMa0 = EMPTY_FLOAT # 当前最新的快速EMA
fastMa1 = EMPTY_FLOAT # 上一根的快速EMA
slowMa0 = EMPTY_FLOAT
slowMa1 = EMPTY_FLOAT
# 参数列表，保存了参数的名称
paramList = ['name',
'className',
'author',
'vtSymbol',
'fastWindow',
'slowWindow']
# 变量列表，保存了变量的名称
varList = ['inited',
'trading',
'pos',
'fastMa0',
'fastMa1',
'slowMa0',
'slowMa1']
# 同步列表，保存了需要保存到数据库的变量名称
syncList = ['pos']
# ----------------------------------------------------------------------
def __init__(self, ctaEngine, setting):
"""Constructor"""
super(DoubleMaStrategy, self).__init__(ctaEngine, setting)
self.bg = BarGenerator(self.onBar,
self.onBar_min01,
self.onBar_min05,
self.onBar_min15,
self.onBar_min30,
self.onBar_min60,
self.onBar_day01,)
self.am_min01 = copy.copy(ArrayManager())
self.am_min05 = copy.copy(ArrayManager())
self.am_min15 = copy.copy(ArrayManager())
self.am_min30 = copy.copy(ArrayManager())
self.am_min60 = copy.copy(ArrayManager())
self.am_day01 = copy.copy(ArrayManager())
# 注意策略类中的可变对象属性（通常是list和dict等），在策略初始化时需要重新创建，
# 否则会出现多个策略实例之间数据共享的情况，有可能导致潜在的策略逻辑错误风险，
# 策略类中的这些可变对象属性可以选择不写，全都放在__init__下面，写主要是为了阅读
# 策略时方便（更多是个编程习惯的选择）
# ----------------------------------------------------------------------
def onInit(self):
"""初始化策略（必须由用户继承实现）"""
self.writeCtaLog(u'双EMA演示策略初始化')
initData = self.loadBar(self.initDays)
for bar in initData:
self.onBar(bar)
self.putEvent()
# ----------------------------------------------------------------------
def onStart(self):
"""启动策略（必须由用户继承实现）"""
self.writeCtaLog(u'双EMA演示策略启动')
self.putEvent()
# ----------------------------------------------------------------------
def onStop(self):
"""停止策略（必须由用户继承实现）"""
self.writeCtaLog(u'双EMA演示策略停止')
self.putEvent()
# ----------------------------------------------------------------------
def onTick(self, tick):
"""收到行情TICK推送（必须由用户继承实现）"""
self.bg.updateTick(tick)
# ----------------------------------------------------------------------
def onBar(self, bar):
"""收到Bar推送（必须由用户继承实现）"""
# 只有一分钟线，加入到K线合成器中
#if bar.interval == INTERVAL_1M:
if bar.interval == INTERVAL_1M:
self.bg.updateBar_01(bar)
# ----------------------------------------------------------------------
def onBar_min01(self, bar):
self.am_min01.updateBar(bar)
if not self.am_min01.inited:
return
# print("收到01分钟数据：" + str(bar.datetime))
# ----------------------------------------------------------------------
def onBar_min05(self, bar):
self.am_min05.updateBar(bar)
if not self.am_min05.inited:
return
# print("收到05分钟数据from：" + str(bar.datetime_start) + " to "+ str(bar.datetime_end))
# time.sleep(0.5)
# ----------------------------------------------------------------------
def onBar_min15(self, bar):
self.am_min15.updateBar(bar)
if not self.am_min15.inited:
return
# print("收到15分钟数据from：" + str(bar.datetime_start) + " to "+ str(bar.datetime_end))
# time.sleep(0.5)
# ----------------------------------------------------------------------
def onBar_min30(self, bar):
# print("收到30分钟数据from：" + str(bar.datetime_start) + " to " + str(bar.datetime_end))
self.am_min30.updateBar(bar)
if not self.am_min30.inited:
return
# time.sleep(0.5)
# ----------------------------------------------------------------------
def onBar_min60(self, bar):
print("收到60分钟数据from：" + str(bar.datetime_start) + " low " + str(bar.datetime_end))
self.am_min60.updateBar(bar)
if not self.am_min60.inited:
return
# time.sleep(0.5)
self.cancelAll()
am = copy.copy(self.am_min60)
# 计算快慢均线
fastMa = am.sma(self.fastWindow, array=True)
self.fastMa0 = fastMa[-1]
self.fastMa1 = fastMa[-2]
slowMa = am.sma(self.slowWindow, array=True)
self.slowMa0 = slowMa[-1]
self.slowMa1 = slowMa[-2]
# 判断买卖
crossOver = self.fastMa0 >= self.slowMa0 and self.fastMa1 <= self.slowMa1 # 金叉上穿
crossBelow = self.fastMa0 <= self.slowMa0 and self.fastMa1 >= self.slowMa1 # 死叉下穿
# 金叉和死叉的条件是互斥
# 所有的委托均以K线收盘价委托（这里有一个实盘中无法成交的风险，考虑添加对模拟市价单类型的支持）
if crossOver:
# 如果金叉时手头没有持仓，则直接做多
if self.pos == 0:
self.buy(bar.close + 20, 1)
# 如果有空头持仓，则先平空，再做多
elif self.pos < 0:
self.cover(bar.close + 10, 1)
self.buy(bar.close + 20, 1)
# 死叉和金叉相反
elif crossBelow:
if self.pos == 0:
self.short(bar.close - 20, 1)
elif self.pos > 0:
self.sell(bar.close - 20, 1)
self.short(bar.close - 20, 1)
# 发出状态更新事件
self.putEvent()
# ----------------------------------------------------------------------
def onBar_day01(self, bar):
# print("收到01日线数据from：" + str(bar.datetime_start) + " to " + str(bar.datetime_end))
am = self.am_day01
am.updateBar(bar)
if not am.inited:
return
# time.sleep(0.5)
# ----------------------------------------------------------------------
def onOrder(self, order):
"""收到委托变化推送（必须由用户继承实现）"""
# 对于无需做细粒度委托控制的策略，可以忽略onOrder
pass
# ----------------------------------------------------------------------
def onTrade(self, trade):
"""收到成交推送（必须由用户继承实现）"""
# 对于无需做细粒度委托控制的策略，可以忽略onOrder
pass
# ----------------------------------------------------------------------
def onStopOrder(self, so):
"""停止单推送"""
pass
class TrailingStopSignal(CtaSignal):
"""跟随出场信号"""
# ----------------------------------------------------------------------
def __init__(self):
"""Constructor"""
super(TrailingStopSignal, self).__init__()
self.slMultiplier = 5
self.bg = BarGenerator(self.onBar, 15, self.on15Bar)
self.signalPos = 100
# 当前持仓
self.holdPos = 0
# 当前atr值
self.atrValue = 0.0
self.intraTradeHigh = 0.0
self.intraTradeLow = 0.0
self.longStop = 0.0
self.shortStop = 0.0
self.stopExit = 0.0
# ------------------ ----------------------------------------------------
def onTick(self, tick):
"""Tick更新"""
self.bg.updateTick(tick)
# ----------------------------------------------------------------------
def onBar(self, bar):
"""K线更新"""
self.bg.updateBar(bar)
# print "@onBar"
# ----------------------------------------------------------------------
def on15Bar(self, bar):
# print "@on15Bar"
if self.holdPos > 0:
self.intraTradeHigh = max(self.intraTradeHigh, bar.high)
self.longStop = self.intraTradeHigh - self.atrValue * self.slMultiplier
# print bar.datetime
# print "atrValue: ", self.atrValue
# print "holdPos: ", self.holdPos
# print "longStop: ",self.longStop
# print "close: ", bar.close
if self.longStop > bar.close:
self.setSignalPos(0)
# print "tailingPos: ", self.getSignalPos()
elif self.holdPos < 0:
self.intraTradeLow = min(self.intraTradeLow, bar.low)
self.shortStop = self.intraTradeLow + self.atrValue * self.slMultiplier
# print bar.datetime
# print "atrValue: ", self.atrValue
# print "holdPos: ", self.holdPos
# print "shortStop: ",self.shortStop
# print "close: ", bar.close
if self.shortStop < bar.close:
self.setSignalPos(0)
elif self.holdPos == 0:
# 空仓时返回100
self.setSignalPos(100)
class Turtle01Strategy(CtaTemplate):
"""Turtle交易策略"""
className = 'Turtle01Strategy'
author = u'Leon Zhao'
# 策略参数
initDays = 35
fixedSize = 2
longDays = 20
shortDays = 20
longExitDays = 10
shortExitDays = 10
atrDays = 20
exitAtr = 2
# 策略变量
barList = [] # K线对象的列表
newTradeDay = False
lastLongEntry = 0
lastLongTime = 0
lastShortEntry = 0
lastShortTime = 0
upperChannel = 0
lowerChannel = 0
longEntry = 0
shortEntry = 0
entryPrice = 0
entryDirection = 0
entryUsage = 'Turtle'
entryUnitNo = 0
longExit = 0
shortExit = 0
longAtrExit = 0
shortAtrExit = 0
longChannelExit = 0
shortChannelExit = 0
atrValue = 0
rangeLow = 0
exitTime = time(hour=15, minute=20) #will not cover position when day close
longEntered = False
shortEntered = False
# 参数列表，保存了参数的名称
paramList = ['name',
'className',
'author',
'vtSymbol',
'longDays',
'shortDays']
# 变量列表，保存了变量的名称
varList = ['inited',
'trading',
'pos',
'longEntry',
'shortEntry',
'exitTime']
# 同步列表，保存了需要保存到数据库的变量名称
syncList = ['pos','entryPrice','entryDirection','entryUsage','entryUnitNo']
#----------------------------------------------------------------------
def __init__(self, ctaEngine, setting):
"""Constructor"""
super(Turtle01Strategy, self).__init__(ctaEngine, setting)
self.bg = BarGenerator(self.onBar,onDayBar = self.ondayBar)
self.am = ArrayManager(max(self.longDays,self.shortDays,self.atrDays)+1)
self.barList = []
#----------------------------------------------------------------------
def onInit(self):
"""初始化策略（必须由用户继承实现）"""
self.writeCtaLog(u'%s策略初始化' %self.name)
# 载入历史数据，并采用回放计算的方式初始化策略数值
initData = self.loadBar(self.initDays)
for bar in initData:
self.onBar(bar)
self.putEvent()
#----------------------------------------------------------------------
def onStart(self):
"""启动策略（必须由用户继承实现）"""
self.writeCtaLog(u'%s策略启动' %self.name)
# No need to add calculation of the Turtle Channel on Start, it may not change over days.
#self.calcPrepare()
self.putEvent()
def readLastTrade(self,):
#read last trade data from database
pass
def calcPrepare(self):
#calculate initials of the strategy
barLength = 0
barLength = max(self.longDays,self.shortDays,self.atrDays)
if self.am.count < barLength + 1:
return
#self.atrValue = talib.ATR(self.am.high, self.am.low, self.am.close,self.atrDays)[-1]
self.atrValue = self.am.atr(self.atrDays,False)
# = atrLine[-1]
self.upperChannel = talib.MAX(self.am.high,self.longDays)[-1]
self.lowerChannel = talib.MIN(self.am.low,self.shortDays)[-1]
self.longChannelExit = talib.MIN(self.am.low,self.longExitDays)[-1]
self.shortChannelExit = talib.MAX(self.am.high,self.shortExitDays)[-1]
def calcKPI(self):
if self.pos>0:
self.longAtrExit = int(self.lastLongEntry - 2*self.atrValue)
if self.longAtrExit > self.longChannelExit:
self.longExit = self.longAtrExit
else:
self.longExit = self.longChannelExit
if self.entryUnitNo == 1:
self.longEntry = int(self.lastLongEntry + self.atrValue)
elif self.entryUnitNo == 2:
self.longEntry = int(self.lastLongEntry +0.5*self.atrValue)
else:
self.longEntry = 0
elif self.pos == 0:
self.longEntry = self.upperChannel
self.shortEntry = self.lowerChannel
else:
self.shortAtrExit = int(self.lastShortEntry + 2*self.atrValue)
if self.shortAtrExit < self.shortChannelExit:
self.shortExit = self.shortAtrExit
else:
self.shortExit = self.shortChannelExit
if self.entryUnitNo == 1:
self.shortEntry = int(self.lastShortEntry-self.atrValue)
elif self.entryUnitNo == 2:
self.shortEntry = int(self.lastShortEntry-0.5*self.atrValue)
else:
self.shortEntry = 0
#----------------------------------------------------------------------
def onStop(self):
"""停止策略（必须由用户继承实现）"""
self.writeCtaLog(u'%s策略停止' %self.name)
self.putEvent()
#----------------------------------------------------------------------
def onTick(self, tick):
"""收到行情TICK推送（必须由用户继承实现）"""
self.bg.updateTick(tick)
#----------------------------------------------------------------------
def onBar(self, bar):
"""收到Bar推送（必须由用户继承实现）"""
# 撤销之前发出的尚未成交的委托（包括限价单和停止单）
self.cancelAll()
self.bg.updateBar(bar)
barLength = 0
barLength = max(self.longDays,self.shortDays,self.atrDays)
if self.am.count < barLength + 1:
return
# 计算指标数值
self.barList.append(bar)
if len(self.barList) <= 2:
return
else:
self.barList.pop(0)
lastBar = self.barList[-2]
# 新的一天
if (lastBar.datetime.hour == 15 or (lastBar.datetime.hour==14 and lastBar.datetime.minute==59)) and ((bar.datetime.hour == 21) or (bar.datetime.hour == 9)):
# 如果已经初始化
if not self.upperChannel :
#do things:
self.calcPrepare()
else:
pass
if self.pos == 0:
self.lastLongTime = 0
self.lastShortTime = 0
self.entryUnitNo = 0
self.calcKPI()
if self.pos > 0:
#self.sell(self.longExit,self.fixedSize,stop)
if bar.close < self.longExit:
self.sell(bar.close-2,self.pos)
elif bar.close > self.longEntry and self.longEntry > 0 :
self.buy(bar.close+2,self.fixedSize)
else:
pass
elif self.pos == 0:
#self.entryUnitNo = 0
if bar.close > self.longEntry and self.longEntry > 0 :
self.buy(bar.close+2,self.fixedSize)
elif bar.close < self.shortEntry and self.shortEntry > 0:
self.short(bar.close -2, self.fixedSize)
else:
pass
else:
if bar.close < self.shortEntry and self.shortEntry > 0 :
self.short(bar.close-2,self.fixedSize)
elif bar.close > self.shortExit:
self.cover(bar.close+2,abs(self.pos))
else:
pass
# 发出状态更新事件
self.putEvent()
#update day chart
def ondayBar(self, dayBar):
"""收到日线推送（必须由用户继承实现）"""
self.am.updateBar(dayBar)
self.calcPrepare()
# 发出状态更新事件
self.putEvent()
#----------------------------------------------------------------------
def onOrder(self, order):
"""收到委托变化推送（必须由用户继承实现）"""
#if order.status == STATUS_ALLTRADED and self.pos != 0:
# How do I know the last trade is open or exit?
# self.entryUnitNo = self.entryUnitNo + 1
#----------------------------------------------------------------------
def onTrade(self, trade):
# 发出状态更新事件
if trade.direction == DIRECTION_LONG and trade.offset == OFFSET_OPEN:
self.entryUnitNo = self.entryUnitNo + 1
self.lastLongEntry = trade.price
self.entryPrice = trade.price
self.entryDirection = DIRECTION_LONG
elif trade.direction == DIRECTION_SHORT and trade.offset == OFFSET_OPEN:
self.entryUnitNo = self.entryUnitNo + 1
self.lastShortEntry = trade.price
self.entryPrice = trade.price
self.entryDirection = DIRECTION_SHORT
elif (trade.offset == OFFSET_CLOSE or trade.offset == OFFSET_CLOSETODAY ):
#print(self.pos)
self.entryUnitNo = 0
self.lastLongEntry = 0
self.lastShortEntry = 0
self.entryPrice = 0
self.entryDirection = OFFSET_CLOSE
else:
pass
self.putEvent()
#----------------------------------------------------------------------
def onStopOrder(self, so):
"""停止单推送"""
pass
class TestPriceStrategy(CtaTemplate):
"""Turtle交易策略"""
className = 'TestPriceStrategy'
author = u'Leon Zhao'
# 策略参数
fixedSize = 1
longDays = 20
shortDays = 20
longExitDays = 10
shortExitDays = 10
initDays = 35
atrDays = 20
exitAtr = 2
# 策略变量
barList = [] # K线对象的列表
newTradeDay = False
lastLongEntry = 0
lastLongTime = 0
lastShortEntry = 0
lastShortTime = 0
upperChannel = 0
lowerChannel = 0
longEntry = 0
shortEntry = 0
entryPrice = 0
entryDirection = 0
entryUsage = 'Turtle'
entryUnitNo = 0
longExit = 0
shortExit = 0
longAtrExit = 0
shortAtrExit = 0
longChannelExit = 0
shortChannelExit = 0
atrValue = 0
entryAtr = 0
rangeLow = 0
exitTime = time(hour=15,
minute=20) #will not cover position when day close
longEntered = False
shortEntered = False
capConfig = 0.0
onTradeCnt = 0
previousTrade = 0
bookTime = datetime.now()
# 参数列表，保存了参数的名称
paramList = [
'name', 'className', 'author', 'vtSymbol', 'longDays', 'shortDays'
]
# 变量列表，保存了变量的名称
varList = [
'inited', 'trading', 'pos', 'longEntry', 'shortEntry', 'exitTime',
'upperChannel', 'lowerChannel'
]
# 同步列表，保存了需要保存到数据库的变量名称
syncList = [
'pos', 'entryPrice', 'entryDirection', 'entryUsage', 'entryUnitNo',
'lastLongEntry', 'lastShortEntry', 'entryAtr'
]
#----------------------------------------------------------------------
def __init__(self, ctaEngine, setting):
"""Constructor"""
super(TestPriceStrategy, self).__init__(ctaEngine, setting)
self.bg = BarGenerator(self.onBar,
onDayBar=self.ondayBar,
vtSymbol=self.vtSymbol)
self.am = ArrayManager(
max(self.longDays, self.shortDays, self.atrDays) + 1)
self.barList = []
if 'strParams' in setting:
self.params = setting['strParams']
if len(self.params) >= 3:
for p in self.params:
if p[0] == 'unit':
self.fixedSize = p[1]
if p[0] == 'p1':
self.longDays = p[1]
if p[0] == 'p2':
self.shortDays = p[1]
if p[0] == 'p3':
self.longExitDays = p[1]
if p[0] == 'p4':
self.shortExitDays = p[1]
if p[0] == 'p5':
self.initDays = p[1]
else:
# 策略参数
self.fixedSize = 1
self.longDays = 20
self.shortDays = 20
self.longExitDays = 10
self.shortExitDays = 10
self.initDays = 35
#print("ma debug:",self.fixedSize,self.longDays,self.shortDays,self.longExitDays,self.shortExitDays,self.initDays)
# Use class variant should be OK, however, to be save just instance them.
self.newTradeDay = False
self.lastLongEntry = 0
self.lastLongTime = 0
self.lastShortEntry = 0
self.lastShortTime = 0
self.upperChannel = 0
self.lowerChannel = 0
self.longEntry = 0
self.shortEntry = 0
self.entryPrice = 0
self.entryDirection = 0
self.entryUsage = 'Turtle'
self.entryUnitNo = 0
self.longExit = 0
self.shortExit = 0
self.longAtrExit = 0
self.shortAtrExit = 0
self.longChannelExit = 0
self.shortChannelExit = 0
self.atrValue = 0
self.entryAtr = 0
self.rangeLow = 0
self.exitTime = time(
hour=15, minute=20) #will not cover position when day close
self.longEntered = False
self.shortEntered = False
self.capConfig = 0.0
self.onTradeCnt = 0
self.bookTime = datetime.now()
self.buyCnt = 0
#----------------------------------------------------------------------
def onInit(self):
"""初始化策略（必须由用户继承实现）"""
self.writeCtaLog(u'%s策略初始化' % self.name)
# 载入历史数据，并采用回放计算的方式初始化策略数值
initData = self.loadBar(self.initDays)
for bar in initData:
self.onBar(bar)
self.putEvent()
#----------------------------------------------------------------------
def onStart(self):
"""启动策略（必须由用户继承实现）"""
self.writeCtaLog(u'%s策略启动' % self.name)
# No need to add calculation of the Turtle Channel on Start, it may not change over days.
#self.calcPrepare()
self.readLastTrade()
self.putEvent()
def readLastTrade(self):
#read last trade data from database
#In fact no need after I persist those two values.
if self.pos > 0:
self.lastLongEntry = self.entryPrice
self.lastShortEntry = 0
elif self.pos < 0:
self.lastShortEntry = self.entryPrice
self.lastLongEntry = 0
pass
def calcUnitNo(self, atr, fixSize):
turtleCap = 0.0
defaultCap = 0.0
unitNo = 0
cust = []
var_sizelist = CtaTemplate.vol_Size
var_size = 0.0
var_Symbol = ""
if len(var_sizelist) == 0:
return fixSize
else:
var_Symbol = var_Symbol.join(
list(filter(lambda x: x.isalpha(), self.vtSymbol)))
var_size = float(var_sizelist[var_Symbol][0])
if var_size - 0 < 0.01:
return fixSize
var_temp = 0.0
if len(CtaTemplate.cust_Setting) > 0:
cust = CtaTemplate.cust_Setting
for cs in cust:
if cs["StrategyGroup"] == "Turtle" and cs["Status"] == 'True':
turtleCap = cs["CaptialAmt"]
break
if cs["StrategyGroup"] == "Default" and cs["Status"] == 'True':
defaultCap = cs["CaptialAmt"]
if turtleCap > 0:
self.capConfig = float(turtleCap)
elif defaultCap > 0:
self.capConfig = float(defaultCap)
else:
self.capConfig = 0.0
unitNo = 0
if self.capConfig - 0 < 0.0001:
unitNo = fixSize
elif var_size - 0 < 0.001:
unitNo = fixSize
else:
unitNo = int(self.capConfig * 0.005 / (atr * var_size))
if unitNo < 1:
unitNo = 1
return unitNo
def calcPrepare(self):
#calculate initials of the strategy
barLength = 0
barLength = max(self.longDays, self.shortDays, self.atrDays)
if self.am.count < barLength + 1:
return
#self.atrValue = talib.ATR(self.am.high, self.am.low, self.am.close,self.atrDays)[-1]
self.atrValue = self.am.atr(self.atrDays, False)
# = atrLine[-1]
if self.atrValue > 0:
self.fixedSize = self.calcUnitNo(self.atrValue, self.fixedSize)
#call method to calc unit
self.upperChannel = talib.MAX(self.am.high, self.longDays)[-1]
self.lowerChannel = talib.MIN(self.am.low, self.shortDays)[-1]
self.longChannelExit = talib.MIN(self.am.low, self.longExitDays)[-1]
self.shortChannelExit = talib.MAX(self.am.high, self.shortExitDays)[-1]
def calcKPI(self):
if self.pos > 0:
self.longAtrExit = int(self.lastLongEntry - 2 * self.entryAtr)
if self.longAtrExit > self.longChannelExit:
self.longExit = self.longAtrExit
else:
self.longExit = self.longChannelExit
if self.entryUnitNo == 1:
self.longEntry = int(self.lastLongEntry + self.entryAtr)
elif self.entryUnitNo == 2:
self.longEntry = int(self.lastLongEntry + 0.5 * self.entryAtr)
else:
self.longEntry = 0
elif self.pos == 0:
self.longEntry = self.upperChannel
self.shortEntry = self.lowerChannel
else:
self.shortAtrExit = int(self.lastShortEntry + 2 * self.entryAtr)
if self.shortAtrExit < self.shortChannelExit:
self.shortExit = self.shortAtrExit
else:
self.shortExit = self.shortChannelExit
if self.entryUnitNo == 1:
self.shortEntry = int(self.lastShortEntry - self.entryAtr)
elif self.entryUnitNo == 2:
self.shortEntry = int(self.lastShortEntry -
0.5 * self.entryAtr)
else:
self.shortEntry = 0
#----------------------------------------------------------------------
def onStop(self):
"""停止策略（必须由用户继承实现）"""
self.writeCtaLog(u'%s策略停止' % self.name)
self.putEvent()
#----------------------------------------------------------------------
def onTick(self, tick):
"""收到行情TICK推送（必须由用户继承实现）"""
self.bg.updateTick(tick)
#----------------------------------------------------------------------
def onBar(self, bar):
"""收到Bar推送（必须由用户继承实现）"""
# 撤销之前发出的尚未成交的委托（包括限价单和停止单）
#self.cancelAll()
self.bg.updateBar(bar)
print(self.buyCnt)
self.fixedSize = 11
if self.buyCnt == 1135:
self.onTradeCnt = 0
sendPrice = float(bar.close)
self.short(sendPrice - 2, 11)
if self.buyCnt == 1137:
self.onTradeCnt = 0
sendPrice = float(bar.close)
self.short(sendPrice - 20, 11)
self.buyCnt += 1
return
barLength = 0
barLength = max(self.longDays, self.shortDays, self.atrDays)
if self.am.count < barLength + 1:
return
# 计算指标数值
self.barList.append(bar)
if len(self.barList) <= 2:
return
else:
self.barList.pop(0)
lastBar = self.barList[-2]
# 新的一天
if (lastBar.datetime.hour == 15 or lastBar.datetime.hour == 14) and (
(bar.datetime.hour == 21) or (bar.datetime.hour == 9)):
# 如果已经初始化
if not self.upperChannel:
#do things:
self.calcPrepare()
else:
pass
if self.pos == 0:
self.lastLongTime = 0
self.lastShortTime = 0
self.entryUnitNo = 0
self.entryAtr = self.atrValue
self.calcKPI()
if self.pos > 0:
#self.sell(self.longExit,self.fixedSize,stop)
if bar.close < self.longExit:
self.sell(bar.close - 2, abs(self.pos))
elif bar.close > self.longEntry and self.longEntry > 0:
self.buy(bar.close + 1, self.fixedSize)
self.bookTime = datetime.now()
self.onTradeCnt = 0
else:
pass
elif self.pos == 0:
#self.entryUnitNo = 0
if bar.close > self.longEntry and self.longEntry > 0:
self.buy(bar.close + 1, self.fixedSize)
self.bookTime = datetime.now()
self.onTradeCnt = 0
elif bar.close < self.shortEntry and self.shortEntry > 0:
self.short(bar.close - 1, self.fixedSize)
self.bookTime = datetime.now()
self.onTradeCnt = 0
else:
pass
else:
if bar.close < self.shortEntry and self.shortEntry > 0:
self.short(bar.close - 1, self.fixedSize)
self.bookTime = datetime.now()
self.onTradeCnt = 0
elif bar.close > self.shortExit:
self.cover(bar.close + 1, abs(self.pos))
else:
pass
# 发出状态更新事件
self.putEvent()
#update day chart
def ondayBar(self, dayBar):
"""收到日线推送（必须由用户继承实现）"""
self.am.updateBar(dayBar)
self.calcPrepare()
# 发出状态更新事件
self.putEvent()
#----------------------------------------------------------------------
def onOrder(self, order):
"""收到委托变化推送（必须由用户继承实现）"""
#if order.status == STATUS_ALLTRADED and self.pos != 0:
# How do I know the last trade is open or exit?
# self.entryUnitNo = self.entryUnitNo + 1
#----------------------------------------------------------------------
def onTrade(self, trade):
# 发出状态更新事件
if trade.direction == DIRECTION_LONG and trade.offset == OFFSET_OPEN:
if (trade.volume + self.onTradeCnt) == self.fixedSize:
self.entryUnitNo = self.entryUnitNo + 1
else:
self.onTradeCnt = trade.volume
self.writeCtaLog(u'%s: 部分成交， 进场次数未累加，注意！' % self.name)
self.lastLongEntry = trade.price
self.entryPrice = trade.price
self.entryDirection = DIRECTION_LONG
self.entryAtr = self.atrValue
elif trade.direction == DIRECTION_SHORT and trade.offset == OFFSET_OPEN:
if (trade.volume + self.onTradeCnt) == self.fixedSize:
self.entryUnitNo = self.entryUnitNo + 1
else:
self.onTradeCnt = trade.volume + self.onTradeCnt
self.writeCtaLog(u'%s: 部分成交， 进场次数未累加，注意！' % self.name)
self.lastShortEntry = trade.price
self.entryPrice = trade.price
self.entryDirection = DIRECTION_SHORT
self.entryAtr = self.atrValue
elif (trade.offset == OFFSET_CLOSE
or trade.offset == OFFSET_CLOSETODAY):
#print(self.pos)
self.entryUnitNo = 0
self.lastLongEntry = 0
self.lastShortEntry = 0
self.entryPrice = 0
self.entryDirection = OFFSET_CLOSE
else:
pass
self.putEvent()
#----------------------------------------------------------------------
def onStopOrder(self, so):
"""停止单推送"""
pass
class KkStrategy(CtaTemplate):
"""基于King Keltner通道的交易策略"""
className = 'KkStrategy'
author = u'用Python的交易员'
# 策略参数
kkLength = 11 # 计算通道中值的窗口数
kkDev = 1.6 # 计算通道宽度的偏差
trailingPrcnt = 0.8 # 移动止损
initDays = 10 # 初始化数据所用的天数
fixedSize = 1 # 每次交易的数量
# 策略变量
kkUp = 0 # KK通道上轨
kkDown = 0 # KK通道下轨
intraTradeHigh = 0 # 持仓期内的最高点
intraTradeLow = 0 # 持仓期内的最低点
buyOrderIDList = [] # OCO委托买入开仓的委托号
shortOrderIDList = [] # OCO委托卖出开仓的委托号
orderList = [] # 保存委托代码的列表
# 参数列表，保存了参数的名称
paramList = ['name',
'className',
'author',
'vtSymbol',
'kkLength',
'kkDev']
# 变量列表，保存了变量的名称
varList = ['inited',
'trading',
'pos',
'kkUp',
'kkDown']
# 同步列表，保存了需要保存到数据库的变量名称
syncList = ['pos',
'intraTradeHigh',
'intraTradeLow']
#----------------------------------------------------------------------
def __init__(self, ctaEngine, setting):
"""Constructor"""
super(KkStrategy, self).__init__(ctaEngine, setting)
self.bg = BarGenerator(self.onBar, 5, self.onFiveBar) # 创建K线合成器对象
self.am = ArrayManager()
self.buyOrderIDList = []
self.shortOrderIDList = []
self.orderList = []
#----------------------------------------------------------------------
def onInit(self):
"""初始化策略（必须由用户继承实现）"""
self.writeCtaLog(u'%s策略初始化' %self.name)
# 载入历史数据，并采用回放计算的方式初始化策略数值
initData = self.loadBar(self.initDays)
for bar in initData:
self.onBar(bar)
self.putEvent()
#----------------------------------------------------------------------
def onStart(self):
"""启动策略（必须由用户继承实现）"""
self.writeCtaLog(u'%s策略启动' %self.name)
self.putEvent()
#----------------------------------------------------------------------
def onStop(self):
"""停止策略（必须由用户继承实现）"""
self.writeCtaLog(u'%s策略停止' %self.name)
self.putEvent()
#----------------------------------------------------------------------
def onTick(self, tick):
"""收到行情TICK推送（必须由用户继承实现）"""
self.bg.updateTick(tick)
#----------------------------------------------------------------------
def onBar(self, bar):
"""收到Bar推送（必须由用户继承实现）"""
self.bg.updateBar(bar)
#----------------------------------------------------------------------
def onFiveBar(self, bar):
"""收到5分钟K线"""
# 撤销之前发出的尚未成交的委托（包括限价单和停止单）
for orderID in self.orderList:
self.cancelOrder(orderID)
self.orderList = []
# 保存K线数据
am = self.am
am.updateBar(bar)
if not am.inited:
return
# 计算指标数值
self.kkUp, self.kkDown = am.keltner(self.kkLength, self.kkDev)
# 判断是否要进行交易
# 当前无仓位，发送OCO开仓委托
if self.pos == 0:
self.intraTradeHigh = bar.high
self.intraTradeLow = bar.low
self.sendOcoOrder(self.kkUp, self.kkDown, self.fixedSize)
# 持有多头仓位
elif self.pos > 0:
self.intraTradeHigh = max(self.intraTradeHigh, bar.high)
self.intraTradeLow = bar.low
l = self.sell(self.intraTradeHigh*(1-self.trailingPrcnt/100),
abs(self.pos), True)
self.orderList.extend(l)
# 持有空头仓位
elif self.pos < 0:
self.intraTradeHigh = bar.high
self.intraTradeLow = min(self.intraTradeLow, bar.low)
l = self.cover(self.intraTradeLow*(1+self.trailingPrcnt/100),
abs(self.pos), True)
self.orderList.extend(l)
# 同步数据到数据库
self.saveSyncData()
# 发出状态更新事件
self.putEvent()
#----------------------------------------------------------------------
def onOrder(self, order):
"""收到委托变化推送（必须由用户继承实现）"""
pass
#----------------------------------------------------------------------
def onTrade(self, trade):
if self.pos != 0:
# 多头开仓成交后，撤消空头委托
if self.pos > 0:
for shortOrderID in self.shortOrderIDList:
self.cancelOrder(shortOrderID)
# 反之同样
elif self.pos < 0:
for buyOrderID in self.buyOrderIDList:
self.cancelOrder(buyOrderID)
# 移除委托号
for orderID in (self.buyOrderIDList + self.shortOrderIDList):
if orderID in self.orderList:
self.orderList.remove(orderID)
# 发出状态更新事件
self.putEvent()
#----------------------------------------------------------------------
def sendOcoOrder(self, buyPrice, shortPrice, volume):
"""
发送OCO委托
OCO(One Cancel Other)委托：
1. 主要用于实现区间突破入场
2. 包含两个方向相反的停止单
3. 一个方向的停止单成交后会立即撤消另一个方向的
"""
# 发送双边的停止单委托，并记录委托号
self.buyOrderIDList = self.buy(buyPrice, volume, True)
self.shortOrderIDList = self.short(shortPrice, volume, True)
# 将委托号记录到列表中
self.orderList.extend(self.buyOrderIDList)
self.orderList.extend(self.shortOrderIDList)
#----------------------------------------------------------------------
def onStopOrder(self, so):
"""停止单推送"""
pass
class MultiTimeframeStrategy(CtaTemplate):
"""跨时间周期交易策略"""
className = 'MultiTimeframeStrategy'
author = u'用Python的交易员'
# 策略参数
rsiSignal = 20 # RSI信号阈值
rsiWindow = 14 # RSI窗口
fastWindow = 5 # 快速均线窗口
slowWindow = 20 # 慢速均线窗口
initDays = 10 # 初始化数据所用的天数
fixedSize = 1 # 每次交易的数量
# 策略变量
rsiValue = 0 # RSI指标的数值
rsiLong = 0 # RSI买开阈值
rsiShort = 0 # RSI卖开阈值
fastMa = 0 # 5分钟快速均线
slowMa = 0 # 5分钟慢速均线
maTrend = 0 # 均线趋势，多头1，空头-1
# 参数列表，保存了参数的名称
paramList = ['name',
'className',
'author',
'vtSymbol',
'rsiSignal',
'rsiWindow',
'fastWindow',
'slowWindow']
# 变量列表，保存了变量的名称
varList = ['inited',
'trading',
'pos',
'rsiValue',
'rsiLong',
'rsiShort',
'fastMa',
'slowMa',
'maTrend']
# 同步列表，保存了需要保存到数据库的变量名称
syncList = ['pos']
#----------------------------------------------------------------------
def __init__(self, ctaEngine, setting):
"""Constructor"""
super(MultiTimeframeStrategy, self).__init__(ctaEngine, setting)
self.rsiLong = 50 + self.rsiSignal
self.rsiShort = 50 - self.rsiSignal
# 创建K线合成器对象
self.bg5 = BarGenerator(self.onBar, 5, self.on5MinBar)
self.am5 = ArrayManager()
self.bg15 = BarGenerator(self.onBar, 15, self.on15MinBar)
self.am15 = ArrayManager()
#----------------------------------------------------------------------
def onInit(self):
"""初始化策略（必须由用户继承实现）"""
self.writeCtaLog(u'%s策略初始化' %self.name)
# 载入历史数据，并采用回放计算的方式初始化策略数值
initData = self.loadBar(self.initDays)
for bar in initData:
self.onBar(bar)
self.putEvent()
#----------------------------------------------------------------------
def onStart(self):
"""启动策略（必须由用户继承实现）"""
self.writeCtaLog(u'%s策略启动' %self.name)
self.putEvent()
#----------------------------------------------------------------------
def onStop(self):
"""停止策略（必须由用户继承实现）"""
self.writeCtaLog(u'%s策略停止' %self.name)
self.putEvent()
#----------------------------------------------------------------------
def onTick(self, tick):
"""收到行情TICK推送（必须由用户继承实现）"""
# 只需要要在一个BarGenerator中合成1分钟K线
self.bg5.updateTick(tick)
#----------------------------------------------------------------------
def onBar(self, bar):
"""收到Bar推送（必须由用户继承实现）"""
# 基于15分钟判断趋势过滤，因此先更新
self.bg15.updateBar(bar)
# 基于5分钟判断
self.bg5.updateBar(bar)
#----------------------------------------------------------------------
def on5MinBar(self, bar):
"""5分钟K线"""
self.cancelAll()
# 保存K线数据
self.am5.updateBar(bar)
if not self.am5.inited:
return
# 如果15分钟数据尚未初始化完毕，则直接返回
if not self.maTrend:
return
# 计算指标数值
self.rsiValue = self.am5.rsi(self.rsiWindow)
# 判断是否要进行交易
# 当前无仓位
if self.pos == 0:
if self.maTrend > 0 and self.rsiValue >= self.rsiLong:
self.buy(bar.close+5, self.fixedSize)
elif self.maTrend < 0 and self.rsiValue <= self.rsiShort:
self.short(bar.close-5, self.fixedSize)
# 持有多头仓位
elif self.pos > 0:
if self.maTrend < 0 or self.rsiValue < 50:
self.sell(bar.close-5, abs(self.pos))
# 持有空头仓位
elif self.pos < 0:
if self.maTrend > 0 or self.rsiValue > 50:
self.cover(bar.close+5, abs(self.pos))
# 发出状态更新事件
self.putEvent()
#----------------------------------------------------------------------
def on15MinBar(self, bar):
"""15分钟K线推送"""
self.am15.updateBar(bar)
if not self.am15.inited:
return
# 计算均线并判断趋势
self.fastMa = self.am15.sma(self.fastWindow)
self.slowMa = self.am15.sma(self.slowWindow)
if self.fastMa > self.slowMa:
self.maTrend = 1
else:
self.maTrend = -1
#----------------------------------------------------------------------
def onOrder(self, order):
"""收到委托变化推送（必须由用户继承实现）"""
pass
#----------------------------------------------------------------------
def onTrade(self, trade):
# 发出状态更新事件
self.putEvent()
#----------------------------------------------------------------------
def onStopOrder(self, so):
"""停止单推送"""
pass
class TurtleTradingStrategy(CtaTemplate):
"""海龟交易策略"""
className = 'TurtleTradingStrategy'
author = u'用Python的交易员'
# 策略参数
entryWindow = 55 # 入场通道窗口
exitWindow = 20 # 出场通道窗口
atrWindow = 20 # 计算ATR波动率的窗口
initDays = 10 # 初始化数据所用的天数
fixedSize = 1 # 每次交易的数量
# 策略变量
entryUp = 0 # 入场通道上轨
entryDown = 0 # 入场通道下轨
exitUp = 0 # 出场通道上轨
exitDown = 0 # 出场通道下轨
atrVolatility = 0 # ATR波动率
longEntry = 0 # 多头入场价格
shortEntry = 0 # 空头入场价格
longStop = 0 # 多头止损价格
shortStop = 0 # 空头止损价格
# 参数列表，保存了参数的名称
paramList = ['name',
'className',
'author',
'vtSymbol',
'entryWindow',
'exitWindow',
'atrWindow',
'initDays',
'fixedSize']
# 变量列表，保存了变量的名称
varList = ['inited',
'trading',
'pos',
'entryUp',
'entryDown',
'exitUp',
'exitDown',
'longEntry',
'shortEntry',
'longStop',
'shortStop']
# 同步列表，保存了需要保存到数据库的变量名称
syncList = ['pos']
#----------------------------------------------------------------------
def __init__(self, ctaEngine, setting):
"""Constructor"""
super(TurtleTradingStrategy, self).__init__(ctaEngine, setting)
self.bg = BarGenerator(self.onBar)
self.am = ArrayManager()
#----------------------------------------------------------------------
def onInit(self):
"""初始化策略（必须由用户继承实现）"""
self.writeCtaLog(u'%s策略初始化' %self.name)
# 载入历史数据，并采用回放计算的方式初始化策略数值
initData = self.loadBar(self.initDays)
for bar in initData:
self.onBar(bar)
self.putEvent()
#----------------------------------------------------------------------
def onStart(self):
"""启动策略（必须由用户继承实现）"""
self.writeCtaLog(u'%s策略启动' %self.name)
self.putEvent()
#----------------------------------------------------------------------
def onStop(self):
"""停止策略（必须由用户继承实现）"""
self.writeCtaLog(u'%s策略停止' %self.name)
self.putEvent()
#----------------------------------------------------------------------
def onTick(self, tick):
"""收到行情TICK推送（必须由用户继承实现）"""
self.bg.updateTick(tick)
#----------------------------------------------------------------------
def onBar(self, bar):
"""收到Bar推送（必须由用户继承实现）"""
self.cancelAll()
# 保存K线数据
self.am.updateBar(bar)
if not self.am.inited:
return
# 计算指标数值
self.entryUp, self.entryDown = self.am.donchian(self.entryWindow)
self.exitUp, self.exitDown = self.am.donchian(self.exitWindow)
if not self.pos:
self.atrVolatility = self.am.atr(self.atrWindow)
# 判断是否要进行交易
if self.pos == 0:
self.longEntry = 0
self.shortEntry = 0
self.longStop = 0
self.shortStop = 0
self.sendBuyOrders(self.entryUp)
self.sendShortOrders(self.entryDown)
elif self.pos > 0:
# 加仓逻辑
self.sendBuyOrders(self.longEntry)
# 止损逻辑
sellPrice = max(self.longStop, self.exitDown)
self.sell(sellPrice, abs(self.pos), True)
elif self.pos < 0:
# 加仓逻辑
self.sendShortOrders(self.shortEntry)
# 止损逻辑
coverPrice = min(self.shortStop, self.exitUp)
self.cover(coverPrice, abs(self.pos), True)
# 同步数据到数据库
self.saveSyncData()
# 发出状态更新事件
self.putEvent()
#----------------------------------------------------------------------
def onOrder(self, order):
"""收到委托变化推送（必须由用户继承实现）"""
pass
#----------------------------------------------------------------------
def onTrade(self, trade):
"""成交推送"""
if trade.direction == DIRECTION_LONG:
self.longEntry = trade.price
self.longStop = self.longEntry - self.atrVolatility * 2
else:
self.shortEntry = trade.price
self.shortStop = self.shortEntry + self.atrVolatility * 2
# 发出状态更新事件
self.putEvent()
#----------------------------------------------------------------------
def onStopOrder(self, so):
"""停止单推送"""
pass
#----------------------------------------------------------------------
def sendBuyOrders(self, price):
"""发出一系列的买入停止单"""
t = self.pos / self.fixedSize
if t < 1:
self.buy(price, self.fixedSize, True)
if t < 2:
self.buy(price + self.atrVolatility*0.5, self.fixedSize, True)
if t < 3:
self.buy(price + self.atrVolatility, self.fixedSize, True)
if t < 4:
self.buy(price + self.atrVolatility*1.5, self.fixedSize, True)
#----------------------------------------------------------------------
def sendShortOrders(self, price):
""""""
t = self.pos / self.fixedSize
if t > -1:
self.short(price, self.fixedSize, True)
if t > -2:
self.short(price - self.atrVolatility*0.5, self.fixedSize, True)
if t > -3:
self.short(price - self.atrVolatility, self.fixedSize, True)
if t > -4:
self.short(price - self.atrVolatility*1.5, self.fixedSize, True)
class tempStrategy(CtaTemplate):
"""双指数均线策略Demo"""
className = 'DoubleMaStrategy'
author = u'用Python的交易员'
# 策略参数
fastWindow = 12 # 快速均线参数
slowWindow = 26 # 慢速均线参数
initDays = 0 # 初始化数据所用的天数
# 策略变量
fastMa0 = EMPTY_FLOAT # 当前最新的快速EMA
fastMa1 = EMPTY_FLOAT # 上一根的快速EMA
slowMa0 = EMPTY_FLOAT
slowMa1 = EMPTY_FLOAT
huice = False
# 参数列表，保存了参数的名称
paramList = [
'name', 'className', 'author', 'vtSymbol', 'fastWindow', 'slowWindow'
]
# 变量列表，保存了变量的名称
varList = [
'inited', 'trading', 'pos', 'fastMa0', 'fastMa1', 'slowMa0', 'slowMa1'
]
# 同步列表，保存了需要保存到数据库的变量名称
syncList = ['pos']
#----------------------------------------------------------------------
def __init__(self, ctaEngine, setting):
"""Constructor"""
super(tempStrategy, self).__init__(ctaEngine, setting)
self.bg = BarGenerator(self.onBar)
self.am = ArrayManager()
self.lastzhibiao = zhibiao(0, 0, 0)
self.celve0 = zerocelve()
# self.celve1 = ceshi()
self.tickCelvezu = [self.celve0]
self.barCelvezu = [self.celve0]
self.tickadd = 1
#断网恢复变量
self.stopcount = None
#交易时间和监控联网状态变量
self.yepan = False
self.yepanhour = None
self.yepanminute = None
self.lastbardatetime = None
self.tradetime = None
#控制开仓和平仓稳定变量
self.tradecount = 0
self.tradingcelve = [self.celve0]
# 注意策略类中的可变对象属性（通常是list和dict等），在策略初始化时需要重新创建，
# 否则会出现多个策略实例之间数据共享的情况，有可能导致潜在的策略逻辑错误风险，
# 策略类中的这些可变对象属性可以选择不写，全都放在__init__下面，写主要是为了阅读
# 策略时方便（更多是个编程习惯的选择）
#----------------------------------------------------------------------
def onInit(self):
"""初始化策略（必须由用户继承实现）"""
self.writeCtaLog(u'双EMA演示策略初始化')
initData = self.loadBar(self.initDays)
for bar in initData:
self.onBar(bar)
self.am.inited = True
self.putEvent()
#----------------------------------------------------------------------
def onStart(self):
"""启动策略（必须由用户继承实现）"""
self.writeCtaLog(u'双EMA演示策略启动')
self.putEvent()
#----------------------------------------------------------------------
def closeAllPosistion(self, price):
print('--closeallpos--')
if self.pos > 0:
self.short(price - self.tickadd, abs(self.pos))
elif self.pos < 0:
self.cover(price + self.tickadd, abs(self.pos))
# ----------------------------------------------------------------------
def datetimePlusMinute(self, datelatime, minute):
newdatetime = datetime.now()
if datelatime.minute + minute < 60:
newdatetime.minute = datelatime.minute + minute
else:
newdatetime.hour = datelatime.hour + 1
newdatetime.minute = datelatime.minute + minute - 60
return newdatetime
# ----------------------------------------------------------------------
def iscontinueTime(self, firstdatetime, seconddatetime):
if (firstdatetime.hour == seconddatetime.hour and firstdatetime.minute + 1 == seconddatetime.minute) \
or (
firstdatetime.hour == seconddatetime.hour - 1 and firstdatetime.minute == 59 and seconddatetime.minute == 0):
return True
# ----------------------------------------------------------------------
def isTradeContinueTime(self, firstdatetime, seconddatetime):
if self.iscontinueTime(firstdatetime, seconddatetime):
return True
elif firstdatetime.hour == 10 and (
firstdatetime.minute == 15 or firstdatetime.minute == 14
) and seconddatetime.hour == 10 and seconddatetime.minute == 30:
return True
elif firstdatetime.hour == 11 and (
firstdatetime.minute == 29 or firstdatetime.minute == 30
) and seconddatetime.hour == 13 and seconddatetime.minute == 30:
return True
elif self.yepan:
if firstdatetime.hour == self.yepanhour and (
firstdatetime.minute == self.yepanminute
or firstdatetime.minute == self.yepanminute - 1
) and seconddatetime.hour == 9 and seconddatetime.miute == 0:
return True
else:
return False
# ----------------------------------------------------------------------
def tickcelve(self, zhibiao, price, tick):
for celve in self.tickCelvezu:
xinhao = celve.celveOntick(zhibiao, self.lastzhibiao)
if xinhao == 100:
print(price, 'kaicangduo', tick.datetime)
if xinhao == 50:
print(price, 'pingcang', tick.datetime)
if xinhao == 200:
print(price, 'kongcang', tick.datetime)
if xinhao == 250:
print(price, 'pingkongcang', tick.datetime)
self.chulikaipingcang(xinhao, price)
# ----------------------------------------------------------------------
def barcelve(self, zhibiao, price):
for celve in self.barCelvezu:
xinhao = celve.celveOnbar(zhibiao, self.lastzhibiao)
if xinhao == 100:
print('kaicangduo,bar')
if xinhao == 50:
print('pingcang,bar')
self.chulikaipingcang(xinhao, price)
# ----------------------------------------------------------------------
def chulikaipingcang(self, celve, price):
# if celve == 100:
# self.buy(price,1)
selfpos = 0
if celve != 0 and celve is not None:
print('nowposis', self.pos, 'celveis', celve, 'andpriceis', price)
if self.pos == 0 and celve == 100:
if self.pos == 0:
# self.weituopos = 1
self.buy(price + 100, 1)
# 如果有空头持仓，则先平空，再做多
elif self.pos < selfpos:
# self.weituopos = 1
self.cover(price, 1)
self.buy(price, 1)
elif self.pos == 1 and celve == 50:
if self.pos > selfpos:
# self.weituopos = 0
self.sell(price - 1, 1)
elif self.pos == 0 and celve == 200:
if self.pos == selfpos:
# self.weituopos = -1
print('iamkonging')
self.short(price - 1, 1)
elif self.pos > selfpos:
self.sell(price, 1)
self.short(price, 1)
# self.weituopos = -1
elif self.pos == -1 and celve == 250:
# self.weituopos += 1
self.cover(price + 100, 1)
# ----------------------------------------------------------------------
def onStop(self):
"""停止策略（必须由用户继承实现）"""
self.writeCtaLog(u'双EMA演示策略停止')
self.putEvent()
#----------------------------------------------------------------------
def onTick(self, tick):
"""收到行情TICK推送（必须由用户继承实现）"""
self.bg.updateTick(tick)
zhibiao = self.am.updateTick(tick)
if not self.tradecount:
self.tickcelve(zhibiao, tick.lastPrice, tick)
elif tick.datetime.second > 55:
print('in tradecount', tick.datetime)
self.tickcelve(zhibiao, tick.lastPrice, tick)
#----------------------------------------------------------------------
def onBar(self, bar):
"""收到Bar推送（必须由用户继承实现）"""
if bar.datetime.hour == 14 and bar.datetime.minute == 59:
self.closeAllPosistion(bar.close)
bartime = bar.datetime
# 处理bar上的刚开仓
self.handleTradeCount()
if self.lastbardatetime is None:
self.lastbardatetime = bar.datetime
else:
if not self.isTradeContinueTime(self.lastbardatetime,
bar.datetime):
#断网了，需要处理断网状态
self.handleDisConnected(bar.close)
#没有断网
else:
if self.stopcount > 0:
self.stopcount -= 1
am = self.am
am.updateBar(bar)
self.bg.updateBar(bar)
# if not am.inited:
# print('retr')
# return
# 计算快慢均线
self.celve0.nowtime = bar.datetime
diff, dea, macd = am.diff, am.dea, am.macd
jisuan = zhibiao(diff, dea, macd)
self.barcelve(jisuan, bar.close)
# 金叉和死叉的条件是互斥
# 所有的委托均以K线收盘价委托（这里有一个实盘中无法成交的风险，考虑添加对模拟市价单类型的支持）
self.lastzhibiao = am.endBar()
# print self.lastzhibiao.diff,self.lastzhibiao.dea
# 发出状态更新事件
self.putEvent()
#----------------------------------------------------------------------
def handleTradeCount(self):
if self.tradecount > 0:
self.tradecount -= 1
def onOrder(self, order):
"""收到委托变化推送（必须由用户继承实现）"""
# 对于无需做细粒度委托控制的策略，可以忽略onOrder
print 'order', order.price, order.direction, order.offset, order.orderTime
pass
#----------------------------------------------------------------------
def onTrade(self, trade):
"""收到成交推送（必须由用户继承实现）"""
# 对于无需做细粒度委托控制的策略，可以忽略onOrder\
if trade.direction == u'多' and trade.offset == u'开仓':
#self.sell(trade.price - 4, 1, stop=True)
self.tradecount = 5
print('kaiduo')
if trade.direction == u'空' and trade.offset == u'开仓':
#self.cover(trade.price + 4, 1, stop=True)
self.tradecount = 5
print('kaikong')
if trade.direction == u'多' and trade.offset != u'开仓':
self.cancelAll()
self.celve0.cangwei += trade.volume
print('pingkong')
if trade.direction == u'空' and trade.offset != u'开仓':
self.cancelAll()
self.celve0.cangwei -= trade.volume
print('pingduo')
print 'trade', trade.price, trade.direction, trade.offset, trade.tradeTime
pass
#----------------------------------------------------------------------
def onStopOrder(self, so):
"""停止单推送"""
pass
def handleDisConnected(self, price):
print('DISCONNECTED')
self.closeAllPosistion(price)
self.stopcount = 15
class TripleMAStrategy02(CtaTemplate):
"""基于三均线的交易策略"""
className = 'TripleMAStrategy'
author = 'Y.Raul'
# 策略参数
# 三均线长度设置
maWindow1 = 10
maWindow2 = 20
maWindow3 = 120
maWindow4 = 5
initDays = 10 # 初始化数据所用的天数
fixedSize = 1 # 每次交易的数量
# 策略变量
# ma次新值
ma10 = 0
ma20 = 0
# ma最新值
ma11 = 0
ma21 = 0
ma31 = 0
longEntry = 0 # 多头开仓
longExit = 0 # 多头平仓
shortEntry = 0
shortExit = 0
orderList = [] # 保存委托代码的列表
# 参数列表，保存了参数的名称
paramList = [
'name', 'className', 'author', 'vtSymbol', 'maWindow1', 'maWindow2',
'maWindow3', 'maWindow4'
'initDays', 'fixedSize'
]
# 变量列表，保存了变量的名称
varList = ['inited', 'trading', 'pos', 'ma10', 'ma11', 'ma20', 'ma21']
# 同步列表
syncList = ['pos']
# ----------------------------------------------------------------------
def __init__(self, ctaEngine, setting):
"""Constructor"""
super(TripleMAStrategy02, self).__init__(ctaEngine, setting)
self.bm = BarGenerator(self.onBar, 5, self.onFiveBar)
# 由于maWindow3的长度是120，所以ArrayManager的size要增加至150
self.am = ArrayManager(size=150)
# ----------------------------------------------------------------------
def onInit(self):
"""初始化策略（必须由用户继承实现）"""
self.writeCtaLog(u'%s策略初始化' % self.name)
# 载入历史数据，并采用回放计算的方式初始化策略数值
initData = self.loadBar(self.initDays)
for bar in initData:
self.onBar(bar)
self.putEvent()
# ----------------------------------------------------------------------
def onStart(self):
"""启动策略（必须由用户继承实现）"""
self.writeCtaLog(u'%s策略启动' % self.name)
self.putEvent()
# ----------------------------------------------------------------------
def onStop(self):
"""停止策略（必须由用户继承实现）"""
self.writeCtaLog(u'%s策略停止' % self.name)
self.putEvent()
# ----------------------------------------------------------------------
def onTick(self, tick):
"""收到行情TICK推送（必须由用户继承实现）"""
self.bm.updateTick(tick)
# ----------------------------------------------------------------------
def onBar(self, bar):
"""收到Bar推送（必须由用户继承实现）"""
self.bm.updateBar(bar)
# ----------------------------------------------------------------------
def onFiveBar(self, bar):
"""收到5分钟K线"""
# 保存K线数据
self.am.updateBar(bar)
if not self.am.inited:
return
# 撤销之前发出的尚未成交的委托（包括限价单和停止单）
self.cancelAll()
import talib
# 计算指标数值
ma3Array = self.am.sma(self.maWindow3, True)
self.ma30 = ma3Array[-2]
self.ma31 = ma3Array[-1]
ma3_ma5 = talib.SMA(ma3Array, self.maWindow4)[-1]
# ma3_ma5 = ma3Array.rolling(window = self.maWindow4)[-1]
ma1Array = self.am.sma(self.maWindow1, True)
self.ma10 = ma1Array[-2]
self.ma11 = ma1Array[-1]
# ma1_ma5 = ma1Array.rolling(window = self.maWindow4)[-1]
ma1_ma5 = talib.SMA(ma1Array, self.maWindow4)[-1]
ma2Array = self.am.sma(self.maWindow2, True)
self.ma20 = ma2Array[-2]
self.ma21 = ma2Array[-1]
# 判断是否要进行交易
# 当前无仓位，发送OCO开仓委托
if self.pos == 0:
# 开多, bar.close > MA120,MA10 > MA120,MA10 上穿MA20，MA10、MA120向上
if bar.close > self.ma31 and self.ma11 > self.ma31 \
and self.ma10 < self.ma20 and self.ma11 > self.ma21\
and self.ma31 > ma3_ma5 and self.ma11 > ma1_ma5:
self.longEntry = bar.close
self.buy(self.longEntry, self.fixedSize, True)
# 开空, bar.close < MA120,MA10 < MA120,MA10 下穿MA20, MA10,MA120向下
elif bar.close < self.ma31 and self.ma11 < self.ma31 \
and self.ma10 > self.ma20 and self.ma11 < self.ma21\
and self.ma31 < ma3_ma5 and self.ma11 < ma1_ma5:
self.shortEntry = bar.close
self.short(self.shortEntry, self.fixedSize, True)
else:
# 持有多头仓位
if self.pos > 0:
self.longExit = bar.close
# 平多，MA10下穿MA20
if self.ma10 > self.ma20 and self.ma11 < self.ma21:
self.sell(self.longExit, abs(self.pos), True)
# 持有空头仓位
if self.pos < 0:
self.shortExit = bar.close
# 平空， MA10上穿MA20
if self.ma10 < self.ma20 and self.ma11 > self.ma21:
self.cover(self.shortExit, abs(self.pos), True)
# 发出状态更新事件
self.putEvent()
# ----------------------------------------------------------------------
def onOrder(self, order):
"""收到委托变化推送（必须由用户继承实现）"""
pass
# ----------------------------------------------------------------------
def onTrade(self, trade):
# 发出状态更新事件
self.putEvent()
# ----------------------------------------------------------------------
def onStopOrder(self, so):
"""停止单推送"""
pass
class MultiTimeframeStrategy(CtaTemplate):
"""跨时间周期交易策略"""
className = 'MultiTimeframeStrategy'
author = u'用Python的交易员'
# 策略参数
rsiSignal = 20 # RSI信号阈值
rsiWindow = 14 # RSI窗口
fastWindow = 5 # 快速均线窗口
slowWindow = 20 # 慢速均线窗口
initDays = 10 # 初始化数据所用的天数
fixedSize = 1 # 每次交易的数量
# 策略变量
rsiValue = 0 # RSI指标的数值
rsiLong = 0 # RSI买开阈值
rsiShort = 0 # RSI卖开阈值
fastMa = 0 # 5分钟快速均线
slowMa = 0 # 5分钟慢速均线
maTrend = 0 # 均线趋势，多头1，空头-1
# 参数列表，保存了参数的名称
paramList = [
'name', 'className', 'author', 'vtSymbol', 'rsiSignal', 'rsiWindow',
'fastWindow', 'slowWindow'
]
# 变量列表，保存了变量的名称
varList = [
'inited', 'trading', 'pos', 'rsiValue', 'rsiLong', 'rsiShort',
'fastMa', 'slowMa', 'maTrend'
]
# 同步列表，保存了需要保存到数据库的变量名称
syncList = ['pos']
#----------------------------------------------------------------------
def __init__(self, ctaEngine, setting):
"""Constructor"""
super(MultiTimeframeStrategy, self).__init__(ctaEngine, setting)
self.rsiLong = 50 + self.rsiSignal
self.rsiShort = 50 - self.rsiSignal
# 创建K线合成器对象
self.bg5 = BarGenerator(self.onBar, 5, self.on5MinBar)
self.am5 = ArrayManager()
self.bg15 = BarGenerator(self.onBar, 15, self.on15MinBar)
self.am15 = ArrayManager()
#----------------------------------------------------------------------
def onInit(self):
"""初始化策略（必须由用户继承实现）"""
self.writeCtaLog(u'%s策略初始化' % self.name)
# 载入历史数据，并采用回放计算的方式初始化策略数值
initData = self.loadBar(self.initDays)
for bar in initData:
self.onBar(bar)
self.putEvent()
#----------------------------------------------------------------------
def onStart(self):
"""启动策略（必须由用户继承实现）"""
self.writeCtaLog(u'%s策略启动' % self.name)
self.putEvent()
#----------------------------------------------------------------------
def onStop(self):
"""停止策略（必须由用户继承实现）"""
self.writeCtaLog(u'%s策略停止' % self.name)
self.putEvent()
#----------------------------------------------------------------------
def onTick(self, tick):
"""收到行情TICK推送（必须由用户继承实现）"""
# 只需要要在一个BM中合成1分钟K线
self.bg5.updateTick(tick)
#----------------------------------------------------------------------
def onBar(self, bar):
"""收到Bar推送（必须由用户继承实现）"""
# 基于15分钟判断趋势过滤，因此先更新
self.bg15.updateBar(bar)
# 基于5分钟判断
self.bg5.updateBar(bar)
#----------------------------------------------------------------------
def on5MinBar(self, bar):
"""5分钟K线"""
self.cancelAll()
# 保存K线数据
self.am5.updateBar(bar)
if not self.am5.inited:
return
# 如果15分钟数据尚未初始化完毕，则直接返回
if not self.maTrend:
return
# 计算指标数值
self.rsiValue = self.am5.rsi(self.rsiWindow)
# 判断是否要进行交易
# 当前无仓位
if self.pos == 0:
if self.maTrend > 0 and self.rsiValue >= self.rsiLong:
self.buy(bar.close + 5, self.fixedSize)
elif self.maTrend < 0 and self.rsiValue <= self.rsiShort:
self.short(bar.close - 5, self.fixedSize)
# 持有多头仓位
elif self.pos > 0:
if self.maTrend < 0 or self.rsiValue < 50:
self.sell(bar.close - 5, abs(self.pos))
# 持有空头仓位
elif self.pos < 0:
if self.maTrend > 0 or self.rsiValue > 50:
self.cover(bar.close + 5, abs(self.pos))
# 发出状态更新事件
self.putEvent()
#----------------------------------------------------------------------
def on15MinBar(self, bar):
"""15分钟K线推送"""
self.am15.updateBar(bar)
if not self.am15.inited:
return
# 计算均线并判断趋势
self.fastMa = self.am15.sma(self.fastWindow)
self.slowMa = self.am15.sma(self.slowWindow)
if self.fastMa > self.slowMa:
self.maTrend = 1
else:
self.maTrend = -1
#----------------------------------------------------------------------
def onOrder(self, order):
"""收到委托变化推送（必须由用户继承实现）"""
pass
#----------------------------------------------------------------------
def onTrade(self, trade):
# 发出状态更新事件
self.putEvent()
#----------------------------------------------------------------------
def onStopOrder(self, so):
"""停止单推送"""
pass
class DualThrustStrategy(CtaTemplate):
"""DualThrust交易策略"""
className = 'DualThrustStrategy'
author = u'用Python的交易员'
# 策略参数
fixedSize = 100
k1 = 0.4
k2 = 0.6
initDays = 10
# 策略变量
barList = [] # K线对象的列表
dayOpen = 0
dayHigh = 0
dayLow = 0
range = 0
longEntry = 0
shortEntry = 0
exitTime = time(hour=14, minute=55)
longEntered = False
shortEntered = False
# 参数列表，保存了参数的名称
paramList = ['name',
'className',
'author',
'vtSymbol',
'k1',
'k2']
# 变量列表，保存了变量的名称
varList = ['inited',
'trading',
'pos',
'range',
'longEntry',
'shortEntry',
'exitTime']
# 同步列表，保存了需要保存到数据库的变量名称
syncList = ['pos']
#----------------------------------------------------------------------
def __init__(self, ctaEngine, setting):
"""Constructor"""
super(DualThrustStrategy, self).__init__(ctaEngine, setting)
self.bg = BarGenerator(self.onBar)
self.barList = []
#----------------------------------------------------------------------
def onInit(self):
"""初始化策略（必须由用户继承实现）"""
self.writeCtaLog(u'%s策略初始化' %self.name)
# 载入历史数据，并采用回放计算的方式初始化策略数值
initData = self.loadBar(self.initDays)
for bar in initData:
self.onBar(bar)
self.putEvent()
#----------------------------------------------------------------------
def onStart(self):
"""启动策略（必须由用户继承实现）"""
self.writeCtaLog(u'%s策略启动' %self.name)
self.putEvent()
#----------------------------------------------------------------------
def onStop(self):
"""停止策略（必须由用户继承实现）"""
self.writeCtaLog(u'%s策略停止' %self.name)
self.putEvent()
#----------------------------------------------------------------------
def onTick(self, tick):
"""收到行情TICK推送（必须由用户继承实现）"""
self.bg.updateTick(tick)
#----------------------------------------------------------------------
def onBar(self, bar):
"""收到Bar推送（必须由用户继承实现）"""
# 撤销之前发出的尚未成交的委托（包括限价单和停止单）
self.cancelAll()
# 计算指标数值
self.barList.append(bar)
if len(self.barList) <= 2:
return
else:
self.barList.pop(0)
lastBar = self.barList[-2]
# 新的一天
if lastBar.datetime.date() != bar.datetime.date():
# 如果已经初始化
if self.dayHigh:
self.range = self.dayHigh - self.dayLow
self.longEntry = bar.open + self.k1 * self.range
self.shortEntry = bar.open - self.k2 * self.range
self.dayOpen = bar.open
self.dayHigh = bar.high
self.dayLow = bar.low
self.longEntered = False
self.shortEntered = False
else:
self.dayHigh = max(self.dayHigh, bar.high)
self.dayLow = min(self.dayLow, bar.low)
# 尚未到收盘
if not self.range:
return
if bar.datetime.time() < self.exitTime:
if self.pos == 0:
if bar.close > self.dayOpen:
if not self.longEntered:
self.buy(self.longEntry, self.fixedSize, stop=True)
else:
if not self.shortEntered:
self.short(self.shortEntry, self.fixedSize, stop=True)
# 持有多头仓位
elif self.pos > 0:
self.longEntered = True
# 多头止损单
self.sell(self.shortEntry, self.fixedSize, stop=True)
# 空头开仓单
if not self.shortEntered:
self.short(self.shortEntry, self.fixedSize, stop=True)
# 持有空头仓位
elif self.pos < 0:
self.shortEntered = True
# 空头止损单
self.cover(self.longEntry, self.fixedSize, stop=True)
# 多头开仓单
if not self.longEntered:
self.buy(self.longEntry, self.fixedSize, stop=True)
# 收盘平仓
else:
if self.pos > 0:
self.sell(bar.close * 0.99, abs(self.pos))
elif self.pos < 0:
self.cover(bar.close * 1.01, abs(self.pos))
# 发出状态更新事件
self.putEvent()
#----------------------------------------------------------------------
def onOrder(self, order):
"""收到委托变化推送（必须由用户继承实现）"""
pass
#----------------------------------------------------------------------
def onTrade(self, trade):
# 发出状态更新事件
self.putEvent()
#----------------------------------------------------------------------
def onStopOrder(self, so):
"""停止单推送"""
pass
