def __init__(self, portfolio, vtSymbol):
self.portfolio = portfolio # 投资组合
self.vtSymbol = vtSymbol # 合约代码
self.am = ArrayManager() # K线容器
self.bar = None # 最新K线
# 策略参数
self.initBars = 60 # 初始化数据所用的天数
self.entryWindow = 20 # 入场通道周期数
self.exitWindow = 50 # 出场通道周期数
self.atrWindow = 5 # 计算ATR周期数
self.profitCheck = True # 是否检查上一笔盈利
self.minx = 'day'
# 策略临时变量
self.atrVolatility = 0 # ATR波动率
self.entryUp = 0 # 入场通道
self.entryDown = 0
self.exitUp = 0 # 出场通道
self.exitDown = 0
self.longEntry1 = 0 # 多头入场位
self.longEntry2 = 0
self.longEntry3 = 0
self.longEntry4 = 0
self.longStop = 0 # 多头止损位
self.shortEntry1 = 0 # 空头入场位
self.shortEntry2 = 0
self.shortEntry3 = 0
self.shortEntry4 = 0
self.shortStop = 0 # 空头止损位
# 需要持久化保存的变量
self.unit = 0
self.result = None # 当前的交易
self.resultList = [] # 交易列表
# 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.portfolio.engine._bc_loadInitBar(self.vtSymbol, self.initBars, self.minx)
for bar in initData:
self.bar = bar
self.am.updateBar(bar)
def __init__(self, portfolio, vtSymbol):
self.portfolio = portfolio # 投资组合
self.vtSymbol = vtSymbol # 合约代码
self.am = ArrayManager() # K线容器
self.bar = None # 最新K线
# 策略参数
self.atrLength = 1 # 计算ATR指标的窗口数
self.atrMaLength = 14 # 计算ATR均线的窗口数
self.rsiLength = 5 # 计算RSI的窗口数
self.rsiEntry = 16 # RSI的开仓信号
self.trailingPercent = 0.7 # 百分比移动止损
self.victoryPercent = 0.3
self.initBars = 60 # 初始化数据所用的天数
self.fixedSize = 1 # 每次交易的数量
self.ratio_atrMa = 0.8
self.minx = 'min5'
# 初始化RSI入场阈值
self.rsiBuy = 50 + self.rsiEntry
self.rsiSell = 50 - self.rsiEntry
# 策略临时变量
self.atrValue = 0 # 最新的ATR指标数值
self.atrMa = 0 # ATR移动平均的数值
self.rsiValue = 0 # RSI指标的数值
self.iswave = True
# 需要持久化保存的变量
self.unit = 0
self.cost = 0
self.intraTradeHigh = 0 # 移动止损用的持仓期内最高价
self.intraTradeLow = 0 # 持仓期内的最低点
self.stop = 0 # 多头止损
self.result = None # 当前的交易
self.resultList = [] # 交易列表
# 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.portfolio.engine._bc_loadInitBar(
self.vtSymbol, self.initBars, self.minx)
for bar in initData:
self.bar = bar
self.am.updateBar(bar)
def __init__(self, portfolio, vtSymbol):
self.type = 'kong'
# 策略参数
self.fixedSize = 1 # 每次交易的数量
self.initBars = 100 # 初始化数据所用的天数
self.minx = 'min30'
# 策略临时变量
self.can_buy = False
self.can_sell = False
self.can_short = False
self.can_cover = False
# 需要持久化保存的变量
self.cost = 0
size_am = 100
assert self.initBars <= size_am
Signal.__init__(self, portfolio, vtSymbol)
self.bm_bar = None
self.bm = ArrayManager(60)
self.init_bm()
class Fut_AtrRsiSignal(object):
#----------------------------------------------------------------------
def __init__(self, portfolio, vtSymbol):
self.portfolio = portfolio # 投资组合
self.vtSymbol = vtSymbol # 合约代码
self.am = ArrayManager() # K线容器
self.bar = None # 最新K线
# 策略参数
self.atrLength = 22 # 计算ATR指标的窗口数
self.atrMaLength = 10 # 计算ATR均线的窗口数
self.rsiLength = 5 # 计算RSI的窗口数
self.rsiEntry = 16 # RSI的开仓信号
self.victoryPercent = 0.8 # 百分比移动止损
self.initBars = 90 # 初始化数据所用的天数
self.fixedSize = 1 # 每次交易的数量
self.minx = 'min5'
# 初始化RSI入场阈值
self.rsiBuy = 50 + self.rsiEntry
self.rsiSell = 50 - self.rsiEntry
# 策略临时变量
self.atrValue = 0 # 最新的ATR指标数值
self.atrMa = 0 # ATR移动平均的数值
self.rsiValue = 0 # RSI指标的数值
# 需要持久化保存的变量
self.unit = 0
self.cost = 0
self.intraTradeHigh = 0 # 移动止损用的持仓期内最高价
self.intraTradeLow = 0 # 持仓期内的最低点
self.stop = 0 # 多头止损
self.result = None # 当前的交易
self.resultList = [] # 交易列表
# 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.portfolio.engine._bc_loadInitBar(
self.vtSymbol, self.initBars, self.minx)
for bar in initData:
self.bar = bar
self.am.updateBar(bar)
#----------------------------------------------------------------------
def set_param(self, param_dict):
if 'atrMaLength' in param_dict:
self.atrMaLength = param_dict['atrMaLength']
if 'rsiLength' in param_dict:
self.rsiLength = param_dict['rsiLength']
if 'victoryPercent' in param_dict:
self.victoryPercent = param_dict['victoryPercent']
#----------------------------------------------------------------------
def onBar(self, bar):
"""新推送过来一个bar，进行处理"""
#print(bar.time, self.vtSymbol)
self.bar = bar
self.am.updateBar(bar)
if not self.am.inited:
return
#print('here')
self.calculateIndicator() # 计算指标
self.generateSignal(bar) # 触发信号，产生交易指令
#----------------------------------------------------------------------
def calculateIndicator(self):
"""计算技术指标"""
atrArray = self.am.atr(self.atrLength, array=True)
# print(len(atrArray))
self.atrValue = atrArray[-1]
self.atrMa = atrArray[-self.atrMaLength:].mean()
self.rsiValue = self.am.rsi(self.rsiLength)
#----------------------------------------------------------------------
def generateSignal(self, bar):
# 当前无仓位
if self.unit == 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, self.fixedSize)
elif self.rsiValue < self.rsiSell:
self.short(bar.close, self.fixedSize)
# 持有多头仓位
elif self.unit > 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.stop = self.intraTradeHigh * (1 - self.victoryPercent / 100)
if bar.close <= self.stop:
# print('平多: ', bar.datetime, self.intraTradeHigh, self.stop, bar.close)
self.sell(bar.close, abs(self.unit))
# 持有空头仓位
elif self.unit < 0:
self.intraTradeLow = min(self.intraTradeLow, bar.low)
self.stop = self.intraTradeLow * (1 + self.victoryPercent / 100)
if bar.close >= self.stop:
# print('平空: ', bar.datetime, self.intraTradeLow, self.stop, bar.close)
self.cover(bar.close, abs(self.unit))
#----------------------------------------------------------------------
def load_var(self):
filename = get_dss() + 'fut/check/signal_atrrsi_var.csv'
df = pd.read_csv(filename)
df = df[df.vtSymbol == self.vtSymbol]
if len(df) > 0:
rec = df.iloc[-1, :] # 取最近日期的记录
self.unit = rec.unit
self.cost = rec.cost
self.intraTradeHigh = rec.intraTradeHigh
self.intraTradeLow = rec.intraTradeLow
self.stop = rec.stop
if rec.has_result == 1:
self.result = SignalResult()
self.result.unit = rec.result_unit
self.result.entry = rec.result_entry
self.result.exit = rec.result_exit
self.result.pnl = rec.result_pnl
#----------------------------------------------------------------------
def save_var(self):
r = []
if self.result is None:
r = [ [self.portfolio.result.date,self.vtSymbol, self.unit, self.cost, \
self.intraTradeHigh, self.intraTradeLow, self.stop, \
0, 0, 0, 0, 0 ] ]
else:
r = [ [self.portfolio.result.date,self.vtSymbol, self.unit, self.cost, \
self.intraTradeHigh, self.intraTradeLow, self.stop, \
1, self.result.unit, self.result.entry, self.result.exit, self.result.pnl ] ]
df = pd.DataFrame(r, columns=['datetime','vtSymbol','unit','cost', \
'intraTradeHigh','intraTradeLow','stop', \
'has_result','result_unit','result_entry','result_exit', 'result_pnl'])
filename = get_dss() + 'fut/check/signal_atrrsi_var.csv'
df.to_csv(filename, index=False, mode='a', header=False)
#----------------------------------------------------------------------
def buy(self, price, volume):
"""买入开仓"""
self.open(price, volume)
self.newSignal(DIRECTION_LONG, OFFSET_OPEN, price, volume)
#----------------------------------------------------------------------
def sell(self, price, volume):
"""卖出平仓"""
volume = abs(self.unit)
self.close(price)
self.newSignal(DIRECTION_SHORT, OFFSET_CLOSE, price, volume)
#----------------------------------------------------------------------
def short(self, price, volume):
"""卖出开仓"""
self.open(price, -volume)
self.newSignal(DIRECTION_SHORT, OFFSET_OPEN, price, volume)
#----------------------------------------------------------------------
def cover(self, price, volume):
"""买入平仓"""
volume = abs(self.unit)
self.close(price)
self.newSignal(DIRECTION_LONG, OFFSET_CLOSE, price, volume)
#----------------------------------------------------------------------
def open(self, price, change):
"""开仓"""
self.unit += change
if not self.result:
self.result = SignalResult()
self.result.open(price, change)
r = [ [self.portfolio.result.date, '多' if change>0 else '空', '开', \
abs(change), price, 0, \
self.atrValue, self.atrMa, self.rsiValue, \
self.iswave, self.intraTradeHigh, self.intraTradeLow, \
self.stop] ]
df = pd.DataFrame(r, columns=['datetime','direction','offset','volume','price','pnl', \
'atrValue', 'atrMa', 'rsiValue', 'iswave', \
'intraTradeHigh','intraTradeLow','stop'])
filename = get_dss(
) + 'fut/deal/signal_turtle_' + self.vtSymbol + '.csv'
df.to_csv(filename, index=False, mode='a', header=False)
#----------------------------------------------------------------------
def close(self, price):
"""平仓"""
self.unit = 0
self.result.close(price)
r = [ [self.portfolio.result.date, '', '平', \
0, price, self.result.pnl, \
self.atrValue, self.atrMa, self.rsiValue, \
self.iswave, self.intraTradeHigh, self.intraTradeLow, \
self.stop] ]
df = pd.DataFrame(r, columns=['datetime','direction','offset','volume','price','pnl', \
'atrValue', 'atrMa', 'rsiValue', 'iswave', \
'intraTradeHigh','intraTradeLow','stop'])
filename = get_dss(
) + 'fut/deal/signal_turtle_' + self.vtSymbol + '.csv'
df.to_csv(filename, index=False, mode='a', header=False)
self.resultList.append(self.result)
self.result = None
class Fut_TurtleSignal(object):
#----------------------------------------------------------------------
def __init__(self, portfolio, vtSymbol):
self.portfolio = portfolio # 投资组合
self.vtSymbol = vtSymbol # 合约代码
self.am = ArrayManager() # K线容器
self.bar = None # 最新K线
# 策略参数
self.initBars = 60 # 初始化数据所用的天数
self.entryWindow = 20 # 入场通道周期数
self.exitWindow = 50 # 出场通道周期数
self.atrWindow = 5 # 计算ATR周期数
self.profitCheck = True # 是否检查上一笔盈利
self.minx = 'day'
# 策略临时变量
self.atrVolatility = 0 # ATR波动率
self.entryUp = 0 # 入场通道
self.entryDown = 0
self.exitUp = 0 # 出场通道
self.exitDown = 0
self.longEntry1 = 0 # 多头入场位
self.longEntry2 = 0
self.longEntry3 = 0
self.longEntry4 = 0
self.longStop = 0 # 多头止损位
self.shortEntry1 = 0 # 空头入场位
self.shortEntry2 = 0
self.shortEntry3 = 0
self.shortEntry4 = 0
self.shortStop = 0 # 空头止损位
# 需要持久化保存的变量
self.unit = 0
self.result = None # 当前的交易
self.resultList = [] # 交易列表
# 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.portfolio.engine._bc_loadInitBar(self.vtSymbol, self.initBars, self.minx)
for bar in initData:
self.bar = bar
self.am.updateBar(bar)
#----------------------------------------------------------------------
def load_param(self):
filename = get_dss() + 'fut/cfg/signal_turtle_param.csv'
if os.path.exists(filename):
df = pd.read_csv(filename)
df = df[ df.pz == get_contract(self.vtSymbol).pz ]
if len(df) > 0:
rec = df.iloc[0,:]
self.rsiLength = rec.rsiLength
self.trailingPercent = rec.trailingPercent
self.victoryPercent = rec.victoryPercent
#----------------------------------------------------------------------
def set_param(self, param_dict):
if 'atrMaLength' in param_dict:
self.atrMaLength = param_dict['atrMaLength']
if 'rsiLength' in param_dict:
self.rsiLength = param_dict['rsiLength']
if 'trailingPercent' in param_dict:
self.trailingPercent = param_dict['trailingPercent']
if 'victoryPercent' in param_dict:
self.victoryPercent = param_dict['victoryPercent']
#----------------------------------------------------------------------
def onBar(self, bar, minx='day'):
"""新推送过来一个bar，进行处理"""
if minx != 'min1':
self.on_bar_day(bar)
if minx == 'min1':
self.on_bar_min1(bar)
#----------------------------------------------------------------------
def on_bar_min1(self, bar):
# 持有多头仓位
if self.unit > 0:
if bar.close <= self.stop:
# print('平多: ', bar.datetime, self.intraTradeHigh, self.stop, bar.close)
self.sell(bar.close, abs(self.unit))
# 持有空头仓位
elif self.unit < 0:
if bar.close >= self.stop:
# print('平空: ', bar.datetime, self.intraTradeLow, self.stop, bar.close)
self.cover(bar.close, abs(self.unit))
#----------------------------------------------------------------------
def on_bar_day(self, bar):
self.bar = bar
self.am.updateBar(bar)
if not self.am.inited:
return
self.generateSignal(bar) # 触发信号，产生交易指令
self.calculateIndicator() # 计算指标
#----------------------------------------------------------------------
def generateSignal(self, bar):
"""
判断交易信号
要注意在任何一个数据点：buy/sell/short/cover只允许执行一类动作
"""
# 如果指标尚未初始化，则忽略
if self.longEntry1 == 0:
return
# 优先检查平仓
if self.unit > 0:
longExit = max(self.longStop, self.exitDown)
if bar.low <= longExit:
self.sell(longExit)
return
elif self.unit < 0:
shortExit = min(self.shortStop, self.exitUp)
if bar.high >= shortExit:
self.cover(shortExit)
return
# 没有仓位或者持有多头仓位的时候，可以做多（加仓）
if self.unit >= 0:
trade = False
if bar.high >= self.longEntry1 and self.unit < 1:
self.buy(self.longEntry1, 1)
trade = True
if bar.high >= self.longEntry2 and self.unit < 2:
self.buy(self.longEntry2, 1)
trade = True
if bar.high >= self.longEntry3 and self.unit < 3:
self.buy(self.longEntry3, 1)
trade = True
if bar.high >= self.longEntry4 and self.unit < 4:
self.buy(self.longEntry4, 1)
trade = True
if trade:
return
# 没有仓位或者持有空头仓位的时候，可以做空（加仓）
if self.unit <= 0:
if bar.low <= self.shortEntry1 and self.unit > -1:
self.short(self.shortEntry1, 1)
if bar.low <= self.shortEntry2 and self.unit > -2:
self.short(self.shortEntry2, 1)
if bar.low <= self.shortEntry3 and self.unit > -3:
self.short(self.shortEntry3, 1)
if bar.low <= self.shortEntry4 and self.unit > -4:
self.short(self.shortEntry4, 1)
#----------------------------------------------------------------------
def calculateIndicator(self):
"""计算技术指标"""
self.entryUp, self.entryDown = self.am.donchian(self.entryWindow)
self.exitUp, self.exitDown = self.am.donchian(self.exitWindow)
# 有持仓后，ATR波动率和入场位等都不再变化
if self.unit == 0:
self.atrVolatility = self.am.atr(self.atrWindow)
self.longEntry1 = self.entryUp
self.longEntry2 = self.entryUp + self.atrVolatility * 0.5
self.longEntry3 = self.entryUp + self.atrVolatility * 1
self.longEntry4 = self.entryUp + self.atrVolatility * 1.5
self.longStop = 0
self.shortEntry1 = self.entryDown
self.shortEntry2 = self.entryDown - self.atrVolatility * 0.5
self.shortEntry3 = self.entryDown - self.atrVolatility * 1
self.shortEntry4 = self.entryDown - self.atrVolatility * 1.5
self.shortStop = 0
#----------------------------------------------------------------------
def load_var(self):
filename = get_dss() + 'fut/check/signal_turtle_var.csv'
df = pd.read_csv(filename)
df = df[df.vtSymbol == self.vtSymbol]
if len(df) > 0:
rec = df.iloc[-1,:] # 取最近日期的记录
self.unit = rec.unit
self.cost = rec.cost
self.intraTradeHigh = rec.intraTradeHigh
self.intraTradeLow = rec.intraTradeLow
self.stop = rec.stop
if rec.has_result == 1:
self.result = SignalResult()
self.result.unit = rec.result_unit
self.result.entry = rec.result_entry
self.result.exit = rec.result_exit
self.result.pnl = rec.result_pnl
#----------------------------------------------------------------------
def save_var(self):
r = []
if self.result is None:
r = [ [self.portfolio.result.date,self.vtSymbol, self.unit, self.cost, \
self.intraTradeHigh, self.intraTradeLow, self.stop, \
0, 0, 0, 0, 0 ] ]
else:
r = [ [self.portfolio.result.date,self.vtSymbol, self.unit, self.cost, \
self.intraTradeHigh, self.intraTradeLow, self.stop, \
1, self.result.unit, self.result.entry, self.result.exit, self.result.pnl ] ]
df = pd.DataFrame(r, columns=['datetime','vtSymbol','unit','cost', \
'intraTradeHigh','intraTradeLow','stop', \
'has_result','result_unit','result_entry','result_exit', 'result_pnl'])
filename = get_dss() + 'fut/check/signal_turtle_var.csv'
df.to_csv(filename, index=False, mode='a', header=False)
#----------------------------------------------------------------------
def newSignal(self, direction, offset, price, volume):
"""调用组合中的接口，传递下单指令"""
self.portfolio._bc_newSignal(self, direction, offset, price, volume)
#----------------------------------------------------------------------
def buy(self, price, volume):
"""买入开仓"""
price = self.calculateTradePrice(DIRECTION_LONG, price)
self.open(price, volume)
self.newSignal(DIRECTION_LONG, OFFSET_OPEN, price, volume)
# 以最后一次加仓价格，加上两倍N计算止损
self.longStop = price - self.atrVolatility * 2
#----------------------------------------------------------------------
def sell(self, price):
"""卖出平仓"""
price = self.calculateTradePrice(DIRECTION_SHORT, price)
volume = abs(self.unit)
self.close(price)
self.newSignal(DIRECTION_SHORT, OFFSET_CLOSE, price, volume)
#----------------------------------------------------------------------
def short(self, price, volume):
"""卖出开仓"""
price = self.calculateTradePrice(DIRECTION_SHORT, price)
self.open(price, -volume)
self.newSignal(DIRECTION_SHORT, OFFSET_OPEN, price, volume)
# 以最后一次加仓价格，加上两倍N计算止损
self.shortStop = price + self.atrVolatility * 2
#----------------------------------------------------------------------
def cover(self, price):
"""买入平仓"""
price = self.calculateTradePrice(DIRECTION_LONG, price)
volume = abs(self.unit)
self.close(price)
self.newSignal(DIRECTION_LONG, OFFSET_CLOSE, price, volume)
#----------------------------------------------------------------------
def open(self, price, change):
"""开仓"""
self.unit += change
if not self.result:
self.result = SignalResult()
self.result.open(price, change)
r = [ [self.portfolio.result.date, '多' if change>0 else '空', '开', \
abs(change), price, 0, \
self.unit] ]
df = pd.DataFrame(r, columns=['datetime','direction','offset','volume','price','pnl', \
'unit'])
filename = get_dss() + 'fut/deal/signal_turtle_' + self.vtSymbol + '.csv'
df.to_csv(filename, index=False, mode='a', header=False)
#----------------------------------------------------------------------
def close(self, price):
"""平仓"""
self.unit = 0
self.result.close(price)
r = [ [self.portfolio.result.date, '', '平', \
0, price, self.result.pnl, \
self.unit] ]
df = pd.DataFrame(r, columns=['datetime','direction','offset','volume','price','pnl', \
'unit'])
filename = get_dss() + 'fut/deal/signal_turtle_' + self.vtSymbol + '.csv'
df.to_csv(filename, index=False, mode='a', header=False)
self.resultList.append(self.result)
self.result = None
#----------------------------------------------------------------------
def getLastPnl(self):
"""获取上一笔交易的盈亏"""
if not self.resultList:
return 0
result = self.resultList[-1]
return result.pnl
#----------------------------------------------------------------------
def calculateTradePrice(self, direction, price):
"""计算成交价格"""
# 买入时，停止单成交的最优价格不能低于当前K线开盘价
if direction == DIRECTION_LONG:
tradePrice = max(self.bar.open, price)
# 卖出时，停止单成交的最优价格不能高于当前K线开盘价
else:
tradePrice = min(self.bar.open, price)
return tradePrice
df['datetime'] = df['date'] + ' ' + df['time']
df = df[df.datetime < startDt]
assert len(df) >= initBars
df = df.sort_values(by=['date', 'time'])
df = df.iloc[-initBars:]
print(df)
for i, row in df.iterrows():
d = dict(row)
#print(d)
# print(type(d))
bar = VtBarData()
bar.__dict__ = d
#print(bar.__dict__)
r.append(bar)
am = ArrayManager(initBars) # K线容器
for bar in r:
am.updateBar(bar)
#rsiValue = am.rsi(5, array=True)
#rsiArray50 = am.rsi(10, array=True)
#rsiMa = rsiValue[-30:].mean()
#atrValue = am.atr(30)
atrValue = am.atr(1, array=True)
atrMa = atrValue[-30:].mean()
print(atrValue)
print(atrMa)
class Fut_DualBandSignal_Kong(Signal):
#----------------------------------------------------------------------
def __init__(self, portfolio, vtSymbol):
self.type = 'kong'
# 策略参数
self.fixedSize = 1 # 每次交易的数量
self.initBars = 100 # 初始化数据所用的天数
self.minx = 'min30'
# 策略临时变量
self.can_buy = False
self.can_sell = False
self.can_short = False
self.can_cover = False
# 需要持久化保存的变量
self.cost = 0
size_am = 100
assert self.initBars <= size_am
Signal.__init__(self, portfolio, vtSymbol)
self.bm_bar = None
self.bm = ArrayManager(60)
self.init_bm()
#----------------------------------------------------------------------
def init_bm(self):
initData = self.portfolio.engine._bc_loadInitBar(
self.vtSymbol, 60, 'day')
for bar in initData:
self.bm_bar = bar
self.bm.updateBar(bar)
#----------------------------------------------------------------------
def load_param(self):
filename = get_dss() + 'fut/engine/dualband/signal_dualband_param.csv'
if os.path.exists(filename):
df = pd.read_csv(filename)
df = df[df.symbol == self.vtSymbol]
if len(df) > 0:
rec = df.iloc[0, :]
print('成功加载策略参数')
#----------------------------------------------------------------------
def set_param(self, param_dict):
if 'fixedSize' in param_dict:
self.fixedSize = param_dict['fixedSize']
print('成功设置策略参数 self.fixedSize: ', self.fixedSize)
#----------------------------------------------------------------------
def onBar(self, bar, minx='min1'):
"""新推送过来一个bar，进行处理"""
if minx == 'day':
self.on_bar_day(bar)
if minx == 'min30':
self.on_bar_minx(bar)
#----------------------------------------------------------------------
def on_bar_day(self, bar):
if self.paused == True:
return
self.bm.updateBar(bar)
if not self.bm.inited:
return
#----------------------------------------------------------------------
def on_bar_minx(self, bar):
self.bar = bar
if self.paused == True:
return
self.am.updateBar(bar)
if not self.am.inited:
return
self.calculateIndicator() # 计算指标
self.generateSignal(bar) # 触发信号，产生交易指令
#----------------------------------------------------------------------
def calculateIndicator(self):
"""计算技术指标"""
self.can_short = False
self.can_cover = False
ma_short_arr = self.am.sma(30, array=True)
ma_long_arr = self.am.sma(90, array=True)
mb_short_arr = self.bm.sma(10, array=True)
mb_long_arr = self.bm.sma(60, array=True)
if self.unit == 0:
if ma_short_arr[-2] >= ma_long_arr[-2] and ma_short_arr[
-1] < ma_long_arr[-1]:
if mb_short_arr[-1] <= mb_long_arr[-1]:
self.can_short = True
if self.unit < 0:
if ma_short_arr[-2] <= ma_long_arr[-2] and ma_short_arr[
-1] > ma_long_arr[-1]:
self.can_cover = True
# r = [[self.bar.date,self.bar.time,self.bar.close,self.can_short,self.can_cover,ma_short_arr[-1],ma_long_arr[-1],mb_short_arr[-1],mb_long_arr[-1]]]
# df = pd.DataFrame(r)
# filename = get_dss() + 'fut/engine/dualband/bar_dualband_'+self.type+ '_' + self.vtSymbol + '.csv'
# if os.path.exists(filename):
# df.to_csv(filename, index=False, mode='a', header=False)
# else:
# df.to_csv(filename, index=False)
#----------------------------------------------------------------------
def generateSignal(self, bar):
# 开多仓
if self.can_buy == True:
self.buy(bar.close, self.fixedSize)
self.cost = bar.close
# 开空仓
if self.can_short == True:
self.short(bar.close, self.fixedSize)
self.cost = bar.close
# 平多仓
if self.can_sell == True:
self.sell(bar.close, self.fixedSize)
self.cost = 0
# 平空仓
if self.can_cover == True:
self.cover(bar.close, self.fixedSize)
self.cost = 0
#----------------------------------------------------------------------
def load_var(self):
pz = str(get_contract(self.vtSymbol).pz)
filename = get_dss(
) + 'fut/engine/dualband/signal_dualband_' + self.type + '_var_' + pz + '.csv'
if os.path.exists(filename):
df = pd.read_csv(filename)
df = df[df.vtSymbol == self.vtSymbol]
df = df.sort_values(by='datetime')
df = df.reset_index()
if len(df) > 0:
rec = df.iloc[-1, :] # 取最近日期的记录
self.unit = rec.unit
self.cost = rec.cost
if rec.has_result == 1:
self.result = SignalResult()
self.result.unit = rec.result_unit
self.result.entry = rec.result_entry
self.result.exit = rec.result_exit
self.result.pnl = rec.result_pnl
#----------------------------------------------------------------------
def save_var(self):
if self.paused == True:
return
r = []
if self.result is None:
r = [ [self.portfolio.result.date,self.vtSymbol, self.unit, self.cost, \
0, 0, 0, 0, 0 ] ]
else:
r = [ [self.portfolio.result.date,self.vtSymbol, self.unit, self.cost, \
1, self.result.unit, self.result.entry, self.result.exit, self.result.pnl ] ]
df = pd.DataFrame(r, columns=['datetime','vtSymbol','unit','cost', \
'has_result','result_unit','result_entry','result_exit', 'result_pnl'])
pz = str(get_contract(self.vtSymbol).pz)
filename = get_dss(
) + 'fut/engine/dualband/signal_dualband_' + self.type + '_var_' + pz + '.csv'
if os.path.exists(filename):
df.to_csv(filename, index=False, mode='a', header=False)
else:
df.to_csv(filename, index=False)
#----------------------------------------------------------------------
def open(self, price, change):
self.unit += change
if not self.result:
self.result = SignalResult()
self.result.open(price, change)
r = [ [self.bar.date+' '+self.bar.time, '多' if change>0 else '空', '开', \
abs(change), price, 0, self.vtSymbol ] ]
df = pd.DataFrame(r,
columns=[
'datetime', 'direction', 'offset', 'volume',
'price', 'pnl', 'symbol'
])
pz = str(get_contract(self.vtSymbol).pz)
filename = get_dss(
) + 'fut/engine/dualband/signal_dualband_' + self.type + '_deal_' + pz + '.csv'
if os.path.exists(filename):
df.to_csv(filename, index=False, mode='a', header=False)
else:
df.to_csv(filename, index=False)
#----------------------------------------------------------------------
def close(self, price):
self.unit = 0
self.result.close(price)
r = [ [self.bar.date+' '+self.bar.time, '', '平', \
0, price, self.result.pnl, self.vtSymbol] ]
df = pd.DataFrame(r,
columns=[
'datetime', 'direction', 'offset', 'volume',
'price', 'pnl', 'symbol'
])
pz = str(get_contract(self.vtSymbol).pz)
filename = get_dss(
) + 'fut/engine/dualband/signal_dualband_' + self.type + '_deal_' + pz + '.csv'
if os.path.exists(filename):
df.to_csv(filename, index=False, mode='a', header=False)
else:
df.to_csv(filename, index=False)
self.result = None