def load_var(self):
filename = get_dss() + 'fut/engine/turtle/signal_turtle_var.csv'
if os.path.exists(filename):
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.atrVolatility = rec.atrVolatility
self.entryUp = rec.entryUp
self.entryDown = rec.entryDown
self.exitUp = rec.exitUp
self.exitDown = rec.exitDown
self.longEntry1 = rec.longEntry1
self.longEntry2 = rec.longEntry2
self.longEntry3 = rec.longEntry3
self.longEntry4 = rec.longEntry4
self.longStop = rec.longStop
self.shortEntry1 = rec.shortEntry1
self.shortEntry2 = rec.shortEntry2
self.shortEntry3 = rec.shortEntry3
self.shortEntry4 = rec.shortEntry4
self.shortStop = rec.shortStop
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 load_var(self):
filename = get_dss() + 'fut/check/signal_aberration_var.csv'
if os.path.exists(filename):
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
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 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/dalicta/signal_dalicta_'+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 open(self, price, change):
"""开仓"""
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 ] ]
df = pd.DataFrame(r,
columns=[
'datetime', 'direction', 'offset', 'volume',
'price', 'pnl'
])
filename = get_dss(
) + 'fut/deal/signal_aberration_' + self.type + '_' + self.vtSymbol + '.csv'
df.to_csv(filename, index=False, mode='a', header=False)
def load_var(self):
filename = get_dss(
) + 'fut/engine/dalicta/signal_dalicta_' + self.type + '_var_' + self.vtSymbol + '.csv'
if os.path.exists(filename):
df = pd.read_csv(filename, sep='$')
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 open(self, price, change):
"""开仓"""
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.intraTradeHigh, self.intraTradeLow, self.stop] ]
df = pd.DataFrame(r, columns=['datetime','direction','offset','volume','price','pnl', \
'intraTradeHigh','intraTradeLow','stop'])
filename = get_dss(
) + 'fut/deal/signal_donchian_' + 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 load_var(self):
filename = get_dss() + 'fut/engine/atrrsi/signal_atrrsi_var.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
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 load_var(self):
pz = str(get_contract(self.vtSymbol).pz)
filename = get_dss(
) + 'fut/engine/rsiboll/signal_rsiboll_' + 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
self.intraTradeHigh = rec.intraTradeHigh
self.intraTradeLow = rec.intraTradeLow
self.stop = rec.stop
self.dida = rec.dida
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 load_var(self):
pz = str(get_contract(self.vtSymbol).pz)
filename = get_dss(
) + 'fut/engine/aberration_enhance/signal_aberration_enhance_' + 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
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
class Fut_TurtleSignal(Signal):
#----------------------------------------------------------------------
def __init__(self, portfolio, vtSymbol):
self.type = 'mix'
# 策略参数
self.entryWindow = 100 # 入场通道周期数
self.exitWindow = 50 # 出场通道周期数
self.atrWindow = 20 # 计算ATR周期数
self.profitCheck = True # 是否检查上一笔盈利
self.initBars = 100 # 初始化数据所用的天数
self.minx = 'min15'
# 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
self.result_list = []
Signal.__init__(self, portfolio, vtSymbol)
#----------------------------------------------------------------------
def load_param(self):
filename = get_dss() + 'fut/engine/turtle/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.entryWindow = rec.entryWindow
self.exitWindow = rec.exitWindow
#----------------------------------------------------------------------
def set_param(self, param_dict):
if 'entryWindow' in param_dict:
self.entryWindow = param_dict['entryWindow']
if 'exitWindow' in param_dict:
self.exitWindow = param_dict['exitWindow']
#----------------------------------------------------------------------
def onBar(self, bar, minx='min15'):
"""新推送过来一个bar，进行处理"""
self.bar = bar
if minx == 'min1':
self.on_bar_min1(bar)
if minx == 'min15':
self.on_bar_minx(bar)
#----------------------------------------------------------------------
def on_bar_min1(self, bar):
# self.generateSignal(bar) # 在min1周期上，触发信号，产生交易指令
pass
#----------------------------------------------------------------------
def on_bar_minx(self, bar):
self.am.updateBar(bar)
if not self.am.inited:
return
self.generateSignal(bar) # 在minx周期上，触发信号，产生交易指令
self.calculateIndicator() # 在minx周期上，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(self.calculateTradePrice(DIRECTION_SHORT, bar.low),
abs(self.unit))
return
elif self.unit < 0:
shortExit = min(self.shortStop, self.exitUp)
if bar.high >= shortExit:
self.cover(self.calculateTradePrice(DIRECTION_LONG, bar.high),
abs(self.unit))
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:
price = self.calculateTradePrice(DIRECTION_LONG,
self.longEntry1)
self.buy(price, 1)
self.longStop = price - self.atrVolatility * 2
trade = True
if bar.high >= self.longEntry2 and self.unit < 2:
price = self.calculateTradePrice(DIRECTION_LONG,
self.longEntry2)
self.buy(price, 1)
self.longStop = price - self.atrVolatility * 2
trade = True
# if bar.high >= self.longEntry3 and self.unit < 3:
# price = self.calculateTradePrice(DIRECTION_LONG, self.longEntry3)
# self.buy(price, 1)
# self.longStop = price - self.atrVolatility * 2
# trade = True
#
# if bar.high >= self.longEntry4 and self.unit < 4:
# price = self.calculateTradePrice(DIRECTION_LONG, self.longEntry4)
# self.buy(price, 1)
# self.longStop = price - self.atrVolatility * 2
# 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:
price = self.calculateTradePrice(DIRECTION_SHORT,
self.shortEntry1)
self.short(price, 1)
self.shortStop = price + self.atrVolatility * 2
if bar.low <= self.shortEntry2 and self.unit > -2:
price = self.calculateTradePrice(DIRECTION_SHORT,
self.shortEntry2)
self.short(price, 1)
self.shortStop = price + self.atrVolatility * 2
# if bar.low <= self.shortEntry3 and self.unit > -3:
# price = self.calculateTradePrice(DIRECTION_SHORT, self.shortEntry3)
# self.short( price, 1 )
# self.shortStop = price + self.atrVolatility * 2
#
# if bar.low <= self.shortEntry4 and self.unit > -4:
# price = self.calculateTradePrice(DIRECTION_SHORT, self.shortEntry4)
# self.short( price, 1 )
# self.shortStop = price + self.atrVolatility * 2
#----------------------------------------------------------------------
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 * 10
self.longEntry3 = self.entryUp + self.atrVolatility * 20
self.longEntry4 = self.entryUp + self.atrVolatility * 30
self.longStop = 0
self.shortEntry1 = self.entryDown
self.shortEntry2 = self.entryDown - self.atrVolatility * 10
self.shortEntry3 = self.entryDown - self.atrVolatility * 20
self.shortEntry4 = self.entryDown - self.atrVolatility * 30
self.shortStop = 0
r = [[self.bar.date,self.bar.time,self.bar.close,self.unit,self.entryUp,self.entryDown,self.atrVolatility, \
self.longEntry1,self.longEntry2,self.longEntry3,self.longEntry4, self.longStop, \
self.shortEntry1,self.shortEntry2,self.shortEntry3,self.shortEntry4, self.shortStop ]]
df = pd.DataFrame(r)
filename = get_dss(
) + 'fut/engine/turtle/bar_turtle_' + self.vtSymbol + '.csv'
df.to_csv(filename, index=False, mode='a', header=False)
#----------------------------------------------------------------------
def load_var(self):
filename = get_dss() + 'fut/engine/turtle/signal_turtle_var.csv'
if os.path.exists(filename):
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.atrVolatility = rec.atrVolatility
self.entryUp = rec.entryUp
self.entryDown = rec.entryDown
self.exitUp = rec.exitUp
self.exitDown = rec.exitDown
self.longEntry1 = rec.longEntry1
self.longEntry2 = rec.longEntry2
self.longEntry3 = rec.longEntry3
self.longEntry4 = rec.longEntry4
self.longStop = rec.longStop
self.shortEntry1 = rec.shortEntry1
self.shortEntry2 = rec.shortEntry2
self.shortEntry3 = rec.shortEntry3
self.shortEntry4 = rec.shortEntry4
self.shortStop = rec.shortStop
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, \
0, 0, 0, 0, 0, \
self.atrVolatility,self.entryUp,self.entryDown,self.exitUp,self.exitDown, \
self.longEntry1,self.longEntry2,self.longEntry3,self.longEntry4,self.longStop, \
self.shortEntry1,self.shortEntry2,self.shortEntry3,self.shortEntry4,self.shortStop
]
]
else:
r = [ [self.portfolio.result.date, self.vtSymbol, self.unit, \
1, self.result.unit, self.result.entry, self.result.exit, self.result.pnl, \
self.atrVolatility,self.entryUp,self.entryDown,self.exitUp,self.exitDown, \
self.longEntry1,self.longEntry2,self.longEntry3,self.longEntry4,self.longStop, \
self.shortEntry1,self.shortEntry2,self.shortEntry3,self.shortEntry4,self.shortStop
]
]
df = pd.DataFrame(r, columns=['datetime','vtSymbol','unit', \
'has_result','result_unit','result_entry','result_exit', 'result_pnl', \
'atrVolatility','entryUp','entryDown','exitUp','exitDown', \
'longEntry1','longEntry2','longEntry3','longEntry4','longStop', \
'shortEntry1','shortEntry2','shortEntry3','shortEntry4','shortStop'
])
filename = get_dss() + 'fut/engine/turtle/signal_turtle_var.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):
"""开仓"""
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
]]
df = pd.DataFrame(r,
columns=[
'datetime', 'direction', 'offset', 'volume',
'price', 'pnl'
])
filename = get_dss(
) + 'fut/engine/turtle/signal_deal_' + self.portfolio.name + '_' + self.vtSymbol + '.csv'
df.to_csv(filename, index=False, mode='a', header=False)
#----------------------------------------------------------------------
def close(self, price, change):
"""平仓"""
self.unit = 0
self.result.close(price)
r = [[
self.bar.date + ' ' + self.bar.time, '', '平', 0, price,
self.result.pnl
]]
df = pd.DataFrame(r,
columns=[
'datetime', 'direction', 'offset', 'volume',
'price', 'pnl'
])
filename = get_dss(
) + 'fut/engine/turtle/signal_deal_' + self.portfolio.name + '_' + self.vtSymbol + '.csv'
df.to_csv(filename, index=False, mode='a', header=False)
self.result_list.append(self.result)
self.result = None
#----------------------------------------------------------------------
def getLastPnl(self):
"""获取上一笔交易的盈亏"""
if not self.result_list:
return 0
result = self.result_list[-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
class Fut_CciBollSignal_Kong(Signal):
#----------------------------------------------------------------------
def __init__(self, portfolio, vtSymbol):
self.type = 'kong'
# 策略参数
self.bollWindow = 20 # 布林通道窗口数
self.bollDev = 3.1 # 布林通道的偏差
self.cciWindow = 10 # CCI窗口数
self.atrWindow = 30 # ATR窗口数
self.slMultiplier = 3 # 计算止损距离的乘数
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 = 'min15'
# 策略临时变量
self.cciValue = 0 # CCI指标数值
self.atrValue = 0 # ATR指标数值
self.bollUp = 0
self.bollDown = 0
self.can_buy = False
self.can_short = False
# 需要持久化保存的变量
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
Signal.__init__(self, portfolio, vtSymbol)
#----------------------------------------------------------------------
def load_param(self):
filename = get_dss() + 'fut/cfg/signal_cciboll_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
#print('成功加载策略参数', self.rsiLength, self.trailingPercent, self.victoryPercent)
#----------------------------------------------------------------------
def set_param(self, param_dict):
if 'bollWindow' in param_dict:
self.bollWindow = param_dict['bollWindow']
#print('成功设置策略参数 self.bollWindow: ',self.bollWindow)
if 'bollDev' in param_dict:
self.bollDev = param_dict['bollDev']
#print('成功设置策略参数 self.bollDev: ',self.bollDev)
if 'slMultiplier' in param_dict:
self.slMultiplier = param_dict['slMultiplier']
#print('成功设置策略参数 self.slMultiplier: ',self.slMultiplier)
#----------------------------------------------------------------------
def onBar(self, bar, minx='min5'):
"""新推送过来一个bar，进行处理"""
self.bar = bar
if minx == 'min1':
self.on_bar_min1(bar)
if minx == self.minx:
self.on_bar_minx(bar)
def on_bar_min1(self, bar):
pass
# 效果提升不明显。不能加开仓逻辑，大幅降低效果
# if self.unit < 0:
# if bar.close >= self.stop:
# self.cover(bar.close, abs(self.unit))
def on_bar_minx(self, 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(1, array=True)
self.atrValue = atrArray[-self.atrWindow:].mean()
self.bollUp, self.bollDown = self.am.boll(self.bollWindow,
self.bollDev)
boll_condition = True if self.bar.close < self.bollDown else False
self.cciValue = self.am.cci(self.cciWindow)
cci_condition = True if self.cciValue < -100 else False
self.can_short = False
if cci_condition and boll_condition:
#if boll_condition:
self.can_short = True
r = [[
self.bar.date, self.bar.time, self.bar.close, self.can_short,
self.bollUp, self.bollDown, self.cciValue, self.atrValue,
self.slMultiplier, boll_condition, cci_condition,
self.intraTradeLow, self.stop
]]
df = pd.DataFrame(r)
filename = get_dss(
) + 'fut/engine/cciboll/bar_cciboll_kong_' + self.vtSymbol + '.csv'
df.to_csv(filename, index=False, mode='a', header=False)
#----------------------------------------------------------------------
def generateSignal(self, bar):
# 当前无仓位
if self.unit == 0:
self.intraTradeHigh = bar.high
self.intraTradeLow = bar.low
if self.can_short == True and self.paused == False:
self.cost = bar.close
self.stop = 100E4
self.intraTradeLow = bar.close
self.short(bar.close, self.fixedSize)
# 持有空头仓位
elif self.unit < 0:
if bar.close >= self.stop:
self.cover(bar.close, abs(self.unit))
self.intraTradeLow = min(self.intraTradeLow, bar.low)
self.stop = self.intraTradeLow + self.atrValue * self.slMultiplier
#----------------------------------------------------------------------
def load_var(self):
pz = str(get_contract(self.vtSymbol).pz)
filename = get_dss(
) + 'fut/engine/cciboll/signal_cciboll_' + 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
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'])
pz = str(get_contract(self.vtSymbol).pz)
filename = get_dss(
) + 'fut/engine/cciboll/signal_cciboll_' + 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):
"""开仓"""
self.unit += change
if not self.result:
self.result = SignalResult()
self.result.open(price, change)
r = [ [self.bar.date+' '+self.bar.time, self.vtSymbol, '多' if change>0 else '空', '开', \
abs(change), price, 0 ] ]
df = pd.DataFrame(r,
columns=[
'datetime', 'symbol', 'direction', 'offset',
'volume', 'price', 'pnl'
])
pz = str(get_contract(self.vtSymbol).pz)
filename = get_dss(
) + 'fut/engine/cciboll/signal_cciboll_' + 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):
"""平仓"""
self.unit = 0
self.result.close(price)
r = [ [self.bar.date+' '+self.bar.time, self.vtSymbol, '', '平', \
0, price, self.result.pnl ] ]
df = pd.DataFrame(r,
columns=[
'datetime', 'symbol', 'direction', 'offset',
'volume', 'price', 'pnl'
])
pz = str(get_contract(self.vtSymbol).pz)
filename = get_dss(
) + 'fut/engine/cciboll/signal_cciboll_' + 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
class Fut_RsiBollSignal_Kong(Signal):
#----------------------------------------------------------------------
def __init__(self, portfolio, vtSymbol):
self.type = 'kong'
# 策略参数
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.fixedSize = 1 # 每次交易的数量
self.initBars = 100 # 初始化数据所用的天数
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.atr_short = 0
self.atr_mid = 0
self.atr_long = 0
self.rsi_value = 0 # RSI指标的数值
self.rsi_ma = 0
self.can_buy = False
self.can_short = False
self.bollUp = 0
self.bollDown = 0
self.gap = 100
self.dida = 0
# 需要持久化保存的变量
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
Signal.__init__(self, portfolio, vtSymbol)
#----------------------------------------------------------------------
def load_param(self):
filename = get_dss() + 'fut/cfg/signal_rsiboll_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
#print('成功加载策略参数', self.rsiLength, self.trailingPercent, self.victoryPercent)
#----------------------------------------------------------------------
def set_param(self, param_dict):
if 'atrMaLength' in param_dict:
self.atrMaLength = param_dict['atrMaLength']
#print('成功设置策略参数 self.atrMaLength: ',self.atrMaLength)
if 'rsiLength' in param_dict:
self.rsiLength = param_dict['rsiLength']
#print('成功设置策略参数 self.rsiLength: ',self.rsiLength)
if 'trailingPercent' in param_dict:
self.trailingPercent = param_dict['trailingPercent']
#print('成功设置策略参数 self.trailingPercent: ',self.trailingPercent)
if 'victoryPercent' in param_dict:
self.victoryPercent = param_dict['victoryPercent']
#print('成功设置策略参数 self.victoryPercent: ',self.victoryPercent)
#----------------------------------------------------------------------
def onBar(self, bar, minx='min5'):
"""新推送过来一个bar，进行处理"""
self.bar = bar
if minx == 'min1':
self.on_bar_min1(bar)
if minx == self.minx:
self.on_bar_minx(bar)
# r = [[minx,bar.date,bar.time,bar.open,bar.close]]
# df = pd.DataFrame(r)
# filename = get_dss() + 'fut/engine/rsiboll/bar_' + self.vtSymbol + '.csv'
# df.to_csv(filename, index=False, mode='a', header=False)
def on_bar_min1(self, bar):
# 开盘有大缺口，暂停开仓
if bar.time in ['09:01:00', '21:01:00']:
if abs(bar.open - self.am.closeArray[-1]) > self.gap:
self.paused = True
# 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_minx(self, 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(
1, array=True
) # 长度为100，有效数据为initBars # print(len(atrArray)); print(atrArray); assert False
self.atr_short = atrArray[-3:].mean()
self.atr_mid = atrArray[-20:].mean()
self.atr_long = atrArray[-50:].mean()
atr_condition = True if self.atr_short > self.atr_mid else False
self.bollUp, self.bollDown = self.am.boll(60, 3)
boll_condition = True if self.bar.close < self.bollDown else False
rsiArray = self.am.rsi(self.rsiLength, array=True)
self.rsi_value = rsiArray[-1]
self.rsi_ma = rsiArray[-35:].mean()
rsi_condition = True if self.rsi_value < self.rsiSell and self.rsi_ma > 40 else False
self.can_short = False
if rsi_condition and boll_condition and atr_condition:
self.can_short = True
# r = [[self.bar.date,self.bar.time,self.bar.close,self.can_short,self.bollUp,self.bollDown,self.rsi_value,self.rsi_ma,self.atr_short,self.atr_mid,rsi_condition, boll_condition, atr_condition]]
# df = pd.DataFrame(r)
# filename = get_dss() + 'fut/engine/rsiboll/bar_rsiboll_kong_' + self.vtSymbol + '.csv'
# df.to_csv(filename, index=False, mode='a', header=False)
#----------------------------------------------------------------------
def generateSignal(self, bar):
# 当前无仓位
if self.unit == 0:
self.intraTradeHigh = bar.high
self.intraTradeLow = bar.low
if self.can_short == True and self.paused == False:
self.cost = bar.close
self.stop = 100E4
self.intraTradeLow = bar.close
self.dida = 0
self.short(bar.close, self.fixedSize)
# 持有空头仓位
elif self.unit < 0:
self.dida += 1
self.intraTradeLow = min(self.intraTradeLow, bar.low)
#self.stop = min( self.stop, self.intraTradeLow * (1+self.victoryPercent/100) )
if self.stop > self.cost:
self.stop = min(
self.stop,
self.intraTradeLow * (1 + self.trailingPercent / 100))
else:
self.stop = min(
self.stop,
self.intraTradeLow * (1 + self.victoryPercent / 100))
if bar.close >= self.stop:
self.cover(bar.close, abs(self.unit))
elif self.dida >= 15 and bar.close < self.cost and self.stop > self.cost:
self.cover(bar.close, abs(self.unit))
#----------------------------------------------------------------------
def load_var(self):
pz = str(get_contract(self.vtSymbol).pz)
filename = get_dss(
) + 'fut/engine/rsiboll/signal_rsiboll_' + 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
self.intraTradeHigh = rec.intraTradeHigh
self.intraTradeLow = rec.intraTradeLow
self.stop = rec.stop
self.dida = rec.dida
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, self.dida, \
0, 0, 0, 0, 0 ] ]
else:
r = [ [self.portfolio.result.date, self.vtSymbol, self.unit, self.cost, \
self.intraTradeHigh, self.intraTradeLow, self.stop, self.dida, \
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', 'dida', \
'has_result','result_unit','result_entry','result_exit', 'result_pnl'])
pz = str(get_contract(self.vtSymbol).pz)
filename = get_dss(
) + 'fut/engine/rsiboll/signal_rsiboll_' + 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):
"""开仓"""
self.unit += change
if not self.result:
self.result = SignalResult()
self.result.open(price, change)
r = [ [self.bar.date+' '+self.bar.time, self.vtSymbol, '多' if change>0 else '空', '开', \
abs(change), price, 0 ] ]
df = pd.DataFrame(r,
columns=[
'datetime', 'symbol', 'direction', 'offset',
'volume', 'price', 'pnl'
])
pz = str(get_contract(self.vtSymbol).pz)
filename = get_dss(
) + 'fut/engine/rsiboll/signal_rsiboll_' + 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):
"""平仓"""
self.unit = 0
self.result.close(price)
# 本次盈利超150点，暂停策略至收盘
if self.result.pnl >= 50 + self.gap:
self.paused = True
r = [ [self.bar.date+' '+self.bar.time, self.vtSymbol, '', '平', \
0, price, self.result.pnl ] ]
df = pd.DataFrame(r,
columns=[
'datetime', 'symbol', 'direction', 'offset',
'volume', 'price', 'pnl'
])
pz = str(get_contract(self.vtSymbol).pz)
filename = get_dss(
) + 'fut/engine/rsiboll/signal_rsiboll_' + 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
class Fut_MaSignal_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 = 60 # 初始化数据所用的天数
self.minx = 'day'
# 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)
#----------------------------------------------------------------------
def load_param(self):
filename = get_dss() + 'fut/engine/ma/signal_ma_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"""
self.bar = bar
if minx == 'day':
self.on_bar_minx(bar)
def on_bar_minx(self, 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(10, array=True)
ma_mid_arr = self.am.sma(30, array=True)
ma_long_arr = self.am.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]:
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]
]]
df = pd.DataFrame(r)
filename = get_dss(
) + 'fut/engine/ma/bar_ma_' + 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/ma/signal_ma_' + 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/ma/signal_ma_' + 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/ma/signal_ma_' + 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/ma/signal_ma_' + 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
class Fut_AberrationSignal_Kong(Signal):
#----------------------------------------------------------------------
def __init__(self, portfolio, vtSymbol):
self.type = 'kong'
# 策略参数
self.bollWindow = 80 # 布林通道窗口数
self.bollDev = 2 # 布林通道的偏差
self.fixedSize = 1 # 每次交易的数量
self.initBars = 90 # 初始化数据所用的天数
self.minx = 'min5'
# 策略临时变量
self.bollUp = 0 # 布林通道上轨
self.bollDown = 0 # 布林通道下轨
# 需要持久化保存的变量
self.stop = 0 # 多头止损
Signal.__init__(self, portfolio, vtSymbol)
#----------------------------------------------------------------------
def load_param(self):
filename = get_dss(
) + 'fut/cfg/signal_aberration_' + self.type + '_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.bollWindow = rec.bollWindow
self.bollDev = rec.bollDev
print('成功加载策略参数', self.bollWindow, self.bollDev)
#----------------------------------------------------------------------
def set_param(self, param_dict):
if 'bollWindow' in param_dict:
self.bollWindow = param_dict['bollWindow']
print('成功设置策略参数 self.bollWindow: ', self.bollWindow)
if 'bollDev' in param_dict:
self.bollDev = param_dict['bollDev']
print('成功设置策略参数 self.bollDev: ', self.bollDev)
#----------------------------------------------------------------------
def onBar(self, bar, minx='min5'):
"""新推送过来一个bar，进行处理"""
self.bar = bar
if minx == 'min1':
self.on_bar_min1(bar)
else:
self.on_bar_minx(bar)
# r = [[minx,bar.date,bar.time,bar.open,bar.close]]
# df = pd.DataFrame(r)
# filename = get_dss() + 'fut/check/bar_' + self.vtSymbol + '.csv'
# df.to_csv(filename, index=False, mode='a', header=False)
def on_bar_min1(self, bar):
pass
def on_bar_minx(self, 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"""
self.bollUp, self.bollDown = self.am.boll(self.bollWindow,
self.bollDev)
self.stop = (self.bollUp + self.bollDown) / 2
#----------------------------------------------------------------------
def generateSignal(self, bar):
# 当前无仓位
if self.unit == 0:
if bar.close < self.bollDown:
self.short(bar.close, self.fixedSize)
# 持有空头仓位
elif self.unit < 0:
if bar.close > self.stop:
self.cover(bar.close, abs(self.unit))
#----------------------------------------------------------------------
def load_var(self):
filename = get_dss(
) + 'fut/check/signal_aberration_' + self.type + '_var.csv'
if os.path.exists(filename):
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
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, \
0, 0, 0, 0, 0 ] ]
else:
r = [ [self.portfolio.result.date,self.vtSymbol, self.unit, \
1, self.result.unit, self.result.entry, self.result.exit, self.result.pnl ] ]
df = pd.DataFrame(r, columns=['datetime','vtSymbol','unit', \
'has_result','result_unit','result_entry','result_exit', 'result_pnl'])
filename = get_dss(
) + 'fut/check/signal_aberration_' + self.type + '_var.csv'
df.to_csv(filename, index=False, mode='a', header=False)
#----------------------------------------------------------------------
def open(self, price, change):
"""开仓"""
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 ] ]
df = pd.DataFrame(r,
columns=[
'datetime', 'direction', 'offset', 'volume',
'price', 'pnl'
])
filename = get_dss(
) + 'fut/deal/signal_aberration_' + self.type + '_' + 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.bar.date+' '+self.bar.time, '', '平', \
0, price, self.result.pnl ] ]
df = pd.DataFrame(r,
columns=[
'datetime', 'direction', 'offset', 'volume',
'price', 'pnl'
])
filename = get_dss(
) + 'fut/deal/signal_aberration_' + self.type + '_' + self.vtSymbol + '.csv'
df.to_csv(filename, index=False, mode='a', header=False)
self.result = None
class Fut_AtrRsiSignal(Signal):
#----------------------------------------------------------------------
def __init__(self, portfolio, vtSymbol):
self.type = 'mix'
# 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.fixedSize = 1 # 每次交易的数量
self.ratio_atrMa = 0.8
self.initBars = 60 # 初始化数据所用的天数
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
self.can_buy = False
self.can_short = False
# 需要持久化保存的变量
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.serialize_list = [
self.atrValue, self.atrMa, self.rsiValue, self.iswave,
self.intraTradeHigh, self.intraTradeLow, self.stop
]
Signal.__init__(self, portfolio, vtSymbol)
#----------------------------------------------------------------------
def load_param(self):
filename = get_dss() + 'fut/cfg/signal_atrrsi_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
print('成功加载策略参数', self.rsiLength, self.trailingPercent,
self.victoryPercent)
#----------------------------------------------------------------------
def set_param(self, param_dict):
if 'atrMaLength' in param_dict:
self.atrMaLength = param_dict['atrMaLength']
print('成功设置策略参数 self.atrMaLength: ', self.atrMaLength)
if 'rsiLength' in param_dict:
self.rsiLength = param_dict['rsiLength']
print('成功设置策略参数 self.rsiLength: ', self.rsiLength)
if 'trailingPercent' in param_dict:
self.trailingPercent = param_dict['trailingPercent']
print('成功设置策略参数 self.trailingPercent: ', self.trailingPercent)
if 'victoryPercent' in param_dict:
self.victoryPercent = param_dict['victoryPercent']
print('成功设置策略参数 self.victoryPercent: ', self.victoryPercent)
#----------------------------------------------------------------------
def onBar(self, bar, minx='min5'):
"""新推送过来一个bar，进行处理"""
self.bar = bar
if minx == 'min1':
self.on_bar_min1(bar)
if minx == self.minx:
self.on_bar_minx(bar)
# r = [[minx,bar.date,bar.time,bar.open,bar.close]]
# df = pd.DataFrame(r)
# filename = get_dss() + 'fut/engine/atrrsi/bar_' + self.vtSymbol + '.csv'
# df.to_csv(filename, index=False, mode='a', header=False)
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_minx(self, 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()
atrMa10 = atrArray[-10:].mean()
atrMa50 = atrArray[-50:].mean()
#self.iswave = False if atrMa10 < self.ratio_atrMa * atrMa50 else True
self.iswave = False if self.atrMa < self.ratio_atrMa * atrMa50 else True
self.rsiValue = self.am.rsi(self.rsiLength)
rsiArray20 = self.am.rsi(20, array=True)
self.can_buy = False
if rsiArray20[-1] > 50 and rsiArray20[-2] > 50 and rsiArray20[-3] > 50:
self.can_buy = True
self.can_short = False
if rsiArray20[-1] < 50 and rsiArray20[-2] < 50 and rsiArray20[-3] < 50:
self.can_short = True
#----------------------------------------------------------------------
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 and self.iswave == False and self.paused == False:
# 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 and self.can_buy == True:
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.cost = bar.close
self.stop = 0
self.intraTradeHigh = bar.close
self.buy(bar.close, self.fixedSize)
#elif self.rsiValue < self.rsiSell and self.can_short == True:
elif self.rsiValue < self.rsiSell:
self.cost = bar.close
self.stop = 100E4
self.intraTradeLow = bar.close
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 = max( self.stop, self.intraTradeHigh * (1-self.victoryPercent/100) )
if self.stop < self.cost:
self.stop = max(
self.stop,
self.intraTradeHigh * (1 - self.trailingPercent / 100))
else:
self.stop = max(
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 = min( self.stop, self.intraTradeLow * (1+self.victoryPercent/100) )
if self.stop > self.cost:
self.stop = min(
self.stop,
self.intraTradeLow * (1 + self.trailingPercent / 100))
else:
self.stop = min(
self.stop,
self.intraTradeLow * (1 + self.victoryPercent / 100))
#print(self.stop)
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/engine/atrrsi/signal_atrrsi_var.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
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/engine/atrrsi/signal_atrrsi_var.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):
"""开仓"""
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.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/engine/atrrsi/signal_atrrsi_' + 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 close(self, price, change):
"""平仓"""
self.unit = 0
self.result.close(price)
r = [ [self.bar.date+' '+self.bar.time, '', '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/engine/atrrsi/signal_atrrsi_' + 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)
self.result = None
class Fut_DonchianSignal_Kong(Signal):
#----------------------------------------------------------------------
def __init__(self, portfolio, vtSymbol):
self.type = 'kong'
# 策略参数
self.trailingPercent = 0.3 # 百分比移动止损
self.victoryPercent = 0.3
self.fixedSize = 1 # 每次交易的数量
self.initBars = 90 # 初始化数据所用的天数
self.minx = 'min5'
# 策略临时变量
self.can_buy = False
self.can_short = False
self.channel_up = 0
self.channel_down = 0
# 需要持久化保存的变量
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
Signal.__init__(self, portfolio, vtSymbol)
#----------------------------------------------------------------------
def load_param(self):
filename = get_dss() + 'fut/cfg/signal_donchian_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
print('成功加载策略参数', self.rsiLength, self.trailingPercent,
self.victoryPercent)
#----------------------------------------------------------------------
def set_param(self, param_dict):
if 'atrMaLength' in param_dict:
self.atrMaLength = param_dict['atrMaLength']
print('成功设置策略参数 self.atrMaLength: ', self.atrMaLength)
if 'rsiLength' in param_dict:
self.rsiLength = param_dict['rsiLength']
print('成功设置策略参数 self.rsiLength: ', self.rsiLength)
if 'trailingPercent' in param_dict:
self.trailingPercent = param_dict['trailingPercent']
print('成功设置策略参数 self.trailingPercent: ', self.trailingPercent)
if 'victoryPercent' in param_dict:
self.victoryPercent = param_dict['victoryPercent']
print('成功设置策略参数 self.victoryPercent: ', self.victoryPercent)
#----------------------------------------------------------------------
def onBar(self, bar, minx='min5'):
"""新推送过来一个bar，进行处理"""
self.bar = bar
if minx == 'min1':
self.on_bar_min1(bar)
else:
self.on_bar_minx(bar)
# r = [[minx,bar.date,bar.time,bar.open,bar.close]]
# df = pd.DataFrame(r)
# filename = get_dss() + 'fut/check/bar_' + self.vtSymbol + '.csv'
# df.to_csv(filename, index=False, mode='a', header=False)
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_minx(self, 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"""
self.channel_up, self.channel_down = self.am.donchian(60, array=True)
donchian_condition = True if self.bar.close < self.channel_down[
-2] else False
self.can_short = False
if donchian_condition:
self.can_short = True
#----------------------------------------------------------------------
def generateSignal(self, bar):
# 当前无仓位
if self.unit == 0:
self.intraTradeHigh = bar.high
self.intraTradeLow = bar.low
if self.can_short == True and self.paused == False:
self.cost = bar.close
self.stop = 100E4
self.intraTradeLow = bar.close
self.short(bar.close, self.fixedSize)
# 持有空头仓位
elif self.unit < 0:
self.intraTradeLow = min(self.intraTradeLow, bar.low)
#self.stop = min( self.stop, self.intraTradeLow * (1+self.victoryPercent/100) )
if self.stop > self.cost:
self.stop = min(
self.stop,
self.intraTradeLow * (1 + self.trailingPercent / 100))
else:
self.stop = min(
self.stop,
self.intraTradeLow * (1 + self.victoryPercent / 100))
#print(self.stop)
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_donchian_' + self.type + '_var.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
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_donchian_' + self.type + '_var.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):
"""开仓"""
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.intraTradeHigh, self.intraTradeLow, self.stop] ]
df = pd.DataFrame(r, columns=['datetime','direction','offset','volume','price','pnl', \
'intraTradeHigh','intraTradeLow','stop'])
filename = get_dss(
) + 'fut/deal/signal_donchian_' + 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 close(self, price):
"""平仓"""
self.unit = 0
self.result.close(price)
r = [ [self.bar.date+' '+self.bar.time, '', '平', \
0, price, self.result.pnl, \
self.intraTradeHigh, self.intraTradeLow, self.stop] ]
df = pd.DataFrame(r, columns=['datetime','direction','offset','volume','price','pnl', \
'intraTradeHigh','intraTradeLow','stop'])
filename = get_dss(
) + 'fut/deal/signal_donchian_' + 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)
self.result = None
