276 lines
9.3 KiB
Python
276 lines
9.3 KiB
Python
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# encoding: UTF-8
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"""
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DualThrust交易策略
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"""
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from datetime import time
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from ..ctaBase import *
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from ..ctaTemplate import CtaTemplate
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########################################################################
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class DualThrustStrategy(CtaTemplate):
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"""DualThrust交易策略"""
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className = 'DualThrustStrategy'
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author = u'用Python的交易员'
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# 策略参数
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fixedSize = 100
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k1 = 0.4
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k2 = 0.6
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initDays = 10
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# 策略变量
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bar = None # K线对象
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barMinute = EMPTY_STRING # K线当前的分钟
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barList = [] # K线对象的列表
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dayOpen = 0
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dayHigh = 0
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dayLow = 0
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range = 0
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longEntry = 0
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shortEntry = 0
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exitTime = time(hour=14, minute=55)
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longEntered = False
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shortEntered = False
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orderList = [] # 保存委托代码的列表
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# 参数列表，保存了参数的名称
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paramList = ['name',
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'className',
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'author',
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'vtSymbol',
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'k1',
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'k2']
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# 变量列表，保存了变量的名称
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varList = ['inited',
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'trading',
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'pos',
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'range',
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'longEntry',
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'shortEntry',
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'exitTime']
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#----------------------------------------------------------------------
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def __init__(self, ctaEngine, setting):
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"""Constructor"""
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super(DualThrustStrategy, self).__init__(ctaEngine, setting)
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self.barList = []
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#----------------------------------------------------------------------
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def onInit(self):
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"""初始化策略（必须由用户继承实现）"""
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self.writeCtaLog(u'%s策略初始化' %self.name)
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# 载入历史数据，并采用回放计算的方式初始化策略数值
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initData = self.loadBar(self.initDays)
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for bar in initData:
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self.onBar(bar)
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self.putEvent()
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#----------------------------------------------------------------------
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def onStart(self):
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"""启动策略（必须由用户继承实现）"""
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self.writeCtaLog(u'%s策略启动' %self.name)
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self.putEvent()
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#----------------------------------------------------------------------
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def onStop(self):
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"""停止策略（必须由用户继承实现）"""
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self.writeCtaLog(u'%s策略停止' %self.name)
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self.putEvent()
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#----------------------------------------------------------------------
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def onTick(self, tick):
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"""收到行情TICK推送（必须由用户继承实现）"""
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# 计算K线
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tickMinute = tick.datetime.minute
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if tickMinute != self.barMinute:
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if self.bar:
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self.onBar(self.bar)
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bar = CtaBarData()
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bar.vtSymbol = tick.vtSymbol
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bar.symbol = tick.symbol
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bar.exchange = tick.exchange
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bar.open = tick.lastPrice
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bar.high = tick.lastPrice
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bar.low = tick.lastPrice
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bar.close = tick.lastPrice
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bar.date = tick.date
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bar.time = tick.time
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bar.datetime = tick.datetime # K线的时间设为第一个Tick的时间
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self.bar = bar # 这种写法为了减少一层访问，加快速度
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self.barMinute = tickMinute # 更新当前的分钟
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else: # 否则继续累加新的K线
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bar = self.bar # 写法同样为了加快速度
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bar.high = max(bar.high, tick.lastPrice)
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bar.low = min(bar.low, tick.lastPrice)
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bar.close = tick.lastPrice
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#----------------------------------------------------------------------
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def onBar(self, bar):
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"""收到Bar推送（必须由用户继承实现）"""
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# 撤销之前发出的尚未成交的委托（包括限价单和停止单）
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for orderID in self.orderList:
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self.cancelOrder(orderID)
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self.orderList = []
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# 计算指标数值
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self.barList.append(bar)
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if len(self.barList) <= 2:
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return
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else:
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self.barList.pop(0)
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lastBar = self.barList[-2]
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# 新的一天
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if lastBar.datetime.date() != bar.datetime.date():
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# 如果已经初始化
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if self.dayHigh:
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self.range = self.dayHigh - self.dayLow
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self.longEntry = bar.open + self.k1 * self.range
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self.shortEntry = bar.open - self.k2 * self.range
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self.dayOpen = bar.open
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self.dayHigh = bar.high
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self.dayLow = bar.low
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self.longEntered = False
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self.shortEntered = False
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else:
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self.dayHigh = max(self.dayHigh, bar.high)
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self.dayLow = min(self.dayLow, bar.low)
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# 尚未到收盘
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if not self.range:
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return
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if bar.datetime.time() < self.exitTime:
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if self.pos == 0:
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if bar.close > self.dayOpen:
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if not self.longEntered:
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vtOrderID = self.buy(self.longEntry, self.fixedSize, stop=True)
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self.orderList.append(vtOrderID)
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else:
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if not self.shortEntered:
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vtOrderID = self.short(self.shortEntry, self.fixedSize, stop=True)
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self.orderList.append(vtOrderID)
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# 持有多头仓位
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elif self.pos > 0:
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self.longEntered = True
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# 多头止损单
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vtOrderID = self.sell(self.shortEntry, self.fixedSize, stop=True)
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self.orderList.append(vtOrderID)
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# 空头开仓单
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if not self.shortEntered:
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vtOrderID = self.short(self.shortEntry, self.fixedSize, stop=True)
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self.orderList.append(vtOrderID)
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# 持有空头仓位
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elif self.pos < 0:
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self.shortEntered = True
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# 空头止损单
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vtOrderID = self.cover(self.longEntry, self.fixedSize, stop=True)
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self.orderList.append(vtOrderID)
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# 多头开仓单
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if not self.longEntered:
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vtOrderID = self.buy(self.longEntry, self.fixedSize, stop=True)
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self.orderList.append(vtOrderID)
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# 收盘平仓
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else:
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if self.pos > 0:
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vtOrderID = self.sell(bar.close * 0.99, abs(self.pos))
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self.orderList.append(vtOrderID)
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elif self.pos < 0:
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vtOrderID = self.cover(bar.close * 1.01, abs(self.pos))
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self.orderList.append(vtOrderID)
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# 发出状态更新事件
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self.putEvent()
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#----------------------------------------------------------------------
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def onOrder(self, order):
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"""收到委托变化推送（必须由用户继承实现）"""
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pass
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#----------------------------------------------------------------------
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def onTrade(self, trade):
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# 发出状态更新事件
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self.putEvent()
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if __name__ == '__main__':
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# 提供直接双击回测的功能
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# 导入PyQt4的包是为了保证matplotlib使用PyQt4而不是PySide，防止初始化出错
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from ctaBacktesting import *
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from PyQt4 import QtCore, QtGui
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# 创建回测引擎
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engine = BacktestingEngine()
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# 设置引擎的回测模式为K线
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engine.setBacktestingMode(engine.BAR_MODE)
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# 设置回测用的数据起始日期
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engine.setStartDate('20120101')
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# 设置产品相关参数
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engine.setSlippage(0.2) # 股指1跳
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engine.setRate(0.3/10000) # 万0.3
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engine.setSize(300) # 股指合约大小
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engine.setPriceTick(0.2) # 股指最小价格变动
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# 设置使用的历史数据库
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engine.setDatabase(MINUTE_DB_NAME, 'IF0000')
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# 在引擎中创建策略对象
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engine.initStrategy(DualThrustStrategy, {})
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# 开始跑回测
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engine.runBacktesting()
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# 显示回测结果
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engine.showBacktestingResult()
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## 跑优化
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#setting = OptimizationSetting() # 新建一个优化任务设置对象
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#setting.setOptimizeTarget('capital') # 设置优化排序的目标是策略净盈利
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#setting.addParameter('atrLength', 12, 20, 2) # 增加第一个优化参数atrLength，起始11，结束12，步进1
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#setting.addParameter('atrMa', 20, 30, 5) # 增加第二个优化参数atrMa，起始20，结束30，步进1
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#setting.addParameter('rsiLength', 5) # 增加一个固定数值的参数
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## 性能测试环境：I7-3770，主频3.4G, 8核心，内存16G，Windows 7 专业版
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## 测试时还跑着一堆其他的程序，性能仅供参考
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#import time
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#start = time.time()
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## 运行单进程优化函数，自动输出结果，耗时：359秒
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#engine.runOptimization(AtrRsiStrategy, setting)
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## 多进程优化，耗时：89秒
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##engine.runParallelOptimization(AtrRsiStrategy, setting)
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#print u'耗时：%s' %(time.time()-start)
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