vnpy/vn.trader/ctaStrategy/strategy/strategyDualThrust.py

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# encoding: UTF-8
"""
2017-04-07 13:46:14 +00:00
DualThrust交易策略
"""
from datetime import time
from ctaBase import *
from ctaTemplate import CtaTemplate
########################################################################
class DualThrustStrategy(CtaTemplate):
"""DualThrust交易策略"""
className = 'DualThrustStrategy'
author = u'用Python的交易员'
# 策略参数
fixedSize = 100
k1 = 0.4
k2 = 0.6
initDays = 10
# 策略变量
bar = None # K线对象
barMinute = EMPTY_STRING # K线当前的分钟
barList = [] # K线对象的列表
dayOpen = 0
dayHigh = 0
dayLow = 0
range = 0
longEntry = 0
shortEntry = 0
exitTime = time(hour=14, minute=55)
longEntered = False
shortEntered = False
orderList = [] # 保存委托代码的列表
# 参数列表,保存了参数的名称
paramList = ['name',
'className',
'author',
'vtSymbol',
'k1',
'k2']
# 变量列表,保存了变量的名称
varList = ['inited',
'trading',
'pos',
'range',
'longEntry',
'shortEntry',
'exitTime']
#----------------------------------------------------------------------
def __init__(self, ctaEngine, setting):
"""Constructor"""
super(DualThrustStrategy, self).__init__(ctaEngine, setting)
self.barList = []
#----------------------------------------------------------------------
def onInit(self):
"""初始化策略(必须由用户继承实现)"""
self.writeCtaLog(u'%s策略初始化' %self.name)
# 载入历史数据,并采用回放计算的方式初始化策略数值
initData = self.loadBar(self.initDays)
for bar in initData:
self.onBar(bar)
self.putEvent()
#----------------------------------------------------------------------
def onStart(self):
"""启动策略(必须由用户继承实现)"""
self.writeCtaLog(u'%s策略启动' %self.name)
self.putEvent()
#----------------------------------------------------------------------
def onStop(self):
"""停止策略(必须由用户继承实现)"""
self.writeCtaLog(u'%s策略停止' %self.name)
self.putEvent()
#----------------------------------------------------------------------
def onTick(self, tick):
"""收到行情TICK推送必须由用户继承实现"""
# 计算K线
tickMinute = tick.datetime.minute
if tickMinute != self.barMinute:
if self.bar:
self.onBar(self.bar)
bar = CtaBarData()
bar.vtSymbol = tick.vtSymbol
bar.symbol = tick.symbol
bar.exchange = tick.exchange
bar.open = tick.lastPrice
bar.high = tick.lastPrice
bar.low = tick.lastPrice
bar.close = tick.lastPrice
bar.date = tick.date
bar.time = tick.time
bar.datetime = tick.datetime # K线的时间设为第一个Tick的时间
self.bar = bar # 这种写法为了减少一层访问,加快速度
self.barMinute = tickMinute # 更新当前的分钟
else: # 否则继续累加新的K线
bar = self.bar # 写法同样为了加快速度
bar.high = max(bar.high, tick.lastPrice)
bar.low = min(bar.low, tick.lastPrice)
bar.close = tick.lastPrice
#----------------------------------------------------------------------
def onBar(self, bar):
"""收到Bar推送必须由用户继承实现"""
# 撤销之前发出的尚未成交的委托(包括限价单和停止单)
for orderID in self.orderList:
self.cancelOrder(orderID)
self.orderList = []
# 计算指标数值
self.barList.append(bar)
if len(self.barList) <= 2:
return
else:
self.barList.pop(0)
lastBar = self.barList[-2]
# 新的一天
if lastBar.datetime.date() != bar.datetime.date():
# 如果已经初始化
if self.dayHigh:
self.range = self.dayHigh - self.dayLow
self.longEntry = bar.open + self.k1 * self.range
self.shortEntry = bar.open - self.k2 * self.range
self.dayOpen = bar.open
self.dayHigh = bar.high
self.dayLow = bar.low
self.longEntered = False
self.shortEntered = False
else:
self.dayHigh = max(self.dayHigh, bar.high)
self.dayLow = min(self.dayLow, bar.low)
# 尚未到收盘
if not self.range:
return
if bar.datetime.time() < self.exitTime:
if self.pos == 0:
if bar.close > self.dayOpen:
if not self.longEntered:
vtOrderID = self.buy(self.longEntry, self.fixedSize, stop=True)
self.orderList.append(vtOrderID)
else:
if not self.shortEntered:
vtOrderID = self.short(self.shortEntry, self.fixedSize, stop=True)
self.orderList.append(vtOrderID)
# 持有多头仓位
elif self.pos > 0:
self.longEntered = True
# 多头止损单
vtOrderID = self.sell(self.shortEntry, self.fixedSize, stop=True)
self.orderList.append(vtOrderID)
# 空头开仓单
if not self.shortEntered:
vtOrderID = self.short(self.shortEntry, self.fixedSize, stop=True)
self.orderList.append(vtOrderID)
# 持有空头仓位
elif self.pos < 0:
self.shortEntered = True
# 空头止损单
vtOrderID = self.cover(self.longEntry, self.fixedSize, stop=True)
self.orderList.append(vtOrderID)
# 多头开仓单
if not self.longEntered:
vtOrderID = self.buy(self.longEntry, self.fixedSize, stop=True)
self.orderList.append(vtOrderID)
# 收盘平仓
else:
if self.pos > 0:
vtOrderID = self.sell(bar.close * 0.99, abs(self.pos))
self.orderList.append(vtOrderID)
elif self.pos < 0:
vtOrderID = self.cover(bar.close * 1.01, abs(self.pos))
self.orderList.append(vtOrderID)
# 发出状态更新事件
self.putEvent()
#----------------------------------------------------------------------
def onOrder(self, order):
"""收到委托变化推送(必须由用户继承实现)"""
pass
#----------------------------------------------------------------------
def onTrade(self, trade):
# 发出状态更新事件
self.putEvent()
if __name__ == '__main__':
# 提供直接双击回测的功能
# 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
from ctaBacktesting import *
from PyQt4 import QtCore, QtGui
# 创建回测引擎
engine = BacktestingEngine()
# 设置引擎的回测模式为K线
engine.setBacktestingMode(engine.BAR_MODE)
# 设置回测用的数据起始日期
engine.setStartDate('20120101')
# 设置产品相关参数
engine.setSlippage(0.2) # 股指1跳
engine.setRate(0.3/10000) # 万0.3
engine.setSize(300) # 股指合约大小
engine.setPriceTick(0.2) # 股指最小价格变动
# 设置使用的历史数据库
engine.setDatabase(MINUTE_DB_NAME, 'IF0000')
# 在引擎中创建策略对象
engine.initStrategy(DualThrustStrategy, {})
# 开始跑回测
engine.runBacktesting()
# 显示回测结果
engine.showBacktestingResult()
## 跑优化
#setting = OptimizationSetting() # 新建一个优化任务设置对象
#setting.setOptimizeTarget('capital') # 设置优化排序的目标是策略净盈利
#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
#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
#setting.addParameter('rsiLength', 5) # 增加一个固定数值的参数
## 性能测试环境I7-3770主频3.4G, 8核心内存16GWindows 7 专业版
## 测试时还跑着一堆其他的程序,性能仅供参考
#import time
#start = time.time()
## 运行单进程优化函数自动输出结果耗时359秒
#engine.runOptimization(AtrRsiStrategy, setting)
## 多进程优化耗时89秒
##engine.runParallelOptimization(AtrRsiStrategy, setting)
#print u'耗时:%s' %(time.time()-start)