300 lines
11 KiB
Python
300 lines
11 KiB
Python
# encoding: UTF-8
|
||
|
||
"""
|
||
基于King Keltner通道的交易策略，适合用在股指上，
|
||
展示了OCO委托和5分钟K线聚合的方法。
|
||
|
||
注意事项：
|
||
1. 作者不对交易盈利做任何保证，策略代码仅供参考
|
||
2. 本策略需要用到talib，没有安装的用户请先参考www.vnpy.org上的教程安装
|
||
3. 将IF0000_1min.csv用ctaHistoryData.py导入MongoDB后，直接运行本文件即可回测策略
|
||
"""
|
||
|
||
from __future__ import division
|
||
|
||
from ctaBase import *
|
||
from ctaTemplate import CtaTemplate
|
||
|
||
import talib
|
||
import numpy as np
|
||
|
||
|
||
########################################################################
|
||
class KkStrategy(CtaTemplate):
|
||
"""基于King Keltner通道的交易策略"""
|
||
className = 'KkStrategy'
|
||
author = u'用Python的交易员'
|
||
|
||
# 策略参数
|
||
kkLength = 32 # 计算通道中值的窗口数
|
||
kkDev = 2.2 # 计算通道宽度的偏差
|
||
initDays = 10 # 初始化数据所用的天数
|
||
fixedSize = 1 # 每次交易的数量
|
||
|
||
# 策略变量
|
||
bar = None # 1分钟K线对象
|
||
barMinute = EMPTY_STRING # K线当前的分钟
|
||
fiveBar = None # 1分钟K线对象
|
||
|
||
bufferSize = 100 # 需要缓存的数据的大小
|
||
bufferCount = 0 # 目前已经缓存了的数据的计数
|
||
highArray = np.zeros(bufferSize) # K线最高价的数组
|
||
lowArray = np.zeros(bufferSize) # K线最低价的数组
|
||
closeArray = np.zeros(bufferSize) # K线收盘价的数组
|
||
|
||
atrValue = 0 # 最新的ATR指标数值
|
||
kkMid = 0 # KK通道中轨
|
||
kkUp = 0 # KK通道上轨
|
||
kkDown = 0 # KK通道下轨
|
||
|
||
buyOrderID = None # OCO委托买入开仓的委托号
|
||
shortOrderID = None # OCO委托卖出开仓的委托号
|
||
orderList = [] # 保存委托代码的列表
|
||
|
||
# 参数列表，保存了参数的名称
|
||
paramList = ['name',
|
||
'className',
|
||
'author',
|
||
'vtSymbol',
|
||
'kkLength',
|
||
'kkDev']
|
||
|
||
# 变量列表，保存了变量的名称
|
||
varList = ['inited',
|
||
'trading',
|
||
'pos',
|
||
'atrValue',
|
||
'kkMid',
|
||
'kkUp',
|
||
'kkDown']
|
||
|
||
#----------------------------------------------------------------------
|
||
def __init__(self, ctaEngine, setting):
|
||
"""Constructor"""
|
||
super(KkStrategy, self).__init__(ctaEngine, setting)
|
||
|
||
#----------------------------------------------------------------------
|
||
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）"""
|
||
# 聚合为1分钟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）"""
|
||
# 如果当前是一个5分钟走完
|
||
if bar.datetime.minute % 5 == 0:
|
||
# 如果已经有聚合5分钟K线
|
||
if self.fiveBar:
|
||
# 将最新分钟的数据更新到目前5分钟线中
|
||
fiveBar = self.fiveBar
|
||
fiveBar.high = max(fiveBar.high, bar.high)
|
||
fiveBar.low = min(fiveBar.low, bar.low)
|
||
fiveBar.close = bar.close
|
||
|
||
# 推送5分钟线数据
|
||
self.onFiveBar(fiveBar)
|
||
|
||
# 清空5分钟线数据缓存
|
||
self.fiveBar = None
|
||
else:
|
||
# 如果没有缓存则新建
|
||
if not self.fiveBar:
|
||
fiveBar = CtaBarData()
|
||
|
||
fiveBar.vtSymbol = bar.vtSymbol
|
||
fiveBar.symbol = bar.symbol
|
||
fiveBar.exchange = bar.exchange
|
||
|
||
fiveBar.open = bar.open
|
||
fiveBar.high = bar.high
|
||
fiveBar.low = bar.low
|
||
fiveBar.close = bar.close
|
||
|
||
fiveBar.date = bar.date
|
||
fiveBar.time = bar.time
|
||
fiveBar.datetime = bar.datetime
|
||
|
||
self.fiveBar = fiveBar
|
||
else:
|
||
fiveBar = self.fiveBar
|
||
fiveBar.high = max(fiveBar.high, bar.high)
|
||
fiveBar.low = min(fiveBar.low, bar.low)
|
||
fiveBar.close = bar.close
|
||
|
||
#----------------------------------------------------------------------
|
||
def onFiveBar(self, bar):
|
||
"""收到5分钟K线"""
|
||
# 撤销之前发出的尚未成交的委托（包括限价单和停止单）
|
||
for orderID in self.orderList:
|
||
self.cancelOrder(orderID)
|
||
self.orderList = []
|
||
|
||
# 保存K线数据
|
||
self.closeArray[0:self.bufferSize-1] = self.closeArray[1:self.bufferSize]
|
||
self.highArray[0:self.bufferSize-1] = self.highArray[1:self.bufferSize]
|
||
self.lowArray[0:self.bufferSize-1] = self.lowArray[1:self.bufferSize]
|
||
|
||
self.closeArray[-1] = bar.close
|
||
self.highArray[-1] = bar.high
|
||
self.lowArray[-1] = bar.low
|
||
|
||
self.bufferCount += 1
|
||
if self.bufferCount < self.bufferSize:
|
||
return
|
||
|
||
# 计算指标数值
|
||
self.atrValue = talib.ATR(self.highArray,
|
||
self.lowArray,
|
||
self.closeArray,
|
||
self.kkLength)[-1]
|
||
self.kkMid = talib.MA(self.closeArray, self.kkLength)[-1]
|
||
self.kkUp = self.kkMid + self.atrValue * self.kkDev
|
||
self.kkDown = self.kkMid - self.atrValue * self.kkdev
|
||
|
||
# 判断是否要进行交易
|
||
|
||
# 当前无仓位，发送OCO开仓委托
|
||
if self.pos == 0:
|
||
self.sendOcoOrder(self.kkUp, self.kkDown, self.fixedSize)
|
||
|
||
# 持有多头仓位
|
||
elif self.pos > 0 and bar.close < self.kkUp:
|
||
orderID = self.sell(bar.close*0.97, abs(self.pos))
|
||
self.orderList.append(orderID)
|
||
|
||
# 持有空头仓位
|
||
elif self.pos < 0 and bar.close > self.kkDown:
|
||
orderID = self.buy(bar.close*1.03, abs(self.pos))
|
||
self.orderList.append(orderID)
|
||
|
||
# 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):
|
||
# 多头开仓成交后，撤消空头委托
|
||
if self.pos > 0:
|
||
self.cancelOrder(self.shortOrderID)
|
||
if self.buyOrderID in self.orderList:
|
||
self.orderList.remove(self.buyOrderID)
|
||
if self.shortOrderID in self.orderList:
|
||
self.orderList.remove(self.shortOrderID)
|
||
# 反之同样
|
||
elif self.pos < 0:
|
||
self.cancelOrder(self.buyOrderID)
|
||
if self.buyOrderID in self.orderList:
|
||
self.orderList.remove(self.buyOrderID)
|
||
if self.shortOrderID in self.orderList:
|
||
self.orderList.remove(self.shortOrderID)
|
||
|
||
# 发出状态更新事件
|
||
self.putEvent()
|
||
|
||
#----------------------------------------------------------------------
|
||
def sendOcoOrder(self, buyPrice, shortPrice, volume):
|
||
"""
|
||
发送OCO委托
|
||
|
||
OCO(One Cancel Other)委托：
|
||
1. 主要用于实现区间突破入场
|
||
2. 包含两个方向相反的停止单
|
||
3. 一个方向的停止单成交后会立即撤消另一个方向的
|
||
"""
|
||
# 发送双边的停止单委托，并记录委托号
|
||
self.buyOrderID = self.buy(buyPrice, volume, True)
|
||
self.shortOrderID = self.short(shortPrice, volume, True)
|
||
|
||
# 将委托号记录到列表中
|
||
self.orderList.append(self.buyOrderID)
|
||
self.orderList.append(self.shortOrderID)
|
||
|
||
|
||
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
|
||
|
||
# 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
|
||
d = {}
|
||
engine.initStrategy(KkStrategy, d)
|
||
|
||
# 开始跑回测
|
||
engine.runBacktesting()
|
||
|
||
# 显示回测结果
|
||
engine.showBacktestingResult() |