@Channelchan 2018-09-19T12:16:16.000000Z 字数 8339 阅读 1298

Xiezhenghang-二号策略（一号策略改进版本）

策略逻辑：设定唐安奇通道上线，为50分钟收盘最大值，当分钟的最大值突破上一分钟通道的上线1.01倍时认为有上涨趋势并做多，分钟最小值突破上线0.99倍且上一分钟是在上线之上时判断有下跌趋势并做空（若有仓位，突破时平仓，并且反向开仓）。

在一号的海龟策略基础上，增加了仓位管理操作，利用ATR判断波动率，波动率小的时候重仓，波动率大的时候弱仓。

# coding: utf-8
from vnpy.trader.vtConstant import *
from vnpy.trader.app.ctaStrategy.ctaTemplate import (CtaTemplate,
                                                     BarGenerator,
                                                     ArrayManager)
from collections import defaultdict
import numpy as np
import talib as ta
import pandas as pd
from datetime import datetime
class wangge_Strategy(CtaTemplate):
    #单边海龟策略+波动率仓位管理
    className = 'wangge_Strategy'
    author = 'sky'
    symbol = EMPTY_STRING  
    # 策略变量
    posSize = 1                     # 每笔下单的数量
    fastWindow = 20    # 快速均线参数
    slowWindow = 80     # 慢速均线参数
    stopRatio = 0.06   # 止损比例
    fixsize = 1
    transactionPrice = EMPTY_FLOAT # 记录成交价格
    wave = EMPTY_FLOAT
    ##########
        # 参数列表，保存了参数的名称
    paramList = ['name',
                 'className',
                 'author',
                 'symbol',
                'fastWindow',
                 'slowWindow',
                 'stopRatio',
                 'profitMultiplier']   
    # 变量列表，保存了变量的名称
    varList = ['inited',
               'trading',
               'posDict',
              'transactionPrice',
              'maTrend']  
    # 同步列表，保存了需要保存到数据库的变量名称
    syncList = ['posDict',
                'eveningDict',
                'bondDict']
    #----------------------------------------------------------------------
    def __init__(self, ctaEngine, setting):
        # 首先找到策略的父类（就是类CtaTemplate），然后把DoubleMaStrategy的对象转换为类CtaTemplate的对象
        super(wangge_Strategy, self).__init__(ctaEngine, setting)
    #----------------------------------------------------------------------
    def onInit(self):
        """初始化策略（必须由用户继承实现）"""
        self.writeCtaLog(u'海龟策略初始化')
        # 初始化仓位字典
        self.symbol = self.symbolList[0]  
        self.generateBarDict(self.onBar)  
        self.generateBarDict(self.onBar,5,self.on5MinBar,size =100)
        if self.ctaEngine.engineType == 'trading':
            # 实盘载入1分钟历史数据，并采用回放计算的方式初始化策略参数
            # 通用可选参数：["1min","5min","15min","30min","60min","4hour","1day","1week","1month"]
            pastbar1 = self.loadHistoryBar(self.Symbol,
                                type_ = "1min",  size = 1000)
            # 更新数据矩阵(optional)
            for bar1 in zip (pastbar1):    
                self.amDict[self.symbol].updateBar(bar1)    
        elif self.ctaEngine.engineType == 'backtesting':
            # 获取回测设置中的initHours长度的历史数据
            self.initBacktesingData()    
        self.putEvent()
    #----------------------------------------------------------------------
    def onStart(self):
        """启动策略（必须由用户继承实现）"""
        self.writeCtaLog(u'网格策略初始化')
        #print('start',file=test)
        self.putEvent()
    #----------------------------------------------------------------------
    def onStop(self):
        """停止策略（必须由用户继承实现）"""
        self.putEvent()
    #----------------------------------------------------------------------
    def onTick(self, tick):
        """收到行情TICK推送（必须由用户继承实现）"""
        pass
    def onBar(self, bar):
        """收到Bar推送（必须由用户继承实现）"""
        self.writeCtaLog('stg_onbar_check_%s_%s_%s'%(bar.vtSymbol,bar.datetime,bar.close))
        self.bg5Dict[bar.vtSymbol].updateBar(bar)
        am = self.am5Dict[self.symbol]
#         fastMa = ta.MA(am.close, self.fastWindow)
#         slowMa = ta.MA(am.close, self.slowWindow)
#         if fastMa[-2] < slowMa[-2] and fastMa[-1] > slowMa[-1]:
#             self.Trend = 1
#         else:
#             self.Trend = 0
#         if slowMa[-1]>slowMa[-2]:
#             self.wave = 1
#         else:
#             self.wave = 0
#         if (self.posDict[self.symbol+"_LONG"] >0 and self.posDict[self.symbol+"_LONG"] <10):
#             if self.wave == 0:
#                 self.sell(self.symbol, bar.close*0.98, self.posDict[self.symbol+"_LONG"], priceType = PRICETYPE_LIMITPRICE,levelRate = 10)
#             n = int((bar.close-self.transactionPrice)/0.001)
#             print('n:%s,bar.close:%s,self.transactionPrice:%s'%(n,bar.close,self.transactionPrice))
#             if n>0:
#                 self.sell(self.symbol, bar.close, n,priceType = PRICETYPE_LIMITPRICE,levelRate = 10)
#                 if self.posDict[self.symbol+"_LONG"] == 0:
#                     if self.wave == 1:
#                         self.buy(self.symbol, bar.close*0.98, 5, priceType = PRICETYPE_LIMITPRICE,levelRate = 10)
#             elif n<0:
#                 self.buy(self.symbol, bar.close*0.98, -n, priceType = PRICETYPE_LIMITPRICE,levelRate = 10)
        if self.posDict[self.symbol+"_LONG"] ==5:
            self.sell(self.symbol, bar.close, 5,priceType = PRICETYPE_LIMITPRICE,levelRate = 10)
    def on5MinBar(self, bar):
        """15分钟K线推送"""
        self.writeCtaLog('stg_on5Minbar_check_%s_%s_%s'%(bar.vtSymbol,bar.datetime,self.am5Dict[bar.vtSymbol].close))
        self.am5Dict[bar.vtSymbol].updateBar(bar)
        am5 = self.am5Dict[self.symbol]
        fastMa = ta.MA(am5.close, self.fastWindow)
        slowMa = ta.MA(am5.close, self.slowWindow)
        if fastMa[-2] < fastMa[-1] and slowMa[-2] > slowMa[-1]:
            self.Trend = 1
        else:
            self.Trend = 0
        if (self.posDict[self.symbol+"_LONG"] == 0) and (self.posDict[self.symbol+"_SHORT"] == 0):
            if self.Trend == 1:
                self.buy(self.symbol, bar.close*1.02 , 5 ,priceType = PRICETYPE_LIMITPRICE,levelRate = 10)
        ######### 计算策略需要的信号-------------------------------------------------####################################        
        self.putEvent()
    def onOrder(self, order):
        """收到委托变化推送（必须由用户继承实现）"""
        # 对于无需做细粒度委托控制的策略，可以忽略onOrder
        pass
    #----------------------------------------------------------------------
    def onTrade(self, trade):
        """收到成交推送（必须由用户继承实现）"""
        self.transactionPrice = trade.price
        #print('price:%s, direction:%s,offset:%s,self.Cross:%s,tradeVolume: %s'
                #%(trade.price, trade.direction, trade.offset,self.Cross,trade.volume),file=test0)
        pass
    #----------------------------------------------------------------------
    def onStopOrder(self, so):
        """停止单推送"""
        pass

from __future__ import division
from vnpy.trader.app.ctaStrategy.ctaBacktesting import BacktestingEngine
from vnpy.trader.app.ctaStrategy.ctaBase import *
if __name__ == '__main__':
    # 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('20180820 01:01',initHours=1)               # 设置回测用的数据起始日期
    engine.setEndDate('20180823 16:01')
    # 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('OANDA_M1')
    # 在引擎中创建策略对象
    d = {'symbolList':['AUD_USD:oanda']}
    engine.initStrategy(wangge_Strategy, d)
    # 开始跑回测
    engine.runBacktesting()
    # 输出策略的回测日志
    import pandas as pd
    from datetime import datetime
    import os 
    log = engine.logList
    dataframe = pd.DataFrame(log)
    filename = 'BTG_' + datetime.now().strftime("%Y%m%d_%H%M%S") +'.csv'
    filename = os.path.abspath(filename) 
    dataframe.to_csv(filename,index=False,sep=',')    
    # 显示回测结果
    engine.showBacktestingResult()
    engine.showDailyResult()

仓位字典构造完成 
初始仓位: {'AUD_USD:oanda_LONG': 0, 'AUD_USD:oanda_SHORT': 0} 
可平仓量: {'AUD_USD:oanda_LONG': 0, 'AUD_USD:oanda_SHORT': 0}
2018-09-18 23:42:54.797719  开始回测
2018-09-18 23:42:54.797719  策略初始化
2018-09-18 23:42:54.798719  载入历史数据。数据范围:[20180820 00:01,20180820 01:01)
2018-09-18 23:42:54.820751  We don't have AUD_USD:oanda in database
2018-09-18 23:42:54.821751  Our database have these symbols: []
2018-09-18 23:42:54.821751  ！！没有数据 没有数据 没有数据！！
2018-09-18 23:42:54.821751  策略初始化完成
2018-09-18 23:42:54.821751  策略启动完成
2018-09-18 23:42:54.821751  开始回放回测数据,回测范围:[20180820 01:01,20180823 16:01)
2018-09-18 23:42:54.822750  载入历史数据。数据范围:[20180820 01:01,20180823 16:01)
2018-09-18 23:42:54.829745  We don't have AUD_USD:oanda in database
2018-09-18 23:42:54.829745  Our database have these symbols: []
2018-09-18 23:42:54.829745  ！！没有数据 没有数据 没有数据！！
2018-09-18 23:42:54.829745  数据回放结束
2018-09-18 23:42:54.839739  计算回测结果
2018-09-18 23:42:54.840746  成交记录为空，无法计算回测结果
2018-09-18 23:42:54.840746  ------------------------------



---------------------------------------------------------------------------

KeyError                                  Traceback (most recent call last)

<ipython-input-2-ba112c76f517> in <module>()
     37     dataframe.to_csv(filename,index=False,sep=',')
     38     # 显示回测结果
---> 39     engine.showBacktestingResult()
     40     engine.showDailyResult()


C:\ProgramData\Anaconda3\lib\site-packages\vnpy_fxdayu-1.1.0-py3.6.egg\vnpy\trader\app\ctaStrategy\ctaBacktesting.py in showBacktestingResult(self)
    990         # 输出
    991         self.output('-' * 30)
--> 992         self.output(u'第一笔交易：\t%s' % d['timeList'][0])
    993         self.output(u'最后一笔交易：\t%s' % d['timeList'][-1])
    994 


KeyError: 'timeList'

def test(symboll):
    from vnpy.trader.app.ctaStrategy.ctaBacktesting import BacktestingEngine, OptimizationSetting, MINUTE_DB_NAME
    # 创建回测引擎对象
    engine = BacktestingEngine()
    # 设置回测使用的数据
    engine.setBacktestingMode(engine.BAR_MODE)    # 设置引擎的回测模式为K线
    engine.setDatabase(MINUTE_DB_NAME)  # 设置使用的历史数据库
    engine.setStartDate('2018001 01:01',initHours=1)               # 设置回测用的数据起始日期
    engine.setEndDate('20180905 16:01')
    # 配置回测引擎参数
    engine.setSlippage(0.2)     # 设置滑点为股指1跳
    engine.setRate(0.3/10000)   # 设置手续费万0.3
    engine.setSize(300)         # 设置股指合约大小
    engine.setPriceTick(0.2)    # 设置股指最小价格变动
    engine.setCapital(1000000)  # 设置回测本金
    # # 在引擎中创建策略对象
    d = {'symbolList':[symboll]}          # 策略参数配置
    engine.initStrategy(DeStrategy, d)    # 创建策略对象
    engine.runBacktesting()
    import pandas as pd
    from datetime import datetime
    import os 
    log = engine.logList
    dataframe = pd.DataFrame(log)
    filename = 'BTG_' + datetime.now().strftime("%Y%m%d_%H%M%S") +'.csv'
    filename = os.path.abspath(filename) 
    dataframe.to_csv(filename,index=False,sep=',')   
    # 显示回测结果
    # 显示逐日回测结果
    engine.showDailyResult()
    # 显示逐笔回测结果
    engine.showBacktestingResult()

test('EOSUSDT:binance')

symbol = ['EOSUSDT:binance','BTCUSDT:binance','ETCUSDT:binance','ETHUSDT:binance','LTCUSDT:binance']

for i in symbol:
    test(i)

# # 显示前10条成交记录
# for i in range(1000):
#     d = engine.tradeDict[str(i+1)].__dict__
#     print('TradeID: %s, Time: %s, Direction: %s, Price: %s, Volume: %s' %(d['tradeID'], d['dt'], d['direction'], d['price'], d['volume']))

Xiezhenghang-二号策略（一号策略改进版本）

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