修改回测模型，支持mysql的tick数据库
修改SendOrder方法，增加返回GatewayName 修改Tick的方法，增加data-》Tick对象。
This commit is contained in:
msincenselee
parent
e373f16ac0
commit
c2f3ba62c7
@ -7,15 +7,21 @@
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from datetime import datetime, timedelta
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from collections import OrderedDict
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from itertools import product
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import pymongo
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import MySQLdb
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import json
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import os
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import cPickle
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from ctaBase import *
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from ctaSetting import *
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from vtConstant import *
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from vtGateway import VtOrderData, VtTradeData
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from vtFunction import loadMongoSetting
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import logging
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########################################################################
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class BacktestingEngine(object):
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@ -23,6 +29,10 @@ class BacktestingEngine(object):
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CTA回测引擎
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函数接口和策略引擎保持一样，
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从而实现同一套代码从回测到实盘。
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# modified by IncenseLee：
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1.增加Mysql数据库的支持；
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2.修改装载数据为批量式后加载模式。
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"""
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TICK_MODE = 'tick'
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@ -51,10 +61,13 @@ class BacktestingEngine(object):
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self.dbClient = None # 数据库客户端
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self.dbCursor = None # 数据库指针
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#self.historyData = [] # 历史数据的列表，回测用
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self.historyData = [] # 历史数据的列表，回测用
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self.initData = [] # 初始化用的数据
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#self.backtestingData = [] # 回测用的数据
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self.backtestingData = [] # 回测用的数据
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self.dbName = '' # 回测数据库名
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self.symbol = '' # 回测集合名
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self.dataStartDate = None # 回测数据开始日期，datetime对象
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self.dataEndDate = None # 回测数据结束日期，datetime对象
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self.strategyStartDate = None # 策略启动日期（即前面的数据用于初始化），datetime对象
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@ -72,33 +85,49 @@ class BacktestingEngine(object):
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self.tick = None
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self.bar = None
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self.dt = None # 最新的时间
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self.gatewayName = u'BackTest'
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#----------------------------------------------------------------------
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def setStartDate(self, startDate='20100416', initDays=10):
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"""设置回测的启动日期"""
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self.dataStartDate = datetime.strptime(startDate, '%Y%m%d')
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# 初始化天数
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initTimeDelta = timedelta(initDays)
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self.strategyStartDate = self.dataStartDate + initTimeDelta
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#----------------------------------------------------------------------
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def setEndDate(self, endDate=''):
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"""设置回测的结束日期"""
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if endDate:
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self.dataEndDate= datetime.strptime(endDate, '%Y%m%d')
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self.dataEndDate = datetime.strptime(endDate, '%Y%m%d')
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else:
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self.dataEndDate = datetime.now()
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def setMinDiff(self, minDiff):
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"""设置回测品种的最小跳价，用于修正数据"""
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self.minDiff = minDiff
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#----------------------------------------------------------------------
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def setBacktestingMode(self, mode):
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"""设置回测模式"""
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self.mode = mode
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#----------------------------------------------------------------------
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def loadHistoryData(self, dbName, symbol):
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def setDatabase(self, dbName, symbol):
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"""设置历史数据所用的数据库"""
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self.dbName = dbName
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self.symbol = symbol
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#----------------------------------------------------------------------
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def loadHistoryDataFromMongo(self):
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"""载入历史数据"""
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host, port = loadMongoSetting()
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self.dbClient = pymongo.MongoClient(host, port)
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collection = self.dbClient[dbName][symbol]
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collection = self.dbClient[self.dbName][self.symbol]
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self.output(u'开始载入数据')
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@ -130,10 +159,370 @@ class BacktestingEngine(object):
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self.dbCursor = collection.find(flt)
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self.output(u'载入完成，数据量：%s' %(initCursor.count() + self.dbCursor.count()))
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#----------------------------------------------------------------------
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def connectMysql(self):
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"""连接MysqlDB"""
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# 载入json文件
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fileName = 'mysql_connect.json'
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try:
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f = file(fileName)
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except IOError:
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self.writeCtaLog(u'回测引擎读取Mysql_connect.json失败')
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return
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# 解析json文件
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setting = json.load(f)
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try:
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mysql_host = str(setting['host'])
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mysql_port = int(setting['port'])
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mysql_user = str(setting['user'])
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mysql_passwd = str(setting['passwd'])
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mysql_db = str(setting['db'])
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except IOError:
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self.writeCtaLog(u'回测引擎读取Mysql_connect.json,连接配置缺少字段，请检查')
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return
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try:
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self.__mysqlConnection = MySQLdb.connect(host=mysql_host, user=mysql_user,
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passwd=mysql_passwd, db=mysql_db, port=mysql_port)
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self.__mysqlConnected = True
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self.writeCtaLog(u'回测引擎连接MysqlDB成功')
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except ConnectionFailure:
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self.writeCtaLog(u'回测引擎连接MysqlDB失败')
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#----------------------------------------------------------------------
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def loadDataHistoryFromMysql(self, symbol, startDate, endDate):
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"""载入历史TICK数据
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如果加载过多数据会导致加载失败,间隔不要超过半年
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"""
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if not endDate:
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endDate = datetime.today()
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# 看本地缓存是否存在
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if self.__loadDataHistoryFromLocalCache(symbol, startDate, endDate):
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self.writeCtaLog(u'历史TICK数据从Cache载入')
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return
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# 每次获取日期周期
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intervalDays = 10
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for i in range (0,(endDate - startDate).days +1, intervalDays):
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d1 = startDate + timedelta(days = i )
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if (endDate - d1).days > 10:
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d2 = startDate + timedelta(days = i + intervalDays -1 )
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else:
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d2 = endDate
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# 从Mysql 提取数据
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self.__qryDataHistoryFromMysql(symbol, d1, d2)
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self.writeCtaLog(u'历史TICK数据共载入{0}条'.format(len(self.historyData)))
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# 保存本地cache文件
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self.__saveDataHistoryToLocalCache(symbol, startDate, endDate)
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def __loadDataHistoryFromLocalCache(self, symbol, startDate, endDate):
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"""看本地缓存是否存在
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added by IncenseLee
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"""
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# 运行路径下cache子目录
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cacheFolder = os.getcwd()+'/cache'
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# cache文件
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cacheFile = u'{0}/{1}_{2}_{3}.pickle'.\
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format(cacheFolder, symbol, startDate.strftime('%Y-%m-%d'), endDate.strftime('%Y-%m-%d'))
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if not os.path.isfile(cacheFile):
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return False
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else:
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# 从cache文件加载
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cache = open(cacheFile,mode='r')
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self.historyData = cPickle.load(cache)
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cache.close()
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return True
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def __saveDataHistoryToLocalCache(self, symbol, startDate, endDate):
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"""保存本地缓存
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added by IncenseLee
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"""
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# 运行路径下cache子目录
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cacheFolder = os.getcwd()+'/cache'
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# 创建cache子目录
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if not os.path.isdir(cacheFolder):
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os.mkdir(cacheFolder)
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# cache 文件名
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cacheFile = u'{0}/{1}_{2}_{3}.pickle'.\
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format(cacheFolder, symbol, startDate.strftime('%Y-%m-%d'), endDate.strftime('%Y-%m-%d'))
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# 重复存在 返回
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if os.path.isfile(cacheFile):
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return False
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else:
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# 写入cache文件
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cache = open(cacheFile, mode='w')
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cPickle.dump(self.historyData,cache)
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cache.close()
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return True
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#----------------------------------------------------------------------
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def __qryDataHistoryFromMysql(self, symbol, startDate, endDate):
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"""从Mysql载入历史TICK数据
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added by IncenseLee
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"""
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try:
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self.connectMysql()
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if self.__mysqlConnected:
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# 获取指针
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cur = self.__mysqlConnection.cursor(MySQLdb.cursors.DictCursor)
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if endDate:
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# 开始日期 ~ 结束日期
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sqlstring = ' select \'{0}\' as InstrumentID, str_to_date(concat(ndate,\' \', ntime),' \
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'\'%Y-%m-%d %H:%i:%s\') as UpdateTime,price as LastPrice,vol as Volume,' \
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'position_vol as OpenInterest,bid1_price as BidPrice1,bid1_vol as BidVolume1, ' \
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'sell1_price as AskPrice1, sell1_vol as AskVolume1 from TB_{0}MI ' \
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'where ndate between cast(\'{1}\' as date) and cast(\'{2}\' as date) order by UpdateTime'.\
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format(symbol, startDate, endDate)
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elif startDate:
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# 开始日期 - 当前
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sqlstring = ' select \'{0}\' as InstrumentID,str_to_date(concat(ndate,\' \', ntime),' \
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'\'%Y-%m-%d %H:%i:%s\') as UpdateTime,price as LastPrice,vol as Volume,' \
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'position_vol as OpenInterest,bid1_price as BidPrice1,bid1_vol as BidVolume1, ' \
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'sell1_price as AskPrice1, sell1_vol as AskVolume1 from TB__{0}MI ' \
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'where ndate > cast(\'{1}\' as date) order by UpdateTime'.\
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format( symbol, startDate)
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else:
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# 所有数据
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sqlstring =' select \'{0}\' as InstrumentID,str_to_date(concat(ndate,\' \', ntime),' \
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'\'%Y-%m-%d %H:%i:%s\') as UpdateTime,price as LastPrice,vol as Volume,' \
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'position_vol as OpenInterest,bid1_price as BidPrice1,bid1_vol as BidVolume1, ' \
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'sell1_price as AskPrice1, sell1_vol as AskVolume1 from TB__{0}MI order by UpdateTime'.\
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format(symbol)
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self.writeCtaLog(sqlstring)
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# 执行查询
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count = cur.execute(sqlstring)
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self.writeCtaLog(u'历史TICK数据共{0}条'.format(count))
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# 分批次读取
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fetch_counts = 0
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fetch_size = 1000
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while True:
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results = cur.fetchmany(fetch_size)
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if not results:
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break
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fetch_counts = fetch_counts + len(results)
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if not self.historyData:
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self.historyData =results
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else:
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self.historyData = self.historyData + results
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self.writeCtaLog(u'{1}~{2}历史TICK数据载入共{0}条'.format(fetch_counts,startDate,endDate))
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else:
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self.writeCtaLog(u'MysqlDB未连接，请检查')
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except MySQLdb.Error, e:
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self.writeCtaLog(u'MysqlDB载入数据失败，请检查.Error {0}'.format(e))
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def __dataToTick(self, data):
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"""
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数据库查询返回的data结构，转换为tick对象
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added by IncenseLee
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"""
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tick = CtaTickData()
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symbol = data['InstrumentID']
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tick.symbol = symbol
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# 创建TICK数据对象并更新数据
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tick.vtSymbol = symbol
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# tick.openPrice = data['OpenPrice']
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# tick.highPrice = data['HighestPrice']
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# tick.lowPrice = data['LowestPrice']
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tick.lastPrice = float(data['LastPrice'])
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tick.volume = data['Volume']
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tick.openInterest = data['OpenInterest']
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# tick.upperLimit = data['UpperLimitPrice']
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# tick.lowerLimit = data['LowerLimitPrice']
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tick.datetime = data['UpdateTime']
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tick.date = tick.datetime.strftime('%Y-%m-%d')
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tick.time = tick.datetime.strftime('%H:%M:%S')
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tick.bidPrice1 = float(data['BidPrice1'])
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# tick.bidPrice2 = data['BidPrice2']
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# tick.bidPrice3 = data['BidPrice3']
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# tick.bidPrice4 = data['BidPrice4']
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# tick.bidPrice5 = data['BidPrice5']
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tick.askPrice1 = float(data['AskPrice1'])
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# tick.askPrice2 = data['AskPrice2']
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# tick.askPrice3 = data['AskPrice3']
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# tick.askPrice4 = data['AskPrice4']
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# tick.askPrice5 = data['AskPrice5']
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tick.bidVolume1 = data['BidVolume1']
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# tick.bidVolume2 = data['BidVolume2']
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# tick.bidVolume3 = data['BidVolume3']
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# tick.bidVolume4 = data['BidVolume4']
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# tick.bidVolume5 = data['BidVolume5']
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tick.askVolume1 = data['AskVolume1']
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# tick.askVolume2 = data['AskVolume2']
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# tick.askVolume3 = data['AskVolume3']
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# tick.askVolume4 = data['AskVolume4']
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# tick.askVolume5 = data['AskVolume5']
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return tick
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#----------------------------------------------------------------------
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def getMysqlDeltaDate(self,symbol, startDate, decreaseDays):
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"""从mysql库中获取交易日前若干天
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added by IncenseLee
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"""
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try:
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if self.__mysqlConnected:
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# 获取mysql指针
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cur = self.__mysqlConnection.cursor()
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sqlstring='select distinct ndate from TB_{0}MI where ndate < ' \
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'cast(\'{1}\' as date) order by ndate desc limit {2},1'.format(symbol, startDate, decreaseDays-1)
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# self.writeCtaLog(sqlstring)
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count = cur.execute(sqlstring)
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if count > 0:
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# 提取第一条记录
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result = cur.fetchone()
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return result[0]
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else:
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self.writeCtaLog(u'MysqlDB没有查询结果，请检查日期')
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else:
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self.writeCtaLog(u'MysqlDB未连接，请检查')
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except MySQLdb.Error, e:
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self.writeCtaLog(u'MysqlDB载入数据失败，请检查.Error {0}: {1}'.format(e.arg[0],e.arg[1]))
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# 出错后缺省返回
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return startDate-timedelta(days=3)
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#----------------------------------------------------------------------
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def runBacktestingWithMysql(self):
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"""运行回测(使用Mysql数据）
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added by IncenseLee
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"""
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if not self.dataStartDate:
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self.writeCtaLog(u'回测开始日期未设置。')
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return
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if not self.dataEndDate:
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self.dataEndDate = datetime.today()
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if len(self.symbol)<1:
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self.writeCtaLog(u'回测对象未设置。')
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return
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# 首先根据回测模式，确认要使用的数据类
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if self.mode == self.BAR_MODE:
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dataClass = CtaBarData
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func = self.newBar
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else:
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dataClass = CtaTickData
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func = self.newTick
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self.output(u'开始回测')
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#self.strategy.inited = True
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self.strategy.onInit()
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self.output(u'策略初始化完成')
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self.strategy.trading = True
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self.strategy.onStart()
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self.output(u'策略启动完成')
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self.output(u'开始回放数据')
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# 每次获取日期周期
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intervalDays = 10
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for i in range (0,(self.dataEndDate - self.dataStartDate).days +1, intervalDays):
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d1 = self.dataStartDate + timedelta(days = i )
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if (self.dataEndDate - d1).days > intervalDays:
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d2 = self.dataStartDate + timedelta(days = i + intervalDays -1 )
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else:
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d2 = self.dataEndDate
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# 提取历史数据
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self.loadDataHistoryFromMysql(self.symbol, d1, d2)
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self.output(u'数据日期:{0} => {1}'.format(d1,d2))
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# 将逐笔数据推送
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for data in self.historyData:
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# 记录最新的TICK数据
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self.tick = self.__dataToTick(data)
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self.dt = self.tick.datetime
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# 处理限价单
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self.crossLimitOrder()
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self.crossStopOrder()
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# 推送到策略引擎中
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self.strategy.onTick(self.tick)
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# 清空历史数据
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self.historyData = []
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self.output(u'数据回放结束')
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#----------------------------------------------------------------------
|
||||
def runBacktesting(self):
|
||||
"""运行回测"""
|
||||
# 载入历史数据
|
||||
self.loadHistoryData()
|
||||
|
||||
# 首先根据回测模式，确认要使用的数据类
|
||||
if self.mode == self.BAR_MODE:
|
||||
dataClass = CtaBarData
|
||||
@ -160,7 +549,7 @@ class BacktestingEngine(object):
|
||||
func(data)
|
||||
|
||||
self.output(u'数据回放结束')
|
||||
|
||||
|
||||
#----------------------------------------------------------------------
|
||||
def newBar(self, bar):
|
||||
"""新的K线"""
|
||||
@ -191,6 +580,8 @@ class BacktestingEngine(object):
|
||||
#----------------------------------------------------------------------
|
||||
def sendOrder(self, vtSymbol, orderType, price, volume, strategy):
|
||||
"""发单"""
|
||||
|
||||
self.writeCtaLog(u'{0},{1},{2}@{3}'.format(vtSymbol,orderType,price,volume))
|
||||
self.limitOrderCount += 1
|
||||
orderID = str(self.limitOrderCount)
|
||||
|
||||
@ -202,6 +593,9 @@ class BacktestingEngine(object):
|
||||
order.orderID = orderID
|
||||
order.vtOrderID = orderID
|
||||
order.orderTime = str(self.dt)
|
||||
|
||||
# added by IncenseLee
|
||||
order.gatewayName = self.gatewayName
|
||||
|
||||
# CTA委托类型映射
|
||||
if orderType == CTAORDER_BUY:
|
||||
@ -220,8 +614,9 @@ class BacktestingEngine(object):
|
||||
# 保存到限价单字典中
|
||||
self.workingLimitOrderDict[orderID] = order
|
||||
self.limitOrderDict[orderID] = order
|
||||
|
||||
return orderID
|
||||
|
||||
# modified by IncenseLee
|
||||
return u'{0}.{1}'.format(order.gatewayName, orderID)
|
||||
|
||||
#----------------------------------------------------------------------
|
||||
def cancelOrder(self, vtOrderID):
|
||||
@ -279,13 +674,15 @@ class BacktestingEngine(object):
|
||||
"""基于最新数据撮合限价单"""
|
||||
# 先确定会撮合成交的价格
|
||||
if self.mode == self.BAR_MODE:
|
||||
buyCrossPrice = self.bar.low # 若买入方向限价单价格高于该价格，则会成交
|
||||
sellCrossPrice = self.bar.high # 若卖出方向限价单价格低于该价格，则会成交
|
||||
bestCrossPrice = self.bar.open # 在当前时间点前发出的委托可能的最优成交价
|
||||
buyCrossPrice = self.bar.low # 若买入方向限价单价格高于该价格，则会成交
|
||||
sellCrossPrice = self.bar.high # 若卖出方向限价单价格低于该价格，则会成交
|
||||
buyBestCrossPrice = self.bar.open # 在当前时间点前发出的买入委托可能的最优成交价
|
||||
sellBestCrossPrice = self.bar.open # 在当前时间点前发出的卖出委托可能的最优成交价
|
||||
else:
|
||||
buyCrossPrice = self.tick.lastPrice
|
||||
sellCrossPrice = self.tick.lastPrice
|
||||
bestCrossPrice = self.tick.lastPrice
|
||||
buyCrossPrice = self.tick.askPrice1
|
||||
sellCrossPrice = self.tick.bidPrice1
|
||||
buyBestCrossPrice = self.tick.askPrice1
|
||||
sellBestCrossPrice = self.tick.bidPrice1
|
||||
|
||||
# 遍历限价单字典中的所有限价单
|
||||
for orderID, order in self.workingLimitOrderDict.items():
|
||||
@ -312,10 +709,10 @@ class BacktestingEngine(object):
|
||||
# 2. 假设在上一根K线结束(也是当前K线开始)的时刻，策略发出的委托为限价105
|
||||
# 3. 则在实际中的成交价会是100而不是105，因为委托发出时市场的最优价格是100
|
||||
if buyCross:
|
||||
trade.price = min(order.price, bestCrossPrice)
|
||||
trade.price = min(order.price, buyBestCrossPrice)
|
||||
self.strategy.pos += order.totalVolume
|
||||
else:
|
||||
trade.price = max(order.price, bestCrossPrice)
|
||||
trade.price = max(order.price, sellBestCrossPrice)
|
||||
self.strategy.pos -= order.totalVolume
|
||||
|
||||
trade.volume = order.totalVolume
|
||||
@ -425,27 +822,27 @@ class BacktestingEngine(object):
|
||||
"""记录日志"""
|
||||
log = str(self.dt) + ' ' + content
|
||||
self.logList.append(log)
|
||||
|
||||
# 写入本地log日志
|
||||
logging.info(content)
|
||||
|
||||
#----------------------------------------------------------------------
|
||||
def output(self, content):
|
||||
"""输出内容"""
|
||||
print content
|
||||
|
||||
print str(datetime.now()) + "\t" + content
|
||||
|
||||
#----------------------------------------------------------------------
|
||||
def showBacktestingResult(self):
|
||||
def calculateBacktestingResult(self):
|
||||
"""
|
||||
显示回测结果
|
||||
计算回测结果
|
||||
"""
|
||||
self.output(u'显示回测结果')
|
||||
self.output(u'计算回测结果')
|
||||
|
||||
# 首先基于回测后的成交记录，计算每笔交易的盈亏
|
||||
pnlDict = OrderedDict() # 每笔盈亏的记录
|
||||
resultDict = OrderedDict() # 交易结果记录
|
||||
longTrade = [] # 未平仓的多头交易
|
||||
shortTrade = [] # 未平仓的空头交易
|
||||
|
||||
# 计算滑点，一个来回包括两次
|
||||
totalSlippage = self.slippage * 2
|
||||
|
||||
|
||||
for trade in self.tradeDict.values():
|
||||
# 多头交易
|
||||
if trade.direction == DIRECTION_LONG:
|
||||
@ -455,12 +852,15 @@ class BacktestingEngine(object):
|
||||
# 当前多头交易为平空
|
||||
else:
|
||||
entryTrade = shortTrade.pop(0)
|
||||
# 计算比例佣金
|
||||
commission = (trade.price+entryTrade.price) * self.rate
|
||||
# 计算盈亏
|
||||
pnl = ((trade.price - entryTrade.price)*(-1) - totalSlippage - commission) \
|
||||
* trade.volume * self.size
|
||||
pnlDict[trade.dt] = pnl
|
||||
|
||||
result = TradingResult(entryTrade.price, trade.price, -trade.volume,
|
||||
self.rate, self.slippage, self.size)
|
||||
|
||||
resultDict[trade.dt] = result
|
||||
|
||||
self.output(u'{0},short:{1},{2},cover:{3},vol:{4},{5}'
|
||||
.format(entryTrade.tradeTime, entryTrade.price,trade.tradeTime,trade.price, trade.volume,result.pnl))
|
||||
|
||||
# 空头交易
|
||||
else:
|
||||
# 如果尚无多头交易
|
||||
@ -469,58 +869,101 @@ class BacktestingEngine(object):
|
||||
# 当前空头交易为平多
|
||||
else:
|
||||
entryTrade = longTrade.pop(0)
|
||||
# 计算比例佣金
|
||||
commission = (trade.price+entryTrade.price) * self.rate
|
||||
# 计算盈亏
|
||||
pnl = ((trade.price - entryTrade.price) - totalSlippage - commission) \
|
||||
* trade.volume * self.size
|
||||
pnlDict[trade.dt] = pnl
|
||||
|
||||
result = TradingResult(entryTrade.price, trade.price, trade.volume,
|
||||
self.rate, self.slippage, self.size)
|
||||
resultDict[trade.dt] = result
|
||||
|
||||
self.output(u'{0},buy:{1},{2},sell:{3},vol:{4},{5}'
|
||||
.format(entryTrade.tradeTime, entryTrade.price,trade.tradeTime,trade.price, trade.volume,result.pnl))
|
||||
|
||||
# 检查是否有交易
|
||||
if not resultDict:
|
||||
self.output(u'无交易结果')
|
||||
return {}
|
||||
|
||||
# 然后基于每笔交易的结果，我们可以计算具体的盈亏曲线和最大回撤等
|
||||
timeList = pnlDict.keys()
|
||||
pnlList = pnlDict.values()
|
||||
capital = 0 # 资金
|
||||
maxCapital = 0 # 资金最高净值
|
||||
drawdown = 0 # 回撤
|
||||
|
||||
capital = 0
|
||||
maxCapital = 0
|
||||
drawdown = 0
|
||||
totalResult = 0 # 总成交数量
|
||||
totalTurnover = 0 # 总成交金额（合约面值）
|
||||
totalCommission = 0 # 总手续费
|
||||
totalSlippage = 0 # 总滑点
|
||||
|
||||
timeList = [] # 时间序列
|
||||
pnlList = [] # 每笔盈亏序列
|
||||
capitalList = [] # 盈亏汇总的时间序列
|
||||
maxCapitalList = [] # 最高盈利的时间序列
|
||||
drawdownList = [] # 回撤的时间序列
|
||||
|
||||
for pnl in pnlList:
|
||||
capital += pnl
|
||||
for time, result in resultDict.items():
|
||||
capital += result.pnl
|
||||
maxCapital = max(capital, maxCapital)
|
||||
drawdown = capital - maxCapital
|
||||
|
||||
pnlList.append(result.pnl)
|
||||
timeList.append(time)
|
||||
capitalList.append(capital)
|
||||
maxCapitalList.append(maxCapital)
|
||||
drawdownList.append(drawdown)
|
||||
|
||||
totalResult += 1
|
||||
totalTurnover += result.turnover
|
||||
totalCommission += result.commission
|
||||
totalSlippage += result.slippage
|
||||
|
||||
# 返回回测结果
|
||||
d = {}
|
||||
d['capital'] = capital
|
||||
d['maxCapital'] = maxCapital
|
||||
d['drawdown'] = drawdown
|
||||
d['totalResult'] = totalResult
|
||||
d['totalTurnover'] = totalTurnover
|
||||
d['totalCommission'] = totalCommission
|
||||
d['totalSlippage'] = totalSlippage
|
||||
d['timeList'] = timeList
|
||||
d['pnlList'] = pnlList
|
||||
d['capitalList'] = capitalList
|
||||
d['drawdownList'] = drawdownList
|
||||
return d
|
||||
|
||||
#----------------------------------------------------------------------
|
||||
def showBacktestingResult(self):
|
||||
"""显示回测结果"""
|
||||
d = self.calculateBacktestingResult()
|
||||
|
||||
if len(d)== 0:
|
||||
self.output(u'无交易结果')
|
||||
return
|
||||
# 输出
|
||||
self.output('-' * 50)
|
||||
self.output(u'第一笔交易时间：%s' % timeList[0])
|
||||
self.output(u'最后一笔交易时间：%s' % timeList[-1])
|
||||
self.output(u'总交易次数：%s' % len(pnlList))
|
||||
self.output(u'总盈亏：%s' % capitalList[-1])
|
||||
self.output(u'最大回撤: %s' % min(drawdownList))
|
||||
self.output('-' * 30)
|
||||
self.output(u'第一笔交易：\t%s' % d['timeList'][0])
|
||||
self.output(u'最后一笔交易：\t%s' % d['timeList'][-1])
|
||||
|
||||
self.output(u'总交易次数：\t%s' % formatNumber(d['totalResult']))
|
||||
self.output(u'总盈亏：\t%s' % formatNumber(d['capital']))
|
||||
self.output(u'最大回撤: \t%s' % formatNumber(min(d['drawdownList'])))
|
||||
|
||||
self.output(u'平均每笔盈利：\t%s' %formatNumber(d['capital']/d['totalResult']))
|
||||
self.output(u'平均每笔滑点：\t%s' %formatNumber(d['totalSlippage']/d['totalResult']))
|
||||
self.output(u'平均每笔佣金：\t%s' %formatNumber(d['totalCommission']/d['totalResult']))
|
||||
|
||||
# 绘图
|
||||
import matplotlib.pyplot as plt
|
||||
#import matplotlib.pyplot as plt
|
||||
|
||||
pCapital = plt.subplot(3, 1, 1)
|
||||
pCapital.set_ylabel("capital")
|
||||
pCapital.plot(capitalList)
|
||||
#pCapital = plt.subplot(3, 1, 1)
|
||||
#pCapital.set_ylabel("capital")
|
||||
#pCapital.plot(d['capitalList'])
|
||||
|
||||
pDD = plt.subplot(3, 1, 2)
|
||||
pDD.set_ylabel("DD")
|
||||
pDD.bar(range(len(drawdownList)), drawdownList)
|
||||
#pDD = plt.subplot(3, 1, 2)
|
||||
#pDD.set_ylabel("DD")
|
||||
#pDD.bar(range(len(d['drawdownList'])), d['drawdownList'])
|
||||
|
||||
pPnl = plt.subplot(3, 1, 3)
|
||||
pPnl.set_ylabel("pnl")
|
||||
pPnl.hist(pnlList, bins=20)
|
||||
#pPnl = plt.subplot(3, 1, 3)
|
||||
#pPnl.set_ylabel("pnl")
|
||||
#pPnl.hist(d['pnlList'], bins=50)
|
||||
|
||||
plt.show()
|
||||
#plt.show()
|
||||
|
||||
#----------------------------------------------------------------------
|
||||
def putStrategyEvent(self, name):
|
||||
@ -529,7 +972,7 @@ class BacktestingEngine(object):
|
||||
|
||||
#----------------------------------------------------------------------
|
||||
def setSlippage(self, slippage):
|
||||
"""设置滑点"""
|
||||
"""设置滑点点数"""
|
||||
self.slippage = slippage
|
||||
|
||||
#----------------------------------------------------------------------
|
||||
@ -542,6 +985,136 @@ class BacktestingEngine(object):
|
||||
"""设置佣金比例"""
|
||||
self.rate = rate
|
||||
|
||||
#----------------------------------------------------------------------
|
||||
def runOptimization(self, strategyClass, optimizationSetting):
|
||||
"""优化参数"""
|
||||
# 获取优化设置
|
||||
settingList = optimizationSetting.generateSetting()
|
||||
targetName = optimizationSetting.optimizeTarget
|
||||
|
||||
# 检查参数设置问题
|
||||
if not settingList or not targetName:
|
||||
self.output(u'优化设置有问题，请检查')
|
||||
|
||||
# 遍历优化
|
||||
resultList = []
|
||||
for setting in settingList:
|
||||
self.clearBacktestingResult()
|
||||
self.output('-' * 30)
|
||||
self.output('setting: %s' %str(setting))
|
||||
self.initStrategy(strategyClass, setting)
|
||||
self.runBacktesting()
|
||||
d = self.calculateBacktestingResult()
|
||||
try:
|
||||
targetValue = d[targetName]
|
||||
except KeyError:
|
||||
targetValue = 0
|
||||
resultList.append(([str(setting)], targetValue))
|
||||
|
||||
# 显示结果
|
||||
resultList.sort(reverse=True, key=lambda result:result[1])
|
||||
self.output('-' * 30)
|
||||
self.output(u'优化结果：')
|
||||
for result in resultList:
|
||||
self.output(u'%s: %s' %(result[0], result[1]))
|
||||
|
||||
#----------------------------------------------------------------------
|
||||
def clearBacktestingResult(self):
|
||||
"""清空之前回测的结果"""
|
||||
# 清空限价单相关
|
||||
self.limitOrderCount = 0
|
||||
self.limitOrderDict.clear()
|
||||
self.workingLimitOrderDict.clear()
|
||||
|
||||
# 清空停止单相关
|
||||
self.stopOrderCount = 0
|
||||
self.stopOrderDict.clear()
|
||||
self.workingStopOrderDict.clear()
|
||||
|
||||
# 清空成交相关
|
||||
self.tradeCount = 0
|
||||
self.tradeDict.clear()
|
||||
|
||||
|
||||
########################################################################
|
||||
class TradingResult(object):
|
||||
"""每笔交易的结果"""
|
||||
|
||||
#----------------------------------------------------------------------
|
||||
def __init__(self, entry, exit, volume, rate, slippage, size):
|
||||
"""Constructor"""
|
||||
self.entry = entry # 开仓价格
|
||||
self.exit = exit # 平仓价格
|
||||
self.volume = volume # 交易数量（+/-代表方向）
|
||||
|
||||
self.turnover = (self.entry+self.exit)*size # 成交金额
|
||||
self.commission = self.turnover*rate # 手续费成本
|
||||
self.slippage = slippage*2*size # 滑点成本
|
||||
self.pnl = ((self.exit - self.entry) * volume * size
|
||||
- self.commission - self.slippage) # 净盈亏
|
||||
|
||||
|
||||
########################################################################
|
||||
class OptimizationSetting(object):
|
||||
"""优化设置"""
|
||||
|
||||
#----------------------------------------------------------------------
|
||||
def __init__(self):
|
||||
"""Constructor"""
|
||||
self.paramDict = OrderedDict()
|
||||
|
||||
self.optimizeTarget = '' # 优化目标字段
|
||||
|
||||
#----------------------------------------------------------------------
|
||||
def addParameter(self, name, start, end, step):
|
||||
"""增加优化参数"""
|
||||
if end <= start:
|
||||
print u'参数起始点必须小于终止点'
|
||||
return
|
||||
|
||||
if step <= 0:
|
||||
print u'参数布进必须大于0'
|
||||
return
|
||||
|
||||
l = []
|
||||
param = start
|
||||
|
||||
while param <= end:
|
||||
l.append(param)
|
||||
param += step
|
||||
|
||||
self.paramDict[name] = l
|
||||
|
||||
#----------------------------------------------------------------------
|
||||
def generateSetting(self):
|
||||
"""生成优化参数组合"""
|
||||
# 参数名的列表
|
||||
nameList = self.paramDict.keys()
|
||||
paramList = self.paramDict.values()
|
||||
|
||||
# 使用迭代工具生产参数对组合
|
||||
productList = list(product(*paramList))
|
||||
|
||||
# 把参数对组合打包到一个个字典组成的列表中
|
||||
settingList = []
|
||||
for p in productList:
|
||||
d = dict(zip(nameList, p))
|
||||
settingList.append(d)
|
||||
|
||||
return settingList
|
||||
|
||||
#----------------------------------------------------------------------
|
||||
def setOptimizeTarget(self, target):
|
||||
"""设置优化目标字段"""
|
||||
self.optimizeTarget = target
|
||||
|
||||
|
||||
#----------------------------------------------------------------------
|
||||
def formatNumber(n):
|
||||
"""格式化数字到字符串"""
|
||||
n = round(n, 2) # 保留两位小数
|
||||
return format(n, ',') # 加上千分符
|
||||
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
@ -560,7 +1133,7 @@ if __name__ == '__main__':
|
||||
engine.setStartDate('20110101')
|
||||
|
||||
# 载入历史数据到引擎中
|
||||
engine.loadHistoryData(MINUTE_DB_NAME, 'IF0000')
|
||||
engine.setDatabase(MINUTE_DB_NAME, 'IF0000')
|
||||
|
||||
# 设置产品相关参数
|
||||
engine.setSlippage(0.2) # 股指1跳
|
||||
|
||||
Loading…
Reference in New Issue
Block a user