[Add]增加海龟策略的测试用数据,初步完成海龟策略

This commit is contained in:
vn.py 2018-11-11 16:04:25 +08:00
parent 846e677bbc
commit 0f212f96f9
9 changed files with 4126 additions and 50 deletions

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@ -8,10 +8,7 @@ from dataService import *
if __name__ == '__main__':
#downloadMinuteBarBySymbol('IF1812')
#downloadAllMinuteBar()
#downloadMinuteBarBySymbol('CU99')
downloadDailyBarBySymbol('CU99')
downloadMinuteBarBySymbol('CU99')
downloadDailyBarBySymbol('IF99')
downloadDailyBarBySymbol('TA99')
downloadDailyBarBySymbol('I99')

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@ -0,0 +1,15 @@
## 海龟交易策略(完整版)
使用说明:
1. 在cmd中运行python loadCsv.py将000300.csv中的沪深300指数数据加载到MongoDB数据库中
2. 使用Jupyter Notebook打开run.ipynb并执行相应的回测分析
开发进度
1. 海龟交易信号(负责判断具体的买卖位置):已完成
2. 海龟投资组合(负责根据信号执行具体交易):已完成
3. 回测引擎配置组合和信号:已完成
4. 回测引擎加载历史数据:已完成
5. 回测引擎回放历史数据:已完成
6. 回测引擎计算每日盈亏情况:已完成
7. 回测引擎统计整体回测结果和画图:未完成

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@ -0,0 +1,37 @@
# encoding: UTF-8
from csv import DictReader
from datetime import datetime
from pymongo import MongoClient
from vnpy.trader.vtObject import VtBarData
from turtleEngine import DAILY_DB_NAME
#----------------------------------------------------------------------
def loadCsv(filename):
""""""
symbol = filename.split('.')[0]
mc = MongoClient()
db = mc[DAILY_DB_NAME]
collection = db[symbol]
with open(filename) as f:
r = DictReader(f)
for d in r:
bar = VtBarData()
bar.datetime = datetime.strptime(d['date'], '%Y/%m/%d')
bar.vtSymbol = symbol
bar.open = float(d['open'])
bar.high = float(d['high'])
bar.low = float(d['low'])
bar.close = float(d['close'])
bar.volume= int(d['volume'])
collection.insert(bar.__dict__)
if __name__ == '__main__':
loadCsv('000300.csv')
loadCsv('000905.csv')

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@ -0,0 +1,3 @@
vtSymbol,size,priceTick,variableCommission,fixedCommission,slippage
000300,1,0.2,0,0,0
000905,1,0.1,0,0,0
1 vtSymbol size priceTick variableCommission fixedCommission slippage
2 000300 1 0.2 0 0 0
3 000905 1 0.1 0 0 0

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@ -73,6 +73,9 @@ class BacktestingEngine(object):
self.portfolio = TurtlePortfolio(self)
self.portfolio.init(portfolioValue, self.vtSymbolList, SIZE_DICT)
self.writeLog(u'投资组合的合约代码%s' %(self.vtSymbolList))
self.writeLog(u'投资组合的初始价值%s' %(portfolioValue))
#----------------------------------------------------------------------
def loadData(self):
""""""
@ -100,6 +103,8 @@ class BacktestingEngine(object):
#----------------------------------------------------------------------
def runBacktesting(self):
""""""
self.writeLog(u'开始回放K线数据')
for dt, barDict in self.dataDict.items():
self.currentDt = dt
@ -116,12 +121,18 @@ class BacktestingEngine(object):
self.resultList.append(result)
self.result = result
self.writeLog(u'K线数据回放结束')
#----------------------------------------------------------------------
def calculateResult(self):
""""""
self.writeLog(u'开始统计回测结果')
for result in self.resultList:
result.calculatePnl()
self.writeLog(u'回测结果统计结束')
#----------------------------------------------------------------------
def sendOrder(self, vtSymbol, direction, offset, price, volume):
""""""
@ -139,7 +150,7 @@ class BacktestingEngine(object):
#----------------------------------------------------------------------
def writeLog(self, content):
""""""
print '%s:%s' %(datetime.now().strftime('%H:%M:%S.%f'), content)
print '%s:\t%s' %(datetime.now().strftime('%H:%M:%S.%f'), content)
########################################################################