def initPortfolio(self, filename, portfolioValue=10000000):
"""初始化投资组合"""
self.portfolioValue = portfolioValue
with open(filename) as f:
r = DictReader(f)
for d in r:
self.vtSymbolList.append(d['vtSymbol'])
SIZE_DICT[d['vtSymbol']] = int(d['size'])
PRICETICK_DICT[d['vtSymbol']] = float(d['priceTick'])
VARIABLE_COMMISSION_DICT[d['vtSymbol']] = float(d['variableCommission'])
FIXED_COMMISSION_DICT[d['vtSymbol']] = float(d['fixedCommission'])
SLIPPAGE_DICT[d['vtSymbol']] = float(d['slippage'])
self.portfolio = TurtlePortfolio(self)
self.portfolio.init(portfolioValue, self.vtSymbolList, SIZE_DICT)
self.output(u'投资组合的合约代码%s' %(self.vtSymbolList))
self.output(u'投资组合的初始价值%s' %(portfolioValue))
def initPortfolio(self, filename, portfolioValue=10000000):
"""初始化投资组合"""
self.portfolioValue = portfolioValue
with open(filename) as f:
r = DictReader(f)
for d in r:
self.vtSymbolList.append(d['vtSymbol'])
SIZE_DICT[d['vtSymbol']] = int(d['size'])
PRICETICK_DICT[d['vtSymbol']] = float(d['priceTick'])
VARIABLE_COMMISSION_DICT[d['vtSymbol']] = float(d['variableCommission'])
FIXED_COMMISSION_DICT[d['vtSymbol']] = float(d['fixedCommission'])
SLIPPAGE_DICT[d['vtSymbol']] = float(d['slippage'])
self.portfolio = TurtlePortfolio(self)
self.portfolio.init(portfolioValue, self.vtSymbolList, SIZE_DICT)
self.output(u'投资组合的合约代码%s' %(self.vtSymbolList))
self.output(u'投资组合的初始价值%s' %(portfolioValue))
class BacktestingEngine(object):
"""组合类CTA策略回测引擎"""
#----------------------------------------------------------------------
def __init__(self):
"""Constructor"""
self.portfolio = None
# 合约配置信息
self.vtSymbolList = []
self.sizeDict = {} # 合约大小字典
self.priceTickDict = {} # 最小价格变动字典
self.variableCommissionDict = {} # 变动手续费字典
self.fixedCommissionDict = {} # 固定手续费字典
self.slippageDict = {} # 滑点成本字典
self.portfolioValue = 0
self.startDt = None
self.endDt = None
self.currentDt = None
self.dataDict = OrderedDict()
self.tradeDict = OrderedDict()
self.result = None
self.resultList = []
#----------------------------------------------------------------------
def setPeriod(self, startDt, endDt):
"""设置回测周期"""
self.startDt = startDt
self.endDt = endDt
#----------------------------------------------------------------------
def initPortfolio(self, filename, portfolioValue=10000000):
"""初始化投资组合"""
self.portfolioValue = portfolioValue
with open(filename) as f:
r = DictReader(f)
for d in r:
self.vtSymbolList.append(d['vtSymbol'])
SIZE_DICT[d['vtSymbol']] = int(d['size'])
PRICETICK_DICT[d['vtSymbol']] = float(d['priceTick'])
VARIABLE_COMMISSION_DICT[d['vtSymbol']] = float(d['variableCommission'])
FIXED_COMMISSION_DICT[d['vtSymbol']] = float(d['fixedCommission'])
SLIPPAGE_DICT[d['vtSymbol']] = float(d['slippage'])
self.portfolio = TurtlePortfolio(self)
self.portfolio.init(portfolioValue, self.vtSymbolList, SIZE_DICT)
self.output(u'投资组合的合约代码%s' %(self.vtSymbolList))
self.output(u'投资组合的初始价值%s' %(portfolioValue))
#----------------------------------------------------------------------
def loadData(self):
"""加载数据"""
mc = MongoClient()
db = mc[DAILY_DB_NAME]
for vtSymbol in self.vtSymbolList:
flt = {'datetime':{'$gte':self.startDt,
'$lte':self.endDt}}
collection = db[vtSymbol]
cursor = collection.find(flt).sort('datetime')
for d in cursor:
bar = VtBarData()
bar.__dict__ = d
barDict = self.dataDict.setdefault(bar.datetime, OrderedDict())
barDict[bar.vtSymbol] = bar
self.output(u'%s数据加载完成，总数据量：%s' %(vtSymbol, cursor.count()))
self.output(u'全部数据加载完成')
#----------------------------------------------------------------------
def runBacktesting(self):
"""运行回测"""
self.output(u'开始回放K线数据')
for dt, barDict in self.dataDict.items():
self.currentDt = dt
previousResult = self.result
self.result = DailyResult(dt)
self.result.updatePos(self.portfolio.posDict)
self.resultList.append(self.result)
if previousResult:
self.result.updatePreviousClose(previousResult.closeDict)
for bar in barDict.values():
self.portfolio.onBar(bar)
self.result.updateBar(bar)
self.output(u'K线数据回放结束')
#----------------------------------------------------------------------
def calculateResult(self, annualDays=240):
"""计算结果"""
self.output(u'开始统计回测结果')
for result in self.resultList:
result.calculatePnl()
resultList = self.resultList
dateList = [result.date for result in resultList]
startDate = dateList[0]
endDate = dateList[-1]
totalDays = len(dateList)
profitDays = 0
lossDays = 0
endBalance = self.portfolioValue
highlevel = self.portfolioValue
totalNetPnl = 0
totalCommission = 0
totalSlippage = 0
totalTradeCount = 0
netPnlList = []
balanceList = []
highlevelList = []
drawdownList = []
ddPercentList = []
returnList = []
for result in resultList:
if result.netPnl > 0:
profitDays += 1
elif result.netPnl < 0:
lossDays += 1
netPnlList.append(result.netPnl)
prevBalance = endBalance
endBalance += result.netPnl
balanceList.append(endBalance)
returnList.append(endBalance/prevBalance - 1)
highlevel = max(highlevel, endBalance)
highlevelList.append(highlevel)
drawdown = endBalance - highlevel
drawdownList.append(drawdown)
ddPercentList.append(drawdown/highlevel*100)
totalCommission += result.commission
totalSlippage += result.slippage
totalTradeCount += result.tradeCount
totalNetPnl += result.netPnl
maxDrawdown = min(drawdownList)
maxDdPercent = min(ddPercentList)
totalReturn = (endBalance / self.portfolioValue - 1) * 100
dailyReturn = np.mean(returnList) * 100
annualizedReturn = dailyReturn * annualDays
returnStd = np.std(returnList) * 100
if returnStd:
sharpeRatio = dailyReturn / returnStd * np.sqrt(annualDays)
else:
sharpeRatio = 0
# 返回结果
result = {
'startDate': startDate,
'endDate': endDate,
'totalDays': totalDays,
'profitDays': profitDays,
'lossDays': lossDays,
'endBalance': endBalance,
'maxDrawdown': maxDrawdown,
'maxDdPercent': maxDdPercent,
'totalNetPnl': totalNetPnl,
'dailyNetPnl': totalNetPnl/totalDays,
'totalCommission': totalCommission,
'dailyCommission': totalCommission/totalDays,
'totalSlippage': totalSlippage,
'dailySlippage': totalSlippage/totalDays,
'totalTradeCount': totalTradeCount,
'dailyTradeCount': totalTradeCount/totalDays,
'totalReturn': totalReturn,
'annualizedReturn': annualizedReturn,
'dailyReturn': dailyReturn,
'returnStd': returnStd,
'sharpeRatio': sharpeRatio
}
timeseries = {
'balance': balanceList,
'return': returnList,
'highLevel': highlevel,
'drawdown': drawdownList,
'ddPercent': ddPercentList,
'date': dateList,
'netPnl': netPnlList
}
return timeseries, result
#----------------------------------------------------------------------
def showResult(self):
"""显示回测结果"""
timeseries, result = self.calculateResult()
# 输出统计结果
self.output('-' * 30)
self.output(u'首个交易日：\t%s' % result['startDate'])
self.output(u'最后交易日：\t%s' % result['endDate'])
self.output(u'总交易日：\t%s' % result['totalDays'])
self.output(u'盈利交易日\t%s' % result['profitDays'])
self.output(u'亏损交易日：\t%s' % result['lossDays'])
self.output(u'起始资金：\t%s' % self.portfolioValue)
self.output(u'结束资金：\t%s' % formatNumber(result['endBalance']))
self.output(u'总收益率：\t%s%%' % formatNumber(result['totalReturn']))
self.output(u'年化收益：\t%s%%' % formatNumber(result['annualizedReturn']))
self.output(u'总盈亏：\t%s' % formatNumber(result['totalNetPnl']))
self.output(u'最大回撤: \t%s' % formatNumber(result['maxDrawdown']))
self.output(u'百分比最大回撤: %s%%' % formatNumber(result['maxDdPercent']))
self.output(u'总手续费：\t%s' % formatNumber(result['totalCommission']))
self.output(u'总滑点：\t%s' % formatNumber(result['totalSlippage']))
self.output(u'总成交笔数：\t%s' % formatNumber(result['totalTradeCount']))
self.output(u'日均盈亏：\t%s' % formatNumber(result['dailyNetPnl']))
self.output(u'日均手续费：\t%s' % formatNumber(result['dailyCommission']))
self.output(u'日均滑点：\t%s' % formatNumber(result['dailySlippage']))
self.output(u'日均成交笔数：\t%s' % formatNumber(result['dailyTradeCount']))
self.output(u'日均收益率：\t%s%%' % formatNumber(result['dailyReturn']))
self.output(u'收益标准差：\t%s%%' % formatNumber(result['returnStd']))
self.output(u'Sharpe Ratio：\t%s' % formatNumber(result['sharpeRatio']))
# 绘图
fig = plt.figure(figsize=(10, 16))
pBalance = plt.subplot(4, 1, 1)
pBalance.set_title('Balance')
plt.plot(timeseries['date'], timeseries['balance'])
pDrawdown = plt.subplot(4, 1, 2)
pDrawdown.set_title('Drawdown')
pDrawdown.fill_between(range(len(timeseries['drawdown'])), timeseries['drawdown'])
pPnl = plt.subplot(4, 1, 3)
pPnl.set_title('Daily Pnl')
plt.bar(range(len(timeseries['drawdown'])), timeseries['netPnl'])
pKDE = plt.subplot(4, 1, 4)
pKDE.set_title('Daily Pnl Distribution')
plt.hist(timeseries['netPnl'], bins=50)
plt.show()
#----------------------------------------------------------------------
def sendOrder(self, vtSymbol, direction, offset, price, volume):
"""记录交易数据（由portfolio调用）"""
# 对价格四舍五入
priceTick = PRICETICK_DICT[vtSymbol]
price = int(round(price/priceTick, 0)) * priceTick
# 记录成交数据
trade = TradeData(vtSymbol, direction, offset, price, volume)
l = self.tradeDict.setdefault(self.currentDt, [])
l.append(trade)
self.result.updateTrade(trade)
#----------------------------------------------------------------------
def output(self, content):
"""输出信息"""
print content
#----------------------------------------------------------------------
def getTradeData(self, vtSymbol=''):
"""获取交易数据"""
tradeList = []
for l in self.tradeDict.values():
for trade in l:
if not vtSymbol:
tradeList.append(trade)
elif trade.vtSymbol == vtSymbol:
tradeList.append(trade)
return tradeList
class BacktestingEngine(object):
"""组合类CTA策略回测引擎"""
#----------------------------------------------------------------------
def __init__(self):
"""Constructor"""
self.portfolio = None
# 合约配置信息
self.vtSymbolList = []
self.sizeDict = {} # 合约大小字典
self.priceTickDict = {} # 最小价格变动字典
self.variableCommissionDict = {} # 变动手续费字典
self.fixedCommissionDict = {} # 固定手续费字典
self.slippageDict = {} # 滑点成本字典
self.portfolioValue = 0
self.startDt = None
self.endDt = None
self.currentDt = None
self.dataDict = OrderedDict()
self.tradeDict = OrderedDict()
self.result = None
self.resultList = []
#----------------------------------------------------------------------
def setPeriod(self, startDt, endDt):
"""设置回测周期"""
self.startDt = startDt
self.endDt = endDt
#----------------------------------------------------------------------
def initPortfolio(self, filename, portfolioValue=10000000):
"""初始化投资组合"""
self.portfolioValue = portfolioValue
with open(filename) as f:
r = DictReader(f)
for d in r:
self.vtSymbolList.append(d['vtSymbol'])
SIZE_DICT[d['vtSymbol']] = int(d['size'])
PRICETICK_DICT[d['vtSymbol']] = float(d['priceTick'])
VARIABLE_COMMISSION_DICT[d['vtSymbol']] = float(
d['variableCommission'])
FIXED_COMMISSION_DICT[d['vtSymbol']] = float(
d['fixedCommission'])
SLIPPAGE_DICT[d['vtSymbol']] = float(d['slippage'])
self.portfolio = TurtlePortfolio(self)
self.portfolio.init(portfolioValue, self.vtSymbolList, SIZE_DICT)
self.output(u'投资组合的合约代码%s' % (self.vtSymbolList))
self.output(u'投资组合的初始价值%s' % (portfolioValue))
#----------------------------------------------------------------------
def loadData(self):
"""加载数据"""
mc = MongoClient()
db = mc[DAILY_DB_NAME]
for vtSymbol in self.vtSymbolList:
flt = {'datetime': {'$gte': self.startDt, '$lte': self.endDt}}
collection = db[vtSymbol]
cursor = collection.find(flt).sort('datetime')
for d in cursor:
bar = BarData()
bar.__dict__ = d
barDict = self.dataDict.setdefault(bar.datetime, OrderedDict())
barDict[bar.vtSymbol] = bar
self.output(u'%s数据加载完成，总数据量：%s' % (vtSymbol, cursor.count()))
self.output(u'全部数据加载完成')
#----------------------------------------------------------------------
def runBacktesting(self):
"""运行回测"""
self.output(u'开始回放K线数据')
for dt, barDict in self.dataDict.items():
self.currentDt = dt
previousResult = self.result
self.result = DailyResult(dt)
self.result.updatePos(self.portfolio.posDict)
self.resultList.append(self.result)
if previousResult:
self.result.updatePreviousClose(previousResult.closeDict)
for bar in barDict.values():
self.portfolio.onBar(bar)
self.result.updateBar(bar)
self.output(u'K线数据回放结束')
#----------------------------------------------------------------------
def calculateResult(self, annualDays=240):
"""计算结果"""
self.output(u'开始统计回测结果')
for result in self.resultList:
result.calculatePnl()
resultList = self.resultList
dateList = [result.date for result in resultList]
startDate = dateList[0]
endDate = dateList[-1]
totalDays = len(dateList)
profitDays = 0
lossDays = 0
endBalance = self.portfolioValue
highlevel = self.portfolioValue
totalNetPnl = 0
totalCommission = 0
totalSlippage = 0
totalTradeCount = 0
netPnlList = []
balanceList = []
highlevelList = []
drawdownList = []
ddPercentList = []
returnList = []
for result in resultList:
if result.netPnl > 0:
profitDays += 1
elif result.netPnl < 0:
lossDays += 1
netPnlList.append(result.netPnl)
prevBalance = endBalance
endBalance += result.netPnl
balanceList.append(endBalance)
returnList.append(endBalance / prevBalance - 1)
highlevel = max(highlevel, endBalance)
highlevelList.append(highlevel)
drawdown = endBalance - highlevel
drawdownList.append(drawdown)
ddPercentList.append(drawdown / highlevel * 100)
totalCommission += result.commission
totalSlippage += result.slippage
totalTradeCount += result.tradeCount
totalNetPnl += result.netPnl
maxDrawdown = min(drawdownList)
maxDdPercent = min(ddPercentList)
totalReturn = (endBalance / self.portfolioValue - 1) * 100
dailyReturn = np.mean(returnList) * 100
annualizedReturn = dailyReturn * annualDays
returnStd = np.std(returnList) * 100
if returnStd:
sharpeRatio = dailyReturn / returnStd * np.sqrt(annualDays)
else:
sharpeRatio = 0
# 返回结果
result = {
'startDate': startDate,
'endDate': endDate,
'totalDays': totalDays,
'profitDays': profitDays,
'lossDays': lossDays,
'endBalance': endBalance,
'maxDrawdown': maxDrawdown,
'maxDdPercent': maxDdPercent,
'totalNetPnl': totalNetPnl,
'dailyNetPnl': totalNetPnl / totalDays,
'totalCommission': totalCommission,
'dailyCommission': totalCommission / totalDays,
'totalSlippage': totalSlippage,
'dailySlippage': totalSlippage / totalDays,
'totalTradeCount': totalTradeCount,
'dailyTradeCount': totalTradeCount / totalDays,
'totalReturn': totalReturn,
'annualizedReturn': annualizedReturn,
'dailyReturn': dailyReturn,
'returnStd': returnStd,
'sharpeRatio': sharpeRatio
}
timeseries = {
'balance': balanceList,
'return': returnList,
'highLevel': highlevel,
'drawdown': drawdownList,
'ddPercent': ddPercentList,
'date': dateList,
'netPnl': netPnlList
}
return timeseries, result
#----------------------------------------------------------------------
def showResult(self):
"""显示回测结果"""
timeseries, result = self.calculateResult()
# 输出统计结果
self.output('-' * 30)
self.output(u'首个交易日：\t%s' % result['startDate'])
self.output(u'最后交易日：\t%s' % result['endDate'])
self.output(u'总交易日：\t%s' % result['totalDays'])
self.output(u'盈利交易日\t%s' % result['profitDays'])
self.output(u'亏损交易日：\t%s' % result['lossDays'])
self.output(u'起始资金：\t%s' % self.portfolioValue)
self.output(u'结束资金：\t%s' % formatNumber(result['endBalance']))
self.output(u'总收益率：\t%s%%' % formatNumber(result['totalReturn']))
self.output(u'年化收益：\t%s%%' % formatNumber(result['annualizedReturn']))
self.output(u'总盈亏：\t%s' % formatNumber(result['totalNetPnl']))
self.output(u'最大回撤: \t%s' % formatNumber(result['maxDrawdown']))
self.output(u'百分比最大回撤: %s%%' % formatNumber(result['maxDdPercent']))
self.output(u'总手续费：\t%s' % formatNumber(result['totalCommission']))
self.output(u'总滑点：\t%s' % formatNumber(result['totalSlippage']))
self.output(u'总成交笔数：\t%s' % formatNumber(result['totalTradeCount']))
self.output(u'日均盈亏：\t%s' % formatNumber(result['dailyNetPnl']))
self.output(u'日均手续费：\t%s' % formatNumber(result['dailyCommission']))
self.output(u'日均滑点：\t%s' % formatNumber(result['dailySlippage']))
self.output(u'日均成交笔数：\t%s' % formatNumber(result['dailyTradeCount']))
self.output(u'日均收益率：\t%s%%' % formatNumber(result['dailyReturn']))
self.output(u'收益标准差：\t%s%%' % formatNumber(result['returnStd']))
self.output(u'Sharpe Ratio：\t%s' % formatNumber(result['sharpeRatio']))
# 绘图
fig = plt.figure(figsize=(10, 16))
pBalance = plt.subplot(4, 1, 1)
pBalance.set_title('Balance')
plt.plot(timeseries['date'], timeseries['balance'])
pDrawdown = plt.subplot(4, 1, 2)
pDrawdown.set_title('Drawdown')
pDrawdown.fill_between(range(len(timeseries['drawdown'])),
timeseries['drawdown'])
pPnl = plt.subplot(4, 1, 3)
pPnl.set_title('Daily Pnl')
plt.bar(range(len(timeseries['drawdown'])), timeseries['netPnl'])
pKDE = plt.subplot(4, 1, 4)
pKDE.set_title('Daily Pnl Distribution')
plt.hist(timeseries['netPnl'], bins=50)
plt.show()
#----------------------------------------------------------------------
def sendOrder(self, vtSymbol, direction, offset, price, volume):
"""记录交易数据（由portfolio调用）"""
# 对价格四舍五入
priceTick = PRICETICK_DICT[vtSymbol]
price = int(round(price / priceTick, 0)) * priceTick
# 记录成交数据
trade = TradeData(vtSymbol, direction, offset, price, volume)
l = self.tradeDict.setdefault(self.currentDt, [])
l.append(trade)
self.result.updateTrade(trade)
#----------------------------------------------------------------------
def output(self, content):
"""输出信息"""
print(content)
#----------------------------------------------------------------------
def getTradeData(self, vtSymbol=''):
"""获取交易数据"""
tradeList = []
for l in self.tradeDict.values():
for trade in l:
if not vtSymbol:
tradeList.append(trade)
elif trade.vtSymbol == vtSymbol:
tradeList.append(trade)
return tradeList
class BacktestingEngine(object):
"""组合类CTA策略回测引擎"""
#----------------------------------------------------------------------
def __init__(self):
"""Constructor"""
self.portfolio = None
# 合约配置信息
self.vtSymbolList = []
self.sizeDict = {} # 合约大小字典
self.priceTickDict = {} # 最小价格变动字典
self.variableCommissionDict = {} # 变动手续费字典
self.fixedCommissionDict = {} # 固定手续费字典
self.slippageDict = {} # 滑点成本字典
self.portfolioValue = 0
self.startDt = None
self.endDt = None
self.currentDt = None
self.dataDict = OrderedDict()
self.tradeDict = OrderedDict()
self.result = None
self.resultList = []
#----------------------------------------------------------------------
def setPeriod(self, startDt, endDt):
"""设置回测周期"""
self.startDt = startDt
self.endDt = endDt
#----------------------------------------------------------------------
def initPortfolio(self, filename, portfolioValue=10000000):
"""初始化投资组合"""
self.portfolioValue = portfolioValue
with open(filename) as f:
r = DictReader(f)
for d in r:
self.vtSymbolList.append(d['vtSymbol'])
SIZE_DICT[d['vtSymbol']] = int(d['size'])
PRICETICK_DICT[d['vtSymbol']] = float(d['priceTick'])
VARIABLE_COMMISSION_DICT[d['vtSymbol']] = float(d['variableCommission'])
FIXED_COMMISSION_DICT[d['vtSymbol']] = float(d['fixedCommission'])
SLIPPAGE_DICT[d['vtSymbol']] = float(d['slippage'])
self.portfolio = TurtlePortfolio(self)
self.portfolio.init(portfolioValue, self.vtSymbolList, SIZE_DICT)
self.output(u'投资组合的合约代码%s' %(self.vtSymbolList))
self.output(u'投资组合的初始价值%s' %(portfolioValue))
#----------------------------------------------------------------------
def loadData(self):
"""加载数据"""
mc = MongoClient()
db = mc[DAILY_DB_NAME]
for vtSymbol in self.vtSymbolList:
flt = {'datetime':{'$gte':self.startDt,
'$lte':self.endDt}}
collection = db[vtSymbol]
cursor = collection.find(flt).sort('datetime')
for d in cursor:
bar = VtBarData()
bar.__dict__ = d
barDict = self.dataDict.setdefault(bar.datetime, OrderedDict())
barDict[bar.vtSymbol] = bar
self.output(u'%s数据加载完成，总数据量：%s' %(vtSymbol, cursor.count()))
self.output(u'全部数据加载完成')
#----------------------------------------------------------------------
def runBacktesting(self):
"""运行回测"""
self.output(u'开始回放K线数据')
for dt, barDict in self.dataDict.items():
# self.currentDt = dt
#
# previousResult = self.result
#
# self.result = DailyResult(dt)
# self.result.updatePos(self.portfolio.posDict)
# self.resultList.append(self.result)
#
# if previousResult:
# self.result.updatePreviousClose(previousResult.closeDict)
#
# for bar in barDict.values():
# self.portfolio.onBar(bar)
# self.result.updateBar(bar)
self.portfolio.onBar(bar)
self.output(u'K线数据回放结束')