def turtle_test(code,start=None,plot=True,dl=60):
feed = ptc.get_tdx_barfeed(code,start,dl=dl)
#myStrategy = pyalg_test.SMACrossOver(feed, "orcl", 20)
pars=[2, 20, 60, 10]
# myStrategy = thrSMA_dayinfo(feed, "orcl",*pars)
myStrategy = BBands(feed, code,20,dl)
# Attach a returns analyzers to the strategy.
# returnsAnalyzer = returns.Returns()
# myStrategy.attachAnalyzer(returnsAnalyzer)
# if dataString =='pyalg_util':
# ds = pyalg_utils.dataSet(myStrategy) #抽取交易数据集语句，若使用系统自带画图功能则不需要该项
from pyalgotrade.stratanalyzer import returns
from pyalgotrade.stratanalyzer import sharpe
from pyalgotrade.stratanalyzer import drawdown
from pyalgotrade.stratanalyzer import trades
retAnalyzer = returns.Returns()
myStrategy.attachAnalyzer(retAnalyzer)
sharpeRatioAnalyzer = sharpe.SharpeRatio()
myStrategy.attachAnalyzer(sharpeRatioAnalyzer)
drawDownAnalyzer = drawdown.DrawDown()
myStrategy.attachAnalyzer(drawDownAnalyzer)
tradesAnalyzer = trades.Trades()
myStrategy.attachAnalyzer(tradesAnalyzer)
# Attach the plotter to the strategy.
# plt = plotter.StrategyPlotter(myStrategy)
# Plot the simple returns on each bar.
if plot:
plt = plotter.StrategyPlotter(myStrategy, True, True, True)
plt.getOrCreateSubplot("returns").addDataSeries("Simple returns", retAnalyzer.getReturns())
myStrategy.run()
myStrategy.info("Final portfolio value: $%.2f" % myStrategy.getResult())
# if dataString =='pyalg_util':
# rs = ds.getDefault() #获取默认的交易信息，dic格式
# plot(rs["cumulativeReturns"][:,0],rs["cumulativeReturns"][:,1]) #简单作图示例
#夏普率
sharp = sharpeRatioAnalyzer.getSharpeRatio(0.05)
#最大回撤
maxdd = drawDownAnalyzer.getMaxDrawDown()
#收益率
return_ = retAnalyzer.getCumulativeReturns()[-1]
#收益曲线
return_list = []
for item in retAnalyzer.getCumulativeReturns():
return_list.append(item)
print "Sharpe ratio: %.2f maxdown:%.2f%% return:%.2f%%" %(sharp,maxdd*100,return_*100)
myStrategy.get_max_min()
plt.plot()
def testStrategy(code, start=None, plot=False):
from pyalgotrade import bar
from pyalgotrade import plotter
strat = Bollinger_Bandit
# instrument = '600288'
market = 'SH'
fromDate = '20150101'
toDate = '20150601'
frequency = bar.Frequency.MINUTE
paras = [40, 15, 35, 15, 60, 2]
# plot = True
#############################################path set ############################33
import os
if frequency == bar.Frequency.MINUTE:
path = os.path.join('..', 'histdata', 'minute')
elif frequency == bar.Frequency.DAY:
path = os.path.join('..', 'histdata', 'day')
# filepath = os.path.join(path, instrument + market + ".csv")
#############################################don't change ############################33
# from pyalgotrade.cn.csvfeed import Feed
from feedutil import dataFramefeed
import powerTech as pt
# barfeed = Feed(frequency)
# barfeed.setDateTimeFormat('%Y-%m-%d %H:%M:%S')
# barfeed.loadBars(instrument, market, fromDate, toDate, filepath)
code = '000002'
start = '2016-01-01'
barfeed = pt.get_tdx_barfeed(code, start)
# pyalgotrade_id = instrument + '.' + market
strat = strat(barfeed, code, *paras)
from pyalgotrade.stratanalyzer import returns
from pyalgotrade.stratanalyzer import sharpe
from pyalgotrade.stratanalyzer import drawdown
from pyalgotrade.stratanalyzer import trades
retAnalyzer = returns.Returns()
strat.attachAnalyzer(retAnalyzer)
sharpeRatioAnalyzer = sharpe.SharpeRatio()
strat.attachAnalyzer(sharpeRatioAnalyzer)
drawDownAnalyzer = drawdown.DrawDown()
strat.attachAnalyzer(drawDownAnalyzer)
tradesAnalyzer = trades.Trades()
strat.attachAnalyzer(tradesAnalyzer)
if plot:
plt = plotter.StrategyPlotter(strat, True, True, True)
strat.run()
if plot:
plt.plot()
#夏普率
sharp = sharpeRatioAnalyzer.getSharpeRatio(0.05)
#最大回撤
maxdd = drawDownAnalyzer.getMaxDrawDown()
#收益率
return_ = retAnalyzer.getCumulativeReturns()[-1]
#收益曲线
return_list = []
for item in retAnalyzer.getCumulativeReturns():
return_list.append(item)