def run_strategy(paras):
feed = dataframefeed.Feed()
feed.addBarsFromDataFrame(instrument, dat)
strat = singleMA.SingleMA(feed, instrument, paras, initialCash)
# attach analyzersgc
returnsAnalyzer = returns.Returns()
strat.attachAnalyzer(returnsAnalyzer)
drawdownAnalyzer = drawdown.DrawDown()
strat.attachAnalyzer(drawdownAnalyzer)
sharpeRatioAnalyzer = sharpe.SharpeRatio()
strat.attachAnalyzer(sharpeRatioAnalyzer)
tradeAnalyzer = trades.Trades()
strat.attachAnalyzer(tradeAnalyzer)
strat.run()
print "Final portfolio value: $%.2f with paras %d" % (
strat.getBroker().getEquity(), paras)
return {
'returns':
returnsAnalyzer.getCumulativeReturns()[-1],
'drawdown':
drawdownAnalyzer.getMaxDrawDown(),
'longestDrawDownDuration':
drawdownAnalyzer.getLongestDrawDownDuration(),
'sr':
sharpeRatioAnalyzer.getSharpeRatio(0.03),
'total trades':
tradeAnalyzer.getCount(),
'win':
tradeAnalyzer.getProfitableCount(),
'lose':
tradeAnalyzer.getUnprofitableCount(),
'average win profit':
tradeAnalyzer.getPositiveReturns().mean(),
'average lose loss':
tradeAnalyzer.getNegativeReturns().mean(),
'wining ratio':
tradeAnalyzer.getProfitableCount() / tradeAnalyzer.getCount(),
'odds':
-tradeAnalyzer.getPositiveReturns().mean() /
tradeAnalyzer.getNegativeReturns().mean()
}
import utility.windutility as wu
from utility import dataframefeed
from pyalgotrade.stratanalyzer import returns
strat = singleMA
instrument = '000001.SH'
fromDate = '20160101'
toDate = '20160727'
frequency = bar.Frequency.MINUTE
paras = [19]
plot = True
data = wu.wsi(instrument, 'open, high, low, close, volume', fromDate,
toDate)
# data['adjclose'] = data['close'] * data['adjfactor'] / data['adjfactor'][-1]
feed = dataframefeed.Feed()
feed.addBarsFromDataFrame(instrument, data)
strat = strat(feed, instrument, *paras)
returnsAnalyzer = returns.Returns()
strat.attachAnalyzer(returnsAnalyzer)
if plot:
# plt = plotter.StrategyPlotter(strat, True, True, True)
# ma = strat.getMA()
# plt.getInstrumentSubplot('indicator').addDataSeries('ma', ma)
plt = plotter.StrategyPlotter(strat)
# plt.getInstrumentSubplot(instrument).addDataSeries('ma', strat.getMA())
plt.getOrCreateSubplot('returns').addDataSeries(
'simple return', returnsAnalyzer.getReturns())