rschLib.analyzeTradeTags(trades, result['rBad30'], result['idxBad30'], '亏损前30%交易', strategy_name, dtes, name, offStart) #get tag names tnames, idxOverLapTagList = rschLib.analyzeTradeTags(trades, r, list(range(len(trades))), '所有交易', strategy_name, dtes, name, offStart) #draw pnl and tag pnl importlib.reload(rschLib) [dtesByTrade, pnlByTrade] = rschLib.getPnl(dtes, tkrs, name, trades, inTime, otTime, dayOff, timeAsFloat, toDatabase='yes', strategy_name=strategy_name) [dtesPnlAggr, pnlAggr, numTrades] = rschLib.aggregatePnlAndDtes(dtesByTrade, pnlByTrade) rschLib.drawPNL(dtesPnlAggr, pnlAggr, dtes, strategy_name, toDatabase='yes') for i in range(len(tnames)): tagName = tnames[i] [dtesWithTag, pnlWithTag, n] = rschLib.aggregatePnlAndDtes(dtesByTrade[idxOverLapTagList[i]], pnlByTrade[idxOverLapTagList[i]]) rschLib.drawPNL(dtesWithTag, pnlWithTag, dtes,
'盈利前30%交易', strategy_name, dtes, name, offStart) rschLib.analyzeTradeTags(trades, result['rBad10'], result['idxBad10'], '亏损前10%交易', strategy_name, dtes, name, offStart) rschLib.analyzeTradeTags(trades, result['rBad20'], result['idxBad20'], '亏损前20%交易', strategy_name, dtes, name, offStart) rschLib.analyzeTradeTags(trades, result['rBad30'], result['idxBad30'], '亏损前30%交易', strategy_name, dtes, name, offStart) # In[8]: importlib.reload(rschLib) [dtesPnl, pnl, numTrades] = rschLib.getPnl(dtes, tkrs, name, trades, inTime, otTime, dayOff, timeAsFloat, toDatabase='yes') # In[ ]: importlib.reload(rschLib) rschLib.pnlVsNumtrades(pnl, numTrades) # In[ ]: # In[ ]: # In[ ]:
def analyzeStrategy(strategy_name, offStart, dtes, name, tkrs): timeAsFloat, timeLabels, maxM, dayOff = rschLib.getTimeLabels(maxD) trades, tradesUsed, Po, r = rschLib.getTradesWithPklCache( strategy_name, name, tkrs, dtes, maxD, maxM) # get trade samples by good/bad trades tradeArea = [inTime, otTime] result = rschLib.getTradeAnalysisSampleGroups(r, tradeArea) # draw price change rschLib.drawPriceChange(r, strategy_name, timeLabels=timeLabels, tp=tradeArea) rschLib.drawPriceChange(result['rGood10'], strategy_name, timeLabels=timeLabels, title='盈利前10%交易', tp=tradeArea) rschLib.drawPriceChange(result['rGood20'], strategy_name, timeLabels=timeLabels, title='盈利前20%交易', tp=tradeArea) rschLib.drawPriceChange(result['rGood30'], strategy_name, timeLabels=timeLabels, title='盈利前30%交易', tp=tradeArea) rschLib.drawPriceChange(result['rBad10'], strategy_name, timeLabels=timeLabels, title='亏损前10%交易', tp=tradeArea) rschLib.drawPriceChange(result['rBad20'], strategy_name, timeLabels=timeLabels, title='亏损前20%交易', tp=tradeArea) rschLib.drawPriceChange(result['rBad30'], strategy_name, timeLabels=timeLabels, title='亏损前30%交易', tp=tradeArea) # analyze tags #rschLib.analyzeTradeTags(tradesUsed, result['rGood10'], result['idxGood10'], '盈利前10%交易',strategy_name, dtes, tkrs, offStart) #rschLib.analyzeTradeTags(tradesUsed, result['rGood20'], result['idxGood20'], '盈利前20%交易',strategy_name, dtes, tkrs, offStart) #rschLib.analyzeTradeTags(tradesUsed, result['rGood30'], result['idxGood30'], '盈利前30%交易',strategy_name, dtes, tkrs, offStart) #rschLib.analyzeTradeTags(tradesUsed, result['rBad10'], result['idxBad10'], '亏损前10%交易',strategy_name, dtes, tkrs, offStart) #rschLib.analyzeTradeTags(tradesUsed, result['rBad20'], result['idxBad20'], '亏损前20%交易',strategy_name, dtes, tkrs, offStart) #rschLib.analyzeTradeTags(tradesUsed, result['rBad30'], result['idxBad30'], '亏损前30%交易',strategy_name, dtes, tkrs, offStart) #get tag names tnames, tagNamesEn, t2 = rschLib.getTagNames() idxOverLapTagList = rschLib.analyzeTradeTags(tradesUsed, r, list(range(len(tradesUsed))), '所有交易', strategy_name, dtes, tkrs, offStart) #draw pnl and tag pnl importlib.reload(rschLib) [dtesByTrade, pnlByTrade] = rschLib.getPnl(dtes, tkrs, name, tradesUsed, inTime, otTime, dayOff, timeAsFloat, toDatabase='yes', strategy_name=strategy_name) [dtesPnlAggr, pnlAggr, numTrades] = rschLib.aggregatePnlAndDtes(dtesByTrade, pnlByTrade) rschLib.drawPNL(dtesPnlAggr, pnlAggr, dtes, strategy_name, toDatabase='yes') for i in range(len(tnames)): tagName = tnames[i] [dtesWithTag, pnlWithTag, n] = rschLib.aggregatePnlAndDtes(dtesByTrade[idxOverLapTagList[i]], pnlByTrade[idxOverLapTagList[i]]) rschLib.drawPNL(dtesWithTag, pnlWithTag, dtes, strategy_name, toDatabase='yes', dateStart=dtesPnlAggr[0], pnlType=tagName) rschLib.drawPNL(dtesWithTag, pnlWithTag, dtes, strategy_name + '+' + tagNamesEn[i], toDatabase='yes', dateStart=dtesPnlAggr[0], pnlType='pnl') #analysis of number of trades vs performance importlib.reload(rschLib) rschLib.pnlVsNumtrades(pnlAggr, numTrades, strategy_name, toDatabase='yes') rschLib.saveOffStart(strategy_name, offStart)