def generatePAndLPlot(self):
plotter = PAndLPlotter(self.settings)
datastore = datastorefactory.get_datastore()
account = Account(self.settings)
positionSizer = PercentOfEquityPositionSizer(self.settings)
outfile = "equitycurve.csv"
plotter.plot(datastore, account, positionSizer, self.trades, outfile)
# TODO try/finally
datastore.close()
def getStatsNew(self):
datastore = PreloadedProxyDataStore(datastorefactory.get_datastore())
try:
maxValidRStr = self.settings.get("TradeManager", "maxValidR")
except:
maxValidRStr = "None"
if maxValidRStr == "None":
maxValidR = None
else:
maxValidR = float(maxValidRStr)
numtrades = float(len(self.trades))
numwins = 0.0
totalpandl = 0.0
totalabspandl = 0.0
totalwin = 0.0
totalloss = 0.0
timeintrade=0
timeinwin=0
timeinloss=0
rs = list()
drawdownsizes = dict()
drawdownsizes["5%"] = None
drawdownsizes["10%"] = None
drawdownsizes["25%"] = None
drawdownsizes["25%"] = None
drawdownsizes["50%"] = None
drawdownsizes["75%"] = None
drawdownsizes["90%"] = None
drawdownsizes["optimal f"] = None
leverage_stats = list()
self.trades = sorted(self.trades, key=lambda trade: trade.getEntryDate())
best_final_equity = 0
for risk in (0.005, 0.01, 0.015, 0.02, 0.03, 0.04, 0.05, 0.06, 0.07, 0.08, 0.09, 0.1, \
0.12, 0.14, 0.15, 0.16, 0.18, 0.2, 0.25, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0, \
1.25, 1.5, 1.75, 2.0, 2.5, 3.0, 4.0,):
trades = copy.deepcopy(self.trades)
account = Account(self.settings)
max_equity = account.cash
posSizer = PercentOfEquityPositionSizer(self.settings, risk, 4.0, 10)
pandlPlotter = PAndLPlotter(self.settings)
equityCurve = pandlPlotter.generate_equity_curve(datastore, account, \
posSizer, trades)
max_drawdown = 0
final_equity = 0
for data in equityCurve:
equity = data["equity"]
if equity < max_equity:
drawdown = (max_equity-equity)/max_equity
if drawdown > max_drawdown:
max_drawdown = drawdown
if equity > max_equity:
max_equity = equity
final_equity = equity
leverage_stat = dict()
leverage_stat["risk"] = risk
leverage_stat["drawdown"] = max_drawdown
leverage_stat["final_equity"] = final_equity
leverage_stats.append(leverage_stat)
keys = list()
if final_equity > best_final_equity:
keys.append("optimal f")
best_final_equity = equity
if max_drawdown < .9:
keys.append("90%")
if max_drawdown < .75:
keys.append("75%")
if max_drawdown < .5:
keys.append("50%")
if max_drawdown < 0.25:
keys.append("25%")
if max_drawdown < 0.1:
keys.append("10%")
if max_drawdown < 0.05:
keys.append("5%")
for key in keys:
if drawdownsizes[key] == None or drawdownsizes[key][1] < final_equity:
drawdownsizes[key] = (risk, final_equity)
for trade in self.trades:
pandl = trade.pandlR()
if pandl == 0:
pandl = 0
rs.append(0)
abspandl = 0
else:
# disregard outrageous R values, per max valid R setting
if maxValidR == None or pandl <= maxValidR:
rs.append(pandl)
abspandl = trade.pandlPercent()
# disregard outrageous R values, per max valid R setting
if maxValidR == None or pandl <= maxValidR:
totalpandl = totalpandl + pandl
totalabspandl = totalabspandl + abspandl
if pandl > 0:
numwins = numwins + 1.0
totalwin = totalwin + pandl
timeinwin = timeinwin + (trade.time_in_trade()/60)
else:
totalloss = totalloss - pandl
timeinloss = timeinloss + (trade.time_in_trade()/60)
timeintrade = timeintrade + (trade.time_in_trade()/60)
if numtrades > 0:
averageWin=0
averageLoss=0
averageDuration=0
averageWinDuration=0
averageLossDuration=0
if numwins > 0:
averageWin = (totalwin/numwins)
averageWinDuration = timeinwin/(60.0*24.0*float(numwins))
if numwins<numtrades:
averageLoss = (totalloss/(numtrades-numwins))
averageLossDuration = timeinloss/(60.0*24.0*float(numtrades-numwins))
if numtrades > 0:
averageDuration = timeintrade/(60.0*24.0*float(numtrades))
rdev = numpy.std(rs)
# TODO move this somewhere sensible
self.generatePAndLPlot()
self.generateTradesCSV()
return Stats(numtrades,(totalabspandl/numtrades), (totalpandl/numtrades), (numwins/numtrades), \
averageWin = averageWin, averageLoss = averageLoss, averageDuration=averageDuration, \
averageWinDuration=averageWinDuration, averageLossDuration=averageLossDuration, rdev=rdev, \
drawdownsizes = drawdownsizes,
leverage_stats = leverage_stats)
else:
return Stats(0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0, 0.0)
