def do_backtest(self, arg):
paramFlag = input('Use current parameters? ([y]/n): ')
if paramFlag is 'n':
# Change parameters here
bbFunctions.choose_parameters()
numLinesLog = bbFunctions.file_len(bbCfg.logFileName)
bbCfg.logFileNameBT = bbFunctions.getLogFileNameBT()
try:
numLinesLogBT = bbFunctions.file_len(bbCfg.logFileNameBT)
except:
numLinesLogBT = 0
if numLinesLogBT != numLinesLog:
bitbot.main('-b')
d,r=bbPerformance.getReturns(bbCfg.logFileNameBT, None, '2014-01-08', None)
bbPerformance.printSummary(r)
def do_performance(self, arg):
startDate = input('Initial Date (YYYY-MM-DD): ')
if len(startDate) is not 10:
startDate = '2014-01-08'
endDate = input('End Date (YYYY-MM-DD): ')
if len(endDate) is not 10:
endDate = None
chooseBT = input('Calculate performance for backtest? y/[n]: ')
if chooseBT == 'y':
bbCfg.logFileNameBT = bbFunctions.getLogFileNameBT()
d,r=bbPerformance.getReturns(bbCfg.logFileNameBT, None,
startDate, endDate)
else:
d,r=bbPerformance.getReturns(bbCfg.logFileName, bbCfg.fundFileName,
startDate, endDate)
bbPerformance.printReturns(d, r)
print('')
bbPerformance.printSummary(r)
def do_calibrate(self, arg):
reload(bbCfg)
old_walkUp = bbCfg.walkUp
old_tradeFactor = bbCfg.tradeFactor
old_allinLimit = bbCfg.allinLimit
old_backupFund = bbCfg.backupFund
m = [0.9, 1.1]
result = []
numLinesLog = bbFunctions.file_len(bbCfg.logFileName)
for i in range(len(m)**4):
sys.stdout.write('|')
sys.stdout.write('\n')
for bbCfg.walkUp in [x * old_walkUp for x in m]:
for bbCfg.tradeFactor in [x * old_tradeFactor for x in m]:
for bbCfg.allinLimit in [x * old_allinLimit for x in m]:
for bbCfg.backupFund in [x * old_backupFund for x in m]:
bbCfg.logFileNameBT = bbFunctions.getLogFileNameBT()
try:
n = bbFunctions.file_len(bbCfg.logFileNameBT)
except:
n = 0
#bbFunctions.display_config()
sys.stdout.write('|')
sys.stdout.flush()
if n != numLinesLog:
bitbot.main('-b -q')
d,r=bbPerformance.getReturns(bbCfg.logFileNameBT,
None, '2014-01-08', None)
result.append([
bbCfg.walkUp,
bbCfg.tradeFactor,
bbCfg.allinLimit,
bbCfg.backupFund,
100*bbPerformance.totalReturn(r[:,3])])
print('')
result = np.array(result)
result = result[np.argsort(result[:, len(result[0])-1])]
print(' '.join('{0:>10}'.format(x) for x in ['walkUp', 'tradeFactor', 'allinLimit', 'backupFund', 'Return']))
for row in result[-10:]:
print(' '.join('{0:10.4}'.format(x) for x in row))
