def check_stocks():
commission = 0.5
comm = bt.CommissionInfo(commission=commission)
size = 10.0
price = 10.0
cash = 1.0
marginok = comm.checkmargin(size=size, price=price, cash=cash)
assert not marginok
cash = 10000.0
size = 100.0
marginok = comm.checkmargin(size=size, price=price, cash=cash)
assert marginok
opcost = comm.getoperationcost(size=size, price=price)
assert opcost == size * price
pos = Position(size=size, price=price)
value = comm.getvalue(pos, price)
assert value == size * price
commcost = comm.getcomm_pricesize(size, price)
assert commcost == size * price * commission
newprice = 5.0
pnl = comm.profitandloss(pos, newprice)
assert pnl == pos.size * (newprice - price)
ca = comm.cashadjust(size, price, newprice)
assert not ca
def check_futures():
commission = 0.5
margin = 10.0
mult = 10.0
comm = bt.CommissionInfo(commission=commission, mult=mult, margin=margin)
price = 10.0
cash = 10000.0
size = 100.0
opcost = comm.getoperationcost(size=size, price=price)
assert opcost == size * margin
pos = Position(size=size, price=price)
value = comm.getvalue(pos, price)
assert value == size * margin
commcost = comm.getcommission(size, price)
assert commcost == size * commission
newprice = 5.0
pnl = comm.profitandloss(pos.size, pos.price, newprice)
assert pnl == pos.size * (newprice - price) * mult
ca = comm.cashadjust(size, price, newprice)
assert ca == size * (newprice - price) * mult
def multi_data_runner():
cerebro = bt.Cerebro()
cerebro.addstrategy(MultiDataStrategy)
firstrate_path = '/Users/jinchaolin/FirstRateReady/futures-active_adjusted_1min_8sjor/'
firstrate_file = 'ES' + '_continuous_adjusted_1min.txt'
dataname = firstrate_path + firstrate_file
data = bt.feeds.GenericCSVData(
dataname=dataname,
fromdate=datetime.datetime(2017, 1, 1),
todate=datetime.datetime(2019, 1, 1),
# nullvalue = 0.0,
dtformat=('%Y-%m-%d %H:%M:%S'),
openinterest=-1)
# Add the Data Feed to Cerebro
cerebro.adddata(data)
cerebro.addanalyzer(btanalyzers.TimeReturn,
_name='time_return',
timeframe=bt.TimeFrame.Months)
cerebro.broker.setcash(500_000.0)
cerebro.addsizer(bt.sizers.FixedSize, stake=10)
commES = bt.CommissionInfo(commission=2.0, margin=5000.0, mult=50.0)
cerebro.broker.addcommissioninfo(commES, name='ES')
res = cerebro.run()
print('Final Portfolio Value: %.2f' % cerebro.broker.getvalue())
import pdb
pdb.set_trace()
cerebro.plot()
def add_chain_data(cerebro, chains, with_comms=False):
"""Add all data from a future chain to Cerebro
:param cerebro: object - Cerebro instance from Backtrader
:param chains: list of object FutureChain - FutureChain to be added to Cerebro
:param with_comms: bool - Add commissions with the data
:return: object Cerebro
"""
# Add Data to Cerebro
for chain in chains:
# Commissions - Note: When throwing margin rejects => due to missing data
comms = bt.CommissionInfo(commission=chain.commission * 2, margin=chain.margin, mult=chain.point)
# Add all data series
for ct in chain.contracts: # [0:15]
# TODO: Check if missing data compared to Reference!
if chain.future_type == oci.FutureType.Spread:
data = SpreadPandasData(dataname=chain.data[ct])
else:
data = bt.feeds.PandasData(dataname=chain.data[ct])
data.plotinfo.plot = False # Do not plot this data
cerebro.adddata(data, name=ct)
# Commissions
if with_comms:
cerebro.broker.addcommissioninfo(comms, name=ct)
return cerebro
def runstrat(args=None):
args = parse_args(args)
cerebro = bt.Cerebro()
cerebro.broker.set_cash(args.cash)
cerebro.broker.set_int2pnl(args.no_int2pnl)
dkwargs = dict()
if args.fromdate is not None:
fromdate = datetime.datetime.strptime(args.fromdate, '%Y-%m-%d')
dkwargs['fromdate'] = fromdate
if args.todate is not None:
todate = datetime.datetime.strptime(args.todate, '%Y-%m-%d')
dkwargs['todate'] = todate
# if dataset is None, args.data has been given
data = bt.feeds.BacktraderCSVData(dataname=args.data, **dkwargs)
cerebro.adddata(data)
cerebro.signal_strategy(St)
cerebro.addsizer(bt.sizers.FixedSize, stake=args.stake)
sigtype = bt.signal.SIGNAL_LONGSHORT
if args.long:
sigtype = bt.signal.SIGNAL_LONG
elif args.short:
sigtype = bt.signal.SIGNAL_SHORT
cerebro.add_signal(sigtype, SMACrossOver, p1=args.period1, p2=args.period2)
if args.no_exit:
if args.long:
cerebro.add_signal(bt.signal.SIGNAL_LONGEXIT, NoExit)
elif args.short:
cerebro.add_signal(bt.signal.SIGNAL_SHORTEXIT, NoExit)
comminfo = bt.CommissionInfo(mult=args.mult,
margin=args.margin,
stocklike=args.stocklike,
interest=args.interest,
interest_long=args.interest_long)
cerebro.broker.addcommissioninfo(comminfo)
cerebro.run()
if args.plot:
pkwargs = dict(style='bar')
if args.plot is not True: # evals to True but is not True
npkwargs = eval('dict(' + args.plot + ')') # args were passed
pkwargs.update(npkwargs)
cerebro.plot(**pkwargs)
def __init__(self):
self.order = None # keep track of our orders
self.buyprice = None # keeps track of our buy price
self.sellprice = None
self.trade = None # store the current trade
commission = 0.0
self.comm = bt.CommissionInfo(commission=commission) # object of commisionInfo class to get pnl
# self.orderHist = []
self.orderDict = {} # stores a dictionary of each trade
self.datelist = 0
self.finalpnl = 0 # final pnl
self.set_tradehistory(True) # cerebro attribute -- ignore
self.time_after_ml = datetime.time(10, 0, 0, 0)
self.after_day = False # to know when to stop trading
self.datastatus = None
self.signals = {} # store the buy/sell signals from csv
# cerebro.addanalyzer(btanalyzers.PositionsValue, _name='position_value')# 有问题
# cerebro.addanalyzer(btanalyzers.PyFolio, _name='pyfolio')# 有问题
# cerebro.addanalyzer(btanalyzers.SQN, _name='sqn')
cerebro.addanalyzer(btanalyzers.TimeReturn, _name='time_return', timeframe=bt.TimeFrame.Months)
# cerebro.addanalyzer(btanalyzers.Transactions, _name='transactions')
# cerebro.addanalyzer(btanalyzers.VWR, _name='variability_weighted_return')
# Set our desired cash start
cerebro.broker.setcash(1_000_000.0)
# Add a FixedSize sizer according to the stake
cerebro.addsizer(bt.sizers.FixedSize, stake=10)
# Define commission
commES = bt.CommissionInfo(commission=2.0, margin=5000.0, mult=50.0)
# Set the commission
# cerebro.broker.setcommission(commission=0.001)
# cerebro.broker.setcommission(commission=2.0, margin=5000.0, mult=50.0, name='ES')
cerebro.broker.addcommissioninfo(commES, name='ES')
# Add a writer
cerebro.addwriter(bt.WriterFile, out='bt_res_2', csv=True)
cerebro.addwriter(bt.WriterFile, out='bt_res', log_dir='/Users/jinchaolin/TradingBT/log/tmp/', csv=True)
# Print out the starting conditions
print('Starting Portfolio Value: %.2f' % cerebro.broker.getvalue())
# Run over everything
# res = cerebro.run()
