def runstrat():
#Create an instance of cerebro
cerebro = bt.Cerebro(exactbars=-1) #exactbars True reduces memory usage significantly, but change to '-1' for partial memory savings (keeping indicators in memory) or 'false' to turn off completely if having trouble accessing bars beyond max indicator paramaters.
cerebro.broker.set_coc(False) #allows you to buy/sell close price of previous bar, vs. default behavior of open on next bar.
cerebro.broker.set_coo(False) #default is False, meaning assuming day bars,orders are put in at end of previous day (end of previous bar) and order execution happens at open of today's bar (at open of current bar). Cheat on open puts order in same day before bar opens, and executes at open price. Such a use case fails when the opening price gaps (up or down, depending on whether buy or sell is in effect) and the cash is not enough for an all-in operation. This forces the broker to reject the operation.
cerebro.broker.set_shortcash(True) #False means decrease cash available when you short, True means increase it
#Add our strategy
cerebro.addstrategy(Strategy)
#Create/Instantiate objects to access parameters from UserInput Class
#Can NOT create object referencing Strategy class as per backtrader
modelp = UserInputs.model_params()
if modelp.get('live_status'):
ibdatalist = UserInputs.datalist('ib')
#Ensure stock lists have no duplicates - duplicates will BREAK program
if len(ibdatalist) != len(set(ibdatalist)):
print("*****You have duplicates in stock list - FIX LIST*****")
else:
datalist = UserInputs.datalist('hist')
if len(datalist) != len(set(datalist)):
print("*****You have duplicates in stock list - FIX LIST*****")
#GET THE DATA
session_start = modelp.get('sessionstart')
session_end = modelp.get('sessionend')
if not modelp.get('live_status'):
#******BACTESTING ONLY - MYSQL DATABASE*********
#mysql configuration items for connection
host = '127.0.0.1'
user = '******'
password = '******'
database = 'Stock_Prices'
table = '5_min_prices'
#Determine data range to run
start_date = modelp.get('start_date')
end_date = modelp.get('end_date')
for i,j in enumerate(datalist):
#Get data from mysql and add data to Cerebro
data = mysql.MySQLData(dbHost = host,
dbUser = user,
dbPWD = password,
dbName = database,
table = table,
symbol = j,
fromdate = start_date,
todate= end_date,
sessionstart = session_start,
sessionend = session_end,
compression = modelp.get('timeframe0'),
)
data_BaseTimeframe = cerebro.adddata(data=data,
name="{}0".format(j),
)
if modelp.get('timeframe1on'):
#Apply resamplings
data_Timeframe1 = cerebro.resampledata(data,
name="{}1".format(j),
timeframe=bt.TimeFrame.Minutes,
compression = modelp.get('timeframe1'),
)
if modelp.get('timeframe2on'):
data_Timeframe2 = cerebro.resampledata(data,
name="{}2".format(j),
timeframe=bt.TimeFrame.Minutes,
compression = modelp.get('timeframe2'),
)
# Set our desired cash start
cerebro.broker.setcash(modelp.get('start_cash'))
# Set the commission
cerebro.broker.setcommission(commission=0.00003,
margin= None,
mult=1.0,
commtype=None,
percabs=True,
stocklike=True,
leverage=1)
"""
#Set the slippage
cerebro.broker.set_slippage_perc(0.001,
slip_open=True,
slip_limit=True,
slip_match=True,
slip_out=False)
"""
elif modelp.get('live_status'):
#***** LIVE TRADING PARAMETERS*******
store = bt.stores.IBStore(host='127.0.0.1',
port=7497,
clientId = 100)
"""
for i,j in enumerate(ibdatalist):
#Data for live IB trading
data = store.getdata(dataname=j,
sectype='STK',
exchange='SMART',
currency='USD',
timeframe=bt.TimeFrame.Minutes,
tz = pytz.timezone('US/Central'),
sessionstart = session_start,
sessionend = session_end,
useRTH = True,
rtbar=True,
)
cerebro.resampledata(data, name="{}0".format(j),timeframe=bt.TimeFrame.Minutes, compression=modelp.get('timeframe0'))
#Apply resamplings
if modelp.get('timeframe1on'):
data_Timeframe1 = cerebro.resampledata(data,name="{}1".format(j),
timeframe=bt.TimeFrame.Minutes,
compression = modelp.get('timeframe1'))
if modelp.get('timeframe2on'):
data_Timeframe2 = cerebro.resampledata(data,name="{}2".format(j),
timeframe=bt.TimeFrame.Minutes,
compression = modelp.get('timeframe2'))
"""
forexdatalist = ['EUR.USD','GBP.USD'] #MAKE SURE NO COMMAS AFTER LAST TICKER
for i,j in enumerate(forexdatalist):
#Data for live IB trading
forexdata = store.getdata(dataname=j,
sectype='CASH',
exchange='IDEALPRO',
timeframe=bt.TimeFrame.Minutes,
tz = pytz.timezone('US/Central'),
sessionstart = session_start,
sessionend = session_end,
)
cerebro.resampledata(forexdata, name="{}0".format(j),timeframe=bt.TimeFrame.Minutes, compression=modelp.get('timeframe0'))
#Apply resamplings
if modelp.get('timeframe1on'):
data_Timeframe1 = cerebro.resampledata(forexdata,name="{}1".format(j),
timeframe=bt.TimeFrame.Minutes,
compression = modelp.get('timeframe1'))
if modelp.get('timeframe2on'):
data_Timeframe2 = cerebro.resampledata(forexdata,name="{}2".format(j),
timeframe=bt.TimeFrame.Minutes,
compression = modelp.get('timeframe2'))
"""
#ADD MARKET BREADTH DATA LIKE TICK
indexdatalist = ['TICK-NYSE'] #MAKE SURE NO COMMAS AFTER LAST TICKER
for i,j in enumerate(indexdatalist):
tickdata = store.getdata(dataname=j,
sectype='IND',
exchange='NYSE',
currency='USD',
timeframe=bt.TimeFrame.Minutes,
what = 'TRADES',
sessionstart = session_start,
sessionend = session_end,
)
cerebro.resampledata(tickdata, name="{}0".format(j),
timeframe=bt.TimeFrame.Minutes,
compression=modelp.get('timeframe0'))
#Apply resamplings
if modelp.get('timeframe1on'):
tickdata_Timeframe1 = cerebro.resampledata(tickdata,name="{}1".format(j),
timeframe=bt.TimeFrame.Minutes,
compression = modelp.get('timeframe1'))
if modelp.get('timeframe2on'):
tickdata_Timeframe2 = cerebro.resampledata(tickdata,name="{}2".format(j),
timeframe=bt.TimeFrame.Minutes,
compression = modelp.get('timeframe2'))
"""
cerebro.broker = store.getbroker() #*****Critical line of code to access broker so you can trade*****
# Add SQN to qualify the trades (rating to analyze quality of trading system: 2.5-3 good, above 3 excellent. SquareRoot(NumberTrades) * Average(TradesProfit) / StdDev(TradesProfit). Need at least 30 trades to be reliable
cerebro.addanalyzer(bt.analyzers.SQN)
#Add Sharpe Ratio - configured for daily returns
cerebro.addanalyzer(bt.analyzers.SharpeRatio)
#Adding my own custom analyzer - when creating analyzer, make sure to include file in _init_.py within backtrader.analyzer folder so it runs
cerebro.addanalyzer(bt.analyzers.AcctStats)
#Adding analyzer for drawdown
cerebro.addanalyzer(bt.analyzers.DrawDown)
# Add TradeAnalyzer to output trade statistics - THESE ARE THE TRADE NOTIFICATIONS THAT ARE PRINTED WHEN PROGRAM IS RUN
#cerebro.addanalyzer(bt.analyzers.Transactions)
#Adds just buy/sell observer to chart (assuming stdstats is set to false)
cerebro.addobservermulti(bt.observers.BuySell,)
#Adds custom observers
cerebro.addobserver(bt.observers.AcctValue) #reports trade statistics in command prompt at end of program run
#cerebro.addobserver(bt.observers.OrderObserver) #reports trades in command prompt when program is run
#Generate output report in csv format
if UserInputs.model_params().get('writer')=='on':
current_time = datetime.now().strftime("%Y-%m-%d_%H.%M.%S.csv")
csv_file = 'C:/Program Files (x86)/Python36-32/Lib/site-packages/backtrader/out/'
csv_file += 'Strategy'
csv_file += current_time
cerebro.addwriter(bt.WriterFile, csv = True, out=csv_file)
print("Writer CSV Report On")
#RUN EVERYTHING
results = cerebro.run(stdstats=False, #enables some additional chart information like profit/loss, buy/sell, etc, but tends to clutter chart
runonce=True,
)
if not modelp.get('live_status'):
#Print analyzers
for alyzer in results[0].analyzers:
alyzer.print()
#Calculate Program end time
end_time = datetime.now().time()
print('Program end at {}'.format(end_time))
#PLOT TRADING RESULTS - **Ensure trading session ends at 2:55 (if it ends at 3, some tickers only go up to 2:55, creating data length mismatches between tickers that doesn't allow plotting)
plot_end = modelp.get('end_date')-timedelta(hours=8, minutes=0, seconds=.01) #Hack to prevent errors with plotting, specifically x and y shape different error
#Chart 5 minute timeframes only, 1 by 1
for i in range (0,len(results[0].datas),3):
for j, d in enumerate(results[0].datas):
d.plotinfo.plot = i ==j
cerebro.plot(end = plot_end, barup='olive', bardown='lightpink',volup = 'lightgreen',voldown='crimson')
def runstrat():
#Create an instance of cerebro
cerebro = bt.Cerebro(exactbars=-1) #exactbars True reduces memory usage significantly, but change to '-1' for partial memory savings (keeping indicators in memory) or 'false' to turn off completely if having trouble accessing bars beyond max indicator paramaters.
cerebro.broker.set_coc(False) #cheat on close allows you to buy the close price of the current bar in which order was made. cheat on open allows you to simulate a market order on the open price of the next bar
cerebro.broker.set_coo(False) #cheat on close allows you to buy the close price of the current bar in which order was made. cheat on open allows you to simulate a market order on the open price of the next bar
#Add our strategy
cerebro.addstrategy(Strategy)
#Create/Instantiate objects to access parameters from UserInput Class
#Can NOT create object referencing Strategy class as per backtrader
modelp = UserInputs.model_params()
indp = UserInputs.ind_params()
datalist = UserInputs.datalist('hist')
ibdatalist = UserInputs.datalist('ib')
#Ensure stock lists have no duplicates - duplicates will BREAK program
if len(datalist) != len(set(datalist)) or len(ibdatalist) != len(set(ibdatalist)):
print("*****You have duplicates in stock list - FIX LIST*****")
#GET THE DATA
session_start = modelp.get('sessionstart')
session_end = modelp.get('sessionend')
start_date = modelp.get('start_date')
end_date = modelp.get('end_date')
sqlstart_date = "{} {}".format(start_date,session_start)
sqlend_date = "{} {}".format(end_date,session_end)
if modelp.get('live_status'):
#***** LIVE TRADING PARAMETERS*******
store = bt.stores.IBStore(host='127.0.0.1',
port=7497,
clientId = 100)
#get number of tickers
ticker_count = len(ibdatalist)
indicator_dict = UserInputs.ind_params()
max_ind = max(indicator_dict.values())
#Data set for live trading IB
for i,j in enumerate(ibdatalist):
#Data for live IB trading
data = store.getdata(dataname=j,
timeframe=bt.TimeFrame.Minutes,
tz = pytz.timezone('US/Central'),
#historical = True,
backfill_start = True, #true enables maximum allowable backfill in single request
useRTH = True,
rtbar=True,
fromdate = UserInputs.ib_backfill_start(UserInputs.max_ind()),#from date determined by today - max period paramater
sessionstart = session_start,
sessionend = session_end,
notifyall=True,
qcheck=2.0,
debug=True)
cerebro.resampledata(data, name="{}0".format(j),timeframe=bt.TimeFrame.Minutes, compression=modelp.get('base_timeframe'))
#Apply resamplings
if modelp.get('timeframe1on'):
data_Timeframe1 = cerebro.resampledata(data,name="{}1".format(j),
timeframe=bt.TimeFrame.Minutes,
compression = modelp.get('timeframe1'))
if modelp.get('timeframe2on'):
data_Timeframe2 = cerebro.resampledata(data,name="{}2".format(j),
timeframe=bt.TimeFrame.Minutes,
compression = modelp.get('timeframe2'))
cerebro.broker = store.getbroker()
elif not modelp.get('live_status'):
#******BACTESTING ONLY - MYSQL DATABASE*********
#get number of tickers
ticker_count = len(datalist)
#mysql configuration items for connection
host = '127.0.0.1'
user = '******'
password = '******'
database = 'Stock_Prices'
table = '5_min_prices'
#Determine data range to run
start_date = modelp.get('start_date')
end_date = modelp.get('end_date')
for i,j in enumerate(datalist):
#Get data from mysql and add data to Cerebro
data = mysql.MySQLData(dbHost = host,
dbUser = user,
dbPWD = password,
dbName = database,
table = table,
symbol = j,
fromdate = start_date,
todate= end_date,
timeframe=bt.TimeFrame.Minutes,
compression = modelp.get('base_timeframe'),
sessionstart=session_start,
sessionend=session_end,
)
data_BaseTimeframe = cerebro.adddata(data=data,
name="{}0".format(j),
)
data_BaseTimeframe.csv=True #Report this data to csv file (true) or not (false)
data_BaseTimeframe.plotinfo.plot = True
if modelp.get('timeframe1on'):
#Apply resamplings
data_Timeframe1 = cerebro.resampledata(data,
name="{}1".format(j),
timeframe=bt.TimeFrame.Minutes,
compression = modelp.get('timeframe1'),
)
data_Timeframe1.csv=False #Report this data to csv file (true) or not (false)
data_Timeframe1.plotinfo.plot = True
#data_Timeframe1.plotinfo.plotmaster = data_BaseTimeframe
if modelp.get('timeframe2on'):
data_Timeframe2 = cerebro.resampledata(data,
name="{}2".format(j),
timeframe=bt.TimeFrame.Minutes,
compression = modelp.get('timeframe2'),
)
data_Timeframe2.csv=False #Report this data to csv file (true) or not (false)
data_Timeframe2.plotinfo.plot = True
#data_Timeframe2.plotinfo.plotmaster = data_BaseTimeframe
# Set our desired cash start
cerebro.broker.setcash(modelp.get('start_cash'))
# Set the commission
cerebro.broker.setcommission(commission=0.00003,
margin= None,
mult=1.0,
commtype=None,
percabs=True,
stocklike=True,
leverage=1)
"""
#Set the slippage
cerebro.broker.set_slippage_perc(0.001,
slip_open=True,
slip_limit=True,
slip_match=True,
slip_out=False)
"""
# Add SQN to qualify the trades (rating to analyze quality of trading system: 2.5-3 good, above 3 excellent. SquareRoot(NumberTrades) * Average(TradesProfit) / StdDev(TradesProfit). Need at least 30 trades to be reliable
cerebro.addanalyzer(bt.analyzers.SQN)
#Adding my own custom analyzer - when creating analyzer, make sure to include file in _init_.py within backtrader.analyzer folder so it runs
cerebro.addanalyzer(bt.analyzers.AcctStats)
#Adding analyzer for drawdown
cerebro.addanalyzer(bt.analyzers.DrawDown)
# Add TradeAnalyzer to output trade statistics
cerebro.addanalyzer(bt.analyzers.Transactions)
#Adds just buy/sell observer to chart (assuming stdstats is set to false)
cerebro.addobservermulti(bt.observers.BuySell)
#Adds custom observers
cerebro.addobserver(bt.observers.AcctValue) #reports trade statistics in command prompt at end of program run
cerebro.addobserver(bt.observers.OrderObserver) #reports trades in command prompt when program is run
#Generate output report in csv format
if UserInputs.model_params().get('writer')=='on':
current_time = datetime.now().strftime("%Y-%m-%d_%H.%M.%S.csv")
csv_file = 'C:/Program Files (x86)/Python36-32/Lib/site-packages/backtrader/out/'
csv_file += 'Strategy'
csv_file += current_time
cerebro.addwriter(bt.WriterFile, csv = True, out=csv_file)
print("Writer CSV Report On")
#RUN EVERYTHING
results = cerebro.run(stdstats=False, #enables some additional chart information like profit/loss, buy/sell, etc, but tends to clutter chart
runonce=False,
)
strats = results[0]
if not modelp.get('live_status'):
#Print analyzers
for alyzer in strats.analyzers:
alyzer.print()
#Calculate Program end time
end_time = datetime.now().time()
print('Program end at {}'.format(end_time))
#Chart all timeframes, one by one
for i in range (len(strats.datas)):
for j, d in enumerate(strats.datas):
d.plotinfo.plot = i ==j
cerebro.plot(volume = True, style='candlestick',barup='olive', bardown='lightpink',volup = 'lightgreen',voldown='crimson')
#Only chart 5 minute graphs, one by one
"""