/
run_BT.py
131 lines (90 loc) · 5.12 KB
/
run_BT.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
import argparse
import datetime
import glob
import os.path
import backtrader as bt
import btoandav20
import pytz
import q_datafeeds.bt_datafeed_postgres as bt_datafeed_postgres
from q_strategies import *
import q_credentials.oanda_cred as oanda_cred
import q_credentials.db_secmaster_cred as db_cred
import q_analyzers.bt_strat_perform_analyzer as bt_strat_performance_analyzer
import q_analyzers.bt_pos_perform_analyzer as bt_pos_performance_analyzer
import q_analyzers.bt_transaction_analyzer as bt_trans_analyzer
import q_analyzers.bt_strategy_id_analyzer as bt_strategy_id_analyzer
import q_analyzers.bt_logger_analyzer as bt_logger_analyzer
import q_tools.args_parse_other as args_parse_other
def run(args=None):
args = parse_args(args)
cerebro = bt.Cerebro()
# Data feed kwargs
dkwargs = dict(**eval('dict(' + args.dargs + ')'))
ticker_list=args.tickers[0].split(',')
dtfmt, tmfmt = '%Y-%m-%d', 'T%H:%M:%S'
if args.fromdate:
fmt = dtfmt + tmfmt * ('T' in args.fromdate)
dkwargs['fromdate'] = datetime.datetime.strptime(args.fromdate, fmt)
if args.todate:
fmt = dtfmt + tmfmt * ('T' in args.todate)
dkwargs['todate'] = datetime.datetime.strptime(args.todate, fmt)
cerebro.addanalyzer(bt_trans_analyzer.transactions_analyzer,_name='position_list')
cerebro.addanalyzer(bt_strategy_id_analyzer.strategy_id_analyzer,_name='strategy_id')
cerebro.addanalyzer(bt_strat_performance_analyzer.strat_performance_analyzer,_name='strat_perf')
cerebro.addanalyzer(bt_pos_performance_analyzer.pos_performance_analyzer,_name='pos_perf')
if args.ml_log:
cerebro.addanalyzer(bt_logger_analyzer.logger_analyzer,_name='ml_logger')
if args.mode=='live':
oandastore = btoandav20.stores.OandaV20Store(token=args.broker_token, account=args.broker_account, practice=True)
for ticker in ticker_list:
data = oandastore.getdata(dataname = ticker,timeframe = bt.TimeFrame.Minutes,compression=1,tz=pytz.timezone('US/Eastern'))
cerebro.adddata(data)
cerebro.broker = oandastore.getbroker()
cerebro.addstrategy(globals()[args.strat_name].St, backtest=False)
elif args.mode=='backtest':
for ticker in ticker_list:
data = bt_datafeed_postgres.PostgreSQL_Daily(dbHost=db_cred.dbHost,dbUser=db_cred.dbUser,dbPWD=db_cred.dbPWD,dbName=db_cred.dbName,ticker=ticker, name=ticker,**dkwargs)
cerebro.adddata(data)
cerebro.broker.setcash(args.cash)
cerebro.addstrategy(globals()[args.strat_name].St, **args.strat_param)
cerebro.addsizer(bt.sizers.FixedSize, stake=1000)
results = cerebro.run(tradehistory=True)
pnl = cerebro.broker.get_value() - args.cash
print('Profit ... or Loss: {:.2f}'.format(pnl))
strats = results
if args.plot:
cerebro.plot(style='candlestick',iplot=False,volume=False)
def parse_args(pargs=None):
parser = argparse.ArgumentParser(
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
description=('Rebalancing with the Conservative Formula'),
)
parser.add_argument('--tickers', nargs='*' ,required=False,default=['EUR_USD,GBP_USD'], type=str,
help='Pass the tickers with space')
parser.add_argument('--dargs', default='',
metavar='kwargs', help='kwargs in k1=v1,k2=v2 format')
parser.add_argument('--fromdate', required=False, default='2010-1-1',
help='Date[time] in YYYY-MM-DD[THH:MM:SS] format')
parser.add_argument('--todate', required=False, default='2019-7-30',
help='Date[time] in YYYY-MM-DD[THH:MM:SS] format')
parser.add_argument('--cerebro', required=False, default='',
metavar='kwargs', help='kwargs in k1=v1,k2=v2 format')
parser.add_argument('--cash', default=10000, type=float,
metavar='kwargs', help='kwargs in k1=v1,k2=v2 format')
parser.add_argument('--strat_name', required=False, default='simple_strategy_2',
metavar='kwargs', help='kwargs in k1=v1,k2=v2 format')
parser.add_argument('--strat_param', required=False, default=dict(ml_serving=False),
action=args_parse_other.StoreDictKeyPair, metavar='kwargs', help='kwargs in k1=v1,k2=v2 format')
parser.add_argument('--ml_log', required=False, default=False, type=args_parse_other.str2bool, const=True, nargs='?',
help='To save ML log or not')
parser.add_argument('--mode', required=False, default='backtest',
help='Live or Backtest')
parser.add_argument('--broker_token', required=False, default=oanda_cred.token_practice,
help='Oanda Broker Token id')
parser.add_argument('--broker_account', required=False, default=oanda_cred.acc_id_practice,
help='Oanda Broker Account id')
parser.add_argument('--plot', required=False, default=False, type=args_parse_other.str2bool, const=True, nargs='?',
help='Plot the results')
return parser.parse_args(pargs)
if __name__ == '__main__':
run()