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bktest_rbreaker.py
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bktest_rbreaker.py
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import sys
import misc
import agent
import data_handler as dh
import pandas as pd
import numpy as np
import strategy as strat
import datetime
import backtest
def r_breaker( asset, start_date, end_date, scenarios, freqs, config):
nearby = config['nearby']
rollrule = config['rollrule']
start_d = misc.day_shift(start_date, '-1b')
file_prefix = config['file_prefix'] + '_' + asset + '_'
ddf = misc.nearby(asset, nearby, start_date, end_date, rollrule, 'd', need_shift=True)
mdf = misc.nearby(asset, nearby, start_date, end_date, rollrule, 'm', need_shift=True)
mdf = backtest.cleanup_mindata(mdf, asset)
#ddf = dh.conv_ohlc_freq(mdf, 'D')
output = {}
for ix, freq in enumerate(freqs):
if freq !='1min':
df = dh.conv_ohlc_freq(mdf, freq)
else:
df = mdf
for iy, k in enumerate(scenarios):
idx = ix*10+iy
config['k'] = k
(res, closed_trades, ts) = r_breaker_sim( ddf, df, config)
output[idx] = res
print 'saving results for scen = %s' % str(idx)
all_trades = {}
for i, tradepos in enumerate(closed_trades):
all_trades[i] = strat.tradepos2dict(tradepos)
fname = file_prefix + str(idx) + '_trades.csv'
trades = pd.DataFrame.from_dict(all_trades).T
trades.to_csv(fname)
fname = file_prefix + str(idx) + '_dailydata.csv'
ts.to_csv(fname)
fname = file_prefix + 'stats.csv'
res = pd.DataFrame.from_dict(output)
res.to_csv(fname)
return
def r_breaker_sim( ddf, mdf, config):
marginrate = config['marginrate']
offset = config['offset']
k = config['k']
a = k[0]
b = k[1]
c = k[2]
start_equity = config['capital']
tcost = config['trans_cost']
unit = config['unit']
close_daily = config['close_daily']
ddf['range'] = (ddf.high - ddf.low).shift(1)
ddf['ssetup'] = (ddf.high+a*(ddf.close - ddf.low)).shift(1)
ddf['bsetup'] = (ddf.low-a*(ddf.high - ddf.close)).shift(1)
ddf['senter'] = ((1+b)*(ddf.high+ddf.close)/2.0 - b * ddf.low).shift(1)
ddf['benter'] = ((1+b)*(ddf.low+ddf.close)/2.0 - b * ddf.high).shift(1)
ddf['bbreak'] = ddf.ssetup + c * (ddf.ssetup - ddf.bsetup)
ddf['sbreak'] = ddf.bsetup - c * (ddf.ssetup - ddf.bsetup)
ll = mdf.shape[0]
mdf['pos'] = pd.Series([0]*ll, index = mdf.index)
mdf['cost'] = pd.Series([0]*ll, index = mdf.index)
curr_pos = []
closed_trades = []
start_d = ddf.index[0]
end_d = mdf.index[-1].date()
prev_d = start_d - datetime.timedelta(days=1)
tradeid = 0
cur_high = 0
cur_low = 0
for dd in mdf.index:
mslice = mdf.ix[dd]
min_id = agent.get_min_id(dd)
d = dd.date()
dslice = ddf.ix[d]
if np.isnan(dslice.bbreak):
continue
if (prev_d < d):
num_trades = 0
cur_high = mslice.high
cur_low = mslice.low
else:
cur_high = max([cur_high, mslice.high])
cur_low = min([cur_low, mslice.low])
prev_d = d
if len(curr_pos) == 0:
pos = 0
else:
pos = curr_pos[0].pos
mdf.ix[dd, 'pos'] = pos
if (min_id >= config['exit_min']):
if (pos != 0) and (close_daily or (d == end_d)):
curr_pos[0].close(mslice.close - misc.sign(pos) * offset , dd)
tradeid += 1
curr_pos[0].exit_tradeid = tradeid
closed_trades.append(curr_pos[0])
curr_pos = []
mdf.ix[dd, 'cost'] -= abs(pos) * (offset + mslice.close*tcost)
pos = 0
elif (min_id <= config['start_min']):
continue
else:
if num_trades >=2:
continue
if ((cur_high < dslice.bbreak) and (cur_high >= dslice.ssetup) and (mslice.close < dslice.senter) and (pos >=0)) or \
((cur_low > dslice.sbreak) and (cur_low <= dslice.bsetup) and (mslice.close > dslice.benter) and (pos <=0)):
if len(curr_pos) > 0:
curr_pos[0].close(mslice.close-misc.sign(pos)*offset, dd)
tradeid += 1
curr_pos[0].exit_tradeid = tradeid
closed_trades.append(curr_pos[0])
curr_pos = []
mdf.ix[dd, 'cost'] -= abs(pos) * (offset + mslice.close*tcost)
new_pos = strat.TradePos([mslice.contract], [1], -unit*misc.sign(pos), mslice.close, 0)
tradeid += 1
new_pos.entry_tradeid = tradeid
new_pos.open(mslice.close + offset*misc.sign(pos), dd)
curr_pos.append(new_pos)
pos = -unit*misc.sign(pos)
mdf.ix[dd, 'cost'] -= abs(pos) * (offset + mslice.close*tcost)
num_trades += 1
elif ((mslice.close >= dslice.bbreak) or (mslice.close <= dslice.sbreak)) and (pos == 0):
if (mslice.close >= dslice.bbreak):
direction = 1
else:
direction = -1
new_pos = strat.TradePos([mslice.contract], [1], unit*direction, mslice.close, 0)
tradeid += 1
new_pos.entry_tradeid = tradeid
new_pos.open(mslice.close + offset*misc.sign(direction), dd)
curr_pos.append(new_pos)
pos = unit*direction
mdf.ix[dd, 'cost'] -= abs(direction) * (offset + mslice.close*tcost)
num_trades += 1
mdf.ix[dd, 'pos'] = pos
(res_pnl, ts) = backtest.get_pnl_stats( mdf, start_equity, marginrate, 'm')
res_trade = backtest.get_trade_stats( closed_trades )
res = dict( res_pnl.items() + res_trade.items())
return (res, closed_trades, ts)
def run_sim(start_date, end_date, daily_close = True):
commod_list1 = ['m','y','l','ru','rb','p','cu','al','v','a','au','zn','ag','i','j','jm'] #
start_dates1 = [datetime.date(2010,10,1)] * 12 + \
[datetime.date(2012,7,1), datetime.date(2013,11,26), datetime.date(2011,6,1),datetime.date(2013,5,1)]
commod_list2 = ['ME', 'CF', 'TA', 'PM', 'RM', 'SR', 'FG', 'OI', 'RI', 'TC', 'WH', 'IF']
start_dates2 = [datetime.date(2012, 2,1)] + [ datetime.date(2012, 6, 1)] * 2 + [datetime.date(2012, 10, 1)] + \
[datetime.date(2013, 2, 1)] * 3 + [datetime.date(2013,6,1)] * 2 + \
[datetime.date(2013, 10, 1), datetime.date(2014,2,1), datetime.date(2010,6,1)]
commod_list = commod_list1 + commod_list2
start_dates = start_dates1 + start_dates2
#sim_list = ['m', 'y', 'l', 'ru', 'rb', 'TA', 'SR', 'CF','ME', 'RM', 'ag', 'au', 'cu', 'al', 'zn']
sim_list = [ 'rb','ru','TA','SR','CF','ag','au','cu','i','al','j','zn', 'a', 'jd']
sdate_list = []
for c, d in zip(commod_list, start_dates):
if c in sim_list:
sdate_list.append(d)
test_folder = backtest.get_bktest_folder()
file_prefix = test_folder + 'RBreaker_'
if daily_close:
file_prefix = file_prefix + 'daily_'
config = {'capital': 10000,
'offset': 0,
'trans_cost': 0.0,
'close_daily': daily_close,
'unit': 1,
'min_rng': 0.015,
'file_prefix': file_prefix}
scenarios = [(0.25, 0.05, 0.15), (0.30, 0.06, 0.20), (0.35, 0.08, 0.25), (0.4, 0.1, 0.3)]
freqs = ['1min', '3min', '5min']
for asset, sdate in zip(sim_list, sdate_list):
config['marginrate'] = ( backtest.sim_margin_dict[asset], backtest.sim_margin_dict[asset])
config['rollrule'] = '-50b'
config['nearby'] = 1
config['start_min'] = 1505
config['exit_min'] = 2055
if asset in ['cu', 'al', 'zn']:
config['nearby'] = 3
config['rollrule'] = '-1b'
elif asset in ['IF']:
config['start_min'] = 1520
config['exit_min'] = 2110
config['rollrule'] = '-1b'
r_breaker( asset, max(sdate, start_date), end_date, scenarios, freqs, config)
return
if __name__=="__main__":
args = sys.argv[1:]
if len(args) < 3:
d_close = True
else:
d_close = (int(args[2])>0)
if len(args) < 2:
end_d = datetime.date(2015,1,23)
else:
end_d = datetime.datetime.strptime(args[1], '%Y%m%d').date()
if len(args) < 1:
start_d = datetime.date(2013,1,2)
else:
start_d = datetime.datetime.strptime(args[0], '%Y%m%d').date()
run_sim(start_d, end_d, d_close)
pass