def run_simulation(param, date_list, product):
pnl_list = []
order_win_list = []
order_profit_list = []
num_rounds_list = []
master = MasterReport()
for date in date_list:
date_pair = get_best_pair(date, market, product)
if type(date_pair) != tuple:
continue
else:
result = back_test(date_pair, date, param)
pnl_list.append(result[0])
order_win_list.append(result[1])
order_profit_list.append(result[2])
num_rounds_list.append(result[3])
runner = result[4]
try:
report = Report(runner)
except IndexError:
print 'WTF? {} has IndexError'.format(date)
continue
report.print_report(to_file=False,
to_screen=False,
to_master=master)
return pnl_list, order_win_list, order_profit_list, num_rounds_list, master
def run_simulation(param, date_list):
total_pnl = 0
total_order = 0
for date in date_list:
date_pair = get_best_pair(date,'ic')
if type(date_pair) != tuple:
continue
else:
tpnl, torder = back_test(date_pair, date, param)
total_pnl += tpnl
total_order += torder
return total_pnl, total_order
def run_simulation(param, date_list):
total_pnl = 0
total_order = 0
for date in date_list:
date_pair = get_best_pair(date,'if')
if type(date_pair) != tuple:
continue
else:
tpnl, torder = back_test(date_pair, date, param)
total_pnl += tpnl
total_order += torder
return total_pnl, total_order
def run_simulation(param, date_list, product):
pnl_list = []
order_win_list = []
order_profit_list = []
num_rounds_list = []
master = MasterReport()
for date in date_list:
date_pair = get_best_pair(date,market, product)
if type(date_pair) != tuple:
continue
else:
result = back_test(date_pair, date, param)
pnl_list.append(result[0])
order_win_list.append(result[1])
order_profit_list.append(result[2])
num_rounds_list.append(result[3])
runner = result[4]
try:
report = Report(runner)
except IndexError:
print 'WTF? {} has IndexError'.format(date)
continue
report.print_report(to_file=False, to_screen=False, to_master=master)
return pnl_list, order_win_list, order_profit_list, num_rounds_list, master
print 'WTF? {} has IndexError'.format(date)
continue
report.print_report(to_file=False, to_screen=False, to_master=master)
return pnl_list, order_win_list, order_profit_list, num_rounds_list, master
date_list = [str(x).split(' ')[0] for x in pd.date_range('2015-01-01','2016-03-31').tolist()]
roll_list = np.concatenate((np.arange(200,500,100), np.arange(500, 3500, 500),[5000, 8000])) #11 params
sd_list = np.concatenate((np.arange(0, 2.1, 0.25),[3,4,5]))#11 params
spread_list = np.concatenate((np.arange(0, 2.1, 0.25),[3,4,5]))#11 params
pars = list(itertools.product(roll_list, sd_list, spread_list))
num_cores = 20
product = 'pb'
trade_day_list = []
for date in date_list:
date_pair = get_best_pair(date, market, product)
if type(date_pair) != tuple:
continue
else:
trade_day_list.append(date)
results = Parallel(n_jobs=num_cores)(delayed(run_simulation)(param,\
date_list, product) for param in pars)
keys = ['roll:{}_sd:{}_spreadcoef:{}'.format(*p) for p in pars]
pnl = [i[0] for i in results]
order_win = [i[1] for i in results]
order_profit = [i[2] for i in results]
num_rounds = [i[3] for i in results]
master = [i[4] for i in results]
pnl_dict = dict(zip(keys, pnl))
pnl_result = pd.DataFrame(pnl_dict)
date_list = [
str(x).split(' ')[0]
for x in pd.date_range('2015-01-01', '2016-03-31').tolist()
]
roll_list = np.concatenate(
(np.arange(200, 500, 100), np.arange(500, 3500, 500), [5000,
8000])) #11 params
sd_list = np.concatenate((np.arange(0, 2.1, 0.25), [3, 4, 5])) #11 params
spread_list = np.concatenate((np.arange(0, 2.1, 0.25), [3, 4, 5])) #11 params
pars = list(itertools.product(roll_list, sd_list, spread_list))
num_cores = 20
product = 'pb'
trade_day_list = []
for date in date_list:
date_pair = get_best_pair(date, market, product)
if type(date_pair) != tuple:
continue
else:
trade_day_list.append(date)
results = Parallel(n_jobs=num_cores)(delayed(run_simulation)(param,\
date_list, product) for param in pars)
keys = ['roll:{}_sd:{}_spreadcoef:{}'.format(*p) for p in pars]
pnl = [i[0] for i in results]
order_win = [i[1] for i in results]
order_profit = [i[2] for i in results]
num_rounds = [i[3] for i in results]
master = [i[4] for i in results]
pnl_dict = dict(zip(keys, pnl))
pnl_result = pd.DataFrame(pnl_dict)
}
settings = { 'date': date,
'path': DATA_PATH,
'tickset': 'top',
'algo': algo}
runner = PairRunner(settings)
runner.run()
account = runner.account
return account
date_list = [str(x).split(' ')[0] for x in pd.date_range('2015-05-01','2016-03-31').tolist()]
result = {}
account_history = {}
pnl = np.zeros(1)
for date in date_list:
date_pair = get_best_pair(date,'ic')
if type(date_pair) != tuple:
continue
else:
pair = date_pair
pre = pair
account = back_test(pair,date)
history = account.history.to_dataframe(account.items)
temp = np.asarray(history.pnl)
pnl = np.concatenate([pnl,pnl[-1] + temp])
account_history[date] = account
result[date] = temp[-1]
print 'final result'
print pnl[-1]
pickle.dump(pnl, open( "/work/rqiao/backtest_result/ic_pnl.p", "wb" ))
pickle.dump(result, open( "/work/rqiao/backtest_result/ic_result.p", "wb" ))