# short when test short_res > roll.mean+sd_coef*roll.sd
elif self.short_roll.test_sigma(short_res, self.sd_coef):
# only short when position is 0 or 1
if pos >= 0:
self.short_y(y_qty=1)
self.last_short_res = short_res
else:
pass
# update rolling
self.long_roll.add(long_res)
self.short_roll.add(short_res)
pair = ['a1505', 'a1509']
date_list = get_trade_day(pair)
algo = {'class': TestAlgo}
algo['param'] = {
'x': pair[0],
'y': pair[1],
'a': 1,
'b': 0,
'rolling': 4000,
'sd_coef': 3,
'block': 100,
'stop_win': 200,
}
settings = {
'date': date_list,
'path': DATA_PATH,
'tickset': 'top',
# short when test short_res > roll.mean+sd_coef*roll.sd
elif self.short_roll.test_sigma(short_res, self.sd_coef):
# only short when position is 0 or 1
if pos >= 0:
self.short_y(y_qty=1)
else:
pass
# update rolling
self.long_roll.add(long_res)
self.short_roll.add(short_res)
pair = ['a1505', 'a1509']
sd_coef = np.arange(2.0, 6.1, 0.5)
rolling = np.arange(1000, 9000, 1000)
Date_list = get_trade_day(pair)
pars = list(itertools.product(rolling, sd_coef))
def run_simulation(p,runner):
runner.run(algo_param={'alpha': p[0], 'stop_win': p[1]})
account = runner.account
orders = account.orders.to_dataframe()
history = account.history.to_dataframe(account.items)
return float(history.pnl.tail(1)), len(orders)
def best_param(date_list):
score = []
num_trades = []
algo = { 'class': TestAlgo }
algo['param'] = {'x': pair[0],
'y': pair[1],