def get_performance_list(self, average_position_signal_array_norm):
# average_position_signal_array_norm = self.get_average_position_signal_array(self.position_signal_array_list)
indi_obj = Indicator(self, average_position_signal_array_norm)
ret = indi_obj.get_total_return()
mean_tvr = indi_obj.get_mean_turnover()
dd, dd_start, dd_end = indi_obj.get_max_drawdown()
sharp = indi_obj.get_sharp()
ret2dd = indi_obj.get_return_divide_dd()
mg_bp = indi_obj.get_margin_bp()
indi_list = [
'average', self.window_period, self.std_num, self.start_time[:-4],
self.end_time[:-4], ret, mean_tvr, sharp, ret2dd, dd, dd_start,
dd_end, mg_bp
]
return indi_list
def roll_test(self, ):
self.set_directory(self.start_time, self.end_time, self.strategy_name)
[
self.price_focused_list, self.volume_focused,
self.instrument_focused, self.datetime_focused
] = self.get_focused_info()
results_single_return_bp = np.zeros(
(len(self.window_period_list), len(self.std_num_list)))
results_return2dd = np.zeros(
(len(self.window_period_list), len(self.std_num_list)))
results_turnover = np.zeros(
(len(self.window_period_list), len(self.std_num_list)))
for i in range(len(self.window_period_list)):
for j in range(len(self.std_num_list)):
self.window_period = self.window_period_list[i]
self.std_num = self.std_num_list[j]
position_signal_focused = self.generate_position_signal()
if hasattr(self, 'loss_threshold'):
position_signal_focused = self.stop_loss_win(
position_signal_focused)
self.position_signal_array = self.map_signal_focused_to_array(
position_signal_focused)
self.position_signal_array_list.append(
self.position_signal_array)
indi_obj = Indicator(self, self.position_signal_array)
self.buysell_signal_array = indi_obj.get_buysell_signal()
# self.compound_return_array = indi_obj.get_compound_return()
self.single_return_array = indi_obj.get_single_return()
self.buysell_info = self.get_buysell_info()
seq = [
self.coinType1 + '-' + self.coinType2,
self.two_contract[0], self.two_contract[1],
self.strategy_name,
str(self.window_period),
str(self.std_num)
]
self.write_buysell_info_to_file(self.buysell_dir, seq,
self.buysell_info)
seq.append('day-return')
ret_unitTime_list, endtime_list = indi_obj.get_return_for_unitTime(
)
ret_unit_df = pd.DataFrame({
'endtime': endtime_list,
'return': ret_unitTime_list
})
self.write_buysell_info_to_file(self.buysell_dir, seq,
ret_unit_df)
del seq[-1]
ret = indi_obj.get_total_return()
mean_tvr = indi_obj.get_mean_turnover()
dd, dd_start, dd_end = indi_obj.get_max_drawdown()
sharp = indi_obj.get_sharp()
ret2dd = indi_obj.get_return_divide_dd()
mg_bp = indi_obj.get_margin_bp()
results_return2dd[i][j] = ret2dd
results_turnover[i][j] = mean_tvr
results_single_return_bp[i][j] = mg_bp
indi_list = [
self.coinType1 + '-' + self.coinType2, self.window_period,
self.std_num, self.start_time[:-4], self.end_time[:-4],
ret, mean_tvr, sharp, ret2dd, dd, dd_start, dd_end, mg_bp
]
self.indi_list_list.append(indi_list)
seq = [
self.coinType1 + '-' + self.coinType2, self.two_contract[0],
self.two_contract[1], self.strategy_name
]
results_list = [
results_single_return_bp, results_return2dd, results_turnover
]
self.results_tag_list = ['mg-bp', 'ret2dd', 'turnover']
self.get_average_result_list(self.results_tag_list)
for i in range(len(results_list)):
# record the data results for each coin type, it's used for calculating the average results
self.average_result_list[i].append(results_list[i])
seq.append(self.results_tag_list[i])
self.write_result_to_file(self.result_dir, seq, results_list[i],
self.window_period_list,
self.std_num_list)
del seq[-1]