def get_analysis(self):
headers = [
'Total trades %s' % jhstats.get_count(self.total_values_arr), 'Absolute', 'Relative',
'Profit trades %s' % jhstats.get_count(self.profit_values_arr), 'Absolute', 'Relative',
'Loss trades %s' % jhstats.get_count(self.loss_values_arr), 'Absolute', 'Relative'
]
table = [
[
'Total result', jhstats.get_absolute(self.total_values_arr), jhstats.get_relative(self.total_values_arr, self.balance_start),
'Total result', jhstats.get_absolute(self.profit_values_arr), jhstats.get_relative(self.profit_values_arr, self.balance_start),
'Total result', jhstats.get_absolute(self.loss_values_arr), jhstats.get_relative(self.loss_values_arr, self.balance_start)
],
[
'Max result', jhstats.get_max_absolute(self.total_values_arr), jhstats.get_max_relative(self.total_values_arr, self.balance_start),
'Max result', jhstats.get_max_absolute(self.profit_values_arr), jhstats.get_max_relative(self.profit_values_arr, self.balance_start),
'Max result', jhstats.get_max_absolute(self.loss_values_arr), jhstats.get_max_relative(self.loss_values_arr, self.balance_start)
],
[
'Min result', jhstats.get_min_absolute(self.total_values_arr), jhstats.get_min_relative(self.total_values_arr, self.balance_start),
'Min result', jhstats.get_min_absolute(self.profit_values_arr), jhstats.get_min_relative(self.profit_values_arr, self.balance_start),
'Min result', jhstats.get_min_absolute(self.loss_values_arr), jhstats.get_min_relative(self.loss_values_arr, self.balance_start)
],
[
'Mean', jhstats.get_mean_absolute(self.total_values_arr), jhstats.get_mean_relative(self.total_values_arr, self.balance_start),
'Mean', jhstats.get_mean_absolute(self.profit_values_arr), jhstats.get_mean_relative(self.profit_values_arr, self.balance_start),
'Mean', jhstats.get_mean_absolute(self.loss_values_arr), jhstats.get_mean_relative(self.loss_values_arr, self.balance_start)
],
[
'Median', jhstats.get_median_absolute(self.total_values_arr), jhstats.get_median_relative(self.total_values_arr, self.balance_start),
'Median', jhstats.get_median_absolute(self.profit_values_arr), jhstats.get_median_relative(self.profit_values_arr, self.balance_start),
'Median', jhstats.get_median_absolute(self.loss_values_arr), jhstats.get_median_relative(self.loss_values_arr, self.balance_start)
],
[
'Variance', jhstats.get_variance_absolute(self.total_values_arr), jhstats.get_variance_relative(self.total_values_arr, self.balance_start),
'Variance', jhstats.get_variance_absolute(self.profit_values_arr), jhstats.get_variance_relative(self.profit_values_arr, self.balance_start),
'Variance', jhstats.get_variance_absolute(self.loss_values_arr), jhstats.get_variance_relative(self.loss_values_arr, self.balance_start)
],
[
'Std Dev', jhstats.get_std_dev_absolute(self.total_values_arr), jhstats.get_std_dev_relative(self.total_values_arr, self.balance_start),
'Std Dev', jhstats.get_std_dev_absolute(self.profit_values_arr), jhstats.get_std_dev_relative(self.profit_values_arr, self.balance_start),
'Std Dev', jhstats.get_std_dev_absolute(self.loss_values_arr), jhstats.get_std_dev_relative(self.loss_values_arr, self.balance_start)
],
[
'Skewness', jhstats.get_skewness_absolute(self.total_values_arr), jhstats.get_skewness_relative(self.total_values_arr, self.balance_start),
'Skewness', jhstats.get_skewness_absolute(self.profit_values_arr), jhstats.get_skewness_relative(self.profit_values_arr, self.balance_start),
'Skewness', jhstats.get_skewness_absolute(self.loss_values_arr), jhstats.get_skewness_relative(self.loss_values_arr, self.balance_start)
],
[
'Kurtosis', jhstats.get_kurtosis_absolute(self.total_values_arr), jhstats.get_kurtosis_relative(self.total_values_arr, self.balance_start),
'Kurtosis', jhstats.get_kurtosis_absolute(self.profit_values_arr), jhstats.get_kurtosis_relative(self.profit_values_arr, self.balance_start),
'Kurtosis', jhstats.get_kurtosis_absolute(self.loss_values_arr), jhstats.get_kurtosis_relative(self.loss_values_arr, self.balance_start)
]
]
print tabulate(table, headers, tablefmt='grid', floatfmt='.4f')
headers = ['Description', 'Value']
table = [
['Bankruptcy date', self.get_bankruptcy_date()],
['Hitrate %', jhstats.get_hitrate(self.total_values_arr, self.profit_values_arr)],
['Profit Loss Ratio', jhstats.get_profit_loss_ratio(jhstats.get_mean_absolute(self.profit_values_arr), jhstats.get_mean_absolute(self.loss_values_arr))],
['Information Ratio', jhstats.get_information_ratio(self.total_values_arr, self.balance_start)],
['Sharpe Ratio', jhstats.get_sharpe_ratio(self.total_values_arr, self.balance_start, 1)],
['Value at Risk', jhstats.get_var(self.total_values_arr, self.balance_start)],
['Expected Value', jhstats.get_expected_value(jhstats.get_hitrate(self.total_values_arr, self.profit_values_arr), jhstats.get_mean_absolute(self.profit_values_arr), jhstats.get_mean_absolute(self.loss_values_arr))],
['Probability of Ruin (POR) (table of Lucas & LeBeau)', jhstats.get_por_lucas_and_lebeau(jhstats.get_hitrate(self.total_values_arr, self.profit_values_arr), jhstats.get_mean_absolute(self.profit_values_arr), jhstats.get_mean_absolute(self.loss_values_arr))],
['Total bars', self.get_bars_total()],
['Up bars', self.get_bar_up_count()],
['Down bars', self.get_bar_down_count()],
['In market bars', self.get_bars_in_market()],
['In market %', self.get_procent_in_market()],
['Result (buy & hold) absolute', self.get_result_buy_and_hold_value()],
['Result (buy & hold) relative', self.get_result_buy_and_hold_procent()]
]
print tabulate(table, headers, tablefmt='grid', floatfmt='.4f')
headers = ['Description', 'Value', 'Description', 'Value', 'Description', 'Value']
table = [
[
'Consecutive profit count', self.get_max_consecutive_profit_count(),
'Consecutive loss count', self.get_max_consecutive_loss_count(),
'Max bar drawdown absolute', self.get_max_bar_drawdown_absolute()
],
[
'Consecutive profit absolute', self.get_max_consecutive_profit_absolute(),
'Consecutive loss absolute', self.get_max_consecutive_loss_absolute(),
'Max position drawdown absolute', self.get_max_position_drawdown_absolute()
]
]
print tabulate(table, headers, tablefmt='grid', floatfmt='.4f')
def main():
# set time and date:
ts = int(time.time())
ts_start = ts - (60*60*24*365.25) # a year
ts_end = ts - (60*60*24*0) # current day
date_start = dt.fromtimestamp(ts_start).strftime('%Y-%m-%d')
date_end = dt.fromtimestamp(ts_end).strftime('%Y-%m-%d')
end_date_time = dt.fromtimestamp(ts_end).strftime('%Y%m%d %H:%M:%S UTC')
# set values:
balance_start = 10000
bankruptcy_at = 8000
multiplier = 200
transaction_costs = 2.9
slippage = 0
# get data:
data = Data()
data.set_contract_ib('EOE', 'IND', 'FTA', 'EUR', 200, '201510')
bars = data.get_data_ib(1, end_date_time, '1 Y', '1 day', 'TRADES', 0, 1)
# get best timeperiod:
best_result = -1000000
best_timeperiod = 0
result_arr = []
timeperiod_arr = []
for timeperiod in range(2, 200):
strat_exam = StrategyMy(
bars,
balance_start,
bankruptcy_at,
multiplier,
transaction_costs,
slippage,
timeperiod
)
strat_exam.run()
result = jhstats.get_absolute(strat_exam.total_values_arr)
# result = jhstats.get_mean_absolute(strat_exam.total_values_arr)
# result = jhstats.get_information_ratio(strat_exam.total_values_arr, strat_exam.balance_start)
# result = jhstats.get_hitrate(strat_exam.total_values_arr, strat_exam.profit_values_arr)
# result = jhstats.get_count(strat_exam.profit_values_arr)
if result > best_result:
best_result = result
best_timeperiod = timeperiod
result_arr.append(result)
timeperiod_arr.append(timeperiod)
print best_result
print best_timeperiod
# get analysis with best timeperiod:
timeperiod = best_timeperiod
strat_exam = StrategyMy(
bars,
balance_start,
bankruptcy_at,
multiplier,
transaction_costs,
slippage,
timeperiod
)
strat_exam.run()
print (('############################################################'))
print (('date start: %s' % date_start))
print (('date end: %s' % date_end))
print (('balance start: %s' % balance_start))
print (('bankruptcy at: %s' % bankruptcy_at))
print (('multiplier: %s' % multiplier))
print (('transaction costs: %s' % transaction_costs))
print (('slippage: %s' % slippage))
print (('best timeperiod: %s' % timeperiod))
print (('############################################################'))
# print (('\a'))
print (('Current time: %s' % end_date_time))
strat_exam.get_analysis()
# equity curve:
# jhgraph.get_equity_curve(strat_exam.bars_pd['datetime'], strat_exam.bars_pd['Close'], strat_exam.equity_curve_arr)
jhgraph.get_equity_curve2(strat_exam.bars_pd['datetime'], strat_exam.bars_pd['Close'], strat_exam.equity_curve_arr, strat_exam.open_equity_curve_arr)
# optimization curve:
jhgraph.get_optimization_curve(timeperiod_arr, result_arr)