record_with_id['aggregate_returns'] = backtest_statistics['aggregate_returns'].tolist()
record_with_id['returns'] = backtest_statistics['transaction_adjusted_returns'].tolist()
record_with_id['statistics'] = backtest_statistics['statistics']
return record
# Generate backtests.
for er_idx in range(len(ers)):
print('er_idx = {0}'.format(er_idx))
er = ers[er_idx]
for mv_idx in range(len(mv_weights)):
print('mv_idx = {0}'.format(mv_idx))
w = mv_weights[mv_idx]
mvu, mvw = rkw_rolling_backtest(gen_mvportfolio(w), er)
mvstats = rkw_statistics(mvu, mvw)
record = dict()
record['id'] = '20160910_er_{0}_mv_{1}'.format(er_idx, mv_idx)
record['er_idx'] = er_idx
record['mv_idx'] = mv_idx
record['portfolio_name'] = 'mean-variance'
record = write_backtest_results_record(
record, mvu, mvw, mvstats)
db.insert(record)
for eta_idx in range(len(etas)):
# print 'eta_idx = {0}'.format(eta_idx)
w = msv_parameters[er_idx][mv_idx][eta_idx]['weight']
eta = msv_parameters[er_idx][mv_idx][eta_idx]['eta']
error = msv_parameters[er_idx][mv_idx][eta_idx]['error']
msvu, msvw = rkw_rolling_backtest(gen_msvportfolio(w, 1.0, eta), er)
results = bt[1]
experiment = db.load_experiment(experiment_id)
backtest_params = db.load_backtests([backtest_id])
returns = db.load_returns(experiment)
excess_returns = returns.values
train, test = backtest.split_returns(
excess_returns,
backtest_params['update_periods'],
backtest_params['trailing_periods'])
portfolios = pg.decimallistseries2nparray(results.portfolio_weights)
portfolio_returns = pg.decimallistseries2nparray(results.test_returns)
train_mean = ps.mean(portfolios[0,:], train[0])
train_variance = ps.variance(portfolios[0,:], train[0])
eta = results.eta.iloc[0]
backtest_statistics = ps.rkw_statistics(
portfolios, portfolio_returns, eta=eta)
test_statistics = backtest_statistics['statistics']
agg_returns = backtest_statistics['aggregate_returns']
output = test_statistics
output['aggregate_returns'] = pg.array2pgarray(agg_returns)
output['train_mean_return'] = train_mean
output['train_variance'] = train_variance
output['parameters_id'] = parameters_id
output['experiment_id'] = experiment_id
output['backtest_id'] = backtest_id
outputs.append(output)
output_table = pd.DataFrame(outputs)
output_table.to_csv('dcc_backtest_statistics.csv', index=False)