Update summary-metrics output
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@ -157,22 +157,25 @@ A backtesting result will look like that:
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| ADA/BTC | 1 | 0.89 | 0.89 | 0.00004434 | 0.44 | 6:00:00 | 1 | 0 | 0 |
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| LTC/BTC | 1 | 0.68 | 0.68 | 0.00003421 | 0.34 | 2:00:00 | 1 | 0 | 0 |
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| TOTAL | 2 | 0.78 | 1.57 | 0.00007855 | 0.78 | 4:00:00 | 2 | 0 | 0 |
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============ SUMMARY METRICS =============
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=============== SUMMARY METRICS ===============
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| Metric | Value |
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|------------------+---------------------|
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|-----------------------+---------------------|
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| Backtesting from | 2019-01-01 00:00:00 |
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| Backtesting to | 2019-05-01 00:00:00 |
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| Total trades | 429 |
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| First trade | 2019-01-01 18:30:00 |
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| First trade Pair | EOS/USDT |
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| Backtesting from | 2019-01-01 00:00:00 |
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| Backtesting to | 2019-05-01 00:00:00 |
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| Trades per day | 3.575 |
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| Best day | 25.27% |
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| Worst day | -30.67% |
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| Avg. Duration Winners | 4:23:00 |
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| Avg. Duration Loser | 6:55:00 |
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| | |
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| Max Drawdown | 50.63% |
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| Drawdown Start | 2019-02-15 14:10:00 |
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| Drawdown End | 2019-04-11 18:15:00 |
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| Market change | -5.88% |
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==========================================
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===============================================
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```
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### Backtesting report table
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@ -227,12 +230,11 @@ It contains some useful key metrics about performance of your strategy on backte
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=============== SUMMARY METRICS ===============
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| Metric | Value |
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|-----------------------+---------------------|
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| Backtesting from | 2019-01-01 00:00:00 |
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| Backtesting to | 2019-05-01 00:00:00 |
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| Total trades | 429 |
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| First trade | 2019-01-01 18:30:00 |
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| First trade Pair | EOS/USDT |
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| Backtesting from | 2019-01-01 00:00:00 |
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| Backtesting to | 2019-05-01 00:00:00 |
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| Trades per day | 3.575 |
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| Best day | 25.27% |
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| Worst day | -30.67% |
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@ -367,11 +367,11 @@ def text_table_add_metrics(strat_results: Dict) -> str:
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if len(strat_results['trades']) > 0:
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min_trade = min(strat_results['trades'], key=lambda x: x['open_date'])
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metrics = [
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('Backtesting from', strat_results['backtest_start'].strftime(DATETIME_PRINT_FORMAT)),
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('Backtesting to', strat_results['backtest_end'].strftime(DATETIME_PRINT_FORMAT)),
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('Total trades', strat_results['total_trades']),
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('First trade', min_trade['open_date'].strftime(DATETIME_PRINT_FORMAT)),
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('First trade Pair', min_trade['pair']),
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('Backtesting from', strat_results['backtest_start'].strftime(DATETIME_PRINT_FORMAT)),
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('Backtesting to', strat_results['backtest_end'].strftime(DATETIME_PRINT_FORMAT)),
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('Trades per day', strat_results['trades_per_day']),
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('Best day', f"{round(strat_results['backtest_best_day'] * 100, 2)}%"),
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('Worst day', f"{round(strat_results['backtest_worst_day'] * 100, 2)}%"),
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