Add avgduration for winners and losers

This commit is contained in:
Matthias 2020-07-03 19:58:02 +02:00
parent 8e0ff4bd86
commit 987188e41f
2 changed files with 31 additions and 18 deletions

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@ -224,23 +224,26 @@ The last element of the backtest report is the summary metrics table.
It contains some useful key metrics about your strategy. It contains some useful key metrics about your strategy.
``` ```
============ SUMMARY METRICS ============= =============== SUMMARY METRICS ===============
| Metric | Value | | Metric | Value |
|------------------+---------------------| |-----------------------+---------------------|
| Total trades | 429 |
| First trade | 2019-01-01 18:30:00 | | Total trades | 429 |
| First trade Pair | EOS/USDT | | First trade | 2019-01-01 18:30:00 |
| Backtesting from | 2019-01-01 00:00:00 | | First trade Pair | EOS/USDT |
| Backtesting to | 2019-05-01 00:00:00 | | Backtesting from | 2019-01-01 00:00:00 |
| Trades per day | 3.575 | | Backtesting to | 2019-05-01 00:00:00 |
| Best day | 25.27% | | Trades per day | 3.575 |
| Worst day | -30.67% | | Best day | 25.27% |
| | | | Worst day | -30.67% |
| Max Drawdown | 50.63% | | Avg. Duration Winners | 4:23:00 |
| Drawdown Start | 2019-02-15 14:10:00 | | Avg. Duration Loser | 6:55:00 |
| Drawdown End | 2019-04-11 18:15:00 | | | |
| Market change | -5.88% | | Max Drawdown | 50.63% |
========================================== | Drawdown Start | 2019-02-15 14:10:00 |
| Drawdown End | 2019-04-11 18:15:00 |
| Market change | -5.88% |
===============================================
``` ```
@ -250,6 +253,7 @@ It contains some useful key metrics about your strategy.
- `Backtesting from` / `Backtesting to`: Backtesting range (usually defined as `--timerange from-to`). - `Backtesting from` / `Backtesting to`: Backtesting range (usually defined as `--timerange from-to`).
- `Trades per day`: Total trades / Backtest duration (this will give you information about how many trades to expect from the strategy). - `Trades per day`: Total trades / Backtest duration (this will give you information about how many trades to expect from the strategy).
- `Best day` / `Worst day`: Best and worst day based on daily profit. - `Best day` / `Worst day`: Best and worst day based on daily profit.
- `Avg. Duration Winners` / `Avg. Duration Loser`: Average durations for winning and losing trades.
- `Max Drawdown`: Maximum drawown experienced. a value of 50% means that from highest to subsequent lowest point, a 50% drop was experiened). - `Max Drawdown`: Maximum drawown experienced. a value of 50% means that from highest to subsequent lowest point, a 50% drop was experiened).
- `Drawdown Start` / `Drawdown End`: From when to when was this large drawdown (can also be visualized via `plot-dataframe` subcommand). - `Drawdown Start` / `Drawdown End`: From when to when was this large drawdown (can also be visualized via `plot-dataframe` subcommand).
- `Market change`: Change of the market during the backtest period. Calculated as average of all pairs changes from the first to the last candle using the "close" column. - `Market change`: Change of the market during the backtest period. Calculated as average of all pairs changes from the first to the last candle using the "close" column.

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@ -218,12 +218,19 @@ def generate_daily_stats(results: DataFrame) -> Dict[str, Any]:
draw_days = sum(daily_profit == 0) draw_days = sum(daily_profit == 0)
losing_days = sum(daily_profit < 0) losing_days = sum(daily_profit < 0)
winning_trades = results.loc[results['profit_percent'] > 0]
losing_trades = results.loc[results['profit_percent'] < 0]
return { return {
'backtest_best_day': best, 'backtest_best_day': best,
'backtest_worst_day': worst, 'backtest_worst_day': worst,
'winning_days': winning_days, 'winning_days': winning_days,
'draw_days': draw_days, 'draw_days': draw_days,
'losing_days': losing_days, 'losing_days': losing_days,
'winner_holding_avg': (timedelta(minutes=round(winning_trades['trade_duration'].mean()))
if not winning_trades.empty else '0:00'),
'loser_holding_avg': (timedelta(minutes=round(losing_trades['trade_duration'].mean()))
if not losing_trades.empty else '0:00'),
} }
@ -390,6 +397,8 @@ def text_table_add_metrics(strat_results: Dict) -> str:
('Worst day', f"{round(strat_results['backtest_worst_day'] * 100, 2)}%"), ('Worst day', f"{round(strat_results['backtest_worst_day'] * 100, 2)}%"),
('Days win/draw/lose', f"{strat_results['winning_days']} / " ('Days win/draw/lose', f"{strat_results['winning_days']} / "
f"{strat_results['draw_days']} / {strat_results['losing_days']}"), f"{strat_results['draw_days']} / {strat_results['losing_days']}"),
('Avg. Duration Winners', f"{strat_results['winner_holding_avg']}"),
('Avg. Duration Loser', f"{strat_results['loser_holding_avg']}"),
('', ''), # Empty line to improve readability ('', ''), # Empty line to improve readability
('Max Drawdown', f"{round(strat_results['max_drawdown'] * 100, 2)}%"), ('Max Drawdown', f"{round(strat_results['max_drawdown'] * 100, 2)}%"),
('Drawdown Start', strat_results['drawdown_start'].strftime(DATETIME_PRINT_FORMAT)), ('Drawdown Start', strat_results['drawdown_start'].strftime(DATETIME_PRINT_FORMAT)),