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Add best / worst pair to summary statistics

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This commit is contained in:
Matthias 2020-11-28 16:56:08 +01:00
parent 56529180eb
commit a00f852cf9
2 changed files with 17 additions and 10 deletions
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12
docs/backtesting.md
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@ -165,8 +165,8 @@ A backtesting result will look like that:
| Max open trades | 3 |
| | |
| Total trades | 429 |
| First trade | 2019-01-01 18:30:00 |
| First trade Pair | EOS/USDT |
| Best Pair | LSK/BTC - 26.26% |
| Worst Pair | ZEC/BTC - -10.18% |
| Total Profit % | 152.41% |
| Trades per day | 3.575 |
| Best day | 25.27% |
@ -238,8 +238,8 @@ It contains some useful key metrics about performance of your strategy on backte
| Max open trades | 3 |
| | |
| Total trades | 429 |
| First trade | 2019-01-01 18:30:00 |
| First trade Pair | EOS/USDT |
| Best Pair | LSK/BTC - 26.26% |
| Worst Pair | ZEC/BTC - -10.18% |
| Total Profit % | 152.41% |
| Trades per day | 3.575 |
| Best day | 25.27% |
@ -258,8 +258,8 @@ It contains some useful key metrics about performance of your strategy on backte
- `Backtesting from` / `Backtesting to`: Backtesting range (usually defined with the `--timerange` option).
- `Max open trades`: Setting of `max_open_trades` (or `--max-open-trades`) - to clearly see settings for this.
- `Total trades`: Identical to the total trades of the backtest output table.
- `First trade`: First trade entered.
- `First trade pair`: Which pair was part of the first trade.
- `Best Pair`: Which pair performed best, and it's corresponding `Cum Profit %`.
- `Worst pair`: Which pair performed worst and it's corresponding `Cum Profit %`.
- `Total Profit %`: Total profit per stake amount. Aligned to the TOTAL column of the first table.
- `Trades per day`: Total trades divided by the backtesting duration in days (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.

15
freqtrade/optimize/optimize_reports.py
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@ -256,13 +256,18 @@ def generate_backtest_stats(btdata: Dict[str, DataFrame],
results=results.loc[results['open_at_end']],
skip_nan=True)
daily_stats = generate_daily_stats(results)
best_pair = max([pair for pair in pair_results if pair['key'] != 'TOTAL'],
key=lambda x: x['profit_sum']) if len(pair_results) > 1 else None
worst_pair = min([pair for pair in pair_results if pair['key'] != 'TOTAL'],
key=lambda x: x['profit_sum']) if len(pair_results) > 1 else None
results['open_timestamp'] = results['open_date'].astype(int64) // 1e6
results['close_timestamp'] = results['close_date'].astype(int64) // 1e6
backtest_days = (max_date - min_date).days
strat_stats = {
'trades': results.to_dict(orient='records'),
'best_pair': best_pair,
'worst_pair': worst_pair,
'results_per_pair': pair_results,
'sell_reason_summary': sell_reason_stats,
'left_open_trades': left_open_results,
@ -395,17 +400,19 @@ def text_table_strategy(strategy_results, stake_currency: str) -> str:
def text_table_add_metrics(strat_results: Dict) -> str:
if len(strat_results['trades']) > 0:
min_trade = min(strat_results['trades'], key=lambda x: x['open_date'])
metrics = [
('Backtesting from', strat_results['backtest_start'].strftime(DATETIME_PRINT_FORMAT)),
('Backtesting to', strat_results['backtest_end'].strftime(DATETIME_PRINT_FORMAT)),
('Max open trades', strat_results['max_open_trades']),
('', ''), # Empty line to improve readability
('Total trades', strat_results['total_trades']),
('First trade', min_trade['open_date'].strftime(DATETIME_PRINT_FORMAT)),
('First trade Pair', min_trade['pair']),
('Total Profit %', f"{round(strat_results['profit_total'] * 100, 2)}%"),
('Trades per day', strat_results['trades_per_day']),
('', ''), # Empty line to improve readability
('Best Pair', f"{strat_results['best_pair']['key']} - "
f"{round(strat_results['best_pair']['profit_sum_pct'], 2)}%"),
('Worst Pair', f"{strat_results['worst_pair']['key']} - "
f"{round(strat_results['worst_pair']['profit_sum_pct'], 2)}%"),
('Best day', f"{round(strat_results['backtest_best_day'] * 100, 2)}%"),
('Worst day', f"{round(strat_results['backtest_worst_day'] * 100, 2)}%"),
('Days win/draw/lose', f"{strat_results['winning_days']} / "