Add short/long metrics to backtest result
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Matthias
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@ -371,9 +371,9 @@ The last element of the backtest report is the summary metrics table.
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It contains some useful key metrics about performance of your strategy on backtesting data.
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```
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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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| Max open trades | 3 |
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@ -386,6 +386,12 @@ It contains some useful key metrics about performance of your strategy on backte
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| Avg. stake amount | 0.001 BTC |
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| Total trade volume | 0.429 BTC |
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| | |
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| Long / Short | 352 / 77 |
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| Total profit Long % | 1250.58% |
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| Total profit Short % | -15.02% |
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| Absolute profit Long | 0.00838792 BTC |
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| Absolute profit Short | -0.00076 BTC |
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| | |
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| Best Pair | LSK/BTC 26.26% |
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| Worst Pair | ZEC/BTC -10.18% |
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| Best Trade | LSK/BTC 4.25% |
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@ -406,7 +412,7 @@ It contains some useful key metrics about performance of your strategy on backte
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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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@ -430,6 +436,9 @@ It contains some useful key metrics about performance of your strategy on backte
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- `Drawdown high` / `Drawdown low`: Profit at the beginning and end of the largest drawdown period. A negative low value means initial capital lost.
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- `Drawdown Start` / `Drawdown End`: Start and end datetime for this largest drawdown (can also be visualized via the `plot-dataframe` sub-command).
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- `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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- `Long / Short`: Split long/short values (Only shown when short trades were made).
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- `Total profit Long %` / `Absolute profit Long`: Profit long trades only (Only shown when short trades were made).
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- `Total profit Short %` / `Absolute profit Short`: Profit short trades only (Only shown when short trades were made).
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### Daily / Weekly / Monthly breakdown
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@ -415,20 +415,20 @@ def generate_strategy_stats(btdata: Dict[str, DataFrame],
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return {}
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config = content['config']
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max_open_trades = min(config['max_open_trades'], len(btdata.keys()))
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starting_balance = config['dry_run_wallet']
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start_balance = config['dry_run_wallet']
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stake_currency = config['stake_currency']
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pair_results = generate_pair_metrics(btdata, stake_currency=stake_currency,
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starting_balance=starting_balance,
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starting_balance=start_balance,
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results=results, skip_nan=False)
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buy_tag_results = generate_tag_metrics("buy_tag", starting_balance=starting_balance,
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buy_tag_results = generate_tag_metrics("buy_tag", starting_balance=start_balance,
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results=results, skip_nan=False)
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sell_reason_stats = generate_sell_reason_stats(max_open_trades=max_open_trades,
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results=results)
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left_open_results = generate_pair_metrics(btdata, stake_currency=stake_currency,
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starting_balance=starting_balance,
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starting_balance=start_balance,
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results=results.loc[results['is_open']],
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skip_nan=True)
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daily_stats = generate_daily_stats(results)
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@ -460,8 +460,12 @@ def generate_strategy_stats(btdata: Dict[str, DataFrame],
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'avg_stake_amount': results['stake_amount'].mean() if len(results) > 0 else 0,
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'profit_mean': results['profit_ratio'].mean() if len(results) > 0 else 0,
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'profit_median': results['profit_ratio'].median() if len(results) > 0 else 0,
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'profit_total': results['profit_abs'].sum() / starting_balance,
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'profit_total': results['profit_abs'].sum() / start_balance,
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'profit_total_long': results.loc[~results['is_short'], 'profit_abs'].sum() / start_balance,
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'profit_total_short': results.loc[results['is_short'], 'profit_abs'].sum() / start_balance,
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'profit_total_abs': results['profit_abs'].sum(),
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'profit_total_long_abs': results.loc[~results['is_short'], 'profit_abs'].sum(),
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'profit_total_short_abs': results.loc[results['is_short'], 'profit_abs'].sum(),
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'backtest_start': min_date.strftime(DATETIME_PRINT_FORMAT),
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'backtest_start_ts': int(min_date.timestamp() * 1000),
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'backtest_end': max_date.strftime(DATETIME_PRINT_FORMAT),
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@ -477,8 +481,8 @@ def generate_strategy_stats(btdata: Dict[str, DataFrame],
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'stake_amount': config['stake_amount'],
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'stake_currency': config['stake_currency'],
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'stake_currency_decimals': decimals_per_coin(config['stake_currency']),
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'starting_balance': starting_balance,
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'dry_run_wallet': starting_balance,
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'starting_balance': start_balance,
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'dry_run_wallet': start_balance,
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'final_balance': content['final_balance'],
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'rejected_signals': content['rejected_signals'],
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'max_open_trades': max_open_trades,
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@ -522,7 +526,7 @@ def generate_strategy_stats(btdata: Dict[str, DataFrame],
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'max_drawdown_high': high_val,
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})
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csum_min, csum_max = calculate_csum(results, starting_balance)
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csum_min, csum_max = calculate_csum(results, start_balance)
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strat_stats.update({
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'csum_min': csum_min,
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'csum_max': csum_max
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@ -711,6 +715,19 @@ def text_table_add_metrics(strat_results: Dict) -> str:
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best_trade = max(strat_results['trades'], key=lambda x: x['profit_ratio'])
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worst_trade = min(strat_results['trades'], key=lambda x: x['profit_ratio'])
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short_metrics = [
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('', ''), # Empty line to improve readability
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('Long / Short',
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f"{strat_results.get('trade_count_long', 'total_trades')} / "
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f"{strat_results.get('trade_count_short', 0)}"),
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('Total profit Long %', f"{strat_results['profit_total_long']:.2%}"),
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('Total profit Short %', f"{strat_results['profit_total_short']:.2%}"),
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('Absolute profit Long', round_coin_value(strat_results['profit_total_long_abs'],
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strat_results['stake_currency'])),
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('Absolute profit Short', round_coin_value(strat_results['profit_total_short_abs'],
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strat_results['stake_currency'])),
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] if strat_results.get('trade_count_short', 0) > 0 else []
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# Newly added fields should be ignored if they are missing in strat_results. hyperopt-show
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# command stores these results and newer version of freqtrade must be able to handle old
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# results with missing new fields.
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@ -721,9 +738,7 @@ def text_table_add_metrics(strat_results: Dict) -> str:
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('', ''), # Empty line to improve readability
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('Total/Daily Avg Trades',
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f"{strat_results['total_trades']} / {strat_results['trades_per_day']}"),
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('Long / Short',
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f"{strat_results.get('trade_count_long', 'total_trades')} / "
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f"{strat_results.get('trade_count_short', 0)}"),
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('Starting balance', round_coin_value(strat_results['starting_balance'],
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strat_results['stake_currency'])),
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('Final balance', round_coin_value(strat_results['final_balance'],
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@ -738,6 +753,7 @@ def text_table_add_metrics(strat_results: Dict) -> str:
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strat_results['stake_currency'])),
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('Total trade volume', round_coin_value(strat_results['total_volume'],
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strat_results['stake_currency'])),
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*short_metrics,
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('', ''), # Empty line to improve readability
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('Best Pair', f"{strat_results['best_pair']['key']} "
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f"{strat_results['best_pair']['profit_sum']:.2%}"),
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