mirror of
https://github.com/freqtrade/freqtrade.git
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Merge pull request #10485 from jainanuj94/feature/8902
Add exit signals to export in backtesting
This commit is contained in:
Matthias
GitHub
commit
611a3ce138
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@ -18,15 +18,13 @@ freqtrade backtesting -c <config.json> --timeframe <tf> --strategy <strategy_nam
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```
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This will tell freqtrade to output a pickled dictionary of strategy, pairs and corresponding
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DataFrame of the candles that resulted in buy signals. Depending on how many buys your strategy
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makes, this file may get quite large, so periodically check your `user_data/backtest_results`
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folder to delete old exports.
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DataFrame of the candles that resulted in entry and exit signals.
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Depending on how many entries your strategy makes, this file may get quite large, so periodically check your `user_data/backtest_results` folder to delete old exports.
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Before running your next backtest, make sure you either delete your old backtest results or run
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backtesting with the `--cache none` option to make sure no cached results are used.
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If all goes well, you should now see a `backtest-result-{timestamp}_signals.pkl` file in the
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`user_data/backtest_results` folder.
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If all goes well, you should now see a `backtest-result-{timestamp}_signals.pkl` and `backtest-result-{timestamp}_exited.pkl` files in the `user_data/backtest_results` folder.
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To analyze the entry/exit tags, we now need to use the `freqtrade backtesting-analysis` command
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with `--analysis-groups` option provided with space-separated arguments:
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@ -103,6 +101,10 @@ The indicators have to be present in your strategy's main DataFrame (either for
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timeframe or for informative timeframes) otherwise they will simply be ignored in the script
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output.
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!!! Note "Indicator List"
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The indicator values will be displayed for both entry and exit points. If `--indicator-list all` is specified,
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only the indicators at the entry point will be shown to avoid excessively large lists, which could occur depending on the strategy.
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There are a range of candle and trade-related fields that are included in the analysis so are
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automatically accessible by including them on the indicator-list, and these include:
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@ -118,6 +120,34 @@ automatically accessible by including them on the indicator-list, and these incl
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- **profit_ratio :** trade profit ratio
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- **profit_abs :** absolute profit return of the trade
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#### Sample Output for Indicator Values
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```bash
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freqtrade backtesting-analysis -c user_data/config.json --analysis-groups 0 --indicator-list chikou_span tenkan_sen
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```
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In this example,
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we aim to display the `chikou_span` and `tenkan_sen` indicator values at both the entry and exit points of trades.
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A sample output for indicators might look like this:
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| pair | open_date | enter_reason | exit_reason | chikou_span (entry) | tenkan_sen (entry) | chikou_span (exit) | tenkan_sen (exit) |
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|-----------|---------------------------|--------------|-------------|---------------------|--------------------|--------------------|-------------------|
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| DOGE/USDT | 2024-07-06 00:35:00+00:00 | | exit_signal | 0.105 | 0.106 | 0.105 | 0.107 |
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| BTC/USDT | 2024-08-05 14:20:00+00:00 | | roi | 54643.440 | 51696.400 | 54386.000 | 52072.010 |
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As shown in the table, `chikou_span (entry)` represents the indicator value at the time of trade entry,
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while `chikou_span (exit)` reflects its value at the time of exit.
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This detailed view of indicator values enhances the analysis.
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The `(entry)` and `(exit)` suffixes are added to indicators
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to distinguish the values at the entry and exit points of the trade.
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!!! Note "Trade-wide Indicators"
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Certain trade-wide indicators do not have the `(entry)` or `(exit)` suffix. These indicators include: `pair`, `stake_amount`,
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`max_stake_amount`, `amount`, `open_date`, `close_date`, `open_rate`, `close_rate`, `fee_open`, `fee_close`, `trade_duration`,
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`profit_ratio`, `profit_abs`, `exit_reason`,`initial_stop_loss_abs`, `initial_stop_loss_ratio`, `stop_loss_abs`, `stop_loss_ratio`,
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`min_rate`, `max_rate`, `is_open`, `enter_tag`, `leverage`, `is_short`, `open_timestamp`, `close_timestamp` and `orders`
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### Filtering the trade output by date
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@ -1,6 +1,6 @@
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import logging
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from pathlib import Path
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from typing import List
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from typing import Dict, List
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import joblib
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import pandas as pd
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@ -8,6 +8,7 @@ import pandas as pd
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from freqtrade.configuration import TimeRange
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from freqtrade.constants import Config
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from freqtrade.data.btanalysis import (
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BT_DATA_COLUMNS,
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get_latest_backtest_filename,
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load_backtest_data,
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load_backtest_stats,
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@ -47,9 +48,14 @@ def _load_signal_candles(backtest_dir: Path):
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return _load_backtest_analysis_data(backtest_dir, "signals")
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def _process_candles_and_indicators(pairlist, strategy_name, trades, signal_candles):
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analysed_trades_dict = {}
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analysed_trades_dict[strategy_name] = {}
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def _load_exit_signal_candles(backtest_dir: Path) -> Dict[str, Dict[str, pd.DataFrame]]:
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return _load_backtest_analysis_data(backtest_dir, "exited")
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def _process_candles_and_indicators(
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pairlist, strategy_name, trades, signal_candles, date_col: str = "open_date"
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):
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analysed_trades_dict: Dict[str, Dict] = {strategy_name: {}}
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try:
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logger.info(f"Processing {strategy_name} : {len(pairlist)} pairs")
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@ -57,7 +63,7 @@ def _process_candles_and_indicators(pairlist, strategy_name, trades, signal_cand
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for pair in pairlist:
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if pair in signal_candles[strategy_name]:
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analysed_trades_dict[strategy_name][pair] = _analyze_candles_and_indicators(
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pair, trades, signal_candles[strategy_name][pair]
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pair, trades, signal_candles[strategy_name][pair], date_col
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)
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except Exception as e:
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print(f"Cannot process entry/exit reasons for {strategy_name}: ", e)
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@ -65,7 +71,9 @@ def _process_candles_and_indicators(pairlist, strategy_name, trades, signal_cand
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return analysed_trades_dict
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def _analyze_candles_and_indicators(pair, trades: pd.DataFrame, signal_candles: pd.DataFrame):
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def _analyze_candles_and_indicators(
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pair: str, trades: pd.DataFrame, signal_candles: pd.DataFrame, date_col: str = "open_date"
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) -> pd.DataFrame:
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buyf = signal_candles
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if len(buyf) > 0:
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@ -75,8 +83,8 @@ def _analyze_candles_and_indicators(pair, trades: pd.DataFrame, signal_candles:
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trades_inds = pd.DataFrame()
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if trades_red.shape[0] > 0 and buyf.shape[0] > 0:
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for t, v in trades_red.open_date.items():
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allinds = buyf.loc[(buyf["date"] < v)]
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for t, v in trades_red.iterrows():
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allinds = buyf.loc[(buyf["date"] < v[date_col])]
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if allinds.shape[0] > 0:
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tmp_inds = allinds.iloc[[-1]]
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@ -235,7 +243,7 @@ def _select_rows_by_tags(df, enter_reason_list, exit_reason_list):
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def prepare_results(
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analysed_trades, stratname, enter_reason_list, exit_reason_list, timerange=None
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):
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) -> pd.DataFrame:
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res_df = pd.DataFrame()
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for pair, trades in analysed_trades[stratname].items():
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if trades.shape[0] > 0:
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@ -252,6 +260,7 @@ def prepare_results(
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def print_results(
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res_df: pd.DataFrame,
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exit_df: pd.DataFrame,
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analysis_groups: List[str],
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indicator_list: List[str],
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csv_path: Path,
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@ -278,9 +287,11 @@ def print_results(
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for ind in indicator_list:
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if ind in res_df:
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available_inds.append(ind)
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ilist = ["pair", "enter_reason", "exit_reason"] + available_inds
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merged_df = _merge_dfs(res_df, exit_df, available_inds)
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_print_table(
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res_df[ilist],
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merged_df,
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sortcols=["exit_reason"],
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show_index=False,
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name="Indicators:",
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@ -291,6 +302,22 @@ def print_results(
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print("\\No trades to show")
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def _merge_dfs(entry_df, exit_df, available_inds):
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merge_on = ["pair", "open_date"]
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signal_wide_indicators = list(set(available_inds) - set(BT_DATA_COLUMNS))
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columns_to_keep = merge_on + ["enter_reason", "exit_reason"] + available_inds
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if exit_df is None or exit_df.empty:
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return entry_df[columns_to_keep]
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return pd.merge(
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entry_df[columns_to_keep],
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exit_df[merge_on + signal_wide_indicators],
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on=merge_on,
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suffixes=(" (entry)", " (exit)"),
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)
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def _print_table(
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df: pd.DataFrame, sortcols=None, *, show_index=False, name=None, to_csv=False, csv_path: Path
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):
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@ -333,6 +360,7 @@ def process_entry_exit_reasons(config: Config):
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if trades is not None and not trades.empty:
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signal_candles = _load_signal_candles(config["exportfilename"])
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exit_signals = _load_exit_signal_candles(config["exportfilename"])
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rej_df = None
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if do_rejected:
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@ -345,20 +373,31 @@ def process_entry_exit_reasons(config: Config):
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timerange=timerange,
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)
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analysed_trades_dict = _process_candles_and_indicators(
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config["exchange"]["pair_whitelist"], strategy_name, trades, signal_candles
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)
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res_df = prepare_results(
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analysed_trades_dict,
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strategy_name,
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entry_df = _generate_dfs(
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config["exchange"]["pair_whitelist"],
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enter_reason_list,
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exit_reason_list,
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timerange=timerange,
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signal_candles,
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strategy_name,
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timerange,
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trades,
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"open_date",
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)
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exit_df = _generate_dfs(
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config["exchange"]["pair_whitelist"],
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enter_reason_list,
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exit_reason_list,
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exit_signals,
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strategy_name,
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timerange,
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trades,
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"close_date",
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)
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print_results(
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res_df,
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entry_df,
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exit_df,
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analysis_groups,
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indicator_list,
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rejected_signals=rej_df,
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@ -368,3 +407,30 @@ def process_entry_exit_reasons(config: Config):
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except ValueError as e:
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raise OperationalException(e) from e
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def _generate_dfs(
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pairlist: list,
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enter_reason_list: list,
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exit_reason_list: list,
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signal_candles: Dict,
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strategy_name: str,
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timerange: TimeRange,
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trades: pd.DataFrame,
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date_col: str,
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) -> pd.DataFrame:
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analysed_trades_dict = _process_candles_and_indicators(
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pairlist,
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strategy_name,
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trades,
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signal_candles,
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date_col,
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)
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res_df = prepare_results(
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analysed_trades_dict,
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strategy_name,
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enter_reason_list,
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exit_reason_list,
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timerange=timerange,
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)
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return res_df
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@ -122,6 +122,7 @@ class Backtesting:
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self.processed_dfs: Dict[str, Dict] = {}
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self.rejected_dict: Dict[str, List] = {}
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self.rejected_df: Dict[str, Dict] = {}
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self.exited_dfs: Dict[str, Dict] = {}
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self._exchange_name = self.config["exchange"]["name"]
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if not exchange:
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@ -1564,11 +1565,14 @@ class Backtesting:
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and self.dataprovider.runmode == RunMode.BACKTEST
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):
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self.processed_dfs[strategy_name] = generate_trade_signal_candles(
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preprocessed_tmp, results
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preprocessed_tmp, results, "open_date"
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)
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self.rejected_df[strategy_name] = generate_rejected_signals(
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preprocessed_tmp, self.rejected_dict
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)
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self.exited_dfs[strategy_name] = generate_trade_signal_candles(
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preprocessed_tmp, results, "close_date"
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)
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return min_date, max_date
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@ -1644,7 +1648,11 @@ class Backtesting:
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and self.dataprovider.runmode == RunMode.BACKTEST
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):
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store_backtest_analysis_results(
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self.config["exportfilename"], self.processed_dfs, self.rejected_df, dt_appendix
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self.config["exportfilename"],
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self.processed_dfs,
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self.rejected_df,
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self.exited_dfs,
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dt_appendix,
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)
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# Results may be mixed up now. Sort them so they follow --strategy-list order.
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@ -90,7 +90,12 @@ def _store_backtest_analysis_data(
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def store_backtest_analysis_results(
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recordfilename: Path, candles: Dict[str, Dict], trades: Dict[str, Dict], dtappendix: str
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recordfilename: Path,
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candles: Dict[str, Dict],
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trades: Dict[str, Dict],
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exited: Dict[str, Dict],
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dtappendix: str,
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) -> None:
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_store_backtest_analysis_data(recordfilename, candles, dtappendix, "signals")
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_store_backtest_analysis_data(recordfilename, trades, dtappendix, "rejected")
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_store_backtest_analysis_data(recordfilename, exited, dtappendix, "exited")
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@ -25,8 +25,8 @@ logger = logging.getLogger(__name__)
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def generate_trade_signal_candles(
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preprocessed_df: Dict[str, DataFrame], bt_results: Dict[str, Any]
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) -> DataFrame:
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preprocessed_df: Dict[str, DataFrame], bt_results: Dict[str, Any], date_col: str
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) -> Dict[str, DataFrame]:
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signal_candles_only = {}
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for pair in preprocessed_df.keys():
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signal_candles_only_df = DataFrame()
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@ -36,8 +36,8 @@ def generate_trade_signal_candles(
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pairresults = resdf.loc[(resdf["pair"] == pair)]
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if pairdf.shape[0] > 0:
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for t, v in pairresults.open_date.items():
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allinds = pairdf.loc[(pairdf["date"] < v)]
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for t, v in pairresults.iterrows():
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allinds = pairdf.loc[(pairdf["date"] < v[date_col])]
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signal_inds = allinds.iloc[[-1]]
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signal_candles_only_df = concat(
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[signal_candles_only_df.infer_objects(), signal_inds.infer_objects()]
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|
|
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@ -18,7 +18,9 @@ def entryexitanalysis_cleanup() -> None:
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Backtesting.cleanup()
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def test_backtest_analysis_nomock(default_conf, mocker, caplog, testdatadir, user_dir, capsys):
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def test_backtest_analysis_on_entry_and_rejected_signals_nomock(
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default_conf, mocker, caplog, testdatadir, user_dir, capsys
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):
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caplog.set_level(logging.INFO)
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(user_dir / "backtest_results").mkdir(parents=True, exist_ok=True)
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@ -158,6 +160,15 @@ def test_backtest_analysis_nomock(default_conf, mocker, caplog, testdatadir, use
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assert "34.049" in captured.out
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assert "0.104" in captured.out
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assert "52.829" in captured.out
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# assert indicator list
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assert "close (entry)" in captured.out
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assert "0.016" in captured.out
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assert "rsi (entry)" in captured.out
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assert "54.320" in captured.out
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assert "close (exit)" in captured.out
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assert "rsi (exit)" in captured.out
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assert "52.829" in captured.out
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assert "profit_abs" in captured.out
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# test group 1
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args = get_args(base_args + ["--analysis-groups", "1"])
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|
|
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@ -293,20 +293,25 @@ def test_store_backtest_candles(testdatadir, mocker):
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candle_dict = {"DefStrat": {"UNITTEST/BTC": pd.DataFrame()}}
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# mock directory exporting
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store_backtest_analysis_results(testdatadir, candle_dict, {}, "2022_01_01_15_05_13")
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store_backtest_analysis_results(testdatadir, candle_dict, {}, {}, "2022_01_01_15_05_13")
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assert dump_mock.call_count == 2
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assert dump_mock.call_count == 3
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assert isinstance(dump_mock.call_args_list[0][0][0], Path)
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assert str(dump_mock.call_args_list[0][0][0]).endswith("_signals.pkl")
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assert str(dump_mock.call_args_list[1][0][0]).endswith("_rejected.pkl")
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assert str(dump_mock.call_args_list[2][0][0]).endswith("_exited.pkl")
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dump_mock.reset_mock()
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# mock file exporting
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filename = Path(testdatadir / "testresult")
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store_backtest_analysis_results(filename, candle_dict, {}, "2022_01_01_15_05_13")
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assert dump_mock.call_count == 2
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store_backtest_analysis_results(filename, candle_dict, {}, {}, "2022_01_01_15_05_13")
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assert dump_mock.call_count == 3
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assert isinstance(dump_mock.call_args_list[0][0][0], Path)
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# result will be testdatadir / testresult-<timestamp>_signals.pkl
|
||||
assert str(dump_mock.call_args_list[0][0][0]).endswith("_signals.pkl")
|
||||
assert str(dump_mock.call_args_list[1][0][0]).endswith("_rejected.pkl")
|
||||
assert str(dump_mock.call_args_list[2][0][0]).endswith("_exited.pkl")
|
||||
|
||||
dump_mock.reset_mock()
|
||||
|
||||
|
||||
|
|
@ -315,7 +320,7 @@ def test_write_read_backtest_candles(tmp_path):
|
|||
|
||||
# test directory exporting
|
||||
sample_date = "2022_01_01_15_05_13"
|
||||
store_backtest_analysis_results(tmp_path, candle_dict, {}, sample_date)
|
||||
store_backtest_analysis_results(tmp_path, candle_dict, {}, {}, sample_date)
|
||||
stored_file = tmp_path / f"backtest-result-{sample_date}_signals.pkl"
|
||||
with stored_file.open("rb") as scp:
|
||||
pickled_signal_candles = joblib.load(scp)
|
||||
|
|
@ -330,7 +335,7 @@ def test_write_read_backtest_candles(tmp_path):
|
|||
|
||||
# test file exporting
|
||||
filename = tmp_path / "testresult"
|
||||
store_backtest_analysis_results(filename, candle_dict, {}, sample_date)
|
||||
store_backtest_analysis_results(filename, candle_dict, {}, {}, sample_date)
|
||||
stored_file = tmp_path / f"testresult-{sample_date}_signals.pkl"
|
||||
with stored_file.open("rb") as scp:
|
||||
pickled_signal_candles = joblib.load(scp)
|
||||
|
|
|
|||
Loading…
Reference in New Issue
Block a user