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Merge pull request #12126 from stash86/main-stash

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Improve lookahead analysis to use full dataframe comparison instead of just the last row
This commit is contained in:
Matthias
2025-08-20 06:45:13 +02:00
committed by GitHub
parent 765a0b52cb a531f8644d
commit 1f21d5e2c2
2 changed files with 32 additions and 32 deletions
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3
docs/lookahead-analysis.md
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@@ -50,8 +50,7 @@ After this initial backtest runs, it will look if the `minimum-trade-amount` is
If this happens, use a wider timerange to get more trades for the analysis, or use a timerange where more trades occur.
After setting the baseline it will then do additional backtest runs for every entry and exit separately.
When these verification backtests complete, it will compare the indicators at the signal candles (both entry or exit)
and report the bias.
When these verification backtests complete, it will compare both dataframes (baseline and sliced) for any difference in columns' value and report the bias.
After all signals have been verified or falsified a result table will be generated for the user to see.
### How to find and remove bias? How can I salvage a biased strategy?

23
freqtrade/optimize/analysis/lookahead.py
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@@ -70,17 +70,12 @@ class LookaheadAnalysis(BaseAnalysis):
cut_df: DataFrame = cut_vars.indicators[current_pair]
full_df: DataFrame = full_vars.indicators[current_pair]
# cut longer dataframe to length of the shorter
full_df_cut = full_df[(full_df.date == cut_vars.compared_dt)].reset_index(drop=True)
cut_df_cut = cut_df[(cut_df.date == cut_vars.compared_dt)].reset_index(drop=True)
# check if dataframes are not empty
if full_df_cut.shape[0] != 0 and cut_df_cut.shape[0] != 0:
# compare dataframes
compare_df = full_df_cut.compare(cut_df_cut)
# trim full_df to the same index and length as cut_df
cut_full_df = full_df.loc[cut_df.index]
compare_df = cut_full_df.compare(cut_df)
if compare_df.shape[0] > 0:
for col_name, values in compare_df.items():
for col_name in compare_df:
col_idx = compare_df.columns.get_loc(col_name)
compare_df_row = compare_df.iloc[0]
# compare_df now comprises tuples with [1] having either 'self' or 'other'
@@ -94,7 +89,7 @@ class LookaheadAnalysis(BaseAnalysis):
if not self.current_analysis.false_indicators.__contains__(col_name[0]):
self.current_analysis.false_indicators.append(col_name[0])
logger.info(
f"=> found look ahead bias in indicator "
f"=> found look ahead bias in column "
f"{col_name[0]}. "
f"{str(self_value)} != {str(other_value)}"
)
@@ -132,7 +127,13 @@ class LookaheadAnalysis(BaseAnalysis):
varholder.data, varholder.timerange = backtesting.load_bt_data()
varholder.timeframe = backtesting.timeframe
varholder.indicators = backtesting.strategy.advise_all_indicators(varholder.data)
temp_indicators = backtesting.strategy.advise_all_indicators(varholder.data)
filled_indicators = dict()
for pair, dataframe in temp_indicators.items():
filled_indicators[pair] = backtesting.strategy.ft_advise_signals(
dataframe, {"pair": pair}
)
varholder.indicators = filled_indicators
varholder.result = self.get_result(backtesting, varholder.indicators)
def fill_entry_and_exit_varHolders(self, result_row):