From df5e6409a46d06b782068cb684c4a1c9389a5b92 Mon Sep 17 00:00:00 2001 From: Matthias Date: Sat, 27 May 2023 20:18:39 +0200 Subject: [PATCH 1/3] Bump develop version to 2023.6-dev --- freqtrade/__init__.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/freqtrade/__init__.py b/freqtrade/__init__.py index f8818c35c..8f7717dd2 100644 --- a/freqtrade/__init__.py +++ b/freqtrade/__init__.py @@ -1,5 +1,5 @@ """ Freqtrade bot """ -__version__ = '2023.5.dev' +__version__ = '2023.6.dev' if 'dev' in __version__: from pathlib import Path From 8ec0469b111e4bbb3793975556adb9dbd1f25611 Mon Sep 17 00:00:00 2001 From: Matthias Date: Sun, 28 May 2023 09:53:46 +0200 Subject: [PATCH 2/3] Fix volatilityfilter behavior closes #8698 --- freqtrade/plugins/pairlist/VolatilityFilter.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/freqtrade/plugins/pairlist/VolatilityFilter.py b/freqtrade/plugins/pairlist/VolatilityFilter.py index 9196026bb..baf4fcd26 100644 --- a/freqtrade/plugins/pairlist/VolatilityFilter.py +++ b/freqtrade/plugins/pairlist/VolatilityFilter.py @@ -74,7 +74,7 @@ class VolatilityFilter(IPairList): needed_pairs: ListPairsWithTimeframes = [ (p, '1d', self._def_candletype) for p in pairlist if p not in self._pair_cache] - since_ms = dt_ts(dt_floor_day(dt_now()) - timedelta(days=self._days - 1)) + since_ms = dt_ts(dt_floor_day(dt_now()) - timedelta(days=self._days)) # Get all candles candles = {} if needed_pairs: From 8a8616925685845afe2d4745d04f77786581edab Mon Sep 17 00:00:00 2001 From: Matthias Date: Sun, 28 May 2023 09:59:57 +0200 Subject: [PATCH 3/3] Better handling of shift --- freqtrade/plugins/pairlist/VolatilityFilter.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/freqtrade/plugins/pairlist/VolatilityFilter.py b/freqtrade/plugins/pairlist/VolatilityFilter.py index baf4fcd26..61a1dcbf0 100644 --- a/freqtrade/plugins/pairlist/VolatilityFilter.py +++ b/freqtrade/plugins/pairlist/VolatilityFilter.py @@ -103,7 +103,7 @@ class VolatilityFilter(IPairList): result = False if daily_candles is not None and not daily_candles.empty: - returns = (np.log(daily_candles.close / daily_candles.close.shift(-1))) + returns = (np.log(daily_candles["close"].shift(1) / daily_candles["close"])) returns.fillna(0, inplace=True) volatility_series = returns.rolling(window=self._days).std() * np.sqrt(self._days)