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14:10:00","label":"live since 2026-11-07"},"seconds":16},{"strategy":"CombinedBinHAndCluc","source":"freqtrade/freqtrade-strategies:berlinguyinca/CombinedBinHAndCluc.py","added":"2026-11-07","days_live":3,"lookahead_bias":null,"code_sha256":"546256271db535f1e326130c6b2d9849dd9a5efb602eb92ed45dad282967f45d","backtest":{"status":"ok","timeframe":"5m","trades":56,"profit_total":-0.04221693334,"profit_abs":-42.21693334,"max_drawdown":0.07071938836125748,"max_drawdown_marked":0.074254,"winrate":0.7857142857142857,"wins":44,"losses":12,"market_change":-0.2525801477555657,"start":"2026-09-26 00:00:00","end":"2026-11-10 14:10:00","days":45,"label":"backtest"},"status":"ok","live":{"status":"ok","timeframe":"5m","trades":5,"profit_total":-0.004600832900000002,"profit_abs":-4.600832900000001,"max_drawdown":0.010222464037081786,"max_drawdown_marked":0.011899,"winrate":0.8,"wins":4,"losses":1,"market_change":-0.03761810772653717,"start":"2026-11-07 00:00:00","end":"2026-11-10 14:10:00","label":"live since 2026-11-07"},"seconds":14},{"strategy":"CombinedBinHAndClucV8XH","source":"phuchust/freqtrade_strategy@4a0176ed284379a060262d5943394f2ca056d3d7:CombinedBinHAndClucV8XH.py","added":"2026-11-10","days_live":0,"lookahead_bias":null,"code_sha256":"c31f2e1a690ff03d2020b0755754bfe070fece8b44692fa02ed0cf7ce7b745cf","backtest":{"status":"error","error":" ssl_down_1h, ssl_up_1h = SSLChannels(informative_1h, 20)\n                             ~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^\n  File \"/freqtrade/user_data/strategies/phuchust_freqtrade_strategy__CombinedBinHAndClucV8XH.py\", line 48, in SSLChannels\n    np.where(df['close'] < df['smaLow'], -1, np.NAN))\n                                             ^^^^^^\n  File \"/home/ftuser/.local/lib/python3.14/site-packages/numpy/__init__.py\", line 769, in __getattr__\n    raise AttributeError(f\"module {__name__!r} has no attribute {attr!r}\")\nAttributeError: module 'numpy' has no attribute 'NAN'. Did you mean: 'nan'?\n","days":45,"label":"backtest"},"status":"error","seconds":6},{"strategy":"CombinedBinHClucAndMADV3","source":"i1ya/freqtrade-strategies@4bf648ce0251225ba2237e343ba3f692b761f964:CombinedBinHClucAndMADV3/CombinedBinHClucAndMADV3.py","added":"2026-11-10","days_live":0,"lookahead_bias":null,"code_sha256":"4ca3200a239bf843a26cda39bdc4bd0a4cf67ed5d7de7ff8d196781d7a042840","backtest":{"status":"ok","timeframe":"5m","trades":25,"profit_total":0.044998489569999994,"profit_abs":44.99848957,"max_drawdown":0.012176081677920577,"max_drawdown_marked":0.032909,"winrate":0.76,"wins":19,"losses":6,"market_change":-0.2525801477555657,"start":"2026-09-26 00:00:00","end":"2026-11-10 14:10:00","days":45,"label":"backtest"},"status":"ok","seconds":9},{"strategy":"CombinedBinHClucAndMADV5","source":"i1ya/freqtrade-strategies@4bf648ce0251225ba2237e343ba3f692b761f964:CombinedBinHClucAndMADV5/CombinedBinHClucAndMADV5.py","added":"2026-11-10","days_live":0,"lookahead_bias":null,"code_sha256":"ec954f77cea1c12ec400a8678fdab881fd3f5ff05722f879f96ec61f25cd4414","backtest":{"status":"error","error":"^^^^^^^^^^^^^\n  File \"/freqtrade/user_data/strategies/i1ya_freqtrade_strategies__CombinedBinHClucAndMADV5.py\", line 53, in SSLChannels\n    df['hlv'] = np.where(df['close'] > df['smaHigh'], 1, np.where(df['close'] < df['smaLow'], -1, np.NAN))\n                                                                                                  ^^^^^^\n  File \"/home/ftuser/.local/lib/python3.14/site-packages/numpy/__init__.py\", line 769, in __getattr__\n    raise AttributeError(f\"module {__name__!r} has no attribute {attr!r}\")\nAttributeError: module 'numpy' has no attribute 'NAN'. Did you mean: 'nan'?\n","days":45,"label":"backtest"},"status":"error","seconds":6},{"strategy":"CombinedBinHClucAndMADV6","source":"i1ya/freqtrade-strategies@4bf648ce0251225ba2237e343ba3f692b761f964:CombinedBinHClucAndMADV6/CombinedBinHClucAndMADV6.py","added":"2026-11-10","days_live":0,"lookahead_bias":null,"code_sha256":"5a2e13597c2efd601245592fae584697b5d9338f69dea4135a99de832a4b8b08","backtest":{"status":"error","error":"^^^^^^^^^^^^^\n  File \"/freqtrade/user_data/strategies/i1ya_freqtrade_strategies__CombinedBinHClucAndMADV6.py\", line 61, in SSLChannels\n    df['hlv'] = np.where(df['close'] > df['smaHigh'], 1, np.where(df['close'] < df['smaLow'], -1, np.NAN))\n                                                                                                  ^^^^^^\n  File \"/home/ftuser/.local/lib/python3.14/site-packages/numpy/__init__.py\", line 769, in __getattr__\n    raise AttributeError(f\"module {__name__!r} has no attribute {attr!r}\")\nAttributeError: module 'numpy' has no attribute 'NAN'. Did you mean: 'nan'?\n","days":45,"label":"backtest"},"status":"error","seconds":6},{"strategy":"CombinedBinHClucAndMADV9","source":"i1ya/freqtrade-strategies@4bf648ce0251225ba2237e343ba3f692b761f964:CombinedBinHClucAndMADV9/CombinedBinHClucAndMADV9.py","added":"2026-11-10","days_live":0,"lookahead_bias":null,"code_sha256":"f7a3a773911e657ff86219c0a3cbead946597ca2c7304708e45aeb1bd566edd8","backtest":{"status":"ok","timeframe":null,"trades":0,"profit_total":null,"profit_abs":null,"max_drawdown":null,"max_drawdown_marked":null,"winrate":null,"wins":null,"losses":null,"market_change":null,"start":null,"end":null,"days":45,"label":"backtest"},"status":"ok","seconds":4},{"strategy":"Combined_NFIv7_SMA","source":"phuchust/freqtrade_strategy@4a0176ed284379a060262d5943394f2ca056d3d7:Combined_NFIv7_SMA.py","added":"2026-11-10","days_live":0,"lookahead_bias":null,"code_sha256":"062f3d84d7aa9c6dff790040c64c9a204ae66df779a40f292ff22245199ae47a","backtest":{"status":"ok","timeframe":"5m","trades":23,"profit_total":0.0221336551,"profit_abs":22.1336551,"max_drawdown":0.007280891744703435,"max_drawdown_marked":0.022335,"winrate":0.782608695652174,"wins":18,"losses":5,"market_change":-0.2525801477555657,"start":"2026-09-26 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2026-11-07"},"seconds":25},{"strategy":"LuxOSC","source":"jilv220/freqtrade-stuff@786f1e7cdea930dc7bfc4fe926e8a9629514e27d:LuxOSC.py","added":"2026-11-10","days_live":0,"lookahead_bias":null,"code_sha256":"4eb4f180d5a086b67fea053de007f8b462a0a6d3dc46f4f76d891a88869851b6","backtest":{"status":"ok","timeframe":"5m","trades":234,"profit_total":-0.20341695871999996,"profit_abs":-203.41695871999997,"max_drawdown":0.2618549992095752,"max_drawdown_marked":0.266206,"winrate":0.5598290598290598,"wins":131,"losses":103,"market_change":-0.2525801477555657,"start":"2026-09-26 00:00:00","end":"2026-11-10 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14:10:00","label":"live since 2026-11-07"},"seconds":16},{"strategy":"Magic_Trailing_Stoploss","source":"brookmiles/freqtrade-stuff@1f52e1feb037b0f1851ce85c8471e7b3e6969bd4:strategies/examples/Magic_Trailing_Stoploss.py","added":"2026-11-10","days_live":0,"lookahead_bias":null,"code_sha256":"2a647c5bda5f690683468d3c4a8828ee02f1f2747662c3df6a1d4f0124935c13","backtest":{"status":"ok","timeframe":"1h","trades":7227,"profit_total":-0.98209873641,"profit_abs":-982.09873641,"max_drawdown":0.9824611136296898,"max_drawdown_marked":0.982415,"winrate":0.19911443199114431,"wins":1439,"losses":5788,"market_change":-0.25274114715662627,"start":"2026-09-26 00:00:00","end":"2026-11-10 13:00:00","days":45,"label":"backtest"},"status":"ok","seconds":11},{"strategy":"MultiMa","source":"freqtrade/freqtrade-strategies:MultiMa.py","added":"2026-11-07","days_live":3,"lookahead_bias":null,"code_sha256":"cae77a6c8f983377e392a2c66bfc541e7c1400fae03c3a413194902b2eda6626","backtest":{"status":"ok","timeframe":"4h","trades":18,"profit_total":-0.17900142581,"profit_abs":-179.00142581,"max_drawdown":0.17901261306030716,"max_drawdown_marked":0.235092,"winrate":0.6111111111111112,"wins":11,"losses":7,"market_change":-0.24716144996148062,"start":"2026-09-26 00:00:00","end":"2026-11-10 08:00:00","days":45,"label":"backtest"},"status":"ok","live":{"status":"ok","timeframe":"4h","trades":0,"profit_total":0.0,"profit_abs":0,"max_drawdown":0.0,"max_drawdown_marked":0.0,"winrate":0,"wins":0,"losses":0,"market_change":-0.033078297313686736,"start":"2026-11-07 00:00:00","end":"2026-11-10 08:00:00","label":"live since 2026-11-07"},"seconds":18},{"strategy":"MultiRSI","source":"freqtrade/freqtrade-strategies:berlinguyinca/MultiRSI.py","added":"2026-11-07","days_live":3,"lookahead_bias":null,"code_sha256":"0bd453350bdf32db4355277d79a3c7268d166d043bab59e30403a1e97687aa06","backtest":{"status":"ok","timeframe":"5m","trades":730,"profit_total":-0.36929246399,"profit_abs":-369.29246399,"max_drawdown":0.3701768694567644,"max_drawdown_marked":0.369651,"winrate":0.4452054794520548,"wins":325,"losses":405,"market_change":-0.2525801477555657,"start":"2026-09-26 00:00:00","end":"2026-11-10 14:10:00","days":45,"label":"backtest"},"status":"ok","live":{"status":"ok","timeframe":"5m","trades":37,"profit_total":-0.02403448393,"profit_abs":-24.03448393,"max_drawdown":0.024589084680000043,"max_drawdown_marked":0.024589,"winrate":0.24324324324324326,"wins":9,"losses":28,"market_change":-0.03761810772653717,"start":"2026-11-07 00:00:00","end":"2026-11-10 14:10:00","label":"live since 2026-11-07"},"seconds":15},{"strategy":"NASOSv5","source":"jilv220/freqtrade-stuff@786f1e7cdea930dc7bfc4fe926e8a9629514e27d:NASOSv5.py","added":"2026-11-10","days_live":0,"lookahead_bias":null,"code_sha256":"f3fa98f6674e4302de66b98a7fe886314fcd95cffcbf9fe59d90908c00e1512c","backtest":{"status":"ok","timeframe":"5m","trades":1,"profit_total":-0.028952712710000002,"profit_abs":-28.95271271,"max_drawdown":0.028952712710000016,"max_drawdown_marked":0.028953,"winrate":0.0,"wins":0,"losses":1,"market_change":-0.2525801477555657,"start":"2026-09-26 00:00:00","end":"2026-11-10 14:10:00","days":45,"label":"backtest"},"status":"ok","seconds":9},{"strategy":"NFI5MOHO_WIP","source":"phuchust/freqtrade_strategy@4a0176ed284379a060262d5943394f2ca056d3d7:NFI5MOHO_WIP.py","added":"2026-11-10","days_live":0,"lookahead_bias":null,"code_sha256":"245f4ab9c80fda0f44ae0425cf8c5f5ca67ba9f7ec6979a7d9b9647f3b0e4048","backtest":{"status":"ok","timeframe":"5m","trades":17,"profit_total":0.014206478450000002,"profit_abs":14.206478450000002,"max_drawdown":0.005419168064517782,"max_drawdown_marked":0.02276,"winrate":0.8235294117647058,"wins":14,"losses":3,"market_change":-0.2525801477555657,"start":"2026-09-26 00:00:00","end":"2026-11-10 14:10:00","days":45,"label":"backtest"},"status":"ok","seconds":11},{"strategy":"NoLost","source":"hansen1015/freqtrade_strategy@4b7d342c2a5c6664c00b6a1855e7354a2ffd8225:NoLost.py","added":"2026-11-10","days_live":0,"lookahead_bias":null,"code_sha256":"416b181f23fa20448a3d399ed7d0303766ff7e87e34ca20440326c72d924f04d","backtest":{"status":"ok","timeframe":null,"trades":0,"profit_total":null,"profit_abs":null,"max_drawdown":null,"max_drawdown_marked":null,"winrate":null,"wins":null,"losses":null,"market_change":null,"start":null,"end":null,"days":45,"label":"backtest"},"status":"ok","seconds":4},{"strategy":"NostalgiaForInfinityV7_SMA","source":"jilv220/freqtrade-stuff@786f1e7cdea930dc7bfc4fe926e8a9629514e27d:NostalgiaForInfinityV7_SMA.py","added":"2026-11-10","days_live":0,"lookahead_bias":null,"code_sha256":"23e102fa76614fd3cd444c7167cb17b2e60422fc035ca8de54c8824bb39bda07","backtest":{"status":"ok","timeframe":"5m","trades":23,"profit_total":0.0221336551,"profit_abs":22.1336551,"max_drawdown":0.007280891744703435,"max_drawdown_marked":0.022335,"winrate":0.782608695652174,"wins":18,"losses":5,"market_change":-0.2525801477555657,"start":"2026-09-26 00:00:00","end":"2026-11-10 14:10:00","days":45,"label":"backtest"},"status":"ok","seconds":13},{"strategy":"NostalgiaForInfinityX6","source":"iterativv/NostalgiaForInfinity@75790918caac247449993f37fca94b9eeea07235:NostalgiaForInfinityX6.py","added":"2026-11-10","days_live":0,"lookahead_bias":null,"code_sha256":"fdc68ca5e4a8386874824de68962225ad0c263471b9bf4186b5b2bfd7c25e945","backtest":{"status":"ok","timeframe":"5m","trades":5,"profit_total":0.0133125858,"profit_abs":13.3125858,"max_drawdown":0.0,"max_drawdown_marked":0.011601,"winrate":1.0,"wins":5,"losses":0,"market_change":-0.2525801477555657,"start":"2026-09-26 00:00:00","end":"2026-11-10 14:10:00","days":45,"label":"backtest"},"status":"ok","seconds":30},{"strategy":"NostalgiaForInfinityX7","source":"iterativv/NostalgiaForInfinity@75790918caac247449993f37fca94b9eeea07235:NostalgiaForInfinityX7.py","added":"2026-11-10","days_live":0,"lookahead_bias":null,"code_sha256":"330adc0d6aea3196b9e672fcd92304207518806ad58cdacdc8961131c4d3b93c","backtest":{"status":"ok","timeframe":"5m","trades":5,"profit_total":0.009710150170000001,"profit_abs":9.71015017,"max_drawdown":0.0,"max_drawdown_marked":0.01371,"winrate":1.0,"wins":5,"losses":0,"market_change":-0.2525801477555657,"start":"2026-09-26 00:00:00","end":"2026-11-10 14:10:00","days":45,"label":"backtest"},"status":"ok","seconds":12},{"strategy":"NostalgiaForInfinityX8","source":"iterativv/NostalgiaForInfinity@75790918caac247449993f37fca94b9eeea07235:NostalgiaForInfinityX8.py","added":"2026-11-10","days_live":0,"lookahead_bias":null,"code_sha256":"5eb5aacb077c91eb87ba0287786b258e736315a5a41ae8b4188d25e7e40b6486","backtest":{"status":"ok","timeframe":"5m","trades":6,"profit_total":0.03612339381,"profit_abs":36.12339381,"max_drawdown":0.0,"max_drawdown_marked":0.018644,"winrate":1.0,"wins":6,"losses":0,"market_change":-0.2525801477555657,"start":"2026-09-26 00:00:00","end":"2026-11-10 14:10:00","days":45,"label":"backtest"},"status":"ok","seconds":13},{"strategy":"ObeliskIM_v1_1","source":"brookmiles/freqtrade-stuff@1f52e1feb037b0f1851ce85c8471e7b3e6969bd4:strategies/archive/ObeliskIM_v1_1.py","added":"2026-11-10","days_live":0,"lookahead_bias":null,"code_sha256":"ee1f7043913f1708026f403da0002fc142168e0f1208f6d75426259efe84396d","backtest":{"status":"error","error":"_data.copy(), {\"pair\": pair}).copy()\n                ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n  File \"/freqtrade/freqtrade/strategy/interface.py\", line 1834, in advise_indicators\n    dataframe = self.populate_indicators(dataframe, metadata)\n  File \"/freqtrade/user_data/strategies/brookmiles_freqtrade_stuff__ObeliskIM_v1_1.py\", line 123, in populate_indicators\n    dataframe['tk_cross_up'].fillna(method='ffill', inplace=True, limit=2)\n    ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nTypeError: NDFrame.fillna() got an unexpected keyword argument 'method'\n","days":45,"label":"backtest"},"status":"error","seconds":7},{"strategy":"ObeliskRSI_v6_1","source":"brookmiles/freqtrade-stuff@1f52e1feb037b0f1851ce85c8471e7b3e6969bd4:strategies/archive/ObeliskRSI_v6_1.py","added":"2026-11-10","days_live":0,"lookahead_bias":null,"code_sha256":"67657bd635589735f89bf2b0e11f871c84671312e5dc28e64985507b83aa3d6e","backtest":{"status":"error","error":"cators(pair_data.copy(), {\"pair\": pair}).copy()\n                ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n  File \"/freqtrade/freqtrade/strategy/interface.py\", line 1834, in advise_indicators\n    dataframe = self.populate_indicators(dataframe, metadata)\n  File \"/freqtrade/user_data/strategies/brookmiles_freqtrade_stuff__ObeliskRSI_v6_1.py\", line 124, in populate_indicators\n    dataframe[resample_rsi_key].fillna(method='ffill', inplace=True)\n    ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nTypeError: NDFrame.fillna() got an unexpected keyword argument 'method'\n","days":45,"label":"backtest"},"status":"error","seconds":6},{"strategy":"Obelisk_3EMA_StochRSI_ATR","source":"brookmiles/freqtrade-stuff@1f52e1feb037b0f1851ce85c8471e7b3e6969bd4:strategies/experimental/Obelisk_3EMA_StochRSI_ATR.py","added":"2026-11-10","days_live":0,"lookahead_bias":null,"code_sha256":"40104f77d8fb196a379b6d4029b7fe260e04bd5617511af517b78fe9e7cc8bff","backtest":{"status":"error","error":"ndicators\n    dataframe = self.populate_indicators(dataframe, metadata)\n  File \"/freqtrade/user_data/strategies/brookmiles_freqtrade_stuff__Obelisk_3EMA_StochRSI_ATR.py\", line 128, in populate_indicators\n    informative = self.do_indicators(informative.copy(), metadata)\n  File \"/freqtrade/user_data/strategies/brookmiles_freqtrade_stuff__Obelisk_3EMA_StochRSI_ATR.py\", line 98, in do_indicators\n    dataframe['take_profit'].fillna(method='ffill', inplace=True)\n    ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nTypeError: NDFrame.fillna() got an unexpected keyword argument 'method'\n","days":45,"label":"backtest"},"status":"error","seconds":6},{"strategy":"Obelisk_Ichimoku_Slow_v1","source":"brookmiles/freqtrade-stuff@1f52e1feb037b0f1851ce85c8471e7b3e6969bd4:strategies/Obelisk_Ichimoku_Slow_v1.py","added":"2026-11-10","days_live":0,"lookahead_bias":null,"code_sha256":"7eb5cdd4734f141dd81143b9e93ddb96bd7edca9c5af7c1c8e815293ab76699e","backtest":{"status":"error","error":"^^^^^^^^^^^^\n  File \"/freqtrade/user_data/strategies/brookmiles_freqtrade_stuff__Obelisk_Ichimoku_Slow_v1.py\", line 64, in SSLChannels\n    df['hlv'] = np.where(df['close'] > df['smaHigh'], 1, np.where(df['close'] < df['smaLow'], -1, np.NAN))\n                                                                                                  ^^^^^^\n  File \"/home/ftuser/.local/lib/python3.14/site-packages/numpy/__init__.py\", line 769, in __getattr__\n    raise AttributeError(f\"module {__name__!r} has no attribute {attr!r}\")\nAttributeError: module 'numpy' has no attribute 'NAN'. Did you mean: 'nan'?\n","days":45,"label":"backtest"},"status":"error","seconds":5},{"strategy":"Obelisk_Ichimoku_Slow_v1_1","source":"brookmiles/freqtrade-stuff@1f52e1feb037b0f1851ce85c8471e7b3e6969bd4:strategies/Obelisk_Ichimoku_Slow_v1_1.py","added":"2026-11-10","days_live":0,"lookahead_bias":null,"code_sha256":"5f3a50e560d4e8e4ba2055b2f075b1dc83c3a823dc6fe5f5d94d8e473b128924","backtest":{"status":"error","error":"^^^^^^^^^^\n  File \"/freqtrade/user_data/strategies/brookmiles_freqtrade_stuff__Obelisk_Ichimoku_Slow_v1_1.py\", line 67, in SSLChannels\n    df['hlv'] = np.where(df['close'] > df['smaHigh'], 1, np.where(df['close'] < df['smaLow'], -1, np.NAN))\n                                                                                                  ^^^^^^\n  File \"/home/ftuser/.local/lib/python3.14/site-packages/numpy/__init__.py\", line 769, in __getattr__\n    raise AttributeError(f\"module {__name__!r} has no attribute {attr!r}\")\nAttributeError: module 'numpy' has no attribute 'NAN'. Did you mean: 'nan'?\n","days":45,"label":"backtest"},"status":"error","seconds":5},{"strategy":"Obelisk_Ichimoku_Slow_v1_2","source":"brookmiles/freqtrade-stuff@1f52e1feb037b0f1851ce85c8471e7b3e6969bd4:strategies/archive/Obelisk_Ichimoku_Slow_v1_2.py","added":"2026-11-10","days_live":0,"lookahead_bias":null,"code_sha256":"50e534f2f23a490f280df510f0036a0178406db291dff2e8c6faf4332794dcfa","backtest":{"status":"error","error":"^^^^^^^^^^^^^^\n  File \"/freqtrade/user_data/strategies/brookmiles_freqtrade_stuff__Obelisk_Ichimoku_Slow_v1_2.py\", line 69, in ssl_atr\n    df['hlv'] = np.where(df['close'] > df['smaHigh'], 1, np.where(df['close'] < df['smaLow'], -1, np.NAN))\n                                                                                                  ^^^^^^\n  File \"/home/ftuser/.local/lib/python3.14/site-packages/numpy/__init__.py\", line 769, in __getattr__\n    raise AttributeError(f\"module {__name__!r} has no attribute {attr!r}\")\nAttributeError: module 'numpy' has no attribute 'NAN'. Did you mean: 'nan'?\n","days":45,"label":"backtest"},"status":"error","seconds":5},{"strategy":"Obelisk_Ichimoku_Slow_v1_3","source":"brookmiles/freqtrade-stuff@1f52e1feb037b0f1851ce85c8471e7b3e6969bd4:strategies/Obelisk_Ichimoku_Slow_v1_3.py","added":"2026-11-10","days_live":0,"lookahead_bias":null,"code_sha256":"01c172c42e2d1ef9259a363909d7349afd31ec7a55ab5d3d59f17020f989b83d","backtest":{"status":"error","error":"^^^^^^^^^^^^^^\n  File \"/freqtrade/user_data/strategies/brookmiles_freqtrade_stuff__Obelisk_Ichimoku_Slow_v1_3.py\", line 64, in ssl_atr\n    df['hlv'] = np.where(df['close'] > df['smaHigh'], 1, np.where(df['close'] < df['smaLow'], -1, np.NAN))\n                                                                                                  ^^^^^^\n  File \"/home/ftuser/.local/lib/python3.14/site-packages/numpy/__init__.py\", line 769, in __getattr__\n    raise AttributeError(f\"module {__name__!r} has no attribute {attr!r}\")\nAttributeError: module 'numpy' has no attribute 'NAN'. Did you mean: 'nan'?\n","days":45,"label":"backtest"},"status":"error","seconds":5},{"strategy":"Obelisk_Ichimoku_ZEMA_v1","source":"brookmiles/freqtrade-stuff@1f52e1feb037b0f1851ce85c8471e7b3e6969bd4:strategies/experimental/Obelisk_Ichimoku_ZEMA_v1.py","added":"2026-11-10","days_live":0,"lookahead_bias":null,"code_sha256":"275da95e2e4afd2c6bebf10ce7897cafc667eb10615f70a685e6b132858c02b1","backtest":{"status":"error","error":"~^^^^^^^^^^^^^^^\n  File \"/freqtrade/user_data/strategies/brookmiles_freqtrade_stuff__Obelisk_Ichimoku_ZEMA_v1.py\", line 29, in ssl_atr\n    df['hlv'] = np.where(df['close'] > df['smaHigh'], 1, np.where(df['close'] < df['smaLow'], -1, np.NAN))\n                                                                                                  ^^^^^^\n  File \"/home/ftuser/.local/lib/python3.14/site-packages/numpy/__init__.py\", line 769, in __getattr__\n    raise AttributeError(f\"module {__name__!r} has no attribute {attr!r}\")\nAttributeError: module 'numpy' has no attribute 'NAN'. Did you mean: 'nan'?\n","days":45,"label":"backtest"},"status":"error","seconds":6},{"strategy":"Obelisk_TradePro_Ichi_v1_1","source":"brookmiles/freqtrade-stuff@1f52e1feb037b0f1851ce85c8471e7b3e6969bd4:strategies/archive/Obelisk_TradePro_Ichi_v1_1.py","added":"2026-11-10","days_live":0,"lookahead_bias":null,"code_sha256":"d0f71da46bcc5628b365100f5aeb6b731e079d2f2051ce7b938e86c106847377","backtest":{"status":"ok","timeframe":"1h","trades":139,"profit_total":-0.25051068412,"profit_abs":-250.51068412,"max_drawdown":0.2505106841199998,"max_drawdown_marked":0.253383,"winrate":0.1223021582733813,"wins":17,"losses":122,"market_change":-0.25274114715662627,"start":"2026-09-26 00:00:00","end":"2026-11-10 13:00:00","days":45,"label":"backtest"},"status":"ok","seconds":6},{"strategy":"Obelisk_TradePro_Ichi_v2","source":"brookmiles/freqtrade-stuff@1f52e1feb037b0f1851ce85c8471e7b3e6969bd4:strategies/archive/Obelisk_TradePro_Ichi_v2.py","added":"2026-11-10","days_live":0,"lookahead_bias":null,"code_sha256":"8ce9634a240808a075810b75e319cb0792849ad440128513440d2da328815e81","backtest":{"status":"error","error":"^^^^^^^^^^^^\n  File \"/freqtrade/user_data/strategies/brookmiles_freqtrade_stuff__Obelisk_TradePro_Ichi_v2.py\", line 58, in SSLChannels\n    df['hlv'] = np.where(df['close'] > df['smaHigh'], 1, np.where(df['close'] < df['smaLow'], -1, np.NAN))\n                                                                                                  ^^^^^^\n  File \"/home/ftuser/.local/lib/python3.14/site-packages/numpy/__init__.py\", line 769, in __getattr__\n    raise AttributeError(f\"module {__name__!r} has no attribute {attr!r}\")\nAttributeError: module 'numpy' has no attribute 'NAN'. Did you mean: 'nan'?\n","days":45,"label":"backtest"},"status":"error","seconds":5},{"strategy":"Obelisk_TradePro_Ichi_v2_2","source":"brookmiles/freqtrade-stuff@1f52e1feb037b0f1851ce85c8471e7b3e6969bd4:strategies/archive/Obelisk_TradePro_Ichi_v2_2.py","added":"2026-11-10","days_live":0,"lookahead_bias":null,"code_sha256":"32cd2080316811f7dbf7b6473e8c39f6ff1cf436a42946d90a35e3c0e6615236","backtest":{"status":"error","error":"^^^^^^^^^^\n  File \"/freqtrade/user_data/strategies/brookmiles_freqtrade_stuff__Obelisk_TradePro_Ichi_v2_2.py\", line 65, in SSLChannels\n    df['hlv'] = np.where(df['close'] > df['smaHigh'], 1, np.where(df['close'] < df['smaLow'], -1, np.NAN))\n                                                                                                  ^^^^^^\n  File \"/home/ftuser/.local/lib/python3.14/site-packages/numpy/__init__.py\", line 769, in __getattr__\n    raise AttributeError(f\"module {__name__!r} has no attribute {attr!r}\")\nAttributeError: module 'numpy' has no attribute 'NAN'. Did you mean: 'nan'?\n","days":45,"label":"backtest"},"status":"error","seconds":6},{"strategy":"PatternRecognition","source":"freqtrade/freqtrade-strategies:PatternRecognition.py","added":"2026-11-07","days_live":3,"lookahead_bias":null,"code_sha256":"cce61e4af8ed3cb8e78a5d9713aba7891ec08d1bdb1da9911c3f550424db795d","backtest":{"status":"ok","timeframe":"1d","trades":7,"profit_total":-0.26159186913000004,"profit_abs":-261.59186913,"max_drawdown":0.2615918691300001,"max_drawdown_marked":0.266775,"winrate":0.0,"wins":0,"losses":7,"market_change":-0.24541935721563188,"start":"2026-09-26 00:00:00","end":"2026-11-09 00:00:00","days":45,"label":"backtest"},"status":"ok","live":{"status":"ok","timeframe":"1d","trades":0,"profit_total":0.0,"profit_abs":0,"max_drawdown":0.0,"max_drawdown_marked":0.0,"winrate":0,"wins":0,"losses":0,"market_change":-0.018897701075811422,"start":"2026-11-07 00:00:00","end":"2026-11-09 00:00:00","label":"live since 2026-11-07"},"seconds":11},{"strategy":"Pmax","source":"werkkrew/freqtrade-strategies@582e9649a88623b6f85f03a63bfa68410cd8ad8a:strategies/archived/Pmax.py","added":"2026-11-10","days_live":0,"lookahead_bias":null,"code_sha256":"0d4334112a7d884ccb3d46f071af464f7c414c704402e066d30be8c48aa3f1a1","backtest":{"status":"error","error":"_indicators(pair_data.copy(), {\"pair\": pair}).copy()\n                ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n  File \"/freqtrade/freqtrade/strategy/interface.py\", line 1834, in advise_indicators\n    dataframe = self.populate_indicators(dataframe, metadata)\n  File \"/freqtrade/user_data/strategies/werkkrew_freqtrade_strategies__Pmax.py\", line 27, in populate_indicators\n    dataframe = PMAX(dataframe, atrperiod=atrperiod, multiplier=multiplier, malength=malength, matype=matype, source=source)\nTypeError: PMAX() got an unexpected keyword argument 'atrperiod'. Did you mean 'period'?\n","days":45,"label":"backtest"},"status":"error","seconds":6},{"strategy":"PowerTower","source":"freqtrade/freqtrade-strategies:PowerTower.py","added":"2026-11-07","days_live":3,"lookahead_bias":null,"code_sha256":"ce423a28ea54cfa46f44566ef5632d2ec04718a0723b16e322e9f9ac92df8f41","backtest":{"status":"ok","timeframe":"5m","trades":93,"profit_total":-0.27544027464,"profit_abs":-275.44027464,"max_drawdown":0.2870533161423624,"max_drawdown_marked":0.292227,"winrate":0.6021505376344086,"wins":56,"losses":37,"market_change":-0.2525801477555657,"start":"2026-09-26 00:00:00","end":"2026-11-10 14:10:00","days":45,"label":"backtest"},"status":"ok","live":{"status":"ok","timeframe":"5m","trades":10,"profit_total":-0.05293591144,"profit_abs":-52.93591144,"max_drawdown":0.05320853701203473,"max_drawdown_marked":0.069116,"winrate":0.2,"wins":2,"losses":8,"market_change":-0.03761810772653717,"start":"2026-11-07 00:00:00","end":"2026-11-10 14:10:00","label":"live since 2026-11-07"},"seconds":15},{"strategy":"Quickie","source":"freqtrade/freqtrade-strategies:berlinguyinca/Quickie.py","added":"2026-11-07","days_live":3,"lookahead_bias":null,"code_sha256":"85733568de6bb80c3db87e26faff93ab5e5da95dbb298cc42737365d3e6500a7","backtest":{"status":"ok","timeframe":"5m","trades":64,"profit_total":-0.19936678602000002,"profit_abs":-199.36678602,"max_drawdown":0.2278650050925402,"max_drawdown_marked":0.226787,"winrate":0.78125,"wins":50,"losses":14,"market_change":-0.2525801477555657,"start":"2026-09-26 00:00:00","end":"2026-11-10 14:10:00","days":45,"label":"backtest"},"status":"ok","live":{"status":"ok","timeframe":"5m","trades":10,"profit_total":-0.03196472201,"profit_abs":-31.96472201,"max_drawdown":0.04155360609298064,"max_drawdown_marked":0.052261,"winrate":0.5,"wins":5,"losses":5,"market_change":-0.03761810772653717,"start":"2026-11-07 00:00:00","end":"2026-11-10 14:10:00","label":"live since 2026-11-07"},"seconds":15},{"strategy":"RSIDirectionalWithTrend","source":"paulcpk/freqtrade-strategies-that-work@1e154a2f6b9aeecbaacb7db5ed6b866603daee2c:RSIDirectionalWithTrend.py","added":"2026-11-10","days_live":0,"lookahead_bias":null,"code_sha256":"d00924757cb9e4b7b67cf0221a4dee3ea043d53422df5ad7812e0526fa906b4a","backtest":{"status":"ok","timeframe":"1h","trades":12,"profit_total":-0.03335219165,"profit_abs":-33.35219165,"max_drawdown":0.04404018477897737,"max_drawdown_marked":0.04837,"winrate":0.08333333333333333,"wins":1,"losses":11,"market_change":-0.25274114715662627,"start":"2026-09-26 00:00:00","end":"2026-11-10 13:00:00","days":45,"label":"backtest"},"status":"ok","seconds":5},{"strategy":"RSIDirectionalWithTrendSlow","source":"paulcpk/freqtrade-strategies-that-work@1e154a2f6b9aeecbaacb7db5ed6b866603daee2c:RSIDirectionalWithTrendSlow.py","added":"2026-11-10","days_live":0,"lookahead_bias":null,"code_sha256":"2660268fb9e3207fcdacb9e2f2d58676bc0fdcc91acf72977f0c86dc147389cf","backtest":{"status":"ok","timeframe":"1h","trades":0,"profit_total":0.0,"profit_abs":0,"max_drawdown":0.0,"max_drawdown_marked":0.0,"winrate":0,"wins":0,"losses":0,"market_change":-0.25274114715662627,"start":"2026-09-26 00:00:00","end":"2026-11-10 13:00:00","days":45,"label":"backtest"},"status":"ok","seconds":5},{"strategy":"RSIDivTirail","source":"jilv220/freqtrade-stuff@786f1e7cdea930dc7bfc4fe926e8a9629514e27d:RSIDivergence.py","added":"2026-11-10","days_live":0,"lookahead_bias":null,"code_sha256":"99148c68949e703e60de0e6e33dec1e55711a30f6c39bcb4df053061a59def48","backtest":{"status":"error","error":"^^^^^^^^^\n    ...<4 lines>...\n        storage_options=self.storage_options,\n        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n    ) as handles:\n    ^\n  File \"/home/ftuser/.local/lib/python3.14/site-packages/pandas/io/common.py\", line 797, in get_handle\n    check_parent_directory(str(handle))\n    ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^\n  File \"/home/ftuser/.local/lib/python3.14/site-packages/pandas/io/common.py\", line 656, in check_parent_directory\n    raise OSError(rf\"Cannot save file into a non-existent directory: '{parent}'\")\nOSError: Cannot save file into a non-existent directory: 'user_data/csvs'\n","days":45,"label":"backtest"},"status":"error","seconds":7},{"strategy":"ReinforcedAverageStrategy","source":"freqtrade/freqtrade-strategies:berlinguyinca/ReinforcedAverageStrategy.py","added":"2026-11-07","days_live":3,"lookahead_bias":null,"code_sha256":"50c8e88441ffead38fd1e1b3d49b151a001068f5eff01a23c10178b1f2c87e38","backtest":{"status":"ok","timeframe":"4h","trades":0,"profit_total":0.0,"profit_abs":0,"max_drawdown":0.0,"max_drawdown_marked":0.0,"winrate":0,"wins":0,"losses":0,"market_change":-0.24716144996148062,"start":"2026-09-26 00:00:00","end":"2026-11-10 08:00:00","days":45,"label":"backtest"},"status":"ok","live":{"status":"ok","timeframe":"4h","trades":0,"profit_total":0.0,"profit_abs":0,"max_drawdown":0.0,"max_drawdown_marked":0.0,"winrate":0,"wins":0,"losses":0,"market_change":-0.033078297313686736,"start":"2026-11-07 00:00:00","end":"2026-11-10 08:00:00","label":"live since 2026-11-07"},"seconds":10},{"strategy":"ReinforcedQuickie","source":"freqtrade/freqtrade-strategies:berlinguyinca/ReinforcedQuickie.py","added":"2026-11-07","days_live":3,"lookahead_bias":null,"code_sha256":"e4b362d68be33ddd90f7c372fafb2754782a9d37422dfa1f21ee89741328a624","backtest":{"status":"ok","timeframe":"5m","trades":400,"profit_total":-0.28153655412,"profit_abs":-281.53655412,"max_drawdown":0.29712499909638324,"max_drawdown_marked":0.300147,"winrate":0.5875,"wins":235,"losses":165,"market_change":-0.2525801477555657,"start":"2026-09-26 00:00:00","end":"2026-11-10 14:10:00","days":45,"label":"backtest"},"status":"ok","live":{"status":"ok","timeframe":"5m","trades":24,"profit_total":-0.023298537470000002,"profit_abs":-23.298537470000003,"max_drawdown":0.030760857004732255,"max_drawdown_marked":0.035303,"winrate":0.5,"wins":12,"losses":12,"market_change":-0.03761810772653717,"start":"2026-11-07 00:00:00","end":"2026-11-10 14:10:00","label":"live since 2026-11-07"},"seconds":16},{"strategy":"ReinforcedSmoothScalp","source":"freqtrade/freqtrade-strategies:berlinguyinca/ReinforcedSmoothScalp.py","added":"2026-11-07","days_live":3,"lookahead_bias":null,"code_sha256":"d510b70a62dfcde39697184f62b48e93cae8a6c87a67670e0fadb8bed51b73c5","backtest":{"status":"ok","timeframe":"1m","trades":692,"profit_total":-0.2751914122,"profit_abs":-275.1914122,"max_drawdown":0.27531857586131797,"max_drawdown_marked":0.273612,"winrate":0.3453757225433526,"wins":239,"losses":453,"market_change":-0.25693302807230284,"start":"2026-09-26 00:00:00","end":"2026-11-10 14:17:00","days":45,"label":"backtest"},"status":"ok","live":{"status":"ok","timeframe":"1m","trades":50,"profit_total":-0.04083880752999999,"profit_abs":-40.83880752999999,"max_drawdown":0.041444942525989605,"max_drawdown_marked":0.039308,"winrate":0.22,"wins":11,"losses":39,"market_change":-0.04056227221935616,"start":"2026-11-07 00:00:00","end":"2026-11-10 14:17:00","label":"live since 2026-11-07"},"seconds":30},{"strategy":"Renko","source":"werkkrew/freqtrade-strategies@582e9649a88623b6f85f03a63bfa68410cd8ad8a:strategies/archived/Renko.py","added":"2026-11-10","days_live":0,"lookahead_bias":null,"code_sha256":"7e11ea5041e5bf77f24c4c3f4725683bebabeac627d281172e0571d92cb3e295","backtest":{"status":"error","error":" 14:53:52,475 - freqtrade.optimize.backtesting - INFO - Running backtesting for Strategy Renko\nanalyze \u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2578                                                                                  2/4  50% \u2022 0:00:01 \u2022 0:00:02\nanalyze \u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501 0/0   0% \u2022 0:00:00 \u2022 0:00:00\n2026-11-10 14:53:53,009 - freqtrade - ERROR - Dataframe returned from strategy has mismatching length.\n","days":45,"label":"backtest"},"status":"error","seconds":6},{"strategy":"RenkoYolo","source":"werkkrew/freqtrade-strategies@582e9649a88623b6f85f03a63bfa68410cd8ad8a:strategies/archived/RenkoYolo.py","added":"2026-11-10","days_live":0,"lookahead_bias":null,"code_sha256":"99cddd5812cd0e7501debd895a33f694d8071da235cb29c8a0755b1bd85ee275","backtest":{"status":"error","error":"  dataframe = self.advise_entry(dataframe, metadata)\n  File \"/freqtrade/freqtrade/strategy/interface.py\", line 1855, in advise_entry\n    df = self.populate_entry_trend(dataframe, metadata)\n  File \"/freqtrade/freqtrade/strategy/interface.py\", line 261, in populate_entry_trend\n    return self.populate_buy_trend(dataframe, metadata)\n           ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^\n  File \"/freqtrade/user_data/strategies/werkkrew_freqtrade_strategies__RenkoYolo.py\", line 55, in populate_buy_trend\n    (dataframe['adx'] > params['adx']) &\n                        ~~~~~~^^^^^^^\nKeyError: 'adx'\n","days":45,"label":"backtest"},"status":"error","seconds":5},{"strategy":"SafeCluc","source":"jilv220/freqtrade-stuff@786f1e7cdea930dc7bfc4fe926e8a9629514e27d:SafeCluc.py","added":"2026-11-10","days_live":0,"lookahead_bias":null,"code_sha256":"e4b12606bdb6925437d76435f1004329069adf13fe94fd66561f90d36d9d5929","backtest":{"status":"ok","timeframe":null,"trades":0,"profit_total":null,"profit_abs":null,"max_drawdown":null,"max_drawdown_marked":null,"winrate":null,"wins":null,"losses":null,"market_change":null,"start":null,"end":null,"days":45,"label":"backtest"},"status":"ok","seconds":4},{"strategy":"SampleStrategy","source":"","added":"2026-11-07","days_live":3,"lookahead_bias":null,"code_sha256":"18d48d64b955dc9bd1b43f59115c16f2002a881c62c2851ceca64569a6f8651c","backtest":{"status":"ok","timeframe":"5m","trades":146,"profit_total":-0.1917275723,"profit_abs":-191.72757230000002,"max_drawdown":0.22360914078325642,"max_drawdown_marked":0.22245,"winrate":0.815068493150685,"wins":119,"losses":27,"market_change":-0.2525801477555657,"start":"2026-09-26 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14:17:00","days":45,"label":"backtest"},"status":"ok","seconds":26},{"strategy":"YourStrat","source":"jilv220/freqtrade-stuff@786f1e7cdea930dc7bfc4fe926e8a9629514e27d:TrailingBuyStrat.py","added":"2026-11-10","days_live":0,"lookahead_bias":null,"code_sha256":"3290f4d72f919da476f24981b55dc5dee6f8e1882914c9fce6109daa76ee3f92","backtest":{"status":"error","error":"_name, config=config, extra_dir=config.get(\"strategy_path\")\n        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n    )\n    ^\n  File \"/freqtrade/freqtrade/resolvers/strategy_resolver.py\", line 297, in _load_strategy\n    strategy = StrategyResolver._load_object(\n        paths=abs_paths,\n    ...<2 lines>...\n        kwargs={\"config\": config},\n    )\n  File \"/freqtrade/freqtrade/resolvers/iresolver.py\", line 184, in _load_object\n    return module(**kwargs)\nTypeError: Can't instantiate abstract class YourStrat without an implementation for abstract method 'populate_indicators'\n","days":45,"label":"backtest"},"status":"error","seconds":4},{"strategy":"adaptive","source":"jilv220/freqtrade-stuff@786f1e7cdea930dc7bfc4fe926e8a9629514e27d:adaptive.py","added":"2026-11-10","days_live":0,"lookahead_bias":null,"code_sha256":"2fa1c2695efd554fe9f9ab509b6354bfb2a4c0fdbdca7ef3f1ec7a2373eff0b8","backtest":{"status":"ok","timeframe":"5m","trades":2,"profit_total":0.0079217194,"profit_abs":7.921719400000001,"max_drawdown":0.0,"max_drawdown_marked":0.0,"winrate":1.0,"wins":2,"losses":0,"market_change":-0.2525801477555657,"start":"2026-09-26 00:00:00","end":"2026-11-10 14:10:00","days":45,"label":"backtest"},"status":"ok","seconds":9},{"strategy":"bbandrsi","source":"phuchust/freqtrade_strategy@4a0176ed284379a060262d5943394f2ca056d3d7:bbandrsi.py","added":"2026-11-10","days_live":0,"lookahead_bias":null,"code_sha256":"dee83a99addda204b4476684e883f82f2f5fbd9f9ef7353bd9cb1aa4c30557ed","backtest":{"status":"ok","timeframe":"15m","trades":111,"profit_total":-0.19864801171,"profit_abs":-198.64801171,"max_drawdown":0.2248578255776822,"max_drawdown_marked":0.231825,"winrate":0.5135135135135135,"wins":57,"losses":54,"market_change":-0.2540870836389258,"start":"2026-09-26 00:00:00","end":"2026-11-10 14:00:00","days":45,"label":"backtest"},"status":"ok","seconds":8},{"strategy":"conny","source":"werkkrew/freqtrade-strategies@582e9649a88623b6f85f03a63bfa68410cd8ad8a:strategies/archived/consensus_strat.py","added":"2026-11-10","days_live":0,"lookahead_bias":null,"code_sha256":"a9c7ea0fbb6cf41aa2fbebc2ae1719b44d36ade67397adc026b31ca5cbf241e5","backtest":{"status":"ok","timeframe":"15m","trades":281,"profit_total":-0.13464733003999999,"profit_abs":-134.64733003999999,"max_drawdown":0.1632415332199825,"max_drawdown_marked":0.167141,"winrate":0.6619217081850534,"wins":186,"losses":95,"market_change":-0.2540870836389258,"start":"2026-09-26 00:00:00","end":"2026-11-10 14:00:00","days":45,"label":"backtest"},"status":"ok","seconds":8},{"strategy":"gettinMoist","source":"werkkrew/freqtrade-strategies@582e9649a88623b6f85f03a63bfa68410cd8ad8a:strategies/archived/gettinMoist.py","added":"2026-11-10","days_live":0,"lookahead_bias":null,"code_sha256":"054a9e6aec20c18155f2159b6540c013fba01b08a4e1600095e0da6ce6738b82","backtest":{"status":"ok","timeframe":"5m","trades":272,"profit_total":-0.30112833624999996,"profit_abs":-301.12833624999996,"max_drawdown":0.3332933111368358,"max_drawdown_marked":0.338759,"winrate":0.5698529411764706,"wins":155,"losses":117,"market_change":-0.2525801477555657,"start":"2026-09-26 00:00:00","end":"2026-11-10 14:10:00","days":45,"label":"backtest"},"status":"ok","seconds":23},{"strategy":"hansencandlepatternV1","source":"hansen1015/freqtrade_strategy@4b7d342c2a5c6664c00b6a1855e7354a2ffd8225:hansencandlepatternV1.py","added":"2026-11-10","days_live":0,"lookahead_bias":null,"code_sha256":"d408e504abc90afb7ecb729ee19c52e47b98236db25079f16e3535979418be4f","backtest":{"status":"ok","timeframe":"1h","trades":430,"profit_total":-0.31377021549,"profit_abs":-313.77021549,"max_drawdown":0.320913932778787,"max_drawdown_marked":0.343943,"winrate":0.2534883720930233,"wins":109,"losses":321,"market_change":-0.25274114715662627,"start":"2026-09-26 00:00:00","end":"2026-11-10 13:00:00","days":45,"label":"backtest"},"status":"ok","seconds":6},{"strategy":"heikin","source":"hansen1015/freqtrade_strategy@4b7d342c2a5c6664c00b6a1855e7354a2ffd8225:heikin.py","added":"2026-11-10","days_live":0,"lookahead_bias":null,"code_sha256":"07066eafd68797351eb47db30804fbc8776de7e7e25afb651718565e7e387821","backtest":{"status":"ok","timeframe":"1h","trades":702,"profit_total":-0.43565479254,"profit_abs":-435.65479254,"max_drawdown":0.43796086294000064,"max_drawdown_marked":0.441082,"winrate":0.2777777777777778,"wins":195,"losses":507,"market_change":-0.25274114715662627,"start":"2026-09-26 00:00:00","end":"2026-11-10 13:00:00","days":45,"label":"backtest"},"status":"ok","seconds":6},{"strategy":"hlhb","source":"freqtrade/freqtrade-strategies:hlhb.py","added":"2026-11-07","days_live":3,"lookahead_bias":null,"code_sha256":"bd4523d134b686b012947896ffd7a5a299add87ac12aa0d18fac36c9e7ca3822","backtest":{"status":"ok","timeframe":"4h","trades":35,"profit_total":-0.08299737539999999,"profit_abs":-82.9973754,"max_drawdown":0.08885945631414449,"max_drawdown_marked":0.109931,"winrate":0.6285714285714286,"wins":22,"losses":13,"market_change":-0.24716144996148062,"start":"2026-09-26 00:00:00","end":"2026-11-10 08:00:00","days":45,"label":"backtest"},"status":"ok","live":{"status":"ok","timeframe":"4h","trades":2,"profit_total":-0.013630538400000001,"profit_abs":-13.6305384,"max_drawdown":0.013630538399999977,"max_drawdown_marked":0.013631,"winrate":0.0,"wins":0,"losses":2,"market_change":-0.033078297313686736,"start":"2026-11-07 00:00:00","end":"2026-11-10 08:00:00","label":"live since 2026-11-07"},"seconds":11},{"strategy":"ichi","source":"werkkrew/freqtrade-strategies@582e9649a88623b6f85f03a63bfa68410cd8ad8a:strategies/archived/Ichis.py","added":"2026-11-10","days_live":0,"lookahead_bias":null,"code_sha256":"dc51fc3f9eb9b61d50b65a31d6af3a52c0334032e48bcb347d1afd3f518d220b","backtest":{"status":"error","error":" SSLChannels(dataframe, 10)\n  File \"/freqtrade/user_data/strategies/werkkrew_freqtrade_strategies__Ichis.py\", line 106, in SSLChannels\n    df['hlv'] = np.where(df['close'] > df['smaHigh'], 1, np.where(df['close'] < df['smaLow'], -1, np.NAN))\n                                                                                                  ^^^^^^\n  File \"/home/ftuser/.local/lib/python3.14/site-packages/numpy/__init__.py\", line 769, in __getattr__\n    raise AttributeError(f\"module {__name__!r} has no attribute {attr!r}\")\nAttributeError: module 'numpy' has no attribute 'NAN'. Did you mean: 'nan'?\n","days":45,"label":"backtest"},"status":"error","seconds":5},{"strategy":"mabStra","source":"freqtrade/freqtrade-strategies:mabStra.py","added":"2026-11-07","days_live":3,"lookahead_bias":null,"code_sha256":"1c483a549398a0244ca6d87f9736a76ed462056aca8a5ee9affd9aa65efd9393","backtest":{"status":"ok","timeframe":"4h","trades":26,"profit_total":-0.23624109712000002,"profit_abs":-236.24109712000003,"max_drawdown":0.24322274382757877,"max_drawdown_marked":0.271639,"winrate":0.46153846153846156,"wins":12,"losses":14,"market_change":-0.24716144996148062,"start":"2026-09-26 00:00:00","end":"2026-11-10 08:00:00","days":45,"label":"backtest"},"status":"ok","live":{"status":"ok","timeframe":"4h","trades":0,"profit_total":0.0,"profit_abs":0,"max_drawdown":0.0,"max_drawdown_marked":0.0,"winrate":0,"wins":0,"losses":0,"market_change":-0.033078297313686736,"start":"2026-11-07 00:00:00","end":"2026-11-10 08:00:00","label":"live since 2026-11-07"},"seconds":11},{"strategy":"multi_tf","source":"freqtrade/freqtrade-strategies:multi_tf.py","added":"2026-11-07","days_live":3,"lookahead_bias":null,"code_sha256":"eb182eaecb785864496023f26be7932857b1e495805c37bddd562d6b1100683b","backtest":{"status":"error","error":"optimize_commands - INFO - Starting freqtrade in Backtesting mode\n2026-11-10 15:07:59,237 - freqtrade.exchange.exchange - INFO - Instance is running with dry_run enabled\n2026-11-10 15:07:59,237 - freqtrade.exchange.exchange - INFO - Using CCXT 4.5.90\n2026-11-10 15:07:59,242 - freqtrade.exchange.exchange - INFO - Using Exchange \"Binance\"\n2026-11-10 15:08:00,590 - freqtrade.resolvers.exchange_resolver - INFO - Using resolved exchange class 'Binance' ...\n2026-11-10 15:08:00,616 - freqtrade - ERROR - Impossible to load Strategy 'multi_tf'. This class does not exist or contains Python code errors.\n","days":45,"label":"backtest"},"status":"error","seconds":4},{"strategy":"true_lambo","source":"jilv220/freqtrade-stuff@786f1e7cdea930dc7bfc4fe926e8a9629514e27d:true_lambo/true_lambo.py","added":"2026-11-10","days_live":0,"lookahead_bias":null,"code_sha256":"c8009a5ea73e3f6ac5ca03902c0115f827438403801167a84699cc5bdc313dd7","backtest":{"status":"ok","timeframe":"5m","trades":37,"profit_total":0.08287139794,"profit_abs":82.87139794,"max_drawdown":0.0,"max_drawdown_marked":0.03133,"winrate":1.0,"wins":37,"losses":0,"market_change":-0.2525801477555657,"start":"2026-09-26 00:00:00","end":"2026-11-10 14:10:00","days":45,"label":"backtest"},"status":"ok","seconds":20}]}