Revert chan to the most valuable one
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jackyu66git
@@ -14,23 +14,20 @@ import talib.abstract as ta
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from pandas import DataFrame
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from datetime import datetime, timedelta
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from freqtrade.persistence import Trade
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from typing import Optional, List, Dict
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from typing import Optional
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import logging
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logger = logging.getLogger(__name__)
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from freqtrade.optimize.space import Categorical, Dimension, Integer, SKDecimal
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### Now you can use logger.info('asfd') to log
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# freqtrade plot-dataframe --strategy ChanLun_BTC_15 --datadir user_data/data/binance -c ./user_data/ChanLun_SOL_15.json --timerange=20250309-
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# freqtrade trade -c ./user_data/Chan/config/ChanLun_BTC_15.json --strategy ChanLun_BTC_15 --strategy-path ./user_data/Chan/strategies
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# freqtrade backtesting -c ./user_data/Chan/config/ChanLun_BTC_15.json --strategy ChanLun_BTC_15 --export none --strategy-path ./user_data/Chan/strategies --timerange=20250525-
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# freqtrade backtesting -c ./user_data/Chan/config/ChanLun_BTC_15.json --strategy ChanLun_BTC_15 --strategy-path ./user_data/Chan/strategies --timerange=20250525-
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# freqtrade download-data -c ./user_data/Chan/config/ChanLun_BTC_15.json -t 1m --pairs SOL/USDT:USDT --timerange=20250405-
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# freqtrade hyperopt --hyperopt-loss SharpeHyperOptLossDaily --spaces stoploss --strategy ChanLun_BTC_15 --strategy-path ./user_data/Chan/strategies -c ./user_data/Chan/config/ChanLun_BTC_15.json -e 200 --timerange=20250201-20250501
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# freqtrade live-backtest -c ./user_data/Chan/config/ChanLun_BTC_15.json --strategy ChanLun_BTC_15 --strategy-path ./user_data/Chan/strategies --timerange=20250525-
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# freqtrade download-data -c ./user_data/Chan/config/ChanLun_BTC_15.json -t 1m --pairs BTC/USDT:USDT --timerange=20250405-
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# freqtrade hyperopt --hyperopt-loss SharpeHyperOptLossDaily --spaces roi stoploss --strategy ChanLun_BTC_15 --strategy-path ./user_data/Chan/strategies -c ./user_data/Chan/config/ChanLun_BTC_15.json -e 200 --timerange=20250201-20250401
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# sudo docker compose run --rm chanlun_btc backtesting -c ./user_data/Chan/config/ChanLun_BTC_15.json --strategy ChanLun_BTC_15 --strategy-path ./user_data/Chan/strategies --timerange=20250525-
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# sudo docker compose run --rm chanlun_btc download-data -c ./user_data/Chan/config/ChanLun_BTC_15.json --pairs BTC/USDT:USDT -t 1m --timerange 20240101-
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# sudo docker compose run --rm chanlun_btc trade -c ./user_data/Chan/config/ChanLun_BTC_15.json --strategy ChanLun_BTC_15 --strategy-path ./user_data/Chan/strategies
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# sudo docker compose run --rm chan_btc backtesting -c ./user_data/Chan/config/ChanLun_SOL.json --strategy ChanLun_SOL --strategy-path ./user_data/Chan/strategies --timerange=20250101-
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# sudo docker compose run --rm chan_btc download-data -c ./user_data/Chan/config/ChanLun_BTC_15.json --pairs BTC/USDT:USDT -t 1m --timerange 20240101-
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# sudo docker compose run --rm chan_btc trade -c ./user_data/Chan/config/ChanLun_BTC_15.json --strategy ChanLun_BTC_15 --strategy-path ./user_data/Chan/strategies
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class ChanLun_BTC_15(IStrategy):
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INTERFACE_VERSION: int = 3
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@@ -38,10 +35,10 @@ class ChanLun_BTC_15(IStrategy):
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# This attribute will be overridden if the config file contains "minimal_roi"
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# 30m and 1h
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minimal_roi = {
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"0": 0.15,
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"240": 0.1,
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"480": 0.02,
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"960": 0
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"0": 0.60,
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"360": 0.2,
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"640": 0.1,
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"1200": 0
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}
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# 5m and 15m
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minimal_roi_1 = {
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@@ -64,13 +61,14 @@ class ChanLun_BTC_15(IStrategy):
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"3600": 0
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}
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can_short = True
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lev = 10
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stoploss = -0.8
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lev = 50.0
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stoploss = -0.3
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trailing_stop = False
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trailing_stop_positive = 0.025
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trailing_stop_positive_offset = 0.045
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trailing_only_offset_is_reached = False
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position_adjustment_enable = True
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startup_candle_count = 600
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time5 = 5
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@@ -173,13 +171,11 @@ class ChanLun_BTC_15(IStrategy):
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def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
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state_str = 'resample_{}_state'.format(self.get_ticker_indicator()*self.time5)
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fx_str = 'resample_{}_fx'.format(self.get_ticker_indicator()*self.time5)
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#state_str = 'state'
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#fx_str = 'fx'
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dataframe.loc[
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(
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#(dataframe['state'] == "-30")
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(dataframe[state_str].shift(self.time5*2) > 0) &
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(dataframe[fx_str].shift(self.time5*2) == -1)
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(dataframe[state_str].shift(self.time5) > 1.0) &
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(dataframe[fx_str].shift(self.time5) == -1)
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#(dataframe['resample_{}_state'.format(self.get_ticker_indicator()*self.time5)].shift(self.time5) == "-10") &
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#(dataframe['resample_{}_state'.format(self.get_ticker_indicator()*self.time30)] == "-10") &
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#(dataframe['resample_{}_state'.format(self.get_ticker_indicator()*self.time5)].shift(self.time5) == "-10")
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@@ -189,8 +185,8 @@ class ChanLun_BTC_15(IStrategy):
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dataframe.loc[
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(
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#(dataframe['state'] == "-30")
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(dataframe[state_str].shift(self.time5*2) > 0) &
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(dataframe[fx_str].shift(self.time5*2) == 1)
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(dataframe[state_str].shift(self.time5) > 1.0) &
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(dataframe[fx_str].shift(self.time5) == 1)
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#(dataframe['resample_{}_state'.format(self.get_ticker_indicator()*self.time5)].shift(self.time5) == "-10") &
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#(dataframe['resample_{}_state'.format(self.get_ticker_indicator()*self.time30)] == "-10") &
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#(dataframe['resample_{}_state'.format(self.get_ticker_indicator()*self.time5)].shift(self.time5) == "-10")
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@@ -201,13 +197,11 @@ class ChanLun_BTC_15(IStrategy):
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def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
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state_str = 'resample_{}_state'.format(self.get_ticker_indicator()*self.time5)
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fx_str = 'resample_{}_fx'.format(self.get_ticker_indicator()*self.time5)
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#state_str = 'state'
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#fx_str = 'fx'
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dataframe.loc[
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(
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#(dataframe['state']== "30")
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(dataframe[state_str].shift(self.time5*2) > 0) &
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(dataframe[fx_str].shift(self.time5*2) == 1)
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(dataframe[state_str].shift(self.time5) > 1.0) &
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(dataframe[fx_str].shift(self.time5) == 1)
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#(dataframe['resample_{}_state'.format(self.get_ticker_indicator()*self.time30)] == "10") &
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#(dataframe['resample_{}_state'.format(self.get_ticker_indicator()*self.time60)] == "10")
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),
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@@ -215,8 +209,8 @@ class ChanLun_BTC_15(IStrategy):
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dataframe.loc[
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(
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#(dataframe['state']== "30")
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(dataframe[state_str].shift(self.time5*2) > 0) &
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(dataframe[fx_str].shift(self.time5*2) == -1)
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(dataframe[state_str].shift(self.time5) > 1.0) &
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(dataframe[fx_str].shift(self.time5) == -1)
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#(dataframe['resample_{}_state'.format(self.get_ticker_indicator()*self.time30)] == "10") &
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#(dataframe['resample_{}_state'.format(self.get_ticker_indicator()*self.time60)] == "10")
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),
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