Change config
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@@ -12,6 +12,7 @@ import freqtrade.vendor.qtpylib.indicators as qtpylib
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from technical.util import resample_to_interval, resampled_merge
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from technical.util import resample_to_interval, resampled_merge
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from freqtrade.persistence import Trade, Order
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from freqtrade.persistence import Trade, Order
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from datetime import datetime, timedelta
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from datetime import datetime, timedelta
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from typing import Optional
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import logging
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import logging
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logger = logging.getLogger(__name__)
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logger = logging.getLogger(__name__)
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# freqtrade plot-dataframe --strategy BB9033 --datadir user_data/data/binance -c ./user_data/ChanLun_SOL_30.json --timerange=20250309-
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# freqtrade plot-dataframe --strategy BB9033 --datadir user_data/data/binance -c ./user_data/ChanLun_SOL_30.json --timerange=20250309-
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@@ -40,10 +41,10 @@ class BB9033(IStrategy):
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INTERFACE_VERSION: int = 3
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INTERFACE_VERSION: int = 3
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# 策略参数
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# 策略参数
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bb_length = 54 # 布林带长度
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bb_length = 90 # 布林带长度
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atr_multiplier = 2.5 # ATR乘数(轨道)
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atr_multiplier = 4.2 # ATR乘数(轨道)
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atr_stop_multiplier = 5.6 # ATR乘数(止损)
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atr_stop_multiplier = 1.8 # ATR乘数(止损)
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atr_length = 17 # ATR计算周期
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atr_length = 14 # ATR计算周期
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# Minimal ROI designed for the strategy.
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# Minimal ROI designed for the strategy.
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# This attribute will be overridden if the config file contains "minimal_roi"
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# This attribute will be overridden if the config file contains "minimal_roi"
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@@ -58,10 +59,10 @@ class BB9033(IStrategy):
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# Optimal timeframe for the strategy
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# Optimal timeframe for the strategy
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timeframe = '3m'
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timeframe = '3m'
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time3 = 60
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time = 30
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# Trailing stop loss
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# Trailing stop loss
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trailing_stop = False
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trailing_stop = False
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lev = 1.0
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# Run "populate_indicators" only for new candle
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# Run "populate_indicators" only for new candle
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process_only_new_candles = False
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process_only_new_candles = False
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@@ -75,7 +76,7 @@ class BB9033(IStrategy):
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"""
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"""
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计算技术指标
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计算技术指标
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"""
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"""
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dataframe_3 = resample_to_interval(dataframe, self.get_ticker_indicator() * self.time3)
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dataframe_3 = resample_to_interval(dataframe, self.get_ticker_indicator() * self.time)
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# 计算ATR(用于止损计算)
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# 计算ATR(用于止损计算)
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dataframe_3['atr'] = ta.ATR(dataframe_3, timeperiod=self.atr_length)
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dataframe_3['atr'] = ta.ATR(dataframe_3, timeperiod=self.atr_length)
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@@ -84,7 +85,8 @@ class BB9033(IStrategy):
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bb_upper, bb_middle, bb_lower = ta.BBANDS(dataframe_3['close'], timeperiod=self.bb_length, nbdevup=self.atr_multiplier, nbdevdn=self.atr_multiplier, matype=0)
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bb_upper, bb_middle, bb_lower = ta.BBANDS(dataframe_3['close'], timeperiod=self.bb_length, nbdevup=self.atr_multiplier, nbdevdn=self.atr_multiplier, matype=0)
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dataframe_3['bb_upper'] = bb_upper
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dataframe_3['bb_upper'] = bb_upper
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dataframe_3['bb_lower'] = bb_lower
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dataframe_3['bb_lower'] = bb_lower
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for i in range(1700, 1800):
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print(dataframe_3.iloc[i])
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# 计算突破条件(与Pine Script保持一致)
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# 计算突破条件(与Pine Script保持一致)
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# 确保所有用于计算的数据都不是NaN
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# 确保所有用于计算的数据都不是NaN
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valid_data = (
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valid_data = (
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@@ -113,8 +115,8 @@ class BB9033(IStrategy):
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"""
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"""
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Based on TA indicators, populates the entry trend columns
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Based on TA indicators, populates the entry trend columns
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"""
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"""
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break_below_lower = 'resample_{}_break_below_lower'.format(self.get_ticker_indicator()*self.time3)
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break_below_lower = 'resample_{}_break_below_lower'.format(self.get_ticker_indicator()*self.time)
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break_above_upper = 'resample_{}_break_above_upper'.format(self.get_ticker_indicator()*self.time3)
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break_above_upper = 'resample_{}_break_above_upper'.format(self.get_ticker_indicator()*self.time)
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# 做多条件:价格跌破下轨
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# 做多条件:价格跌破下轨
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dataframe.loc[
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dataframe.loc[
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@@ -138,8 +140,8 @@ class BB9033(IStrategy):
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"""
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"""
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Based on TA indicators, populates the exit trend columns
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Based on TA indicators, populates the exit trend columns
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"""
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"""
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bb_upper_str = 'resample_{}_bb_upper'.format(self.get_ticker_indicator()*self.time3)
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bb_upper_str = 'resample_{}_bb_upper'.format(self.get_ticker_indicator()*self.time)
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bb_lower_str = 'resample_{}_bb_lower'.format(self.get_ticker_indicator()*self.time3)
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bb_lower_str = 'resample_{}_bb_lower'.format(self.get_ticker_indicator()*self.time)
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# 多头止盈:价格突破上轨(与Pine Script一致)
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# 多头止盈:价格突破上轨(与Pine Script一致)
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dataframe.loc[
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dataframe.loc[
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@@ -215,9 +217,9 @@ class BB9033(IStrategy):
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latest_candle = dataframe.iloc[-1]
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latest_candle = dataframe.iloc[-1]
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# 使用重采样后的字段名
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# 使用重采样后的字段名
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bb_upper_str = 'resample_{}_bb_upper'.format(self.get_ticker_indicator() * self.time3)
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bb_upper_str = 'resample_{}_bb_upper'.format(self.get_ticker_indicator() * self.time)
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bb_lower_str = 'resample_{}_bb_lower'.format(self.get_ticker_indicator() * self.time3)
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bb_lower_str = 'resample_{}_bb_lower'.format(self.get_ticker_indicator() * self.time)
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atr_str = 'resample_{}_atr'.format(self.get_ticker_indicator() * self.time3)
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atr_str = 'resample_{}_atr'.format(self.get_ticker_indicator() * self.time)
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# 确保技术指标有效
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# 确保技术指标有效
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if (np.isnan(latest_candle[bb_upper_str]) or
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if (np.isnan(latest_candle[bb_upper_str]) or
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@@ -243,7 +245,7 @@ class BB9033(IStrategy):
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return
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return
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# 获取开仓时的ATR值
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# 获取开仓时的ATR值
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atr_str = 'resample_{}_atr'.format(self.get_ticker_indicator() * self.time3)
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atr_str = 'resample_{}_atr'.format(self.get_ticker_indicator() * self.time)
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# 找到最接近开仓时间的K线
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# 找到最接近开仓时间的K线
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open_candle = dataframe.iloc[-1] # 使用最新的K线作为开仓时的数据
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open_candle = dataframe.iloc[-1] # 使用最新的K线作为开仓时的数据
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@@ -275,6 +277,9 @@ class BB9033(IStrategy):
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if trade_id in self.trade_stop_prices:
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if trade_id in self.trade_stop_prices:
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del self.trade_stop_prices[trade_id]
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del self.trade_stop_prices[trade_id]
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logger.info(f"交易 {trade.id} 已关闭,清理止损价格记录")
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logger.info(f"交易 {trade.id} 已关闭,清理止损价格记录")
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def leverage(self, pair: str, current_time: datetime, current_rate: float,
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proposed_leverage: float, max_leverage: float, entry_tag: Optional[str], side: str,
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**kwargs) -> float:
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return self.lev
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def get_ticker_indicator(self):
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def get_ticker_indicator(self):
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return int(self.timeframe[:-1])
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return int(self.timeframe[:-1])
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