add more strategies
This commit is contained in:
jackyu66git
+58
-41
@@ -5,8 +5,12 @@ from typing import Dict, List
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from functools import reduce
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from pandas import DataFrame
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import numpy as np
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import pandas as pd
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# --------------------------------
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# 设置pandas选项以避免FutureWarning
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pd.set_option('future.no_silent_downcasting', True)
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import talib.abstract as ta
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import freqtrade.vendor.qtpylib.indicators as qtpylib
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from technical.util import resample_to_interval, resampled_merge
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@@ -28,38 +32,37 @@ logger = logging.getLogger(__name__)
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class BB9033(IStrategy):
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"""
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布林带ATR反转策略
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基于ATR动态调整布林带轨道，实现反转交易
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布林带反转策略（与Pine Script保持一致）
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基于EMA和标准差计算布林带，实现反转交易
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交易逻辑：
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- 做多：价格跌破下轨后反转
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- 做空：价格突破上轨后反转
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- 止盈：价格触及对侧轨道
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- 做多止盈：价格减去0.5倍ATR突破上轨
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- 做空止盈：价格跌破下轨
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- 止损：基于ATR动态设置
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"""
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INTERFACE_VERSION: int = 3
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# 策略参数
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bb_length = 90 # 布林带长度
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atr_multiplier = 4.2 # ATR乘数(轨道)
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atr_stop_multiplier = 1.8 # ATR乘数(止损)
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atr_length = 14 # ATR计算周期
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# 策略参数（与Pine Script保持一致）
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bb_length = 41 # 布林带长度
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atr_multiplier = 2.3 # 布林带倍数
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atr_stop_multiplier = 3 # 止损ATR倍数
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atr_length = 11 # ATR计算周期
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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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minimal_roi = {
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"0": 0.5
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}
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can_short = True
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# Optimal stoploss designed for the strategy
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# This attribute will be overridden if the config file contains "stoploss"
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stoploss = -0.3
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use_custom_stoploss = True
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# Optimal timeframe for the strategy
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timeframe = '3m'
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time = 30
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time = 5
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# Trailing stop loss
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trailing_stop = False
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lev = 1.0
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@@ -67,26 +70,27 @@ class BB9033(IStrategy):
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process_only_new_candles = False
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# Number of candles the strategy requires before producing valid signals
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startup_candle_count: int = max(bb_length, atr_length) + 10
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startup_candle_count: int = max(bb_length*time, atr_length*time) + 10
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# 存储每个交易的止损价格
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trade_stop_prices: Dict[str, float] = {}
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def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
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"""
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计算技术指标
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计算技术指标（与Pine Script保持一致）
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"""
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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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dataframe_3['atr'] = ta.ATR(dataframe_3, timeperiod=self.atr_length)
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# 计算布林带（使用标准方法：移动平均线 ± 标准差倍数）
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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_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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# 计算布林带（使用EMA作为基础，与Pine Script保持一致）
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bb_basis = ta.EMA(dataframe_3['close'], timeperiod=self.bb_length)
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bb_dev = self.atr_multiplier * ta.STDDEV(dataframe_3['close'], timeperiod=self.bb_length)
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dataframe_3['bb_upper'] = bb_basis + bb_dev
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dataframe_3['bb_middle'] = bb_basis
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dataframe_3['bb_lower'] = bb_basis - bb_dev
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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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valid_data = (
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@@ -98,16 +102,20 @@ class BB9033(IStrategy):
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dataframe_3['bb_lower'].shift(1).notna()
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)
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# 做空条件：价格突破上轨
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dataframe_3['break_above_upper'] = (
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(dataframe_3['close'] > dataframe_3['bb_upper']) &
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(dataframe_3['close'].shift(1) <= dataframe_3['bb_upper'].shift(1)) &
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valid_data
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)
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# 做多条件：价格跌破下轨
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dataframe_3['break_below_lower'] = (
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(dataframe_3['close'] < dataframe_3['bb_lower']) &
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(dataframe_3['close'].shift(1) >= dataframe_3['bb_lower'].shift(1)) &
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valid_data
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)
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dataframe = resampled_merge(dataframe, dataframe_3)
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return dataframe
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@@ -118,23 +126,25 @@ class BB9033(IStrategy):
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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.time)
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# 做多条件：价格跌破下轨
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# 检测多头信号：价格跌破下轨
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dataframe.loc[
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(
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(dataframe[break_below_lower] == True) & # 价格跌破下轨，明确检查True值
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(dataframe[break_below_lower].notna()) # 确保不是NaN
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(dataframe[break_below_lower] == True) &
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(pd.notna(dataframe[break_below_lower]))
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),
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'enter_long'] = 1
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['enter_long', 'enter_tag']] = (1, 'long_signal_chan')
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# 做空条件：价格突破上轨
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# 检测空头信号：价格突破上轨
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dataframe.loc[
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(
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(dataframe[break_above_upper] == True) & # 价格突破上轨，明确检查True值
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(dataframe[break_above_upper].notna()) # 确保不是NaN
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(dataframe[break_above_upper] == True) &
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(pd.notna(dataframe[break_above_upper]))
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),
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'enter_short'] = 1
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['enter_short', 'enter_tag']] = (1, 'short_signal_chan')
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return dataframe
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def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
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"""
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@@ -142,24 +152,30 @@ class BB9033(IStrategy):
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"""
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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.time)
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atr_str = 'resample_{}_atr'.format(self.get_ticker_indicator()*self.time)
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close_str = 'resample_{}_close'.format(self.get_ticker_indicator()*self.time)
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low_str = 'resample_{}_low'.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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# 做多止盈条件：价格突破上轨（与Pine Script保持一致）
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dataframe.loc[
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(
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(dataframe['close'] > dataframe[bb_upper_str]) & # 当前价格突破上轨
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(dataframe[bb_upper_str].notna()) & # 确保布林带上轨不是NaN
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(dataframe['close'].notna()) # 确保收盘价不是NaN
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(dataframe[close_str] > dataframe[bb_upper_str]) & # close-atr_value*0.5 > bb_upper
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(dataframe[bb_upper_str].notna()) & # 确保布林带上轨不是NaN
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(dataframe[close_str].notna()) & # 确保收盘价不是NaN
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(dataframe[atr_str].notna()) & # 确保ATR不是NaN
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(len(self.trade_stop_prices) > 0)
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),
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'exit_long'] = 1
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['exit_long', 'exit_tag']] = (1, 'long_close_signal_chan')
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# 空头止盈：价格跌破下轨（与Pine Script一致）
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# 做空止盈条件：价格跌破下轨（与Pine Script保持一致）
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dataframe.loc[
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(
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(dataframe['close'] < dataframe[bb_lower_str]) & # 当前价格跌破下轨
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(dataframe[bb_lower_str].notna()) & # 确保布林带下轨不是NaN
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(dataframe['close'].notna()) # 确保收盘价不是NaN
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(dataframe[low_str] < dataframe[bb_lower_str]) & # low < bb_lower
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(dataframe[bb_lower_str].notna()) & # 确保布林带下轨不是NaN
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(dataframe[low_str].notna()) & # 确保最低价不是NaN
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(len(self.trade_stop_prices) > 0)
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),
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'exit_short'] = 1
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['exit_short', 'exit_tag']] = (1, 'short_close_signal_chan')
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return dataframe
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@@ -180,8 +196,9 @@ class BB9033(IStrategy):
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if len(dataframe) < 2:
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return self.stoploss
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# 使用上一个K线的收盘价
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last_close = dataframe.iloc[-2]['close'] # 上一个完整K线的收盘价
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# 使用上一个K线的收盘价（重采样后的数据）
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close_str = 'resample_{}_close'.format(self.get_ticker_indicator()*self.time)
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last_close = dataframe.iloc[-2][close_str] # 上一个完整K线的收盘价
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stop_price = self.trade_stop_prices[trade_id]
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@@ -266,7 +283,7 @@ class BB9033(IStrategy):
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self.trade_stop_prices[str(trade.id)] = stop_price
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#logger.info(f"交易 {trade.id} 开仓，记录止损价格: {stop_price}, ATR: {atr_value}, 开仓价: {trade.open_rate}")
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#logger.info(f"{current_time} {pair} {trade.open_rate} {stop_price} {atr_value}")
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logger.info(f"{current_time} {pair} {trade.open_rate} {stop_price} {atr_value}")
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def trade_exit(self, pair: str, trade: Trade, order: Order, current_time: datetime,
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**kwargs) -> None:
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"""
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@@ -0,0 +1,295 @@
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# --- Do not remove these libs ---
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from freqtrade.strategy import IStrategy
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from typing import Dict, List
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from functools import reduce
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from pandas import DataFrame
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import numpy as np
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import pandas as pd
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# --------------------------------
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# 设置pandas选项以避免FutureWarning
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pd.set_option('future.no_silent_downcasting', True)
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import talib.abstract as ta
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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 freqtrade.persistence import Trade, Order
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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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logger = logging.getLogger(__name__)
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# freqtrade plot-dataframe --strategy BB90331 --datadir user_data/data/binance -c ./user_data/ChanLun_SOL_30.json --timerange=20250309-
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# freqtrade trade -c ./user_data/Chan/config/ChanLun_BTC_30.json --strategy BB90331 --strategy-path ./user_data/Chan/strategies
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# freqtrade backtesting -c ./user_data/Chan/config/ChanLun_BTC_30.json --strategy BB90331 --strategy-path ./user_data/Chan/strategies --timerange=20250623-
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# freqtrade download-data -c ./user_data/Chan/config/ChanLun_BTC_30.json -t 1m --pairs BTC/USDT:USDT --timerange=20250501-
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# freqtrade hyperopt --hyperopt-loss SharpeHyperOptLossDaily --spaces roi stoploss --strategy BB90331 --strategy-path ./user_data/Chan/strategies -c ./user_data/Chan/config/ChanLun_BTC_30.json -e 200 --timerange=20250201-20250401
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# sudo docker compose run --rm chan_btc backtesting -c ./user_data/Chan/config/ChanLun_BTC_30.json --strategy BB90331 --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_30.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_30.json --strategy BB90331 --strategy-path ./user_data/Chan/strategies
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class BB90331(IStrategy):
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"""
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布林带ATR反转策略
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基于ATR动态调整布林带轨道，实现反转交易
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交易逻辑：
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- 做多：价格跌破下轨后反转
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- 做空：价格突破上轨后反转
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- 止盈：价格触及对侧轨道
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- 止损：基于ATR动态设置
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"""
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INTERFACE_VERSION: int = 3
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# 策略参数
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bb_length = 90 # 布林带长度
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atr_multiplier = 3.0 # ATR乘数(轨道)
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atr_stop_multiplier = 1 # ATR乘数(止损)
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atr_length = 11 # ATR计算周期
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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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minimal_roi = {
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}
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can_short = True
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# Optimal stoploss designed for the strategy
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# This attribute will be overridden if the config file contains "stoploss"
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stoploss = -0.3
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use_custom_stoploss = True
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# Optimal timeframe for the strategy
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time =1
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# Trailing stop loss
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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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process_only_new_candles = False
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# Number of candles the strategy requires before producing valid signals
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startup_candle_count: int = max(bb_length*time, atr_length*time) + 10
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# 存储每个交易的止损价格
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trade_stop_prices: Dict[str, float] = {}
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# 信号确认机制相关变量 - 已删除，不再使用确认机制
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# first_signal_time: Optional = None
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# first_signal_type: Optional[str] = None # 'long' 或 'short'
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# signal_confirm_hours = 4 # 4小时内需要确认信号
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def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
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"""
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计算技术指标
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"""
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# 计算ATR（用于止损计算）
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dataframe['atr'] = ta.ATR(dataframe, timeperiod=self.atr_length)
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# 计算布林带（使用标准方法：移动平均线 ± 标准差倍数）
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bb_upper, bb_middle, bb_lower = ta.BBANDS(dataframe['close'], timeperiod=self.bb_length, nbdevup=self.atr_multiplier, nbdevdn=self.atr_multiplier, matype=0)
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dataframe['bb_upper'] = bb_upper
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dataframe['bb_middle'] = bb_middle
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dataframe['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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# 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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dataframe['close'].notna() &
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dataframe['bb_upper'].notna() &
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dataframe['bb_lower'].notna() &
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dataframe['close'].shift(1).notna() &
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dataframe['bb_upper'].shift(1).notna() &
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dataframe['bb_lower'].shift(1).notna()
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)
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dataframe['break_above_upper'] = (
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(dataframe['close'] > dataframe['bb_upper']) &
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(dataframe['close'].shift(1) <= dataframe['bb_upper'].shift(1)) &
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valid_data
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)
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dataframe['break_below_lower'] = (
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(dataframe['close'] < dataframe['bb_lower']) &
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(dataframe['close'].shift(1) >= dataframe['bb_lower'].shift(1)) &
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valid_data
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)
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return dataframe
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def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
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"""
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Based on TA indicators, populates the entry trend columns
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直接开仓策略：检测到信号立即开仓，不需要确认机制
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"""
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break_below_lower = 'break_below_lower'
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break_above_upper = 'break_above_upper'
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# 多头信号：价格跌破下轨后直接开仓
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dataframe.loc[
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(
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(dataframe[break_below_lower] == True) &
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(dataframe[break_below_lower].notna())
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),
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['enter_long', 'enter_tag']
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] = (1, 'long_signal_chan_direct')
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# 空头信号：价格突破上轨后直接开仓
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dataframe.loc[
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(
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(dataframe[break_above_upper] == True) &
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(dataframe[break_above_upper].notna())
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),
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['enter_short', 'enter_tag']
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] = (1, 'short_signal_chan_direct')
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return dataframe
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|
||||
def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
|
||||
"""
|
||||
Based on TA indicators, populates the exit trend columns
|
||||
"""
|
||||
bb_middle_str = 'bb_middle'
|
||||
|
||||
# 多头止盈：价格回到中轨时平仓
|
||||
dataframe.loc[
|
||||
(
|
||||
(dataframe['close'] >= dataframe[bb_middle_str]) & # 当前价格回到中轨
|
||||
(dataframe[bb_middle_str].notna()) & # 确保布林带中轨不是NaN
|
||||
(dataframe['close'].notna()) & # 确保收盘价不是NaN
|
||||
(len(self.trade_stop_prices) > 0)
|
||||
),
|
||||
['exit_long', 'exit_tag']] = (1, 'long_close_signal_chan')
|
||||
|
||||
# 空头止盈：价格回到中轨时平仓
|
||||
dataframe.loc[
|
||||
(
|
||||
(dataframe['close'] <= dataframe[bb_middle_str]) & # 当前价格回到中轨
|
||||
(dataframe[bb_middle_str].notna()) & # 确保布林带中轨不是NaN
|
||||
(dataframe['close'].notna()) & # 确保收盘价不是NaN
|
||||
(len(self.trade_stop_prices) > 0)
|
||||
),
|
||||
['exit_short', 'exit_tag']] = (1, 'short_close_signal_chan')
|
||||
|
||||
return dataframe
|
||||
|
||||
def custom_stoploss(self, pair: str, trade: Trade, current_time: datetime,
|
||||
current_rate: float, current_profit: float,
|
||||
after_fill: bool, **kwargs) -> float:
|
||||
"""
|
||||
自定义止损逻辑：使用开单时记录的ATR止损价格
|
||||
"""
|
||||
|
||||
# 检查是否有存储的止损价格
|
||||
trade_id = str(trade.id)
|
||||
if trade_id not in self.trade_stop_prices:
|
||||
return self.stoploss
|
||||
|
||||
# 获取最新的K线数据
|
||||
dataframe, _ = self.dp.get_analyzed_dataframe(pair, self.timeframe)
|
||||
if len(dataframe) < 2:
|
||||
return self.stoploss
|
||||
|
||||
# 使用上一个K线的收盘价
|
||||
last_close = dataframe.iloc[-2]['close'] # 上一个完整K线的收盘价
|
||||
|
||||
stop_price = self.trade_stop_prices[trade_id]
|
||||
|
||||
if trade.is_short:
|
||||
# 空头止损：上一个K线收盘价超过止损价格时触发止损
|
||||
if last_close >= stop_price:
|
||||
stop_loss_pct = -abs((last_close - stop_price) / last_close)
|
||||
else:
|
||||
stop_loss_pct = 1.0 # 不触发止损
|
||||
else:
|
||||
# 多头止损：上一个K线收盘价低于止损价格时触发止损
|
||||
if last_close <= stop_price:
|
||||
stop_loss_pct = -abs((stop_price - last_close) / last_close)
|
||||
else:
|
||||
stop_loss_pct = 1.0 # 不触发止损
|
||||
|
||||
# 确保止损不会比默认止损更宽松
|
||||
return max(stop_loss_pct, self.stoploss)
|
||||
|
||||
def confirm_trade_entry(self, pair: str, order_type: str, amount: float, rate: float,
|
||||
time_in_force: str, current_time: datetime, entry_tag: str,
|
||||
side: str, **kwargs) -> bool:
|
||||
"""
|
||||
确认交易进场
|
||||
"""
|
||||
|
||||
# 获取最新数据进行最终确认
|
||||
dataframe, _ = self.dp.get_analyzed_dataframe(pair, self.timeframe)
|
||||
|
||||
if len(dataframe) == 0:
|
||||
return False
|
||||
|
||||
latest_candle = dataframe.iloc[-1]
|
||||
|
||||
# 使用重采样后的字段名
|
||||
bb_upper_str = 'bb_upper'
|
||||
bb_lower_str = 'bb_lower'
|
||||
atr_str = 'atr'
|
||||
|
||||
# 确保技术指标有效
|
||||
if (np.isnan(latest_candle[bb_upper_str]) or
|
||||
np.isnan(latest_candle[bb_lower_str]) or
|
||||
np.isnan(latest_candle[atr_str])):
|
||||
return False
|
||||
|
||||
return True
|
||||
|
||||
def order_filled(self, pair: str, trade: Trade, order: Order, current_time: datetime,
|
||||
**kwargs) -> None:
|
||||
"""
|
||||
当订单填充时的回调函数
|
||||
在开仓时记录基于开单时ATR的止损价格
|
||||
"""
|
||||
|
||||
# 处理开仓订单（包括做多和做空）
|
||||
if (order.ft_order_side == 'buy' or order.ft_order_side == 'sell') and trade.is_open:
|
||||
# 获取开仓时的数据
|
||||
dataframe, _ = self.dp.get_analyzed_dataframe(pair, self.timeframe)
|
||||
|
||||
if len(dataframe) == 0:
|
||||
return
|
||||
|
||||
# 获取开仓时的ATR值
|
||||
atr_str = 'atr'
|
||||
|
||||
# 找到最接近开仓时间的K线
|
||||
open_candle = dataframe.iloc[-1] # 使用最新的K线作为开仓时的数据
|
||||
atr_value = open_candle[atr_str]
|
||||
|
||||
if not np.isnan(atr_value) and atr_value > 0:
|
||||
# 计算止损价格并存储
|
||||
atr_stop_distance = self.atr_stop_multiplier * atr_value
|
||||
|
||||
if trade.is_short:
|
||||
# 空头止损：入场价 + ATR止损距离
|
||||
stop_price = trade.open_rate + atr_stop_distance
|
||||
else:
|
||||
# 多头止损：入场价 - ATR止损距离
|
||||
stop_price = trade.open_rate - atr_stop_distance
|
||||
|
||||
# 使用trade_id作为key存储止损价格
|
||||
self.trade_stop_prices[str(trade.id)] = stop_price
|
||||
|
||||
#logger.info(f"交易 {trade.id} 开仓，记录止损价格: {stop_price}, ATR: {atr_value}, 开仓价: {trade.open_rate}")
|
||||
logger.info(f"{current_time} {pair} {trade.open_rate} {stop_price} {atr_value}")
|
||||
def trade_exit(self, pair: str, trade: Trade, order: Order, current_time: datetime,
|
||||
**kwargs) -> None:
|
||||
"""
|
||||
当交易退出时的回调函数
|
||||
清理存储的止损价格记录
|
||||
"""
|
||||
trade_id = str(trade.id)
|
||||
if trade_id in self.trade_stop_prices:
|
||||
del self.trade_stop_prices[trade_id]
|
||||
logger.info(f"交易 {trade.id} 已关闭，清理止损价格记录")
|
||||
def leverage(self, pair: str, current_time: datetime, current_rate: float,
|
||||
proposed_leverage: float, max_leverage: float, entry_tag: Optional[str], side: str,
|
||||
**kwargs) -> float:
|
||||
return self.lev
|
||||
def get_ticker_indicator(self):
|
||||
return int(self.timeframe[:-1])
|
||||
@@ -1,32 +1,30 @@
|
||||
//@version=6
|
||||
strategy("布林带ATR反转策略", shorttitle="BBB_ATR", overlay=true, default_qty_type=strategy.percent_of_equity, default_qty_value=100, calc_on_every_tick=true)
|
||||
//@version=5
|
||||
strategy("布林带反转策略", shorttitle="BB_REV", overlay=true, default_qty_type=strategy.percent_of_equity, default_qty_value=100, calc_on_every_tick=true)
|
||||
|
||||
// 输入参数
|
||||
bb_length = input.int(90, "布林带长度", minval=10, maxval=200)
|
||||
atr_multiplier = input.float(3.0, "ATR乘数(轨道)", minval=1.0, maxval=10.0, step=0.1)
|
||||
atr_stop_multiplier = input.float(3.0, "ATR乘数(止损)", minval=0.5, maxval=5.0, step=0.1)
|
||||
atr_length = input.int(9, "ATR计算周期", minval=5, maxval=50)
|
||||
bb_length = input.int(41, "布林带长度", minval=10, maxval=200)
|
||||
bb_mult = input.float(2.3, "布林带倍数", minval=1.0, maxval=10.0, step=0.1)
|
||||
atr_length = input.int(11, "ATR计算周期", minval=5, maxval=90)
|
||||
atr_mult = input.float(3, "止损ATR倍数", minval=0.5, maxval=10.0, step=0.1)
|
||||
|
||||
// 显示设置
|
||||
show_bands = input.bool(true, "显示布林带")
|
||||
show_signals = input.bool(true, "显示信号")
|
||||
|
||||
// 计算移动平均线(中线)
|
||||
bb_middle = ta.sma(close, bb_length)
|
||||
// 计算布林带（保持标准差计算）
|
||||
bb_basis = ta.ema(close, bb_length)
|
||||
bb_dev = bb_mult * ta.stdev(close, bb_length)
|
||||
bb_upper = bb_basis + bb_dev
|
||||
bb_lower = bb_basis - bb_dev
|
||||
|
||||
// 计算ATR
|
||||
// 计算ATR（仅用于止损）
|
||||
atr_value = ta.atr(atr_length)
|
||||
|
||||
// 计算上下轨
|
||||
bb_upper = bb_middle + (atr_multiplier * atr_value)
|
||||
bb_lower = bb_middle - (atr_multiplier * atr_value)
|
||||
|
||||
// 显示布林带
|
||||
plot(show_bands ? bb_middle : na, "中线", color=color.blue, linewidth=2)
|
||||
plot(show_bands ? bb_basis : na, "中线", color=color.blue, linewidth=2)
|
||||
plot(show_bands ? bb_upper : na, "上轨", color=color.red, linewidth=2)
|
||||
plot(show_bands ? bb_lower : na, "下轨", color=color.green, linewidth=2)
|
||||
|
||||
|
||||
// 交易条件
|
||||
// 做空条件：价格突破上轨
|
||||
short_condition = close > bb_upper and close[1] <= bb_upper[1]
|
||||
@@ -35,10 +33,10 @@ short_condition = close > bb_upper and close[1] <= bb_upper[1]
|
||||
long_condition = close < bb_lower and close[1] >= bb_lower[1]
|
||||
|
||||
// 做空止盈条件：价格跌破下轨
|
||||
short_take_profit = close < bb_lower
|
||||
short_take_profit = low < bb_lower
|
||||
|
||||
// 做多止盈条件：价格突破上轨
|
||||
long_take_profit = close > bb_upper
|
||||
long_take_profit = close-atr_value*0.5 > bb_upper
|
||||
|
||||
// 记录入场价格和止损位
|
||||
var float long_entry_price = na
|
||||
@@ -51,12 +49,12 @@ if strategy.position_size == 0
|
||||
if long_condition
|
||||
strategy.entry("做多", strategy.long)
|
||||
long_entry_price := close
|
||||
long_stop_loss := close - (atr_stop_multiplier * atr_value)
|
||||
long_stop_loss := close - (atr_mult * atr_value)
|
||||
|
||||
if short_condition
|
||||
strategy.entry("做空", strategy.short)
|
||||
short_entry_price := close
|
||||
short_stop_loss := close + (atr_stop_multiplier * atr_value)
|
||||
short_stop_loss := close + (atr_mult * atr_value)
|
||||
|
||||
// 多头仓位管理
|
||||
if strategy.position_size > 0
|
||||
@@ -99,21 +97,20 @@ if show_signals
|
||||
plot(strategy.position_size > 0 and not na(long_stop_loss) ? long_stop_loss : na, "多头止损", color=color.red, style=plot.style_linebr, linewidth=1)
|
||||
plot(strategy.position_size < 0 and not na(short_stop_loss) ? short_stop_loss : na, "空头止损", color=color.red, style=plot.style_linebr, linewidth=1)
|
||||
|
||||
|
||||
// 信息表格
|
||||
if barstate.islast
|
||||
var table info_table = table.new(position.top_right, 2, 10, bgcolor=color.white, border_width=1)
|
||||
table.cell(info_table, 0, 0, "布林带ATR反转策略", text_color=color.black, bgcolor=color.gray)
|
||||
table.cell(info_table, 0, 0, "布林带反转策略", text_color=color.black, bgcolor=color.gray)
|
||||
table.cell(info_table, 1, 0, "", text_color=color.black, bgcolor=color.gray)
|
||||
|
||||
table.cell(info_table, 0, 1, "布林带长度", text_color=color.black)
|
||||
table.cell(info_table, 1, 1, str.tostring(bb_length), text_color=color.black)
|
||||
|
||||
table.cell(info_table, 0, 2, "ATR轨道乘数", text_color=color.black)
|
||||
table.cell(info_table, 1, 2, str.tostring(atr_multiplier), text_color=color.black)
|
||||
table.cell(info_table, 0, 2, "布林带倍数", text_color=color.black)
|
||||
table.cell(info_table, 1, 2, str.tostring(bb_mult), text_color=color.black)
|
||||
|
||||
table.cell(info_table, 0, 3, "ATR止损乘数", text_color=color.black)
|
||||
table.cell(info_table, 1, 3, str.tostring(atr_stop_multiplier), text_color=color.black)
|
||||
table.cell(info_table, 0, 3, "ATR止损倍数", text_color=color.black)
|
||||
table.cell(info_table, 1, 3, str.tostring(atr_mult), text_color=color.black)
|
||||
|
||||
table.cell(info_table, 0, 4, "当前ATR", text_color=color.black)
|
||||
table.cell(info_table, 1, 4, str.tostring(math.round(atr_value, 4)), text_color=color.black)
|
||||
|
||||
Reference in New Issue
Block a user