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zhangkun9038@dingtalk.com
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@ -53,21 +53,21 @@ class FreqaiPrimer(IStrategy):
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"ema200": {"color": "blue"},
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"bb_upperband": {"color": "gray"},
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"bb_lowerband": {"color": "gray"},
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"bb_middleband": {"color": "gray"}
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},
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"subplots": {
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"Signals": {
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"enter_long": {"color": "green"},
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"exit_long": {"color": "red"}
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"enter_long": {"color": "green", "type": "scatter"},
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"exit_long": {"color": "red", "type": "scatter"}
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},
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"Price-Value Divergence": {
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"&-price_value_divergence": {"color": "purple"}
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"Indicators": {
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"&-price_value_divergence": {"color": "purple"},
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"volume_z_score": {"color": "orange"},
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"rsi": {"color": "cyan"},
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"stochrsi_k": {"color": "magenta"},
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},
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"Volume Z-Score": {
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"volume_z_score": {"color": "orange"}
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},
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"RSI": {
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"rsi": {"color": "cyan"}
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"Bearish Signals": {
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"bearish_signal": {"type": "bar", "color": "red"},
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"stochrsi_overbought": {"type": "bar", "color": "orange"},
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}
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}
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}
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@ -156,9 +156,9 @@ class FreqaiPrimer(IStrategy):
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dataframe["volume_mean_20"] = dataframe["volume"].rolling(20).mean()
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dataframe["volume_std_20"] = dataframe["volume"].rolling(20).std()
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dataframe["volume_z_score"] = (dataframe["volume"] - dataframe["volume_mean_20"]) / dataframe["volume_std_20"]
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dataframe["volume_z_score"] = dataframe["volume_z_score"].replace([np.inf, -np.inf], 0).ffill().fillna(0)
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dataframe["&-price_value_divergence"] = dataframe["&-price_value_divergence"].replace([np.inf, -np.inf], 0).ffill().fillna(0)
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dataframe["volume_z_score"] = dataframe["volume_z_score"].replace([np.inf, -np.inf], 0).ffill().fillna(0)
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return dataframe
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def is_stochrsi_overbought(self, dataframe: DataFrame, period=10, threshold=85) -> bool:
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@ -172,50 +172,62 @@ class FreqaiPrimer(IStrategy):
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avg_stochrsi = dataframe['stochrsi_k'].rolling(window=period).mean()
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return avg_stochrsi > threshold
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def is_bearish_market(self, dataframe: DataFrame, metadata: dict, timeframe: str = "4h") -> DataFrame:
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def is_bearish_market(self, dataframe: DataFrame, metadata: dict, timeframe: str = "4h") -> pd.Series:
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"""
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判断是否为熊市信号（使用已有的 4h 指标）
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返回一个与 dataframe 等长的布尔 Series
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"""
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pair = metadata.get('pair', 'Unknown')
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logger.debug(f"[{pair}] 开始计算 is_bearish_market")
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# 防御性检查
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required_columns = ['close_4h', 'high_4h', 'low_4h', 'open_4h', 'stochrsi_k_4h', 'stochrsi_d_4h', 'bb_middle_4h']
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missing = [col for col in required_columns if col not in dataframe.columns]
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if missing:
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logger.error(f"[{pair}] 缺少必要列：{missing}，返回全 False")
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return pd.Series([False] * len(dataframe), index=dataframe.index)
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# 条件1：价格低于布林带中轨
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cond1 = dataframe['close'] < dataframe['bb_middle']
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cond1 = dataframe['close_4h'] < dataframe['bb_middle_4h']
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# 条件2：STOCHRSI 超买后反转（K > 80 并开始向下交叉 D）
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cond2 = (dataframe['stochrsi_k'] > 80) & (dataframe['stochrsi_k'] < dataframe['stochrsi_d'])
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# 条件2：STOCHRSI 超买后反转
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stochrsi_k = dataframe['stochrsi_k_4h']
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stochrsi_d = dataframe['stochrsi_d_4h']
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cond2 = (stochrsi_k > 80) & (stochrsi_k < stochrsi_d)
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# 条件3：出现看跌蜡烛图形态（如乌云盖顶、看跌吞没等）
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def detect_candlestick_bearish(df, i):
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open = df['open'].iloc[i]
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high = df['high'].iloc[i]
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low = df['low'].iloc[i]
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close = df['close'].iloc[i]
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prev_open = df['open'].iloc[i - 1] if i > 0 else open
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prev_close = df['close'].iloc[i - 1] if i > 0 else close
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# 条件3：看跌蜡烛图形态
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open = dataframe['open_4h']
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close = dataframe['close_4h']
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high = dataframe['high_4h']
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low = dataframe['low_4h']
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prev_open = open.shift(1)
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prev_close = close.shift(1)
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# 看跌吞没形态
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if open < prev_close and close > prev_open and close < prev_close:
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return True
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# 乌云盖顶
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if close < prev_open and open > prev_close and close < ((prev_open + prev_close) / 2):
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return True
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# 射击之星
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body = abs(open - close)
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upper_wick = high - max(open, close)
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lower_wick = min(open, close) - low
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if upper_wick > 2 * body and lower_wick < body:
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return True
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# 看跌吞没形态
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cond_engulfing = (
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(open < prev_close) &
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(close > prev_open) &
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(close < prev_close)
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)
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return False
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# 乌云盖顶
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cond_dark_cloud_cover = (
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(close < prev_open) &
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(open > prev_close) &
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(close < (prev_open + prev_close) / 2)
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)
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# 在 dataframe 上逐行应用蜡烛图识别
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bearish_candle = pd.Series(index=dataframe.index, dtype=bool)
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for i in range(len(dataframe)):
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bearish_candle.iloc[i] = detect_candlestick_bearish(dataframe, i)
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# 射击之星
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body = abs(open - close)
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upper_wick = high - np.maximum(open, close)
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lower_wick = np.minimum(open, close) - low
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cond_shooting_star = (upper_wick > 2 * body) & (lower_wick < body)
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# 构造最终的熊市信号
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bearish_candle = cond_engulfing | cond_dark_cloud_cover | cond_shooting_star
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# 最终熊市信号
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bearish_signal = cond1 & cond2 & bearish_candle
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logger.debug(f"[{pair}] 熊市信号生成完成，共 {bearish_signal.sum()} 根 K 线符合")
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return bearish_signal
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def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
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@ -261,9 +273,10 @@ class FreqaiPrimer(IStrategy):
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dataframe_4h['bb_middle'] = middleband
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dataframe_4h['bb_lower'] = lowerband
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# 将 4h 指标映射回主时间框架（3m）
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for col in ['stochrsi_k', 'stochrsi_d', 'bb_upper', 'bb_middle', 'bb_lower']:
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dataframe[col + '_4h'] = dataframe_4h[col].reindex(dataframe.index, method='ffill').fillna(method='bfill')
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# 映射 OHLC 和其他指标到主时间框架，添加 _4h 后缀
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for col in ['open', 'high', 'low', 'close', 'stochrsi_k', 'stochrsi_d', 'bb_upper', 'bb_middle', 'bb_lower']:
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new_col = f"{col}_4h"
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dataframe[new_col] = dataframe_4h[col].reindex(dataframe.index, method='ffill').bfill()
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# 数据清理
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for col in ["ema200", "bb_upperband", "bb_middleband", "bb_lowerband", "rsi", "volume_z_score", "&-price_value_divergence", "price_value_divergence"]:
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@ -379,7 +392,11 @@ class FreqaiPrimer(IStrategy):
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stochrsi_threshold = self.linear_map(trend_score, 0, 100, stochrsi_max, stochrsi_min)
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# 获取 4h 时间框架的数据
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dataframe_4h = self.dp.get_pair_dataframe(pair=pair, timeframe="4h")
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dataframe_4h = dataframe[['close', 'stochrsi_k_4h', 'stochrsi_d_4h', 'bb_middle_4h', 'open']].copy()
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bearish_signal = self.is_bearish_market(dataframe_4h, metadata, timeframe="4h")
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bearish_signal_aligned = bearish_signal.reindex(dataframe.index, method='ffill').fillna(False)
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cond6 = ~bearish_signal_aligned
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# 确保指标存在（或提前在 populate_indicators 中计算好）
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if not dataframe_4h.empty and 'stochrsi_k' in dataframe_4h.columns:
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stochrsi_overbought = self.is_stochrsi_overbought(dataframe_4h, period=10, threshold=85)
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@ -393,14 +410,22 @@ class FreqaiPrimer(IStrategy):
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dataframe_4h['stochrsi_k'] = stochrsi['fastk']
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dataframe_4h['stochrsi_d'] = stochrsi['fastd']
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real = ta.TYPPRICE(dataframe_4h)
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upperband, middleband, lowerband = ta.BBANDS(real, timeperiod=20, nbdevup=2.0, nbdevdn=2.0)
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dataframe_4h['bb_upper'] = upperband
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dataframe_4h['bb_middle'] = middleband
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dataframe_4h['bb_lower'] = lowerband
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# 在 populate_entry_trend 中
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high = dataframe['high_4h'].values
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low = dataframe['low_4h'].values
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close = dataframe['close_4h'].values
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# 使用已经准备好的 dataframe_4h
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bearish_signal = self.is_bearish_market(dataframe_4h, metadata, timeframe="4h")
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# 手动实现 TYPPRICE
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real = (high + low + close) / 3
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upperband, middleband, lowerband = ta.BBANDS(real, timeperiod=20, nbdevup=2.0, nbdevdn=2.0)
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# 将结果放回 dataframe
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dataframe["bb_upperband-period"] = upperband
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dataframe["bb_middleband-period"] = middleband
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dataframe["bb_lowerband-period"] = lowerband
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# 调用熊市判断函数
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bearish_signal = self.is_bearish_market(dataframe, metadata, timeframe="4h")
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# 映射回主时间框架
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dataframe['bearish_signal'] = bearish_signal.reindex(dataframe.index, method='ffill').fillna(False)
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@ -427,34 +452,29 @@ class FreqaiPrimer(IStrategy):
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cond4 = (dataframe["close"] <= dataframe["bb_lowerband"])
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cond5 = (dataframe["stochrsi_k"] < stochrsi_threshold)
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cond6 = ~self.is_bearish_market(dataframe_4h, metadata, timeframe="4h")
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# cond7 定义
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cond7 = ~stochrsi_overbought_aligned
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buy_condition = cond1 & cond2 & cond3 & cond4 & cond5 & cond6 & cond7
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#buy_condition = cond1 & cond2 & cond3 & cond4 & cond5
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conditions.append(buy_condition)
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logger.debug(f"[{pair}] 买入条件检查 - "
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f"&-price_value_divergence={divergence_value:.6f} < {self.buy_threshold:.6f}: {cond1.iloc[-1]}, "
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f"volume_z_score={volume_z_score_value:.2f} > {volume_z_score_threshold:.2f}: {cond2.iloc[-1]}, "
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f"rsi={rsi_value:.2f} < {rsi_threshold:.2f}: {cond3.iloc[-1]}, "
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f"close={bb_close_value:.6f} <= bb_lowerband={bb_lower_value:.6f}: {cond4.iloc[-1]}, "
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f"stochrsi_k={stochrsi_value:.2f} < {stochrsi_threshold:.2f}: {cond5.iloc[-1]}, "
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f"非熊市={cond6.iloc[-1]}, "
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f"STOCHRSI未持续超买={cond7.iloc[-1]}")
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bearish_signal = cond6.iloc[-1]
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# logger.debug(f"[{pair}] 买入条件检查 - "
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# f"&-price_value_divergence={divergence_value:.6f} < {self.buy_threshold:.6f}: {cond1.iloc[-1]}, "
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# f"volume_z_score={volume_z_score_value:.2f} > {volume_z_score_threshold:.2f}: {cond2.iloc[-1]}, "
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# f"rsi={rsi_value:.2f} < {rsi_threshold:.2f}: {cond3.iloc[-1]}, "
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# f"close={bb_close_value:.6f} <= bb_lowerband={bb_lower_value:.6f}: {cond4.iloc[-1]}, "
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# f"stochrsi_k={stochrsi_value:.2f} < {stochrsi_threshold:.2f}: {cond5.iloc[-1]}, "
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# f"非熊市={cond6.iloc[-1]}, "
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# f"STOCHRSI未持续超买={cond7.iloc[-1]}")
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# bearish_signal = cond6.iloc[-1]
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buy_condition = cond1 & cond2 & cond3 & cond4 & cond5 & cond6
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conditions.append(buy_condition)
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logger.debug(f"[{pair}] 买入条件检查 - "
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f"&-price_value_divergence={divergence_value:.6f} < {self.buy_threshold:.6f}: {cond1.iloc[-1]}, "
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f"volume_z_score={volume_z_score_value:.2f} > {volume_z_score_threshold:.2f}: {cond2.iloc[-1]}, "
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f"rsi={rsi_value:.2f} < {rsi_threshold:.2f}: {cond3.iloc[-1]}, "
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f"close={bb_close_value:.6f} <= bb_lowerband={bb_lower_value:.6f}: {cond4.iloc[-1]}, "
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f"stochrsi_k={stochrsi_value:.2f} < {stochrsi_threshold:.2f}: {cond5.iloc[-1]}, "
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f"非熊市={bearish_signal}")
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# logger.debug(f"[{pair}] 买入条件检查 - "
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# f"&-price_value_divergence={divergence_value:.6f} < {self.buy_threshold:.6f}: {cond1.iloc[-1]}, "
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# f"volume_z_score={volume_z_score_value:.2f} > {volume_z_score_threshold:.2f}: {cond2.iloc[-1]}, "
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# f"rsi={rsi_value:.2f} < {rsi_threshold:.2f}: {cond3.iloc[-1]}, "
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# f"close={bb_close_value:.6f} <= bb_lowerband={bb_lower_value:.6f}: {cond4.iloc[-1]}, "
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# f"stochrsi_k={stochrsi_value:.2f} < {stochrsi_threshold:.2f}: {cond5.iloc[-1]}, "
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# f"非熊市={bearish_signal}")
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else:
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logger.warning(f"[{pair}] ⚠️ &-price_value_divergence 列缺失，跳过买入信号生成")
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