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hyperopted

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zhangkun9038@dingtalk.com 2025-09-07 23:42:47 +08:00
parent 34238eb875
commit a74000e3ba
1 changed files with 17 additions and 8 deletions
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freqtrade/templates/freqaiprimer.py
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@ -87,6 +87,15 @@ class FreqaiPrimer(IStrategy):
rsi_overbought = IntParameter(50, 70, default=58, optimize=True, load=True, space='buy')
rsi_oversold = IntParameter(30, 50, default=42, optimize=True, load=True, space='buy')
# 入场条件阈值参数
bb_lower_deviation = DecimalParameter(1.01, 1.05, decimals=2, default=1.03, optimize=True, load=True, space='buy')
rsi_bull_threshold = IntParameter(45, 55, default=50, optimize=True, load=True, space='buy')
stochrsi_bull_threshold = IntParameter(30, 40, default=35, optimize=True, load=True, space='buy')
stochrsi_neutral_threshold = IntParameter(20, 30, default=25, optimize=True, load=True, space='buy')
volume_multiplier = DecimalParameter(1.2, 2.0, decimals=1, default=1.5, optimize=True, load=True, space='buy')
bb_width_threshold = DecimalParameter(0.01, 0.03, decimals=3, default=0.02, optimize=True, load=True, space='buy')
min_condition_count = IntParameter(2, 4, default=3, optimize=True, load=True, space='buy')
# 剧烈拉升检测参数 - 使用Hyperopt可优化参数
h1_max_candles = IntParameter(100, 300, default=200, optimize=True, load=True, space='buy')
h1_rapid_rise_threshold = DecimalParameter(0.05, 0.15, decimals=3, default=0.11, optimize=True, load=True, space='buy')
@ -350,35 +359,35 @@ class FreqaiPrimer(IStrategy):
dataframe['prev_market_state'] = 'neutral'
# 条件1: 价格接近布林带下轨（允许一定偏差）
close_to_bb_lower_1h = (dataframe['close'] <= dataframe['bb_lower_1h'] * 1.03) # 放宽到3%偏差
close_to_bb_lower_1h = (dataframe['close'] <= dataframe['bb_lower_1h'] * self.bb_lower_deviation.value) # 可优化偏差
# 条件2: RSI 不高于阈值（根据市场状态动态调整）
# 为每一行创建动态阈值
rsi_condition_1h = dataframe.apply(lambda row:
row['rsi_1h'] < 50 if row['prev_market_state'] in ['strong_bull', 'weak_bull'] else row['rsi_1h'] < self.rsi_oversold.value,
row['rsi_1h'] < self.rsi_bull_threshold.value if row['prev_market_state'] in ['strong_bull', 'weak_bull'] else row['rsi_1h'] < self.rsi_oversold.value,
axis=1)
# 条件3: StochRSI 处于超卖区域（根据市场状态动态调整）
stochrsi_condition_1h = dataframe.apply(lambda row:
(row['stochrsi_k_1h'] < 35 and row['stochrsi_d_1h'] < 35) if row['prev_market_state'] in ['strong_bull', 'weak_bull']
else (row['stochrsi_k_1h'] < 25 and row['stochrsi_d_1h'] < 25),
(row['stochrsi_k_1h'] < self.stochrsi_bull_threshold.value and row['stochrsi_d_1h'] < self.stochrsi_bull_threshold.value) if row['prev_market_state'] in ['strong_bull', 'weak_bull']
else (row['stochrsi_k_1h'] < self.stochrsi_neutral_threshold.value and row['stochrsi_d_1h'] < self.stochrsi_neutral_threshold.value),
axis=1)
# 条件4: MACD 上升趋势
macd_condition_1h = dataframe['macd_1h'] > dataframe['macd_signal_1h']
# 条件5: 成交量显著放大（可选条件）
volume_spike = dataframe['volume'] > dataframe['volume_ma'] * 1.5
volume_spike = dataframe['volume'] > dataframe['volume_ma'] * self.volume_multiplier.value
# 条件6: 布林带宽度过滤（避免窄幅震荡）
bb_width = (dataframe['bb_upper_1h'] - dataframe['bb_lower_1h']) / dataframe['close']
bb_width_condition = bb_width > 0.02 # 布林带宽度大于2%
bb_width_condition = bb_width > self.bb_width_threshold.value # 可优化的布林带宽度阈值
# 辅助条件: 3m 和 15m 趋势确认（允许部分时间框架不一致）
trend_confirmation = (dataframe['trend_3m'] == 1) | (dataframe['trend_15m'] == 1)
# 合并所有条件（减少强制性条件）
# 至少满足5个条件中的3个
# 至少满足多个条件中的一定数量
condition_count = (
close_to_bb_lower_1h.astype(int) +
rsi_condition_1h.astype(int) +
@ -387,7 +396,7 @@ class FreqaiPrimer(IStrategy):
(volume_spike | bb_width_condition).astype(int) + # 成交量或布林带宽度满足其一即可
trend_confirmation.astype(int)
)
final_condition = condition_count >= 3
final_condition = condition_count >= self.min_condition_count.value
# 设置入场信号
dataframe.loc[final_condition, 'enter_long'] = 1