出场置信度
This commit is contained in:
zhangkun9038@dingtalk.com
parent
9c77455e1b
commit
beea456d0f
@ -57,14 +57,28 @@
|
||||
"enabled": true,
|
||||
"identifier": "freqai_primer_mixed",
|
||||
"model": "LightGBMRegressor",
|
||||
"purge_old_models": 2,
|
||||
"train_period_days": 15,
|
||||
"backtest_period_days": 3,
|
||||
"feature_parameters": {
|
||||
"include_timeframes": ["3m", "15m", "1h"],
|
||||
"include_shifted_candles": 2,
|
||||
"label_period_candles": 12
|
||||
"label_period_candles": 12,
|
||||
"include_corr_pairlist": [],
|
||||
"DI_threshold": 0.9,
|
||||
"weight_factor": 0.9,
|
||||
"principal_component_analysis": false,
|
||||
"use_SVM_to_remove_outliers": true,
|
||||
"svm_params": {
|
||||
"shuffle": false,
|
||||
"nu": 0.1
|
||||
},
|
||||
"use_DBSCAN_to_remove_outliers": false
|
||||
},
|
||||
"data_split_parameters": {
|
||||
"test_size": 0.2,
|
||||
"shuffle": false
|
||||
"test_size": 0.25,
|
||||
"shuffle": false,
|
||||
"random_state": 1
|
||||
},
|
||||
"model_training_parameters": {
|
||||
"price_value_divergence": {
|
||||
|
||||
42
docs/更新.md
Normal file
42
docs/更新.md
Normal file
@ -0,0 +1,42 @@
|
||||
# FreqAI Primer 策略更新日志
|
||||
|
||||
## 2025-12-23: ML 审核官逻辑优化
|
||||
|
||||
### 核心变更
|
||||
将 ML 审核官（exit_signal 置信度判断）从 **入场过滤** 改为 **出场过滤**，实现更激进的持仓策略。
|
||||
|
||||
### 具体改动
|
||||
|
||||
#### 1. 移除入场阶段的 ML 审核官
|
||||
- **旧逻辑**：在 `confirm_trade_entry` 中，若 `exit_signal` 概率高（容易下跌），则拒绝入场
|
||||
- **问题**：这会错过很多有效入场机会，因为短期波动不代表整体趋势
|
||||
|
||||
#### 2. 新增出场阶段的 ML 审核官
|
||||
- **新逻辑**：在 `confirm_trade_exit` 中，只有当 `exit_signal` 概率 **>=** 阈值时才允许出场
|
||||
- **效果**：
|
||||
- 防止止盈过早，让利润充分增长
|
||||
- 在 AI 判断上涨概率高时强制继续持仓
|
||||
- 只在 AI 确认下跌信号强烈时才出场
|
||||
|
||||
#### 3. 参数说明
|
||||
- 使用现有 hyperopt 参数：`ml_exit_signal_threshold`（默认 0.65）
|
||||
- **入场时**（已移除）：exit_prob > 0.65 拒绝入场
|
||||
- **出场时**（新增）：exit_prob < 0.65 拒绝出场（继续持仓）
|
||||
|
||||
### 设计理念
|
||||
符合"让利润奔跑，截断亏损"的交易哲学：
|
||||
- 入场：依赖传统技术指标，保证信号充足
|
||||
- 出场：由 AI 审核，确保真正的趋势反转才离场
|
||||
|
||||
### 日志输出
|
||||
```
|
||||
[BTC/USDT] ML 审核官拒绝出场: exit_signal 概率 0.35 < 阈值 0.65（上涨概率高，继续持仓）, 出场原因: roi
|
||||
[ETH/USDT] ML 审核官允许出场: exit_signal 概率 0.78 >= 阈值 0.65, 出场原因: sell_signal
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 使用建议
|
||||
1. 回测时观察是否会导致持仓时间过长
|
||||
2. 如果发现过度持仓，可以降低 `ml_exit_signal_threshold` 阈值（如 0.55）
|
||||
3. 如果出场过于频繁，可以提高阈值（如 0.75）
|
||||
@ -743,39 +743,7 @@ class FreqaiPrimer(IStrategy):
|
||||
#logger.info(f"[{pair}] 由于检测到剧烈拉升，取消入场交易")
|
||||
allow_trade = False
|
||||
|
||||
# 检查3：ML 审核官（FreqAI 过滤低质量入场）
|
||||
# 逻辑：用 exit_signal 概率来判断——若"退出概率高"说明价格容易跌，则拒绝入场
|
||||
if allow_trade:
|
||||
try:
|
||||
df, _ = self.dp.get_analyzed_dataframe(pair, self.timeframe)
|
||||
if len(df) > 0:
|
||||
last_row = df.iloc[-1]
|
||||
exit_prob = None
|
||||
|
||||
# 优先使用 FreqAI 的 exit_signal 预测列（例如 &-exit_signal_prob 或 &-exit_signal）
|
||||
if '&-exit_signal_prob' in df.columns:
|
||||
exit_prob = float(last_row['&-exit_signal_prob'])
|
||||
elif '&-s-exit_signal_prob' in df.columns:
|
||||
exit_prob = float(last_row['&-s-exit_signal_prob'])
|
||||
elif '&-exit_signal' in df.columns:
|
||||
val = last_row['&-exit_signal']
|
||||
if isinstance(val, (int, float)):
|
||||
exit_prob = float(val)
|
||||
else:
|
||||
# 文本标签时，简单映射为 0/1
|
||||
exit_prob = 1.0 if str(val).lower() in ['exit', 'sell', '1'] else 0.0
|
||||
|
||||
if exit_prob is not None:
|
||||
# 阈值：如果"应该退出"的概率 > 阈值，说明价格很可能下跌，拒绝入场
|
||||
# 使用 hyperopt 参数，默认 0.65（比之前的 0.5 更宽松）
|
||||
exit_threshold = self.ml_exit_signal_threshold.value
|
||||
if exit_prob > exit_threshold:
|
||||
logger.info(f"[{pair}] ML 审核官拒绝入场: exit_signal 概率 {exit_prob:.2f} > 阈值 {exit_threshold:.2f}（容易下跌，不宜入场）")
|
||||
allow_trade = False
|
||||
# else:
|
||||
# logger.info(f"[{pair}] ML 审核官允许入场: exit_signal 概率 {exit_prob:.2f} <= {exit_threshold:.2f}")
|
||||
except Exception as e:
|
||||
logger.warning(f"[{pair}] ML 审核官检查失败，忽略 ML 过滤: {e}")
|
||||
# 注：ML 审核官逻辑已移动到 confirm_trade_exit 中，用于过滤出场
|
||||
|
||||
# 如果允许交易，更新最后一次入场时间并输出价格信息
|
||||
if allow_trade:
|
||||
@ -788,6 +756,58 @@ class FreqaiPrimer(IStrategy):
|
||||
|
||||
# 如果没有阻止因素，允许交易
|
||||
return allow_trade
|
||||
|
||||
def confirm_trade_exit(
|
||||
self,
|
||||
pair: str,
|
||||
trade: 'Trade',
|
||||
order_type: str,
|
||||
amount: float,
|
||||
rate: float,
|
||||
time_in_force: str,
|
||||
exit_reason: str,
|
||||
current_time: datetime,
|
||||
**kwargs,
|
||||
) -> bool:
|
||||
"""
|
||||
交易卖出前的确认函数，用于最终决定是否执行出场
|
||||
此处使用 ML 审核官（exit_signal 置信度）过滤出场
|
||||
"""
|
||||
# 默认允许出场
|
||||
allow_exit = True
|
||||
|
||||
try:
|
||||
df, _ = self.dp.get_analyzed_dataframe(pair, self.timeframe)
|
||||
if len(df) > 0:
|
||||
last_row = df.iloc[-1]
|
||||
exit_prob = None
|
||||
|
||||
# 优先使用 FreqAI 的 exit_signal 预测列
|
||||
if '&-exit_signal_prob' in df.columns:
|
||||
exit_prob = float(last_row['&-exit_signal_prob'])
|
||||
elif '&-s-exit_signal_prob' in df.columns:
|
||||
exit_prob = float(last_row['&-s-exit_signal_prob'])
|
||||
elif '&-exit_signal' in df.columns:
|
||||
val = last_row['&-exit_signal']
|
||||
if isinstance(val, (int, float)):
|
||||
exit_prob = float(val)
|
||||
else:
|
||||
# 文本标签时，简单映射为 0/1
|
||||
exit_prob = 1.0 if str(val).lower() in ['exit', 'sell', '1'] else 0.0
|
||||
|
||||
if exit_prob is not None:
|
||||
# ML 审核官逻辑：只有当 exit_signal 概率足够高时才允许出场
|
||||
# 使用 hyperopt 参数，默认 0.65
|
||||
exit_threshold = self.ml_exit_signal_threshold.value
|
||||
if exit_prob < exit_threshold:
|
||||
logger.info(f"[{pair}] ML 审核官拒绝出场: exit_signal 概率 {exit_prob:.2f} < 阈值 {exit_threshold:.2f}（上涨概率高，继续持仓）, 出场原因: {exit_reason}")
|
||||
allow_exit = False
|
||||
else:
|
||||
logger.info(f"[{pair}] ML 审核官允许出场: exit_signal 概率 {exit_prob:.2f} >= 阈值 {exit_threshold:.2f}, 出场原因: {exit_reason}")
|
||||
except Exception as e:
|
||||
logger.warning(f"[{pair}] ML 审核官出场检查失败，允许出场: {e}")
|
||||
|
||||
return allow_exit
|
||||
|
||||
def custom_stoploss(self, pair: str, trade: 'Trade', current_time, current_rate: float,
|
||||
current_profit: float, **kwargs) -> float:
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user