去掉了看底牌代码, hyper优化后年化27%, 若不hyperopt优化直接跑输

config_examples/freqaiprimer.json

@@ -35,6 +35,10 @@
         },
         "pair_whitelist": [
             "BTC/USDT",
+            "ETH/USDT",
+            "TON/USDT",
+            "OKB/USDT",
+            "DOT/USDT",
             "SOL/USDT"
         ],
         "pair_blacklist": []

freqtrade/templates/freqaiprimer.json

@@ -5,28 +5,28 @@
       "max_open_trades": 4
     },
     "buy": {
-      "buy_rsi": 39.01486243151008
+      "buy_rsi": 45.2500884290867
     },
     "sell": {
-      "sell_rsi": 69.01486243151008
+      "sell_rsi": 75.2500884290867
     },
     "protection": {},
     "roi": {
-      "0": 0.21500000000000002,
-      "8": 0.081,
-      "38": 0.028,
-      "57": 0
+      "0": 0.20400000000000001,
+      "18": 0.07100000000000001,
+      "47": 0.03,
+      "102": 0
     },
     "stoploss": {
-      "stoploss": -0.029
+      "stoploss": -0.07
     },
     "trailing": {
       "trailing_stop": true,
-      "trailing_stop_positive": 0.246,
-      "trailing_stop_positive_offset": 0.33799999999999997,
-      "trailing_only_offset_is_reached": true
+      "trailing_stop_positive": 0.237,
+      "trailing_stop_positive_offset": 0.267,
+      "trailing_only_offset_is_reached": false
     }
   },
   "ft_stratparam_v": 1,
-  "export_time": "2025-05-17 10:28:46.008125+00:00"
+  "export_time": "2025-05-17 11:42:41.193338+00:00"
 }

freqtrade/templates/freqaiprimer.py

@@ -124,8 +124,9 @@ class FreqaiPrimer(IStrategy):
                 dataframe["%-volatility"] = dataframe["%-volatility"].ffill()
                 dataframe["%-volatility"] = dataframe["%-volatility"].fillna(0)
 
+# 移除 shift(-label_period)，改为使用当前及过去的数据
             dataframe["&-buy_rsi"] = ta.RSI(dataframe, timeperiod=14)
-            dataframe["&-buy_rsi"] = dataframe["&-buy_rsi"].shift(-label_period).ffill().bfill()
+            dataframe["&-buy_rsi"] = dataframe["&-buy_rsi"].rolling(window=label_period).mean().ffill().bfill()
 
             for col in ["&-buy_rsi", "%-volatility"]:
                 dataframe[col] = dataframe[col].replace([np.inf, -np.inf], 0)
@@ -154,8 +155,9 @@ class FreqaiPrimer(IStrategy):
         dataframe["tema"] = ta.TEMA(dataframe, timeperiod=9)
 
         label_period = self.freqai_info["feature_parameters"]["label_period_candles"]
+# 使用滚动窗口而非未来函数来生成 up_or_down 列
         dataframe["up_or_down"] = np.where(
-            dataframe["close"].shift(-label_period) > dataframe["close"], 1, 0
+            dataframe["close"].rolling(window=label_period).mean() > dataframe["close"], 1, 0
         )
 
         if "&-buy_rsi" in dataframe.columns:
@@ -168,7 +170,7 @@ class FreqaiPrimer(IStrategy):
 
             dataframe["&-sell_rsi"] = dataframe["&-buy_rsi"] + 30
             dataframe["&-stoploss"] = self.stoploss - (dataframe["%-volatility"] * 5).clip(-0.05, 0.05)
-            dataframe["&-roi_0"] = (dataframe["close"].shift(-label_period) / dataframe["close"] - 1).clip(0, 0.2)
+            dataframe["&-roi_0"] = (dataframe["close"].rolling(window=label_period).mean() / dataframe["close"] - 1).clip(0, 0.2)
 
             for col in ["&-buy_rsi", "&-sell_rsi", "&-stoploss", "&-roi_0"]:
                 dataframe[col] = dataframe[col].replace([np.inf, -np.inf], 0)

tools/dryrun.sh

@@ -41,7 +41,7 @@ docker-compose run -d --rm -p 8080:8080 freqtrade trade \
   --freqaimodel LightGBMRegressor \
   --config /freqtrade/config_examples/$CONFIG_FILE \
   --strategy $STRATEGY_NAME \
-  --fee 0.0008 \
+  --fee 0.0016 \
   --strategy-path /freqtrade/templates
 
 #python3 tools/filter.py