add spaces

2025-10-14 04:34:00 +00:00 · 2025-10-14 04:34:00 +00:00 · 9ad6d112f6
commit 9ad6d112f6
parent 64a99a90b4
7 changed files with 525 additions and 55 deletions
--- a/config_examples/martingale.json
+++ b/config_examples/martingale.json
@ -25,21 +25,25 @@
    "use_order_book": false
  },
  "exchange": {
-    "name": "binance",
-    "key": "",
-    "secret": "",
-    "ccxt_config": {
-      "enableRateLimit": true
-    },
-    "ccxt_async_config": {
-      "enableRateLimit": true
-    },
-    "pair_whitelist": [
-      "BTC/USDT"
-    ],
-    "pair_blacklist": [
-      "BNB/.*"
-    ]
+      "name": "okx",
+      "key": "314e75b0-1113-47e8-ad01-1fca7e3c0496",
+      "secret": "9C8B170390F46EA6FB87592AD46F5A34",
+      "password": "nekFoylf:Om0",
+      "enable_ws": false,
+      "ccxt_config": {
+          "enableRateLimit": true,
+          "rateLimit": 500,
+          "options": {
+              "defaultType": "spot"
+          }
+      },
+      "ccxt_async_config": {
+          "enableRateLimit": true,
+          "rateLimit": 3000,
+          "timeout": 20000
+      },
+      "pair_whitelist": ["BTC/USDT",  "TON/USDT", "DOT/USDT", "XRP/USDT",  "OKB/USDT", "SOL/USDT", "DOGE/USDT", "WCT/USDT", "TRUMP/USDT", "SUI/USDT", "PEPE/USDT", "TRB/USDT", "MASK/USDT", "UNI/USDT", "KAITO/USDT"],
+      "pair_blacklist": ["DORA/USDT"]
  },
  "pairlists": [
    {
@ -77,4 +81,4 @@
      "heartbeat_interval": 20,
      "loglevel": "DEBUG"
  }
-}
+}
--- a/config_examples/mystrategy.json
+++ b/config_examples/mystrategy.json
@ -0,0 +1,148 @@
+{
+    "$schema": "https://schema.freqtrade.io/schema.json",
+    "redis": {
+        "url": "redis://192.168.1.215:6379/0"
+    },
+    "trading_mode": "spot",
+    "margin_mode": "isolated",
+    "max_open_trades": 5,
+    "stake_currency": "USDT",
+    "stake_amount": 1,
+    "tradable_balance_ratio": 1,
+    "process_only_new_candles": false,
+    "fiat_display_currency": "USD",
+    "dry_run": true,
+    "timeframe": "3m",
+    "additional_timeframes": ["4h"],
+    "dry_run_wallet": 2000,
+    "cancel_open_orders_on_exit": true,
+    "stoploss": -0.14,
+    "max_entry_position_adjustment": 3,
+    "position_adjustment_enable": true,
+    "amount_reserve_percent": 0.05,
+    "unfilledtimeout": {
+        "entry": 5,
+        "exit": 15
+    },
+    "dry_run": false,
+    "startup_candle_count": 200,
+    "exchange": {
+        "name": "okx",
+        "key": "314e75b0-1113-47e8-ad01-1fca7e3c0496",
+        "secret": "9C8B170390F46EA6FB87592AD46F5A34",
+	      "password": "nekFoylf:Om0",
+        "enable_ws": false,
+        "ccxt_config": {
+            "enableRateLimit": true,
+            "rateLimit": 500,
+            "options": {
+                "defaultType": "spot"
+            }
+        },
+        "ccxt_async_config": {
+            "enableRateLimit": true,
+            "rateLimit": 3000,
+            "timeout": 20000
+        },
+        "pair_whitelist": ["BTC/USDT",  "TON/USDT", "DOT/USDT", "XRP/USDT",  "OKB/USDT", "SOL/USDT", "DOGE/USDT", "WCT/USDT", "TRUMP/USDT", "SUI/USDT", "PEPE/USDT", "TRB/USDT", "MASK/USDT", "UNI/USDT", "KAITO/USDT"],
+        "pair_blacklist": ["DORA/USDT"]
+    },
+    "entry_pricing": {
+        "price_side": "same",
+        "use_order_book": true,
+        "order_book_top": 1,
+        "price_last_balance": 0.0,
+        "check_depth_of_market": {
+            "enabled": false,
+            "bids_to_ask_delta": 1
+        }
+    },
+    "exit_pricing": {
+        "price_side": "other",
+        "use_order_book": true,
+        "order_book_top": 1
+    },
+    "pairlists": [
+        {
+            "method": "StaticPairList"
+        }    
+    ],
+    "freqai": {
+        "enabled": true,
+        "data_kitchen": {
+            "fillna": "ffill"
+        },
+        "freqaimodel": "LightGBMMultiTargetRegressor",
+        "purge_old_models": 2,
+        "identifier": "test58",
+        "train_period_days": 7,
+        "backtest_period_days": 1,
+        "live_retrain_hours": 2,
+        "outlier_detection": {
+            "method": "IsolationForest",
+            "contamination": 0.1
+        },
+        "feature_selection": {
+          "method": "recursive_elimination"
+        },
+        "feature_parameters": {
+            "include_timeframes": [
+                "3m",
+                "15m",
+                "1h"
+            ],
+            "include_corr_pairlist": [
+                "BTC/USDT",
+                "SOL/USDT"
+            ],
+            "outlier_protection_percentage": 0.1,
+            "label_period_candles": 24,
+            "include_shifted_candles": 3,
+            "DI_threshold": 0.7,
+            "weight_factor": 0.9,
+            "principal_component_analysis": false,
+            "use_SVM_to_remove_outliers": true,
+            "indicator_periods_candles": [
+                10,
+                20,
+                50
+            ],
+            "plot_feature_importances": 10
+        },
+        "data_split_parameters": {
+            "test_size": 0.2,
+              "shuffle": false
+        },
+        "model_training_parameters": {
+            "n_estimators": 400,
+            "learning_rate": 0.03,
+            "num_leaves": 40,
+            "max_depth": 10,
+            "min_data_in_leaf": 20,
+            "feature_fraction": 0.8,
+            "bagging_fraction": 0.8,
+            "bagging_freq": 5,
+            "verbose": -1
+        }
+    },
+    "api_server": {
+        "enabled": true,
+        "listen_ip_address": "0.0.0.0",
+        "listen_port": 8080,
+        "verbosity": "error",
+        "enable_openapi": false,
+        "jwt_secret_key": "6a599ab046dbb419014807dffd7b8823bfa7e5df56b17d545485deb87331b4ca",
+        "ws_token": "6O5pBDiRigiZrmIsofaE2rkKMJtf9h8zVQ",
+        "CORS_origins": [],
+        "username": "freqAdmin",
+        "password": "admin"
+    },
+    "bot_name": "freqtrade",
+    "initial_state": "running",
+    "force_entry_enable": false,
+    "internals": {
+        "process_throttle_secs": 5,
+        "heartbeat_interval": 20,
+        "loglevel": "DEBUG"
+    }
+}
--- a/freqtrade/templates/freqaiprimer.json
+++ b/freqtrade/templates/freqaiprimer.json
@ -46,4 +46,4 @@
  },
  "ft_stratparam_v": 1,
  "export_time": "2025-10-05 16:38:39.948030+00:00"
-}
+}
--- a/freqtrade/templates/martingale.json
+++ b/freqtrade/templates/martingale.json
@ -1,16 +1,32 @@
 {
-  "strategy": "MartinGale",
+  "strategy_name": "MartinGale",
  "params": {
+    "roi": {},
+    "stoploss": {
+      "stoploss": -0.14
+    },
+    "trailing": {
+      "trailing_stop": true,
+      "trailing_stop_positive": 0.007,
+      "trailing_stop_positive_offset": 0.045,
+      "trailing_only_offset_is_reached": false
+    },
+    "max_open_trades": {
+      "max_open_trades": 1
+    },
    "buy": {
-      "rsi_length": 14,
+      "add_position_callback": 0.014,
+      "max_entry_adjustments": 14,
+      "rsi_length": 18,
      "rsi_oversold": 30,
-      "max_entry_adjustments": 10,
-      "add_position_callback": 0.0066,
-      "step_coefficient": 1.05,
-      "stake_divisor": 1.0
+      "stake_divisor": 0.91,
+      "step_coefficient": 1.03
    },
    "sell": {
-      "take_profit_target": 0.025
-    }
-  }
+      "take_profit_target": 0.027
+    },
+    "protection": {}
+  },
+  "ft_stratparam_v": 1,
+  "export_time": "2025-10-14 04:28:32.713751+00:00"
 }
--- a/freqtrade/templates/mystrategy.json
+++ b/freqtrade/templates/mystrategy.json
@ -0,0 +1,49 @@
+{
+  "strategy_name": "MyStrategy",
+  "params": {
+    "roi": {},
+    "stoploss": {
+      "stoploss": -0.14
+    },
+    "trailing": {
+      "trailing_stop": true,
+      "trailing_stop_positive": 0.0125,
+      "trailing_stop_positive_offset": 0.045,
+      "trailing_only_offset_is_reached": false
+    },
+    "max_open_trades": {
+      "max_open_trades": 5
+    },
+    "buy": {
+      "bb_std": 3.0,
+      "bb_width_threshold": 0.012,
+      "h1_max_candles": 200,
+      "h1_max_consecutive_candles": 3,
+      "max_entry_adjustments": 4,
+      "rsi_bull_threshold": 54,
+      "rsi_length": 16,
+      "stochrsi_bull_threshold": 36,
+      "volume_multiplier": 1.6,
+      "add_position_callback": 0.053,
+      "bb_length": 14,
+      "bb_lower_deviation": 1.05,
+      "h1_rapid_rise_threshold": 0.065,
+      "min_condition_count": 2,
+      "rsi_oversold": 42,
+      "stake_divisor": 2.793,
+      "step_coefficient": 1.45,
+      "stochrsi_neutral_threshold": 29
+    },
+    "sell": {
+      "exit_bb_upper_deviation": 0.99,
+      "exit_volume_multiplier": 1.7,
+      "roi_param_a": -6e-05,
+      "roi_param_k": 132,
+      "roi_param_t": 0.168,
+      "rsi_overbought": 58
+    },
+    "protection": {}
+  },
+  "ft_stratparam_v": 1,
+  "export_time": "2025-10-05 16:38:39.948030+00:00"
+}
--- a/freqtrade/templates/mystrategy.py
+++ b/freqtrade/templates/mystrategy.py
@ -0,0 +1,279 @@
+import logging
+import numpy as np
+from functools import reduce
+import talib.abstract as ta
+from pandas import DataFrame
+from technical import qtpylib
+from freqtrade.strategy import IStrategy, IntParameter, DecimalParameter
+
+logger = logging.getLogger(__name__)
+
+class MyStrategy(IStrategy):
+    minimal_roi = {
+        0: 0.135,
+        9: 0.052,
+        15: 0.007,
+        60: 0
+    }
+    stoploss = -0.263
+    trailing_stop = True
+    trailing_stop_positive = 0.324
+    trailing_stop_positive_offset = 0.411
+    trailing_only_offset_is_reached = False
+    max_open_trades = 4
+    process_only_new_candles = True
+    use_exit_signal = True
+    startup_candle_count: int = 40
+    can_short = False
+
+    buy_rsi = IntParameter(low=10, high=50, default=30, space="buy", optimize=False, load=True)
+    sell_rsi = IntParameter(low=50, high=90, default=70, space="sell", optimize=False, load=True)
+    roi_0 = DecimalParameter(low=0.01, high=0.2, default=0.135, space="roi", optimize=True, load=True)
+    roi_15 = DecimalParameter(low=0.005, high=0.1, default=0.052, space="roi", optimize=True, load=True)
+    roi_30 = DecimalParameter(low=0.001, high=0.05, default=0.007, space="roi", optimize=True, load=True)
+    stoploss_param = DecimalParameter(low=-0.35, high=-0.1, default=-0.263, space="stoploss", optimize=True, load=True)
+    trailing_stop_positive_param = DecimalParameter(low=0.1, high=0.5, default=0.324, space="trailing", optimize=True, load=True)
+    trailing_stop_positive_offset_param = DecimalParameter(low=0.2, high=0.6, default=0.411, space="trailing", optimize=True, load=True)
+
+    freqai_info = {
+        "model": "LightGBMRegressor",
+        "feature_parameters": {
+            "include_timeframes": ["5m", "15m", "1h"],
+            "include_corr_pairlist": [],
+            "label_period_candles": 12,
+            "include_shifted_candles": 3,
+        },
+        "data_split_parameters": {
+            "test_size": 0.2,
+            "shuffle": False,
+        },
+        "model_training_parameters": {
+            "n_estimators": 200,
+            "learning_rate": 0.05,
+            "num_leaves": 31,
+            "verbose": -1,
+        },
+    }
+
+    plot_config = {
+        "main_plot": {},
+        "subplots": {
+            "&-buy_rsi": {"&-buy_rsi": {"color": "green"}},
+            "&-sell_rsi": {"&-sell_rsi": {"color": "red"}},
+            "&-stoploss": {"&-stoploss": {"color": "purple"}},
+            "&-roi_0": {"&-roi_0": {"color": "orange"}},
+            "do_predict": {"do_predict": {"color": "brown"}},
+        },
+    }
+
+    def feature_engineering_expand_all(self, dataframe: DataFrame, period: int, metadata: dict, **kwargs) -> DataFrame:
+        dataframe["%-rsi-period"] = ta.RSI(dataframe, timeperiod=period)
+        dataframe["%-mfi-period"] = ta.MFI(dataframe, timeperiod=period)
+        dataframe["%-sma-period"] = ta.SMA(dataframe, timeperiod=period)
+        dataframe["%-ema-period"] = ta.EMA(dataframe, timeperiod=period)
+        dataframe["%-adx-period"] = ta.ADX(dataframe, timeperiod=period)
+        bollinger = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=period, stds=2.2)
+        dataframe["bb_lowerband-period"] = bollinger["lower"]
+        dataframe["bb_middleband-period"] = bollinger["mid"]
+        dataframe["bb_upperband-period"] = bollinger["upper"]
+        dataframe["%-bb_width-period"] = (
+            dataframe["bb_upperband-period"] - dataframe["bb_lowerband-period"]
+        ) / dataframe["bb_middleband-period"]
+        dataframe["%-close-bb_lower-period"] = dataframe["close"] / dataframe["bb_lowerband-period"]
+        dataframe["%-roc-period"] = ta.ROC(dataframe, timeperiod=period)
+        dataframe["%-relative_volume-period"] = (
+            dataframe["volume"] / dataframe["volume"].rolling(period).mean()
+        )
+        dataframe = dataframe.replace([np.inf, -np.inf], 0)
+        dataframe = dataframe.ffill()
+        dataframe = dataframe.fillna(0)
+        return dataframe
+
+    def feature_engineering_expand_basic(self, dataframe: DataFrame, metadata: dict, **kwargs) -> DataFrame:
+        dataframe["%-pct-change"] = dataframe["close"].pct_change()
+        dataframe["%-raw_volume"] = dataframe["volume"]
+        dataframe["%-raw_price"] = dataframe["close"]
+        dataframe = dataframe.replace([np.inf, -np.inf], 0)
+        dataframe = dataframe.ffill()
+        dataframe = dataframe.fillna(0)
+        return dataframe
+
+    def feature_engineering_standard(self, dataframe: DataFrame, metadata: dict, **kwargs) -> DataFrame:
+        if len(dataframe["close"]) < 20:
+            logger.warning(f"数据不足 {len(dataframe)} 根 K 线，%-volatility 可能不完整")
+        dataframe["%-day_of_week"] = dataframe["date"].dt.dayofweek
+        dataframe["%-hour_of_day"] = dataframe["date"].dt.hour
+        dataframe["%-volatility"] = dataframe["close"].pct_change().rolling(20, min_periods=1).std()
+        dataframe["%-volatility"] = dataframe["%-volatility"].replace([np.inf, -np.inf], 0)
+        dataframe["%-volatility"] = dataframe["%-volatility"].ffill()
+        dataframe["%-volatility"] = dataframe["%-volatility"].fillna(0)
+        return dataframe
+
+    def set_freqai_targets(self, dataframe: DataFrame, metadata: dict, **kwargs) -> DataFrame:
+        logger.info(f"设置 FreqAI 目标，交易对：{metadata['pair']}")
+        if "close" not in dataframe.columns:
+            logger.error("数据框缺少必要的 'close' 列")
+            raise ValueError("数据框缺少必要的 'close' 列")
+
+        try:
+            label_period = self.freqai_info["feature_parameters"]["label_period_candles"]
+            if "%-volatility" not in dataframe.columns:
+                logger.warning("缺少 %-volatility 列，强制重新生成")
+                dataframe["%-volatility"] = dataframe["close"].pct_change().rolling(20, min_periods=1).std()
+                dataframe["%-volatility"] = dataframe["%-volatility"].replace([np.inf, -np.inf], 0)
+                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"].rolling(window=label_period).mean().ffill().bfill()
+
+            for col in ["&-buy_rsi", "%-volatility"]:
+                dataframe[col] = dataframe[col].replace([np.inf, -np.inf], 0)
+                dataframe[col] = dataframe[col].ffill()
+                dataframe[col] = dataframe[col].fillna(0)
+                if dataframe[col].isna().any():
+                    logger.warning(f"目标列 {col} 仍包含 NaN，数据预览：\n{dataframe[col].tail(10)}")
+        except Exception as e:
+            logger.error(f"创建 FreqAI 目标失败：{str(e)}")
+            raise
+
+        logger.info(f"目标列预览：\n{dataframe[['&-buy_rsi']].head().to_string()}")
+        return dataframe
+
+    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        logger.info(f"处理交易对：{metadata['pair']}")
+        logger.debug(f"输入特征列：{list(dataframe.columns)}")
+        dataframe = self.freqai.start(dataframe, metadata, self)
+        logger.debug(f"FreqAI 输出特征列：{list(dataframe.columns)}")
+
+        dataframe["rsi"] = ta.RSI(dataframe, timeperiod=14)
+        bollinger = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=2)
+        dataframe["bb_lowerband"] = bollinger["lower"]
+        dataframe["bb_middleband"] = bollinger["mid"]
+        dataframe["bb_upperband"] = bollinger["upper"]
+        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"].rolling(window=label_period).mean() > dataframe["close"], 1, 0
+        )
+
+        if "&-buy_rsi" in dataframe.columns:
+            if "%-volatility" not in dataframe.columns:
+                logger.warning("缺少 %-volatility 列，强制重新生成")
+                dataframe["%-volatility"] = dataframe["close"].pct_change().rolling(20, min_periods=1).std()
+                dataframe["%-volatility"] = dataframe["%-volatility"].replace([np.inf, -np.inf], 0)
+                dataframe["%-volatility"] = dataframe["%-volatility"].ffill()
+                dataframe["%-volatility"] = dataframe["%-volatility"].fillna(0)
+
+            dataframe["&-sell_rsi"] = dataframe["&-buy_rsi"] + 30
+            dataframe["&-stoploss"] = self.stoploss - (dataframe["%-volatility"] * 5).clip(-0.05, 0.05)
+            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)
+                dataframe[col] = dataframe[col].ffill()
+                dataframe[col] = dataframe[col].fillna(0)
+
+            dataframe["buy_rsi_pred"] = dataframe["&-buy_rsi"].rolling(5).mean().clip(10, 50)
+            dataframe["sell_rsi_pred"] = dataframe["&-sell_rsi"].rolling(5).mean().clip(50, 90)
+            dataframe["stoploss_pred"] = dataframe["&-stoploss"].clip(-0.35, -0.1)
+            dataframe["roi_0_pred"] = dataframe["&-roi_0"].clip(0.01, 0.2)
+
+            for col in ["buy_rsi_pred", "sell_rsi_pred", "stoploss_pred", "roi_0_pred"]:
+                if dataframe[col].isna().any():
+                    logger.warning(f"列 {col} 包含 NaN，填充为默认值")
+                    dataframe[col] = dataframe[col].ffill()
+                    dataframe[col] = dataframe[col].fillna(dataframe[col].mean())
+
+            dataframe["trailing_stop_positive"] = (dataframe["roi_0_pred"] * 0.5).clip(0.01, 0.3)
+            dataframe["trailing_stop_positive_offset"] = (dataframe["roi_0_pred"] * 0.75).clip(0.02, 0.4)
+
+            self.buy_rsi.value = float(dataframe["buy_rsi_pred"].iloc[-1])
+            self.sell_rsi.value = float(dataframe["sell_rsi_pred"].iloc[-1])
+            self.stoploss = float(self.stoploss_param.value)
+            self.minimal_roi = {
+                0: float(self.roi_0.value),
+                15: float(self.roi_15.value),
+                30: float(self.roi_30.value),
+                60: 0
+            }
+            self.trailing_stop_positive = float(self.trailing_stop_positive_param.value)
+            self.trailing_stop_positive_offset = float(self.trailing_stop_positive_offset_param.value)
+
+            logger.info(f"动态参数：buy_rsi={self.buy_rsi.value}, sell_rsi={self.sell_rsi.value}, "
+                        f"stoploss={self.stoploss}, trailing_stop_positive={self.trailing_stop_positive}")
+        else:
+            logger.warning(f"&-buy_rsi 列缺失，跳过 FreqAI 预测逻辑，检查 freqai.start 输出")
+
+        dataframe = dataframe.replace([np.inf, -np.inf], 0)
+        dataframe = dataframe.ffill()
+        dataframe = dataframe.fillna(0)
+
+        logger.info(f"up_or_down 值统计：\n{dataframe['up_or_down'].value_counts().to_string()}")
+        logger.info(f"do_predict 值统计：\n{dataframe['do_predict'].value_counts().to_string()}")
+        logger.debug(f"最终特征列：{list(dataframe.columns)}")
+
+        return dataframe
+
+    def populate_entry_trend(self, df: DataFrame, metadata: dict) -> DataFrame:
+        enter_long_conditions = [
+            qtpylib.crossed_above(df["rsi"], df["buy_rsi_pred"]),
+            df["tema"] > df["tema"].shift(1),
+            df["volume"] > 0,
+            df["do_predict"] == 1,
+            df["up_or_down"] == 1
+        ]
+        if enter_long_conditions:
+            df.loc[
+                reduce(lambda x, y: x & y, enter_long_conditions),
+                ["enter_long", "enter_tag"]
+            ] = (1, "long")
+        return df
+
+    def populate_exit_trend(self, df: DataFrame, metadata: dict) -> DataFrame:
+        exit_long_conditions = [
+            qtpylib.crossed_above(df["rsi"], df["sell_rsi_pred"]),
+            (df["close"] < df["close"].shift(1) * 0.97),
+            df["volume"] > 0,
+            df["do_predict"] == 1,
+            df["up_or_down"] == 0
+        ]
+        if exit_long_conditions:
+            df.loc[
+                reduce(lambda x, y: x & y, exit_long_conditions),
+                "exit_long"
+            ] = 1
+        return df
+
+    def confirm_trade_entry(
+        self, pair: str, order_type: str, amount: float, rate: float,
+        time_in_force: str, current_time, entry_tag, side: str, **kwargs
+    ) -> bool:
+        try:
+            df, _ = self.dp.get_analyzed_dataframe(pair, self.timeframe)
+            if df is None or df.empty:
+                logger.warning(f"无法获取 {pair} 的分析数据，拒绝交易")
+                return False
+
+            last_candle = df.iloc[-1].squeeze()
+            if "close" not in last_candle or np.isnan(last_candle["close"]):
+                logger.warning(f"{pair} 的最新 K 线缺少有效 close 价格，拒绝交易")
+                return False
+
+            if side == "long":
+                max_rate = last_candle["close"] * (1 + 0.0025)  # 0.25% 滑点阈值
+                if rate > max_rate:
+                    logger.debug(f"拒绝 {pair} 的买入，价格 {rate} 超过最大允许价格 {max_rate}")
+                    return False
+            elif side == "short":
+                logger.warning(f"{pair} 尝试做空，但策略不支持做空 (can_short={self.can_short})")
+                return False
+
+            logger.debug(f"确认 {pair} 的交易：side={side}, rate={rate}, close={last_candle['close']}")
+            return True
+        except Exception as e:
+            logger.error(f"确认 {pair} 交易时出错：{str(e)}")
+            return False
--- a/tools/hyperopt_org.sh
+++ b/tools/hyperopt_org.sh
@ -323,35 +323,9 @@ docker-compose run --rm freqtrade hyperopt $PAIRS_FLAG \
  --timerange ${START_DATE}-${END_DATE} \
  --random-state 19 \
  -e 2500 \
-  -j 20 \
+  -j 4 \
  --hyperopt-loss SharpeHyperOptLossDaily \
-  --spaces sell \
-  --fee 0.001 >output.log 2>&1
+  --spaces roi stoploss trailing \
+  --fee 0.001

-sed -i 's/\x1B\[[0-9;]*m//g' output.log

-rm ./result/*.json -fr
-rm ./result/*.py -fr
-mv ./user_data/backtest_results/* ./result/
-
-cd ./result
-# 查找当前目录下的所有 zip 文件
-zip_files=(*.zip)
-
-# 检查是否只有一个 zip 文件
-if [ ${#zip_files[@]} -eq 1 ]; then
-  # 解压缩该 zip 文件到当前目录
-  unzip "${zip_files[0]}"
-  rm *.zip
-  rm *.feather
-else
-  echo "当前目录下没有 zip 文件或者有多个 zip 文件，无法操作。"
-fi
-
-cd -
-sed -i 's/\x1B\[[0-9;]*m//g' output.log
-cp output.log result/ -f
-cd tools/
-python tradestocsv.py
-python analytic.py >../result/analytic.log
-cd ../