add files

backtest.py

@@ -0,0 +1,45 @@
+import pandas as pd
+
+class BacktestEngine:
+    def __init__(self, df):
+        """
+        df: 包含历史k线的DataFrame，至少包括open, high, low, close字段
+        """
+        self.df = df
+
+    def run_strategy(self, strategy):
+        """
+        执行策略的run_backtest，得到信号序列
+        """
+        return strategy.run_backtest(self.df)
+
+    def combine_signals(self, signals_list, weights, buy_threshold, sell_threshold):
+        """
+        多策略信号加权合成，并根据阈值生成最终信号
+        返回合成信号序列
+        """
+        df_signals = pd.concat(signals_list, axis=1).fillna(0)
+        weighted_signals = df_signals * weights
+        combined = weighted_signals.sum(axis=1)
+
+        def apply_threshold(score):
+            if score >= buy_threshold:
+                return 1
+            elif score <= sell_threshold:
+                return -1
+            else:
+                return 0
+
+        combined_signal = combined.apply(apply_threshold)
+        return combined_signal
+
+    def calc_returns(self, signals):
+        """
+        根据信号计算策略回测收益率（简化版）
+        """
+        df = self.df.copy()
+        df['signal'] = signals.shift(1).fillna(0)  # 防止未来函数
+        df['returns'] = df['close'].pct_change()
+        df['strategy_returns'] = df['signal'] * df['returns']
+        cum_ret = (1 + df['strategy_returns']).cumprod() - 1
+        return cum_ret