同步回测与tqsdk

src/analysis/analysis_utils.py

@@ -51,9 +51,14 @@ def calculate_metrics(
 
     total_days = (df_values.index.max() - df_values.index.min()).days
     if total_days > 0:
-        annualized_return = (1 + total_return) ** (252 / total_days) - 1
+        if total_return > -1:
+            annualized_return = (1 + total_return) ** (252 / total_days) - 1
+        else:
+            annualized_return = -9999999
     else:
         annualized_return = 0.0
+    print(f'total_return: {total_return}, annualized_return:{annualized_return}, 252 / total_days:{252 / total_days}')
+
 
     rolling_max = df_values["total_value"].cummax()
     daily_drawdown = (rolling_max - df_values["total_value"]) / rolling_max
@@ -63,7 +68,10 @@ def calculate_metrics(
     daily_volatility = excess_daily_returns.std()
 
     if daily_volatility > 0:
-        sharpe_ratio = np.sqrt(252) * (excess_daily_returns.mean() / daily_volatility)
+        if total_return > -1:
+            sharpe_ratio = np.sqrt(252) * (excess_daily_returns.mean() / daily_volatility)
+        else:
+            sharpe_ratio = -10
     else:
         sharpe_ratio = 0.0
 

src/strategies/SimpleLimitBuyStrategy.py

@@ -330,6 +330,8 @@ class SimpleLimitBuyStrategyShort(Strategy):
         # 只有当有持仓时才考虑平仓
         if current_pos_volume < 0:  # 假设只做多，所以持仓量 > 0
             avg_entry_price = self.get_average_position_price(self.symbol)
+            self.log(f'avg_entry_price {avg_entry_price}, bar.open {bar.open}')
+
             if avg_entry_price is not None:
                 pnl_per_unit = (
                     avg_entry_price - bar.open