diff --git a/README.zh_Hant.md b/README.zh_Hant.md
index aa8303b81..7d6bf9501 100644
--- a/README.zh_Hant.md
+++ b/README.zh_Hant.md
@@ -63,9 +63,9 @@ ValueCell 是一個社群驅動的多智能體金融應用平台。
 
 
 ## 多智能體系統
-- **DeepResearch Agent**：獲取並分析股票的 SEC 文件，輸出準確的數據與可解釋的總結
+- **DeepResearch Agent**：獲取並分析股票的 SEC 文件,輸出準確的數據與可解釋的總結
 - **Auto Trading Agent**：支援多種加密資產與 AI 自動交易策略
-**Trading Agents**: 專責市場分析、情緒分析、新聞分析與基本面分析的智能體協同運作
+- **Trading Agents**: 專責市場分析、情緒分析、新聞分析與基本面分析的智能體協同運作
 - **AI-Hedge-Fund**：智能體協作提供全面的金融洞見
 - **其他智能體**：更多智能體正在規劃中…
 
diff --git a/python/valuecell/agents/auto_trading_agent/market_data.py b/python/valuecell/agents/auto_trading_agent/market_data.py
index 7bce5f807..166760e12 100644
--- a/python/valuecell/agents/auto_trading_agent/market_data.py
+++ b/python/valuecell/agents/auto_trading_agent/market_data.py
@@ -111,7 +111,8 @@ def _calculate_rsi(df: pd.DataFrame, period: int = 14):
         delta = df["Close"].diff()
         gain = (delta.where(delta > 0, 0)).rolling(window=period).mean()
         loss = (-delta.where(delta < 0, 0)).rolling(window=period).mean()
-        rs = gain / loss
+        # Avoid division by zero: if loss is 0, RSI = 100 (maximum strength)
+        rs = gain / loss.replace(0, float("inf"))
         df["rsi"] = 100 - (100 / (1 + rs))
 
     @staticmethod