refactor: Improve price fetching reliability and portfolio value calculation

src/pages/journal/trading_journal_page.py

@@ -251,9 +251,9 @@ def trading_journal_page():
                     avg_entry = float(summary['avg_entry_price'])
                     
                     # Calculate position value using current market price
-                    position_value = current_price * shares  # Changed from avg_entry to current_price
+                    position_value = current_price * shares if current_price > 0 else avg_entry * shares
                     total_invested_value += position_value
-                    total_paper_pl += (current_price - avg_entry) * shares
+                    total_paper_pl += (current_price - avg_entry) * shares if current_price > 0 else 0
 
             # Calculate total portfolio value (cash + invested value)
             total_portfolio_value = cash_balance + total_invested_value

src/utils/data_utils.py

@@ -11,37 +11,73 @@ def get_float_input(prompt: str) -> Optional[float]:
 
 def get_current_prices(tickers: list) -> dict:
     """Get current prices for multiple tickers using yfinance"""
+    if not tickers:
+        return {}
+        
+    prices = {}
     try:
         # Create a space-separated string of tickers
         ticker_str = " ".join(tickers)
-        # Get data for all tickers at once
+        # Get data for all tickers at once with more reliable settings
-        data = yf.download(ticker_str, period="1d", interval="1m", group_by='ticker')
+        data = yf.download(
+            ticker_str, 
+            period="1d",  # Just today's data
+            interval="1d",  # Daily interval 
+            group_by='ticker',
+            progress=False,
+            prepost=True  # Include pre/post market prices
+        )
         
-        prices = {}
-        if len(tickers) == 1:
         # Handle single ticker case
-            if 'Close' in data.columns:
+        if len(tickers) == 1:
-                prices[tickers[0]] = data['Close'].iloc[-1]
+            if isinstance(data, pd.DataFrame) and 'Close' in data.columns:
+                prices[tickers[0]] = float(data['Close'].iloc[-1])
             else:
-                print(f"No close price found for {tickers[0]}")
+                # Try alternative method
+                try:
+                    stock = yf.Ticker(tickers[0])
+                    price = stock.info.get('regularMarketPrice', 0.0)
+                    prices[tickers[0]] = float(price)
+                except:
+                    prices[tickers[0]] = 0.0
         else:
             # Handle multiple tickers
             for ticker in tickers:
                 try:
                     if isinstance(data, pd.DataFrame) and (ticker, 'Close') in data.columns:
-                        prices[ticker] = data[ticker]['Close'].iloc[-1]
+                        prices[ticker] = float(data[ticker]['Close'].iloc[-1])
                     else:
-                        print(f"No close price found for {ticker}")
+                        # Try alternative method
+                        stock = yf.Ticker(ticker)
+                        price = stock.info.get('regularMarketPrice', 0.0)
+                        prices[ticker] = float(price)
+                except:
+                    prices[ticker] = 0.0
+                    
+        # Verify we have prices for all tickers
+        for ticker in tickers:
+            if ticker not in prices or prices[ticker] == 0:
+                try:
+                    stock = yf.Ticker(ticker)
+                    price = stock.info.get('regularMarketPrice', 0.0)
+                    if price:
+                        prices[ticker] = float(price)
+                except:
+                    if ticker not in prices:
+                        prices[ticker] = 0.0
+                        
     except Exception as e:
-                    print(f"Error getting price for {ticker}: {e}")
+        print(f"Error in batch price fetch: {e}")
+        # Fall back to individual ticker fetching
+        for ticker in tickers:
+            try:
+                stock = yf.Ticker(ticker)
+                price = stock.info.get('regularMarketPrice', 0.0)
+                prices[ticker] = float(price)
+            except:
+                prices[ticker] = 0.0
     
     return prices
-    except Exception as e:
-        print(f"Error fetching current prices: {e}")
-        print(f"Data structure received: {type(data)}")
-        if isinstance(data, pd.DataFrame):
-            print(f"Available columns: {data.columns}")
-        return {}
 
 def validate_signal_date(signal_date: datetime) -> datetime:
     """