Update app.py

app.py

@@ -49,13 +49,13 @@ def fetch_polymarket_data(search_term="S&P"):
 # Function to fetch Yahoo Finance data and calculate drift/volatility
 def fetch_yahoo_data(ticker):
     try:
-        stock = yf.download(ticker, period="1y", progress=False)
+        stock = yf.download(ticker, period="1y", auto_adjust=False, progress=False)
         if stock.empty:
             return None, None, None
-        daily_returns = stock["Adj Close"].pct_change().dropna()
+        daily_returns = stock["Close"].pct_change().dropna()  # Use raw Close prices
         mu = daily_returns.mean() * 252  # Annualized drift
         sigma = daily_returns.std() * np.sqrt(252)  # Annualized volatility
-        last_price = stock["Adj Close"][-1]
+        last_price = stock["Close"][-1]  # Use most recent unadjusted Close
         return mu, sigma, last_price
     except Exception:
         return None, None, None
@@ -115,7 +115,7 @@ def run_simulation(investment, ticker, horizon, num_sims, risk_factor):
     
     # Prepare summary text
     summary = f"Market Data (Yahoo Finance):\n"
-    summary += f"- Drift (μ): {mu:.4f}\n"
+    summary += f"- Drift (μ): {mu:.4f} (based on unadjusted Close)\n"
     summary += f"- Volatility (σ): {sigma:.4f}\n\n"
     if pm_data:
         summary += f"Polymarket Data:\n- Question: {pm_data['question']}\n"
@@ -134,7 +134,7 @@ def run_simulation(investment, ticker, horizon, num_sims, risk_factor):
 # Gradio UI
 with gr.Blocks(title="Investment Simulation Platform") as demo:
     gr.Markdown("# Investment Decision Simulation Platform")
-    gr.Markdown("Simulate investment outcomes using Yahoo Finance data and Polymarket probabilities.")
+    gr.Markdown("Simulate investment outcomes using Yahoo Finance data (unadjusted) and Polymarket probabilities.")
     
     with gr.Row():
         with gr.Column():