Create # predict

# predict

@@ -0,0 +1,37 @@
+import yfinance as yf
+import pandas as pd
+import joblib
+from tabulate import tabulate
+import os
+
+tickers = ['GME', 'SOFI', 'RIVN', 'UCL', 'DGHI']
+
+def load_model(ticker):
+    try:
+        return joblib.load(f"{ticker}_model.pkl")
+    except:
+        return None
+
+def predict_stock_move(ticker):
+    model = load_model(ticker)
+    if not model:
+        return None
+
+    data = yf.download(ticker, period='2d', interval='1d')
+    if data.shape[0] < 2:
+        return None
+    latest = data.iloc[-1][['Open', 'High', 'Low', 'Close', 'Volume']].values.reshape(1, -1)
+    prediction = model.predict(latest)[0]
+    return round(prediction, 2)
+
+def main():
+    results = []
+    for ticker in tickers:
+        pred = predict_stock_move(ticker)
+        if pred is not None:
+            results.append([ticker, f"{pred:+.2f}%"])
+
+    print(tabulate(results, headers=["Ticker", "Predicted % Change (7d)"]))
+
+if __name__ == "__main__":
+    main()