Update app.py

app.py

@@ -96,7 +96,7 @@ for company in companies:
     df_c['StrategyA_Cumulative'] = 0.0
     for i in range(1, len(df_c)):
         pct = df_c.loc[i, 'PctChangeDaily'] if pd.notnull(df_c.loc[i,'PctChangeDaily']) else 0
-        price = df_c.loc[i-1, f'Close_{TICKERS[c]}']  # prezzo di acquisto del giorno precedente
+        price = df_c.loc[i-1, f'Close_{TICKERS[company]}']  # prezzo di acquisto del giorno precedente
         
         if df_c.loc[i, 'Sentiment'] == "UP" and df_c.loc[i,'Confidence'] > 0.8:
             df_c.loc[i,'StrategyA_Cumulative'] = df_c.loc[i-1,'StrategyA_Cumulative'] + price * pct
@@ -108,7 +108,7 @@ for company in companies:
     df_c['StrategyB_Cumulative'] = 0.0
     for i in range(1, len(df_c)):
         pct = df_c.loc[i, 'PctChangeDaily'] if pd.notnull(df_c.loc[i,'PctChangeDaily']) else 0
-        price = df_c.loc[i-1, f'Close_{TICKERS[c]}']
+        price = df_c.loc[i-1, f'Close_{TICKERS[company]}']
         predicted = df_c.loc[i, 'Predicted']
     
         if predicted > 1:
@@ -123,7 +123,7 @@ for company in companies:
     df_c['StrategyC_Cumulative'] = 0.0
     for i in range(1, len(df_c)):
         pct = df_c.loc[i, 'PctChangeDaily'] if pd.notnull(df_c.loc[i,'PctChangeDaily']) else 0
-        price = df_c.loc[i-1, f'Close_{TICKERS[c]}']
+        price = df_c.loc[i-1, f'Close_{TICKERS[company]}']
         
         if df_c.loc[i, 'FinBERT_Sentiment'] == "POSITIVE" and df_c.loc[i,'FinBERT_Confidence'] > 0.8:
             df_c.loc[i,'StrategyC_Cumulative'] = df_c.loc[i-1,'StrategyC_Cumulative'] + price * pct