Investigates the use of the Autoregressive Integrated Moving Average (ARIMA) model in predicting stock prices. Employing historical stock data retrieved through yfinance, examine the effectiveness of ARIMA with evaluation metrics, including Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and R-squared.
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Investigates the use of the Autoregressive Integrated Moving Average (ARIMA) model in predicting stock prices. Employing historical stock data retrieved through yfinance, examine the effectiveness of ARIMA with evaluation metrics, including Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and R-squared.
nickdgas/AAPL-Market-Price-Forecaster
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Investigates the use of the Autoregressive Integrated Moving Average (ARIMA) model in predicting stock prices. Employing historical stock data retrieved through yfinance, examine the effectiveness of ARIMA with evaluation metrics, including Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and R-squared.
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