Abstract

Since the beginning of time, scholars have been interested in developing more precise predictive models because of the significance of stock price prediction in banking and economics. In this study, the price of AirAsia’s shares is predicted using the ARIMA model, a time-series analytic tool included in prediction algorithms. The technique of AirAsia’s stock price forecasting utilising the ARIMA model is demonstrated in the current study paper. Stock price forecasting using the ARIMA model has been done using historical stock data (July 2021) and it run them under Monte Carlo Simulation from Covid-19. It demonstrates that the ARIMA model’s results are more accurate for short-term forecasting and may be supported by current strategies for stock price redaction during COVID-19.

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