A Comparison of the Forecasting Accuracy in the Rate of Changes of Security Prices in Thailand, Using Arima Models
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This article aims to compare the performance of the appropriate forecasting accuracy in the rate of changes of security prices in the resource groups, by using the Arima model (0,0,0) to (3,3,3). Its purpose is to analyze the most accurate performance model, with the MAE (Mean Absolute Error) and the square root of RMSE (Root Mean Square Error). This research investigated the quarterly data of resource group, dated from 1 January 2004 to 31 December 2020, totaling 3,200 days from 30 companies to create an effective forecasting model. The research results show that the Arima model (3,1,1) yields the lowest mean absolute error MAE value of 14.22. It is considered that the derived forecast from genuine data is as accurate as 85.78 percent. The square root of RMSE (Root Mean Square Error) has the lowest RMSE value of 27.95, which assumes that the derived forecast from the actual data is as accurate as 72.05 percent. Therefore, this model is suitable for forecasting the stock price in the resource group.
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