ตัวแบบสำหรับการพยากรณ์ราคาขายทองคำแท่งของประเทศไทย

Warangkhana Riansut; Supamit Wiriyakulopast; Nipat Tantiputtikul; Netitorn Kawmali

Authors

Warangkhana Riansut Mathematics and Data Management Program, Faculty of Science and Digital Innovation, Thaksin University, Paphayom, Phatthalung 93210, Thailand.
Supamit Wiriyakulopast Princess Chulabhorn Science High School Nakhon Si Thammarat, Muang, Nakhon Si Thammarat 80330, Thailand.
Nipat Tantiputtikul Princess Chulabhorn Science High School Nakhon Si Thammarat, Muang, Nakhon Si Thammarat 80330, Thailand.
Netitorn Kawmali Princess Chulabhorn Science High School Nakhon Si Thammarat, Muang, Nakhon Si Thammarat 80330, Thailand.

Keywords:

Gold Bullion Forecasting, Box-Jenkins, Exponential Smoothing, Combined Forecasting

Abstract

This study aims to construct models for forecasting the gold bullion selling price. The gold bullion time series, gathered from the reliable website of the Gold Traders Association from January 2012 to May 2023, contained 137 values and was divided into 2 sets. The first set, consisting of 125 values from January 2012 to May 2022, was used to construct forecasting models using the Box-Jenkins method, Holt’s exponential smoothing method, Brown’s exponential smoothing method, the damped trend exponential smoothing method, and the combined forecasting method. The second set, comprising 12 values from June 2022 to May 2023, was used to compare the forecasting models’ accuracy using the lowest mean absolute percentage error (MAPE) and root mean square error (RMSE). The results indicated that the combined forecasting method using Box-Jenkins and Holt’s exponential smoothing was the most accurate, with an error of 1.44% (MAPE = 1.4391) and 537.72 baht (RMSE = 537.72).

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