Development of Time Series Model to Predict Daily Gold Price

Abstract

Gold is ancient and one of the most precious and popular commoditi es in the world. Gold price forecasti ng is criti cal in fi nancial decision-making, providing valuable informati on for investors in the gold market, sellers of gold items and stakeholders. Not much studies have been carried out in to forecast daily gold prices of Sri Lanka. The aim of this paper is to forecast the daily gold price rate (Rupees/troy ounce) using data from 2nd January 2018 to 14th June 2024 published by the Central Bank of Sri Lanka. The best fi tt ed model was identi fi ed as ARIMA (1,1,1) + ARCH (2). The model was trained using data from 2nd January 2018 to 31st May 2024 and validated using data from the 3rd of June 2024 to 14th of June 2024. The model was stati sti cally tested using standard stati sti cal procedure and errors were found as white noise. The Mean Absolute Percentage Error (MAPE) for the training data set and validati on data set were 0.748% and 1.002% respecti vely. The validati on confi rmed that the ARIMA (1,1,1) + ARCH (2) model eff ecti vely captures the dynamics of gold price movements, off ering robust predicti ve power. These results indicate that the model is highly accurate and reliable for forecasti ng, making it a valuable tool for fi nancial insti tuti ons and investors aiming to predict market trends and make informed investment decisions.