Comparative Analysis of Moving Average Methods for Forecasting the Gold Price Volatility
DOI:
https://doi.org/10.24252/msa.v13i2.59853Keywords:
Gold Price Forecasting, Moving Average, KAMA, Volatility, Time SeriesAbstract
Forecasting gold prices is challenging due to high market volatility and uncertainty. This study compares moving average forecasting methods—Simple Moving Average (SMA), Double Moving Average (DMA), Exponential Moving Average (EMA), and Kaufman’s Adaptive Moving Average (KAMA)—using daily gold price data from January 2014 to August 2024. Gold prices exhibited a notable upward trend, particularly after 2019, with a spike during the COVID-19 pandemic and subsequent increases driven by inflation and safe-haven demand. The results show KAMA achieves the lowest Root Mean Square Error (RMSE) of 25.2685 and Mean Absolute Percentage Error (MAPE) of 1.2108, offering superior forecasting of gold price changes in volatile markets. This suggests KAMA can improve trading strategies and investment decisions involving gold.
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