Forecasting gold market trends using Forward Newton’s Divided Difference interpolation - Mohd Zin, Nurul Athirah Soleha; Azat, Nurshazrin Izzati; Abd Rahman, Nor Hanim; Kechil, Rafizah (Unit Penerbitan JSKM, 2025)
Accurate prediction of gold prices is crucial due to gold’s role as a safe asset in times of economic uncertainty. This study investigates the use of Newton’s Forward Divided Difference (NFDD) interpolation method to model and forecast gold prices using historical data from March 2022 to April 2025. By constructing polynomial equations of degree-3 and degree-7 using NFDD, the study evaluates prediction accuracy using Percentage Absolute Relative Error (PARE). The findings highlight the practical viability of classical interpolation methods in financial forecasting, offering a computationally efficient alternative to complex machine learning models.