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Enhancing gold futures volatility forecasts: integrating growth-rate changepoint correction into the TVP-SVM model

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  • Lu Wang
  • Zhuoyue Liu
  • Chao Liang

Abstract

This paper enhances gold futures volatility forecasting by integrating a novel growth rate changepoint correction (GRCPC) filter into the traditional time-varying parameter stochastic volatility in mean (TVP-SVM) model. The GRCPC filter adaptively corrects data using the Prophet model’s trend term growth rate to adjust changepoints, significantly filters noise and aligns corrected values with the overall trend. Out-of-sample results show that the TVP-SVM-GRCPC model markedly improves gold futures volatility forecasting accuracy. Further study evaluates the model’s efficacy in forecasting volatility during various risk periods and examines the impact of selectively applying the filter strategy in large sample.

Suggested Citation

  • Lu Wang & Zhuoyue Liu & Chao Liang, 2026. "Enhancing gold futures volatility forecasts: integrating growth-rate changepoint correction into the TVP-SVM model," Applied Economics, Taylor & Francis Journals, vol. 58(31), pages 6299-6318, July.
    • Handle: RePEc:taf:applec:v:58:y:2026:i:31:p:6299-6318
    DOI: 10.1080/00036846.2025.2519936
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