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A hybrid prediction model with time‐varying gain tracking differentiator in Taylor expansion: Evidence from precious metals

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  • Zhidan Luo
  • Wei Guo
  • Qingfu Liu
  • Yiuman Tse

Abstract

In this paper, we propose a modified hybrid prediction model to capture both linear and nonlinear patterns in time‐series data by incorporating autoregressive integrated moving average (ARIMA) models and Taylor expansions. We introduce a time‐varying gain in the tracking differentiator to reduce the peaking value that occurs in a constant high‐gain design. The models are tested with gold and silver futures prices. The results show that the hybrid model with time‐varying high gain tracking differentiator outperforms other hybrid models.

Suggested Citation

  • Zhidan Luo & Wei Guo & Qingfu Liu & Yiuman Tse, 2023. "A hybrid prediction model with time‐varying gain tracking differentiator in Taylor expansion: Evidence from precious metals," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(5), pages 1138-1149, August.
    • Handle: RePEc:wly:jforec:v:42:y:2023:i:5:p:1138-1149
    DOI: 10.1002/for.2935
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