Latent factor models for the Chinese commodity futures markets

Yanchu Liu, Heyang Zhou and Haisheng Yang

Pacific-Basin Finance Journal, 2025, vol. 93, issue C

Abstract: The rapid growth of Chinese commodity futures markets over the past several decades has created a fertile ground for exploring underlying market dynamics. In this research, we utilize Instrumented Principal Component Analysis (IPCA) alongside the Conditional Autoencoder (CA) method to construct latent factor models tailored to this market. By uncovering hidden patterns and intrinsic characteristics that drive futures prices, our empirical results demonstrate robust out-of-sample predictive accuracy.

Keywords: Factor model; Commodity futures; Instrumented principal component analysis; Conditional autoencoder; Machine learning (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:pacfin:v:93:y:2025:i:c:s0927538x25002276

DOI: 10.1016/j.pacfin.2025.102890

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