Hans Jarett Ong

Hans Jarett Ong

PhD candidate at NAIST specializing in Causal AI. My research connects theory with practical applications to build robust and fair AI systems, drawing on my experience deploying ML models.

Dynamic Principal Component Analysis for the Construction of High-Frequency Economic Indicators

Published in International Conference on Advances in Computational Science and Engineering, 2023

This study explores the use of dynamic principal component analysis (DPCA) to construct real-time economic indicators from high-frequency data, enabling better-informed policy decisions.

Applied to Philippine financial data—including stock exchange prices, exchange rates, and forward rates—DPCA extracted latent factors corresponding to:

  • Business and investment conditions
  • Economic performance
  • Economic outlook

Further validation using the Isolation Forest anomaly detection algorithm demonstrated sensitivity to real-world events like:

  • The 2013 taper tantrum
  • The 2020 COVID-19 lockdown

The study highlights the practical value of DPCA and its potential extensions using alternative and nontraditional data sources.

Recommended citation: Lim, Brian Godwin, Ong, Hans Jarett, Tan, Renzo Roel, and Ikeda, Kazushi. (2023). "Dynamic Principal Component Analysis for the Construction of High-Frequency Economic Indicators." International Conference on Advances in Computational Science and Engineering. pp. 645-663.