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Reduced-order autoregressive dynamics of a complex financial system: a PCA-based approach

Author

Listed:
  • Pouriya Khalilian
  • Sara Azizi
  • Mohammad Hossein Amiri
  • Javad T. Firouzjaee

Abstract

This study analyzes the dynamic interactions among the NASDAQ index, crude oil, gold, and the US dollar using a reduced-order modeling approach. Time-delay embedding and principal component analysis are employed to encode high-dimensional financial dynamics, followed by linear regression in the reduced space. Correlation and lagged regression analyses reveal heterogeneous cross-asset dependencies. Model performance, evaluated using the coefficient of determination ($R^2$), demonstrates that a limited number of principal components is sufficient to capture the dominant dynamics of each asset, with varying complexity across markets.

Suggested Citation

  • Pouriya Khalilian & Sara Azizi & Mohammad Hossein Amiri & Javad T. Firouzjaee, 2022. "Reduced-order autoregressive dynamics of a complex financial system: a PCA-based approach," Papers 2212.12044, arXiv.org, revised Dec 2025.
    • Handle: RePEc:arx:papers:2212.12044
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    File URL: http://arxiv.org/pdf/2212.12044
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