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

Pouriya Khalilian, Sara Azizi, Mohammad Hossein Amiri and Javad T. Firouzjaee

Papers from arXiv.org

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.

Date: 2022-12, Revised 2025-12
New Economics Papers: this item is included in nep-big, nep-cmp and nep-fmk
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Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:2212.12044

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