2022/12/22 by Khalilian, Pouriya, Azizi, Sara, Amiri, Mohammad Hossein +1
#Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #FOS: Economics and business #Statistical Finance (q-fin.ST)
paper · doi:10.48550/arxiv.2212.12044
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 (R2), demonstrates that a limited number of principal components is sufficient to capture the dominant dynamics of each asset, with varying complexity across markets.