Dynamical analysis of financial stocks network: improving forecasting using network properties

2024/08/21 by Ixandra Achitouv, Achitouv, Ixandra · 2 citations
Economics, Econometrics and Finance · #Complex Systems and Time Series Analysis #Computational Finance (q-fin.CP) #FOS: Economics and business #FOS: Physical sciences #Physics and Society (physics.soc-ph) #Statistical Finance (q-fin.ST)

paper · pdf · doi:10.48550/arxiv.2408.11759

openalex publication_date 2024/08/21 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

Applying a network analysis to stock return correlations, we study the dynamical properties of the network and how they correlate with the market return, finding meaningful variables that partially capture the complex dynamical processes of stock interactions and the market structure. We then use the individual properties of stocks within the network along with the global ones, to find correlations with the future returns of individual S&P 500 stocks. Applying these properties as input variables for forecasting, we find a 50% improvement on the R2score in the prediction of stock returns on long time scales (per year), and 3% on short time scales (2 days), relative to baseline models without network variables.

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