A novel circular dynamics in financial networks with cross-correlated volatility and asset movements

Subhrajit Saha, Debashis Chatterjee

Article ID: 9177
Vol 7, Issue 2, 2024

VIEWS - 378 (Abstract)

Abstract


In this paper, we propose a novel application of classical directional statistics to model the cross-correlation of asset volatility in financial networks. The proposed novel Circular Volatility Model (CVM) provides a framework for studying the interdependencies of financial assets whose returns exhibit periodic behaviors. By extending traditional volatility models into a circular framework, we establish new pathways for understanding the cyclicity inherent in market dynamics. Our model is rigorously grounded in classical \& directional statistics, utilizing von Mises distributions for parameter estimation and novel circular covariance structures. We offer formal derivations, maximum likelihood estimates, and a novel goodness-of-fit testing framework for this circular model. We establish our methodologies using simulation studies.


Keywords


circular volatility model; von mises distribution; angular data; financial networks; volatility modeling; Maximum Likelihood Estimation (MLE); confidence intervals

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References


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DOI: https://doi.org/10.24294/fsj9177

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