Dependence Modeling and Risk Assessment of a Financial Portfolio with ARMA-APARCH-EVT models based on HACs

TL;DR

This paper presents a comprehensive approach combining ARMA-APARCH, EVT, and HAC models to improve risk assessment and VaR modeling for financial portfolios, demonstrating enhanced accuracy with international stock data.

Contribution

It introduces a sequential modeling framework integrating HACs with ARMA-APARCH and EVT for better portfolio risk assessment, expanding practical applications.

Findings

HAC-based models improve VaR accuracy.

The combined ARMA-APARCH-EVT-HAC approach outperforms traditional methods.

Empirical results confirm the model's effectiveness on international stock data.

Abstract

This study aims to widen the sphere of pratical applicability of the HAC model combined with the ARMA-APARCH volatility forecast model and the extreme values theory. A sequential process of modeling of the VaR of a portfolio based on the ARMA-APARCH-EVT-HAC model was discussed. The empirical analysis conducted with data from international stock market indices clearly illustrates the performance and accuracy of modeling based on HACs.