Unveiling Portfolio Resilience: Harnessing Asymmetric Copulas for Dynamic Risk Assessment in the Knowledge Economy

Xia Li ()
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Xia Li: Henan University

Journal of the Knowledge Economy, 2024, vol. 15, issue 3, No 12, 10200-10226

Abstract: Abstract The dynamic landscape of modern financial analysis relies on the versatile instrument of copulas to unravel intricate interdependencies between variables. Value-at-risk (VAR) analysis, a crucial domain in risk assessment, seeks to navigate the complexities inherent in financial markets. Within portfolio management, risk minimization drives the selection of assets with diminished correlations. Copula models, particularly the symmetric Spearman ρ and Kendall τ, have traditionally underpinned VAR analysis. However, real-world financial assets exhibit asymmetric dependencies, necessitating a paradigm shift toward asymmetric copulas. This paper explores the potency of asymmetric copulas in VAR analysis for financial assets. Employing Monte Carlo simulations of copula functions, it juxtaposes nested Archimedean copulas with conventional symmetric counterparts. The study illuminates the role of asymmetric copulas in deciphering complex relationships inherent to financial variables, enriching the discourse on risk assessment and investment strategies. The paper’s journey traverses methodology, empirical findings, and introspective analysis, bridging theory and practice. It demonstrates that meticulous copula model selection and skillful Monte Carlo simulation execution are pivotal for accurate VAR analysis. The application of asymmetric copulas, particularly nested Archimedean copulas, effectively captures intricate dependencies among financial assets, spotlighting their potential in risk management. This study’s theoretical implications underscore the necessity of accurately modeling complex dependencies and tail events within portfolio risk management. Asymmetric copulas pave the way for dynamic models adaptable to evolving financial market dynamics. Managerially, the study guides risk managers in crafting tailored hedging and diversification strategies to enhance portfolio resilience. The study enhances risk management strategies by emphasizing sophisticated methodologies and nuanced risk assessment and contributes to stable financial outcomes.

Keywords: Asymmetric Copula models; Interdependencies; Monte Carlo; Value-at-risk; Financial risk (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s13132-023-01503-6

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