Copula Models Comparison for Portfolio Risk Assessment

Mikhail Semenov () and Daulet Smagulov
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Mikhail Semenov: Tomsk Polytechnic University
Daulet Smagulov: Tomsk Polytechnic University

Chapter Chapter 9 in Global Economics and Management: Transition to Economy 4.0, 2019, pp 91-102 from Springer

Abstract: Abstract This paper presents the results of copula-based variable dependence analysis in short financial time series (253 observations). We propose the algorithm of risk measure computation using copula models. Using the optimal mean-CVaR portfolio, we compute portfolio’s Profit & Loss series and corresponded risk measures curves. Value-at-riskValue-at-risk and Conditional-Value-at-riskValue-at-risk curves were simulated by three copula models: full Gaussian, Student’s t and regular vine copulaVine copula. Amongst many interesting findings, we discover that regular vine copulaVine copula model is the most conservative one, and it does not underestimate the risk. We found that the portfolio Profit & Loss curve movements through a copula line based on CVaR models twice only while VaR models breaks—five times. We have established that the regular vine copulaVine copula model has superior forecasting ability than the Gaussian and the Student’s t one.

Keywords: Value-at-risk; Risk assessment; Optimal portfolio; Vine copula; Multivariate dependence (search for similar items in EconPapers)
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:spr:prbchp:978-3-030-26284-6_9

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DOI: 10.1007/978-3-030-26284-6_9

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