Value-at-risk performance in emerging and developed countries

PurposeThe purpose of this paper is to evaluate the predictive capacity of market risk estimation models in times of financial crises.Design/methodology/approachFor this, value-at-risk (VaR) valuation models applied to the daily returns of portfolios composed of stock indexes of developed and emergi...

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Bibliographic Details
Published in:International journal of managerial finance 2018-09, Vol.14 (5), p.591-612
Main Authors: Gaio, Luiz Eduardo, Tabajara Pimenta Júnior, Fabiano Guasti Lima, Ivan Carlin Passos, Nelson Oliveira Stefanelli
Format: Article
Language:English
Subjects:
Bankruptcy
Banks
Committees
Economic crisis
Financial institutions
Interest rates
International agreements
International finance
Investments
Performance evaluation
Regulation of financial institutions
Simulation
Stock exchanges
Volatility
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Summary:PurposeThe purpose of this paper is to evaluate the predictive capacity of market risk estimation models in times of financial crises.Design/methodology/approachFor this, value-at-risk (VaR) valuation models applied to the daily returns of portfolios composed of stock indexes of developed and emerging countries were tested. The Historical Simulation VaR model, multivariate ARCH models (BEKK, VECH and constant conditional correlation), artificial neural networks and copula functions were tested. The data sample refers to the periods of two international financial crises, the Asian Crisis of 1997, and the US Sub Prime Crisis of 2008.FindingsThe results pointed out that the multivariate ARCH models (VECH and BEKK) and Copula-Clayton had similar performance, with good adjustments in 100 percent of the tests. It was not possible to perceive significant differences between the adjustments for developed and emerging countries and of the crisis and normal periods, which was different to what was expected.Originality/valuePrevious studies focus on the estimation of VaR by a group of models. One of the contributions of this paper is to use several forms of estimation.
ISSN:1743-9132
1758-6569
DOI:10.1108/IJMF-10-2017-0244