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https://doi.org/10.1080/1331677X.2015.1028243

Performance of Value at Risk models in the midst of the global financial crisis in selected CEE emerging capital markets

Mirjana Miletic
Sinisa Miletic

Puni tekst: engleski, pdf (566 KB) str. 132-166 preuzimanja: 151* citiraj
APA 6th Edition
Miletic, M. i Miletic, S. (2015). Performance of Value at Risk models in the midst of the global financial crisis in selected CEE emerging capital markets. Economic research - Ekonomska istraživanja, 28 (1), 132-166. https://doi.org/10.1080/1331677X.2015.1028243
MLA 8th Edition
Miletic, Mirjana i Sinisa Miletic. "Performance of Value at Risk models in the midst of the global financial crisis in selected CEE emerging capital markets." Economic research - Ekonomska istraživanja, vol. 28, br. 1, 2015, str. 132-166. https://doi.org/10.1080/1331677X.2015.1028243. Citirano 25.01.2020.
Chicago 17th Edition
Miletic, Mirjana i Sinisa Miletic. "Performance of Value at Risk models in the midst of the global financial crisis in selected CEE emerging capital markets." Economic research - Ekonomska istraživanja 28, br. 1 (2015): 132-166. https://doi.org/10.1080/1331677X.2015.1028243
Harvard
Miletic, M., i Miletic, S. (2015). 'Performance of Value at Risk models in the midst of the global financial crisis in selected CEE emerging capital markets', Economic research - Ekonomska istraživanja, 28(1), str. 132-166. https://doi.org/10.1080/1331677X.2015.1028243
Vancouver
Miletic M, Miletic S. Performance of Value at Risk models in the midst of the global financial crisis in selected CEE emerging capital markets. Economic research - Ekonomska istraživanja [Internet]. 2015 [pristupljeno 25.01.2020.];28(1):132-166. https://doi.org/10.1080/1331677X.2015.1028243
IEEE
M. Miletic i S. Miletic, "Performance of Value at Risk models in the midst of the global financial crisis in selected CEE emerging capital markets", Economic research - Ekonomska istraživanja, vol.28, br. 1, str. 132-166, 2015. [Online]. https://doi.org/10.1080/1331677X.2015.1028243

Sažetak
The aim of this paper is to investigate the performance of Value at Risk (VaR) models in selected Central and Eastern European (CEE) emerging capital markets. Daily returns of Croatian (CROBEX), Czech (PX50), Hungarian (BUX) and Romanian (BET) stock exchange indices are analysed for the period January, 2000 – February, 2012, while daily returns of the Serbian (BELEX15) index is examined for the period September, 2005 – February, 2012. In recent years there has been much research conducted into VaR in developed markets, while papers dealing with VaR calculation in CEE are rare. Furthermore, VaR models created and suited for liquid and welldeveloped markets that assume normal distribution are less reliable for capital markets in emerging economies, such as Central and Eastern European Union
member and candidate states. Since capital markets in European emerging economies are highly volatile, less liquid and strongly dependent on the unexpected external shocks, market risk estimation based on normality assumption in CEE countries is more problematic. This motivates us to implement GARCH-type methods that involve time varying volatility and heavy tails of the empirical distribution of returns. We test the hypothesis that using the assumption of heavy tailed distribution it is possible to forecast market risk more precisely, especially in times of crisis, than under the assumption of normal distribution or using historical simulations method. Our backtesting results for the last 500 observations are based on the Kupiec POF
and Christoffersen independence test. They show that GARCH-type models with terror distribution in most analysed cases give better VaR estimation than GARCH type models with normal errors in the case of a 99% confidence level, while in the case of a 95% confidence level it is the opposite. The results of backtesting analysis for the crisis period (after the collapse of Lehman Brothers) show that GARCH-type
models with t-distribution of residuals provide better VaR estimates compared with GARCH-type models with normal distribution, historical simulations and RiskMetrics methods. The RiskMetrics method in the most cases underestimates market risk.

Ključne riječi
Value at Risk (VaR); emerging European Economies; GARCH models; backtesting

Hrčak ID: 171495

URI
https://hrcak.srce.hr/171495

Posjeta: 249 *