A Comparative Analysis of Value at Risk Measurement on Emerging Stock Markets: Case of Montenegro
References
- 1. Alexander, C. O., Leigh, C. T. (1997), “On the covariance matrices used in Value at Risk models”, Journal of Derivatives, Vol. 4, No. 3, pp. 50-62.
- 2. Anđelić, G., Djaković, V., Radišić, S. (2010), “Application of VaR in Emerging markets: A Case of Selected Central and Eastern European Countries”, African Journal of Business Management, Vol. 4, No. 17, pp. 3666-3680.
- 3. Anđelić, G., Milošev, I., Djaković, V. (2010), “Extreme value theory in emerging markets”, Economic Annals, Vol. LV, No. 185, pp. 63-106.
- 4. Angelidis, T., Benos, A., Degiannakis, S. (2004), “The use of GARCH models in VaR estimation”, Statistical Methodology, Vol. 1, No. 2, pp. 105-128.
- 5. Bollerslev, T. (1986), “Generalized autoregressive conditional heteroskedasticity”, Journal of Econometrics, Vol. 31, No. 3, pp. 307-327.
- 6. Bao, Y., Lee, T., Saltoglu, B. (2006), “Evaluating Predictive Performance of Value-at-Risk Models in Emerging Markets: A Reality Check”, Journal of Forecasting, Vol. 25, No. 2, pp. 101-128.
- 7. Bučevska, V. (2013), “An Empirical Evaluation of GARCH Models in Value-at-Risk Estimation: Evidence from the Macedonian Stock Exchange”, Business Systems Research, Vol. 4, No. 1, pp. 49-64.
- 8. Cerović, J. (2014), “Value at risk measuring and Extreme value theory: Evidence from Montenegro”, Facta Universitatis, Series: Economics and Organization, Vol. 11, No. 2, pp. 175-189.
- 9. Christoffersen, P., Hahn, J., Inoue, A. (2001), “Testing and Comparing Value-at-Risk Measures”, Journal of Empirical Finance, Vol. 8, No. 3, pp. 325-342.
- 10. Da Silva, A., Beatriz, V., de Melo Mendes, B., (2003), “Value-at-Risk and Extreme Returns in Asian Stock markets”, International Journal of Business, Vol. 8, No. 1, pp. 17-40.
- 11. De Haan, L., Ferreira, A. (2006). Extreme Value Theory: an Introduction. New York: Springer Science+Business Media LLC.
- 12. Embrechts, P., Resnick, S. I., Samorodnitsky, G. (1998), “Living on the edge”, Risk, Vol. 11, No. 1, pp. 96-100.
- 13. Engle, R. F. (1982), “Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom inflation”, Econometrica, Vol. 50, No. 4, pp. 987-1007.
- 14. Gençay, R., Selçuk, F. (2004), „Extreme value theory and value-at-risk: Relative performance in emerging markets“, International Journal of Forecasting, Vol. 20, No. 2, pp. 287-303.
- 15. Gilli, M., Kellezi, E. (2006), “An Application of Extreme Value Theory for Measuring Financial Risk”, Computational Economics, Vol. 27, No. 2, pp. 207-228.
- 16. Guermat, C., Harris, D. F. (2002), “Forecasting value at risk allowing for time and kurtosis of portfolio returns”, International Journal of Forecasting, Vol. 18, No. 3, pp. 409-419.
- 17. Harmantzis, F., L. Miao, Chien, Y. (2006), “Empirical Study of Value-at-Risk and Expected Shortfall Models with Heavy Tails”, Journal of Risk Finance, Vol. 7, No. 2, pp. 117-135.
- 18. Jorion, P. (2007). Value at Risk: The New Benchmark for Managing Financial Risk, 3rd ed., New York: McGraw-Hill.
- 19. Karadžić, V., Cerović, J. (2014), “Market Risk of the Western Balkans countries during the global financial crisis”, Economic Annals-XXI, Vol. 2014, No. 11-12, pp. 19-23.
- 20. Longerstaey, J., More, L. (1995). Introduction to RiskMetrics. Morgan Guaranty Trust Company.
- 21. Longin, F. M. (1996), “The Asymptotic Distribution of Extreme Stock Market Returns”, Journal of Business, Vol. 69, No. 3, pp. 383-408.
- 22. Manganelli, S., Engle, R. F. (2001), “Value at Risk Models in Finance”, available at: http://ssrn.com/abstract=356220 (12 December 2011)
- 23. McNeil, A. J., Frey, R. (2000), “Estimation of tail-related risk measures for heteroscedastic financial time series: An extreme value approach”, Journal of Empirical Finance, Vol. 7, No. 3-4, pp. 271- 300.
- 24. McNeil, A.J., Frey, R., Embrechts, P., (2005). Quantitative Risk Management. Princeton: Princeton University Press.
- 25. Mladenović Z., Miletić, M., Miletić, S. (2012), “Value at Risk in European Emerging Economies: Empirical Assessment of Financial Crisis Period”, paper presented at Scientific Conference: from Global Crisis to Economic Growth: which way to take?, 20.09-22.09.2012, Faculty of Economics, Belgrade.
- 26. Montenegroberza AD Podgorica, available at http://www.montenegroberza.com (18.06.2013).
- 27. Nikolić-Đorić, E., Đorić, D. (2011), “Dynamic Value at Risk Estimation for BELEX15”, Metodološki zvezki, Vol. 8, No. 1, pp. 79-98.
- 28. Onour, I. A. (2010), “Extreme Risk and Fat-Tails Distribution: Empirical Analysis”, Journal of Money, Investment and Banking, Vol. 13, No. 13, pp. 27-34.
- 29. Taylor, S. (1986). Modelling Financial Time Series. Chichester: Wiley.
- 30. Tsay, Ruey, S. (2010). Analysis of Financial Time Series, Third Edition. Hoboken, New Jersey: John Wiley & Sons, Inc.
- 31. Žiković, S., Aktan, B. (2009), “Global financial crisis and VaR performance in emerging markets: A case of EU candidate state - Turkey and Croatia”, Zbornik radova Ekonomskog fakulteta u Rijeci, Vol. 27, No. 1, pp.145-170.
- 32. Žiković, S., (2007), “Measuring Market Risk in EU New Member States”, available at: http://www.hnb.hr/dub-konf/13-konferencija/zivkovic.pdf (12 December 2011)
- 33. Wong, C. S., Cheng, Y. W., Wong, Y. P. (2002), “Market risk management of banks: Implications from the accuracy of VaR forecasts”, Journal of Forecasting, Vol. 22, No. 1, pp. 22-33.
Language: English
Page range: 36 - 55
Submitted on: May 10, 2014
Accepted on: Oct 31, 2014
Published on: May 9, 2015
Published by: IRENET - Society for Advancing Innovation and Research in Economy
In partnership with: Paradigm Publishing Services
Keywords:
Related subjects:
© 2015 Julija Cerović, Milena Lipovina-Božović, Saša Vujošević, published by IRENET - Society for Advancing Innovation and Research in Economy
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.