Value at Risk and Extreme Value Theory: Application To The Johannesburg Securities Exchange

References

• Abad, P., Benito, S. & Lopez, C. 2014. ‘A comprehensive review of value at risk methodologies’, The Spanish Review of Financial Economics, 12(1): 15–32.
   Google Scholar
• Alexander, C. 2009. Market risk analysis, value at risk models (Vol. 4). England: John Wiley & Sons.
   Google Scholar
• Angelidis, T. & Benos, A. 2008. ‘Value-at-risk for Greek stocks’, Multinational Finance Journal, 12(1): 67–104.
   Google Scholar
• Balkema, A.A. & De Haan, L. 1974. ‘Residual life time at great age’, The Annals of Probability, 2(5): 792 – 804.
   Web of Science ®Google Scholar
• Campbell, S.D. 2006. ‘A review of backtesting and backtesting procedures’, The Journal of Risk, 9(2): 1–17.
   Google Scholar
• Coles, S., Bawa, J., Trenner, L. & Dorazio, P. 2001. An introduction to statistical modeling of extreme values (Vol. 208). London: Springer.
   Google Scholar
• Danielsson, J. 2011. Financial riskforecasting: The theory and practice of forecasting market risk with implementation in R and Matlab (Vol. 588). United Kingdom: John Wiley & Sons.
   Google Scholar
• Danielsson, J. & De Vries, C.G. 2000. ‘Value-at-risk and extreme returns’, Annales d'Economie et de Statistique, 60: 239–270.
   Google Scholar
• Dicks, A., Conradie, W.J. & De Wet, T. 2014. ‘Value at risk using GARCH volatility models augmented with extreme value theory’, Journal of Studies in Economics and Econometrics, 38(3): 1 – 18
   Google Scholar
• Diebold, F.X., Schuermann, T. & Stroughair, J.D. 2000. ‘Pitfalls and opportunities in the use of extreme value theory in risk management’, The Journal of Risk Finance, 1(2): 30–35.
   Google Scholar
• Gençay, R. & Selçuk, F. 2004. ‘Extreme value theory and value-at-risk: Relative performance in emerging markets’, International Journal of Forecasting, 20(2): 287–303.
   Web of Science ®Google Scholar
• Gençay, R., Selçuk, F. & Ulugulyagci, A. 2003. ‘High volatility, thick tails and extreme value theory in value-at-risk estimation’, Insurance: Mathematics and Economics, 33(2): 337–356.
   Web of Science ®Google Scholar
• Ghorbel, A. &Trabelsi, A. 2009. ‘Measure of financial risk using conditional extreme value copulas with EVT margins’, Journal of Risk, 11(4): 51–85.
   Web of Science ®Google Scholar
• Jansen, D.W. & De Vries, C.G. 1991. ‘On the frequency of large stock returns: Putting booms and busts into perspective’, The Review of Economics and Statistics, 73(1): 18–24.
   Web of Science ®Google Scholar
• Koedijk, K.G., Schafgans, M.M. & De Vries, C.G. 1990. ‘The tail index of exchange rate returns’, Journal of International Economics, 29(1-2-): 93–108.
   Web of Science ®Google Scholar
• Kupiec, P.H. 1995. ‘Techniques for verifying the accuracy of risk measurement models’, The Journal of Derivatives, 3(2): 79–84.
   Google Scholar
• Mancini, L. & Trojani, F. 2005. Robust semiparametric bootstrap methods for value at risk prediction under GARCH-type volatility processes. SSRN Working Paper. University of St. Gallen.
   Google Scholar
• Marimoutou, V., Raggad, B. & Trabelsi, A. 2009. ‘Extreme value theory and value at risk: Application to oil market’, Energy Economics, 31(4): 519–530.
   Web of Science ®Google Scholar
• McMillan, D. & Thupayagale, P. 2010. ‘Evaluating stock index return value-at-risk estimates in South Africa: Comparative evidence for symmetric, asymmetric and long memory GARCH models’, Journal of Emerging Market Finance, 9(3): 325–345.
   Google Scholar
• 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, 7(3-4-): 271–300.
   Google Scholar
• Nieppola, O. 2009. Backtesting value-at-risk models. Helsinki School of Economics. [Online] Available: https://aaltodoc.aalto.fi/handle/123456789/181
   Google Scholar
• Pattarathammas, S., Mokkhavesa, S. & Nilla-Or, P. 2008. Value-at-risk and expected shortfall under extreme value theory framework: An empirical study on Asian markets. In 2nd European Risk Conference, Milano.
   Google Scholar
• Pickands, J. 1975. ‘Statisticak inference using extreme order statistics’, The Annals of Statistics, 3(1): 119 – 131.
   Web of Science ®Google Scholar
• Rocco, M. 2014. ‘Extreme value theory for finance: A survey’, Journal of Economic Surveys, 28(1): 82–108.
   Web of Science ®Google Scholar
• Seymour, A.J. & Polakow, D.A. 2003. ‘A coupling of extreme-value theory and volatility estimation in emerging markets: A South African test’, Multinational Finance Journal, 7(1/2): 323.
   Google Scholar