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Disturbing Extremal Behavior of Spot Rate Dynamics

Citations

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Cited by:

  1. Li, Longqing, 2017. "A Comparative Study of GARCH and EVT Model in Modeling Value-at-Risk," MPRA Paper 85645, University Library of Munich, Germany.
  2. Straetmans, Stefan & Chaudhry, Sajid M., 2015. "Tail risk and systemic risk of US and Eurozone financial institutions in the wake of the global financial crisis," Journal of International Money and Finance, Elsevier, vol. 58(C), pages 191-223.
  3. Karmakar, Madhusudan & Shukla, Girja K., 2015. "Managing extreme risk in some major stock markets: An extreme value approach," International Review of Economics & Finance, Elsevier, vol. 35(C), pages 1-25.
  4. Turan G. Bali, 2007. "A Generalized Extreme Value Approach to Financial Risk Measurement," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(7), pages 1613-1649, October.
  5. Krehbiel, Tim & Adkins, Lee C., 2008. "Extreme daily changes in U.S. Dollar London inter-bank offer rates," International Review of Economics & Finance, Elsevier, vol. 17(3), pages 397-411.
  6. Paraschiv, Florentina & Mudry, Pierre-Antoine & Andries, Alin Marius, 2015. "Stress-testing for portfolios of commodity futures," Economic Modelling, Elsevier, vol. 50(C), pages 9-18.
  7. Samit Paul & Madhusudan Karmakar, 2017. "Relative Efficiency of Component GARCH-EVT Approach in Managing Intraday Market Risk," Multinational Finance Journal, Multinational Finance Journal, vol. 21(4), pages 247-283, December.
  8. Karmakar, Madhusudan & Paul, Samit, 2016. "Intraday risk management in International stock markets: A conditional EVT approach," International Review of Financial Analysis, Elsevier, vol. 44(C), pages 34-55.
  9. Yuan, Ying & Zhuang, Xin-tian & Liu, Zhi-ying & Huang, Wei-qiang, 2012. "Time-clustering behavior of sharp fluctuation sequences in Chinese stock markets," Chaos, Solitons & Fractals, Elsevier, vol. 45(6), pages 838-845.
  10. Chebbi, Ali & Hedhli, Amel, 2022. "Revisiting the accuracy of standard VaR methods for risk assessment: Using the Copula–EVT multidimensional approach for stock markets in the MENA region," The Quarterly Review of Economics and Finance, Elsevier, vol. 84(C), pages 430-445.
  11. Marco Rocco, 2011. "Extreme value theory for finance: a survey," Questioni di Economia e Finanza (Occasional Papers) 99, Bank of Italy, Economic Research and International Relations Area.
  12. Benjamin R. Auer & Benjamin Mögel, 2016. "How Accurate are Modern Value-at-Risk Estimators Derived from Extreme Value Theory?," CESifo Working Paper Series 6288, CESifo.
  13. Turan Bali & Panayiotis Theodossiou, 2007. "A conditional-SGT-VaR approach with alternative GARCH models," Annals of Operations Research, Springer, vol. 151(1), pages 241-267, April.
  14. Aditya Banerjee & Samit Paul, 2024. "Idiosyncrasies of Intraday Risk in Emerging and Developed Markets: Efficacy of the MCS-GARCH Model and Extreme Value Theory," Global Business Review, International Management Institute, vol. 25(2), pages 468-490, April.
  15. S. T. M. Straetmans & W. F. C. Verschoor & C. C. P. Wolff, 2008. "Extreme US stock market fluctuations in the wake of 9|11," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(1), pages 17-42.
  16. Candia, Claudio & Herrera, Rodrigo, 2024. "An empirical review of dynamic extreme value models for forecasting value at risk, expected shortfall and expectile," Journal of Empirical Finance, Elsevier, vol. 77(C).
  17. James W. Taylor & Keming Yu, 2016. "Using auto-regressive logit models to forecast the exceedance probability for financial risk management," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 179(4), pages 1069-1092, October.
  18. Benjamin Mögel & Benjamin R. Auer, 2018. "How accurate are modern Value-at-Risk estimators derived from extreme value theory?," Review of Quantitative Finance and Accounting, Springer, vol. 50(4), pages 979-1030, May.
  19. Basu, Sanjay, 2011. "Comparing simulation models for market risk stress testing," European Journal of Operational Research, Elsevier, vol. 213(1), pages 329-339, August.
  20. Xue Deng & Ying Liang, 2023. "Robust Portfolio Optimization Based on Semi-Parametric ARMA-TGARCH-EVT Model with Mixed Copula Using WCVaR," Computational Economics, Springer;Society for Computational Economics, vol. 61(1), pages 267-294, January.
  21. Bali, Turan G. & Weinbaum, David, 2007. "A conditional extreme value volatility estimator based on high-frequency returns," Journal of Economic Dynamics and Control, Elsevier, vol. 31(2), pages 361-397, February.
  22. Yun Feng & Weijie Hou & Yuping Song, 2024. "Tail risk forecasting and its application to margin requirements in the commodity futures market," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(5), pages 1513-1529, August.
  23. Youssef, Manel & Belkacem, Lotfi & Mokni, Khaled, 2015. "Value-at-Risk estimation of energy commodities: A long-memory GARCH–EVT approach," Energy Economics, Elsevier, vol. 51(C), pages 99-110.
  24. Tolikas, Konstantinos, 2014. "Unexpected tails in risk measurement: Some international evidence," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 476-493.
  25. Allen, Linda & Bali, Turan G., 2007. "Cyclicality in catastrophic and operational risk measurements," Journal of Banking & Finance, Elsevier, vol. 31(4), pages 1191-1235, April.
  26. Manel Youssef & Lotfi Belkacem & Khaled Mokni, 2015. "Extreme Value Theory and long-memory-GARCH Framework: Application to Stock Market," International Journal of Economics and Empirical Research (IJEER), The Economics and Social Development Organization (TESDO), vol. 3(8), pages 371-388, August.
  27. Riedel, Christoph & Wagner, Niklas, 2015. "Is risk higher during non-trading periods? The risk trade-off for intraday versus overnight market returns," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 39(C), pages 53-64.
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