IDEAS home Printed from https://ideas.repec.org/r/eee/empfin/v12y2005i2p339-352.html
   My bibliography  Save this item

A comparison of extreme value theory approaches for determining value at risk

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Ana-Maria Gavril, 2009. "Exchange Rate Risk: Heads or Tails," Advances in Economic and Financial Research - DOFIN Working Paper Series 35, Bucharest University of Economics, Center for Advanced Research in Finance and Banking - CARFIB.
  2. George Kouretas & Leonidas Zarangas, 2005. "Conditional autoregressive valu at risk by regression quantile: Estimatingmarket risk for major stock markets," Working Papers 0521, University of Crete, Department of Economics.
  3. John Cotter & Kevin Dowd, 2010. "Estimating financial risk measures for futures positions: A nonparametric approach," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 30(7), pages 689-703, July.
  4. Ergün, A. Tolga & Jun, Jongbyung, 2010. "Time-varying higher-order conditional moments and forecasting intraday VaR and Expected Shortfall," The Quarterly Review of Economics and Finance, Elsevier, vol. 50(3), pages 264-272, August.
  5. Chrétien, Stéphane & Coggins, Frank, 2010. "Performance and conservatism of monthly FHS VaR: An international investigation," International Review of Financial Analysis, Elsevier, vol. 19(5), pages 323-333, December.
  6. Abdoul G. Sam, 2010. "Nonparametric estimation of market risk: an application to agricultural commodity futures," Agricultural Finance Review, Emerald Group Publishing Limited, vol. 70(2), pages 285-297, August.
  7. Alex Yi-Hou Huang & Tsung-Wei Tseng, 2009. "Forecast of value at risk for equity indices: an analysis from developed and emerging markets," Journal of Risk Finance, Emerald Group Publishing, vol. 10(4), pages 393-409, August.
  8. 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.
  9. Kole, Erik & Koedijk, Kees & Verbeek, Marno, 2007. "Selecting copulas for risk management," Journal of Banking & Finance, Elsevier, vol. 31(8), pages 2405-2423, August.
  10. 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.
  11. Dias, Alexandra, 2014. "Semiparametric estimation of multi-asset portfolio tail risk," Journal of Banking & Finance, Elsevier, vol. 49(C), pages 398-408.
  12. Davide Ferrari & Sandra Paterlini, 2009. "The Maximum Lq-Likelihood Method: An Application to Extreme Quantile Estimation in Finance," Methodology and Computing in Applied Probability, Springer, vol. 11(1), pages 3-19, March.
  13. Halkos, George & Tsirivis, Apostolos, 2019. "Using Value-at-Risk for effective energy portfolio risk management," MPRA Paper 91674, University Library of Munich, Germany.
  14. 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.
  15. Kokoszka Piotr & Miao Hong & Stoev Stilian & Zheng Ben, 2019. "Risk Analysis of Cumulative Intraday Return Curves," Journal of Time Series Econometrics, De Gruyter, vol. 11(2), pages 1-31, July.
  16. Julia S. Mehlitz & Benjamin R. Auer, 2021. "Time‐varying dynamics of expected shortfall in commodity futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(6), pages 895-925, June.
  17. Davide Ferrari & Sandra Paterlini, 2007. "The Maximum Lq-Likelihood Method: an Application to Extreme Quantile Estimation in Finance," Department of Economics 555, University of Modena and Reggio E., Faculty of Economics "Marco Biagi".
  18. Timotheos Angelidis & Alexandros Benos & Stavros Degiannakis, 2007. "A robust VaR model under different time periods and weighting schemes," Review of Quantitative Finance and Accounting, Springer, vol. 28(2), pages 187-201, February.
  19. Wei Sun & Svetlozar Rachev & Frank J. Fabozzi, 2009. "A New Approach for Using Lévy Processes for Determining High‐Frequency Value‐at‐Risk Predictions," European Financial Management, European Financial Management Association, vol. 15(2), pages 340-361, March.
  20. Palandri, Alessandro, 2020. "Sequential elimination: Fast sorts for unbiased quantile estimation," Finance Research Letters, Elsevier, vol. 33(C).
  21. Timotheos Angelidis & Alexandros Benos, 2006. "Liquidity adjusted value-at-risk based on the components of the bid-ask spread," Applied Financial Economics, Taylor & Francis Journals, vol. 16(11), pages 835-851.
  22. Halkos, George E. & Tsirivis, Apostolos S., 2019. "Value-at-risk methodologies for effective energy portfolio risk management," Economic Analysis and Policy, Elsevier, vol. 62(C), pages 197-212.
  23. Dias, Alexandra, 2013. "Market capitalization and Value-at-Risk," Journal of Banking & Finance, Elsevier, vol. 37(12), pages 5248-5260.
  24. Roland Füss & Zeno Adams & Dieter G Kaiser, 2010. "The predictive power of value-at-risk models in commodity futures markets," Journal of Asset Management, Palgrave Macmillan, vol. 11(4), pages 261-285, October.
  25. Jolanta Tamošaitienė & Vahidreza Yousefi & Hamed Tabasi, 2021. "Project Portfolio Construction Using Extreme Value Theory," Sustainability, MDPI, vol. 13(2), pages 1-13, January.
  26. Hamidreza Arian & Hossein Poorvasei & Azin Sharifi & Shiva Zamani, 2020. "The Uncertain Shape of Grey Swans: Extreme Value Theory with Uncertain Threshold," Papers 2011.06693, arXiv.org.
  27. Wei, Yu & Chen, Wang & Lin, Yu, 2013. "Measuring daily Value-at-Risk of SSEC index: A new approach based on multifractal analysis and extreme value theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(9), pages 2163-2174.
  28. Yuru Sun & Worapree Maneesoonthorn & Ruben Loaiza-Maya & Gael M. Martin, 2023. "Optimal probabilistic forecasts for risk management," Papers 2303.01651, arXiv.org.
  29. Paolella, Marc S., 2017. "Asymmetric stable Paretian distribution testing," Econometrics and Statistics, Elsevier, vol. 1(C), pages 19-39.
  30. González-Sánchez, Mariano & Nave Pineda, Juan M., 2023. "Where is the distribution tail threshold? A tale on tail and copulas in financial risk measurement," International Review of Financial Analysis, Elsevier, vol. 86(C).
  31. Chavez-Demoulin, V. & Embrechts, P. & Sardy, S., 2014. "Extreme-quantile tracking for financial time series," Journal of Econometrics, Elsevier, vol. 181(1), pages 44-52.
  32. Grażyna Trzpiot & Justyna Majewska, 2010. "Estimation of Value at Risk: extreme value and robust approaches," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 20(1), pages 131-143.
  33. Safarian, Mher, 2013. "On portfolio risk estimation," Working Paper Series in Economics 52, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
  34. Abdul-Aziz Ibn Musah & Jianguo Du & Hira Salah Ud din Khan & Alhassan Alolo Abdul-Rasheed Akeji, 2018. "The Asymptotic Decision Scenarios of an Emerging Stock Exchange Market: Extreme Value Theory and Artificial Neural Network," Risks, MDPI, vol. 6(4), pages 1-24, November.
  35. Hamed Tabasi & Vahidreza Yousefi & Jolanta Tamošaitienė & Foroogh Ghasemi, 2019. "Estimating Conditional Value at Risk in the Tehran Stock Exchange Based on the Extreme Value Theory Using GARCH Models," Administrative Sciences, MDPI, vol. 9(2), pages 1-17, May.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.