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Citations for "Methods for evaluating value-at-risk estimates"

by Jose A. Lopez

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  1. Odeh, Oluwarotimi O. & Featherstone, Allen M. & Sanjoy, Das, 2006. "Predicting Credit Default in an Agricultural Bank: Methods and Issues," 2006 Annual Meeting, February 5-8, 2006, Orlando, Florida 35359, Southern Agricultural Economics Association.
  2. McAleer, M.J. & Jiménez-Martín, J.A. & Pérez-Amaral, T., 2010. "GFC-Robust Risk Management Strategies under the Basel Accord," Econometric Institute Research Papers EI 2010-59, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  3. Louzis, Dimitrios P. & Xanthopoulos-Sisinis, Spyros & Refenes, Apostolos P., 2011. "Are realized volatility models good candidates for alternative Value at Risk prediction strategies?," MPRA Paper 30364, University Library of Munich, Germany.
  4. Roberto Casarin & Chia-Lin Chang & Juan-Ángel Jiménez-Martín & Michael McAleer & Teodosio Pérez Amaral, 2011. "Risk Management of Risk Under the Basel Accord: A Bayesian Approach to Forecasting Value-at-Risk of VIX Futures," Working Papers in Economics 11/26, University of Canterbury, Department of Economics and Finance.
  5. Jose A. Lopez, 1998. "Methods for evaluating value-at-risk estimates," Economic Policy Review, Federal Reserve Bank of New York, issue Oct, pages 119-124.
  6. Wai Yan Cheng & Michael Chak Sham Wong & Clement Yuk Pang Wong, 2003. "Market risk management of banks: implications from the accuracy of Value-at-Risk forecasts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 22(1), pages 23-33.
  7. Hashem Pesaran & Paolo Zaffaroni & Banca d'Italia), 2004. "Model Averaging and Value-at-Risk based Evaluation of Large Multi Asset Volatility Models for Risk Management," Money Macro and Finance (MMF) Research Group Conference 2004 101, Money Macro and Finance Research Group.
  8. McAleer, M.J. & Jiménez-Martín, J.A. & Pérez-Amaral, T., 2012. "Has the Basel Accord Improved Risk Management During the Global Financial Crisis?," Econometric Institute Research Papers EI 2012-29, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  9. Hung, Jui-Cheng & Lee, Ming-Chih & Liu, Hung-Chun, 2008. "Estimation of value-at-risk for energy commodities via fat-tailed GARCH models," Energy Economics, Elsevier, vol. 30(3), pages 1173-1191, May.
  10. Su, Jung-Bin & Lee, Ming-Chih & Chiu, Chien-Liang, 2014. "Why does skewness and the fat-tail effect influence value-at-risk estimates? Evidence from alternative capital markets," International Review of Economics & Finance, Elsevier, vol. 31(C), pages 59-85.
  11. Bahram Pesaran & M. Hashem Pesaran, 2010. "Conditional Volatility and Correlations of Weekly Returns and the VaR Analysis of 2008 Stock Market Crash," CESifo Working Paper Series 3023, CESifo Group Munich.
  12. 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.
  13. Liao, Yin, 2013. "The benefit of modeling jumps in realized volatility for risk prediction: Evidence from Chinese mainland stocks," Pacific-Basin Finance Journal, Elsevier, vol. 23(C), pages 25-48.
  14. Louzis, Dimitrios P. & Xanthopoulos-Sisinis, Spyros & Refenes, Apostolos P., 2014. "Realized volatility models and alternative Value-at-Risk prediction strategies," Economic Modelling, Elsevier, vol. 40(C), pages 101-116.
  15. da Veiga, Bernardo & Chan, Felix & McAleer, Michael, 2008. "Evaluating the impact of market reforms on Value-at-Risk forecasts of Chinese A and B shares," Pacific-Basin Finance Journal, Elsevier, vol. 16(4), pages 453-475, September.
  16. Dinghai Xu & Tony S. Wirjanto, 2008. "An Empirical Characteristic Function Approach to VaR under a Mixture of Normal Distribution with Time-Varying Volatility," Working Papers 08008, University of Waterloo, Department of Economics.
  17. Nomikos, Nikos K. & Pouliasis, Panos K., 2011. "Forecasting petroleum futures markets volatility: The role of regimes and market conditions," Energy Economics, Elsevier, vol. 33(2), pages 321-337, March.
  18. Ewa Ratuszny, 2015. "Risk Modeling of Commodities using CAViaR Models, the Encompassing Method and the Combined Forecasts," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 15, pages 129-156.
  19. Billio, Monica & Caporin, Massimiliano, 2009. "A generalized Dynamic Conditional Correlation model for portfolio risk evaluation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(8), pages 2566-2578.
  20. Joanna Górka, 2010. "The Sign RCA Models: Comparing Predictive Accuracy of VaR Measures," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 10, pages 61-80.
  21. Gaglianone, Wagner Piazza & Lima, Luiz Renato & Linton, Oliver & Smith, Daniel R., 2011. "Evaluating Value-at-Risk Models via Quantile Regression," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(1), pages 150-160.
  22. Jose A. Lopez & Marc R. Saidenberg, 1999. "Evaluating credit risk models," Working Papers in Applied Economic Theory 99-06, Federal Reserve Bank of San Francisco.
  23. Chiu, Yen-Chen & Chuang, I-Yuan & Lai, Jing-Yi, 2010. "The performance of composite forecast models of value-at-risk in the energy market," Energy Economics, Elsevier, vol. 32(2), pages 423-431, March.
  24. Christophe Boucher & Jón Daníelsson & Patrick Kouontchou & Bertrand Maillet, 2014. "Risk model-at-risk," Post-Print hal-01370130, HAL.
  25. Abad, Pilar & Benito, Sonia, 2013. "A detailed comparison of value at risk estimates," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 94(C), pages 258-276.
  26. repec:eme:mfipps:v:36:y:2010:i:3:p:436-452 is not listed on IDEAS
  27. Cerrato, Mario & Crosby, John & Kim, Minjoo & Zhao, Yang, 2017. "Relation between higher order comoments and dependence structure of equity portfolio," Journal of Empirical Finance, Elsevier, vol. 40(C), pages 101-120.
  28. Amengual, Dante & Fiorentini, Gabriele & Sentana, Enrique, 2013. "Sequential estimation of shape parameters in multivariate dynamic models," Journal of Econometrics, Elsevier, vol. 177(2), pages 233-249.
  29. M. Hashem Pesaran & Bahram Pesaran, 2007. "Volatilities and Conditional Correlations in Futures Markets with a Multivariate t Distribution," CESifo Working Paper Series 2056, CESifo Group Munich.
  30. Şener, Emrah & Baronyan, Sayad & Ali Mengütürk, Levent, 2012. "Ranking the predictive performances of value-at-risk estimation methods," International Journal of Forecasting, Elsevier, vol. 28(4), pages 849-873.
  31. Su, Jung-Bin, 2014. "Empirical analysis of long memory, leverage, and distribution effects for stock market risk estimates," The North American Journal of Economics and Finance, Elsevier, vol. 30(C), pages 1-39.
  32. Mapa, Dennis S. & Suaiso, Oliver Q., 2009. "Measuring market risk using extreme value theory," MPRA Paper 21246, University Library of Munich, Germany.
  33. Dinghai Xu, 2009. "The Applications of Mixtures of Normal Distributions in Empirical Finance: A Selected Survey," Working Papers 0904, University of Waterloo, Department of Economics, revised Sep 2009.
  34. Ruiz, Esther & Nieto, María Rosa, 2008. "Measuring financial risk : comparison of alternative procedures to estimate VaR and ES," DES - Working Papers. Statistics and Econometrics. WS ws087326, Universidad Carlos III de Madrid. Departamento de Estadística.
  35. Hamid, Alain & Heiden, Moritz, 2015. "Forecasting volatility with empirical similarity and Google Trends," Journal of Economic Behavior & Organization, Elsevier, vol. 117(C), pages 62-81.
  36. Degiannakis, Stavros & Potamia, Artemis, 2017. "Multiple-days-ahead value-at-risk and expected shortfall forecasting for stock indices, commodities and exchange rates: Inter-day versus intra-day data," International Review of Financial Analysis, Elsevier, vol. 49(C), pages 176-190.
  37. Ender Su & Thomas W. Knowles, 2006. "Asian Pacific Stock Market Volatility Modeling and Value at Risk Analysis," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 42(2), pages 18-62, April.
  38. Stavros Degiannakis, 2004. "Volatility forecasting: evidence from a fractional integrated asymmetric power ARCH skewed-t model," Applied Financial Economics, Taylor & Francis Journals, vol. 14(18), pages 1333-1342.
  39. Ning, Cathy & Xu, Dinghai & Wirjanto, Tony S., 2015. "Is volatility clustering of asset returns asymmetric?," Journal of Banking & Finance, Elsevier, vol. 52(C), pages 62-76.
  40. Flavio Bazzana, 2001. "I modelli interni per la valutazione del rischio di mercato secondo l'approccio del Value at Risk," Alea Tech Reports 011, Department of Computer and Management Sciences, University of Trento, Italy, revised 14 Jun 2008.
  41. Zikovic, Sasa & Aktan, Bora, 2011. "Decay factor optimisation in time weighted simulation -- Evaluating VaR performance," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1147-1159, October.
  42. Lima, Luiz Renato Regis de Oliveira & Neri, Breno de Andrade Pinheiro, 2006. "Comparing value-at-risk methodologies," Economics Working Papers (Ensaios Economicos da EPGE) 629, FGV/EPGE Escola Brasileira de Economia e Finanças, Getulio Vargas Foundation (Brazil).
  43. Chien-Liang Chiu & Ming-Chih Lee & Jui-Cheng Hung, 2005. "Estimation of Value-at-Risk under jump dynamics and asymmetric information," Applied Financial Economics, Taylor & Francis Journals, vol. 15(15), pages 1095-1106.
  44. Chiu, Yen-Chen & Chuang, I-Yuan, 2016. "The performance of the switching forecast model of value-at-risk in the Asian stock markets," Finance Research Letters, Elsevier, vol. 18(C), pages 43-51.
  45. Pesaran, B. & Pesaran, M.H., 2007. "Modelling Volatilities and Conditional Correlations in Futures Markets with a Multivariate t Distribution," Cambridge Working Papers in Economics 0734, Faculty of Economics, University of Cambridge.
  46. Andrés Eduardo Jiménez Gómez & Luis Fernando Melo Velandia, 2014. "Modelación de la asimetría y curtosis condicionales: una aplicación VaR para series colombianas," Borradores de Economia 834, Banco de la Republica de Colombia.
  47. Alizadeh, Amir H. & Gabrielsen, Alexandros, 2013. "Dynamics of credit spread moments of European corporate bond indexes," Journal of Banking & Finance, Elsevier, vol. 37(8), pages 3125-3144.
  48. Trino-Manuel Ñíguez & Javier Perote, 2012. "Forecasting Heavy-Tailed Densities with Positive Edgeworth and Gram-Charlier Expansions," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 74(4), pages 600-627, 08.
  49. Trino-Manuel Ñíguez, 2003. "Volatility And Var Forecasting For The Ibex-35 Stock-Return Index Using Figarch-Type Processes And Different Evaluation Criteria," Working Papers. Serie AD 2003-33, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
  50. Timotheos Angelidis & Stavros Degiannakis, 2007. "Backtesting VaR Models: An Expected Shortfall Approach," Working Papers 0701, University of Crete, Department of Economics.
  51. Kilic, Ekrem, 2006. "Violation duration as a better way of VaR model evaluation : evidence from Turkish market portfolio," MPRA Paper 5610, University Library of Munich, Germany.
  52. Christian T. Brownlees & Giampiero Gallo, 2007. "Volatility Forecasting Using Explanatory Variables and Focused Selection Criteria," Econometrics Working Papers Archive wp2007_04, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
  53. Ane, Thierry, 2006. "An analysis of the flexibility of Asymmetric Power GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 1293-1311, November.
This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.