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Citations for "Evaluating Interval Forecasts"

by Christoffersen, Peter F

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  1. Geetesh Bhardwaj & Norman Swanson, 2004. "An Empirical Investigation of the Usefulness of ARFIMA Models for Predicting Macroeconomic and Financial Time Series," Departmental Working Papers 200422, Rutgers University, Department of Economics.
  2. Juan Carlos Escanciano & Carlos Velasco, 2008. "Specification Tests of Parametric Dynamic Conditional Quantiles," Caepr Working Papers 2008-021, Center for Applied Economics and Policy Research, Economics Department, Indiana University Bloomington.
  3. Knüppel, Malte & Schultefrankenfeld, Guido, 2008. "How informative are macroeconomic risk forecasts? An examination of the Bank of England's inflation forecasts," Discussion Paper Series 1: Economic Studies 2008,14, Deutsche Bundesbank, Research Centre.
  4. Lambert, Philippe & Laurent, Sébastien & Veredas, David, 2012. "Testing conditional asymmetry: A residual-based approach," Journal of Economic Dynamics and Control, Elsevier, vol. 36(8), pages 1229-1247.
  5. El Bouhadi, Abdelhamid & Achibane, Khalid, 2009. "The Predictive Power of Conditional Models: What Lessons to Draw with Financial Crisis in the Case of Pre-Emerging Capital Markets?," MPRA Paper 19482, University Library of Munich, Germany.
  6. SBRANA, Giacomo & SILVESTRINI, Andrea, 2010. "Aggregation of exponential smoothing processes with an application to portfolio risk evaluation," CORE Discussion Papers 2010039, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  7. Francis X. Diebold & Todd A. Gunther & Anthony S. Tay, . "Evaluating Density Forecasts," CARESS Working Papres 97-18, University of Pennsylvania Center for Analytic Research and Economics in the Social Sciences.
  8. Chuang, I-Yuan & Chiu, Yen-Chen & Edward Wang, C., 2008. "The performance of Asian airlines in the recent financial turmoil based on VaR and modified Sharpe ratio," Journal of Air Transport Management, Elsevier, vol. 14(5), pages 257-262.
  9. Houda Ben Hadj Boubaker, 2011. "The Forecasting Performance of Seasonal and Nonlinear Models," Asian Economic and Financial Review, Asian Economic and Social Society, vol. 1(1), pages 26-39, March.
  10. Bos, C.S. & Mahieu, R.J. & van Dijk, H.K., 1999. "Daily exchange rate behaviour and hedging of currency risk," Econometric Institute Research Papers EI 9936/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  11. M. Hashem Pesaran & Paolo Zaffaroni, 2004. "Model Averaging and Value-at-Risk Based Evaluation of Large Multi Asset Volatility Models for Risk Management," CESifo Working Paper Series 1358, CESifo Group Munich.
  12. Giordani, Paolo & Villani, Mattias, 2009. "Forecasting Macroeconomic Time Series With Locally Adaptive Signal Extraction," Working Paper Series 234, Sveriges Riksbank (Central Bank of Sweden).
  13. Cifter, Atilla & Ozun, Alper, 2007. "The Predictive Performance of Asymmetric Normal Mixture GARCH in Risk Management: Evidence from Turkey," MPRA Paper 2489, University Library of Munich, Germany.
  14. Chen, Qian & Gerlach, Richard H., 2013. "The two-sided Weibull distribution and forecasting financial tail risk," International Journal of Forecasting, Elsevier, vol. 29(4), pages 527-540.
  15. Cheng, Wan-Hsiu & Hung, Jui-Cheng, 2011. "Skewness and leptokurtosis in GARCH-typed VaR estimation of petroleum and metal asset returns," Journal of Empirical Finance, Elsevier, vol. 18(1), pages 160-173, January.
  16. Weron, Rafal & Misiorek, Adam, 2008. "Forecasting spot electricity prices: A comparison of parametric and semiparametric time series models," International Journal of Forecasting, Elsevier, vol. 24(4), pages 744-763.
  17. Jose A. Lopez, 1999. "Methods for evaluating value-at-risk estimates," Economic Review, Federal Reserve Bank of San Francisco, pages 3-17.
  18. Dick van Dijk & Timo Terasvirta & Philip Hans Franses, 2002. "Smooth Transition Autoregressive Models — A Survey Of Recent Developments," Econometric Reviews, Taylor & Francis Journals, vol. 21(1), pages 1-47.
  19. 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.
  20. Anastassios A. Drakos & Georgios P. Kouretas & Leonidas P. Zarangas, 2010. "Forecasting financial volatility of the Athens stock exchange daily returns: an application of the asymmetric normal mixture GARCH model," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 15(4), pages 331-350.
  21. Deschamps, Philippe J., 2011. "Bayesian Estimation of Generalized Hyperbolic Skewed Student GARCH Models," DQE Working Papers 16, Department of Quantitative Economics, University of Freiburg/Fribourg Switzerland, revised 09 Jun 2012.
  22. Reza Habibi, 2011. "A Simple Estimate of VAR under Garch Modelling," Ekonomia, Cyprus Economic Society and University of Cyprus, vol. 14(2), pages 127-136, Winter.
  23. Giacomo Bormetti & Maria Elena De Giuli & Danilo Delpini & Claudia Tarantola, 2008. "Bayesian Analysis of Value-at-Risk with Product Partition Models," Papers 0809.0241, arXiv.org, revised May 2009.
  24. Guermat, Cherif & Harris, Richard D. F., 2002. "Forecasting value at risk allowing for time variation in the variance and kurtosis of portfolio returns," International Journal of Forecasting, Elsevier, vol. 18(3), pages 409-419.
  25. 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.
  26. Christian T. Brownlees & Giampiero Gallo, 2008. "Comparison of Volatility Measures: a Risk Management Perspective," Econometrics Working Papers Archive wp2008_03, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
  27. Polanski, Arnold & Stoja, Evarist & Zhang, Ren, 2013. "Multidimensional risk and risk dependence," Journal of Banking & Finance, Elsevier, vol. 37(8), pages 3286-3294.
  28. Goodness C. Aye & Mehmet Balcilar & Adél Bosch & Rangan Gupta & Francois Stofberg, 2013. "The out-of-sample forecasting performance of non-linear models of real exchange rate behaviour: The case of the South African Rand," European Journal of Comparative Economics, Cattaneo University (LIUC), vol. 10(1), pages 121-148, April.
  29. Shawkat Hammoudeh & Farooq Malik & Michael McAleer, 2011. "Risk Management of Precious Metals," Documentos del Instituto Complutense de Análisis Económico 2011-04, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales.
  30. Robert F. Engle & Simone Manganelli, 2004. "CAViaR: Conditional Autoregressive Value at Risk by Regression Quantiles," Journal of Business & Economic Statistics, American Statistical Association, vol. 22, pages 367-381, October.
  31. Wang, Kehluh & Chen, Yi-Hsuan & Huang, Szu-Wei, 2011. "The dynamic dependence between the Chinese market and other international stock markets: A time-varying copula approach," International Review of Economics & Finance, Elsevier, vol. 20(4), pages 654-664, October.
  32. Raggi, Davide & Bordignon, Silvano, 2006. "Comparing stochastic volatility models through Monte Carlo simulations," Computational Statistics & Data Analysis, Elsevier, vol. 50(7), pages 1678-1699, April.
  33. Cees Diks & Valentyn Panchenko & Dick van Dijk, 2011. "Likelihood-based scoring rules for comparing density forecasts in tails," Post-Print peer-00834423, HAL.
  34. Young Shin Kim & Rachev, Svetlozar T. & Bianchi, Michele Leonardo & Mitov, Ivan & Fabozzi, Frank J., 2010. "Time series analysis for financial market meltdowns," Working Paper Series in Economics 2, Karlsruhe Institute of Technology (KIT), Department of Economics and Business Engineering.
  35. Charles S. Bos & Philip Hans Franses & Marius Ooms, 2001. "Inflation, Forecast Intervals and Long Memory Regression Models," Tinbergen Institute Discussion Papers 01-029/4, Tinbergen Institute.
  36. Genaro Sucarrat & Alvaro Escribano, 2009. "Automated financial multi-path GETS modelling," Economics Working Papers we093620, Universidad Carlos III, Departamento de Economía.
  37. Valentina Corradi & Norman Swanson, 2003. "Some Recent Developments in Predictive Accuracy Testing With Nested Models and (Generic) Nonlinear Alternatives," Departmental Working Papers 200316, Rutgers University, Department of Economics.
  38. Dimitrios P. Louzis & Spyros Xanthopoulos‐Sisinis & Apostolos P. Refenes, 2013. "The Role of High‐Frequency Intra‐daily Data, Daily Range and Implied Volatility in Multi‐period Value‐at‐Risk Forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(6), pages 561-576, 09.
  39. Clements, Michael P. & Smith, Jeremy, 2002. "Evaluating multivariate forecast densities: a comparison of two approaches," International Journal of Forecasting, Elsevier, vol. 18(3), pages 397-407.
  40. Ludwig, Alexander, 2013. "Sovereign risk contagion in the Eurozone: a time-varying coefficient approach," MPRA Paper 52340, University Library of Munich, Germany.
  41. Chib, Siddhartha & Nardari, Federico & Shephard, Neil, 2006. "Analysis of high dimensional multivariate stochastic volatility models," Journal of Econometrics, Elsevier, vol. 134(2), pages 341-371, October.
  42. Su, Jung-Bin & Hung, Jui-Cheng, 2011. "Empirical analysis of jump dynamics, heavy-tails and skewness on value-at-risk estimation," Economic Modelling, Elsevier, vol. 28(3), pages 1117-1130, May.
  43. David E. Allen & Michael McAleer & Marcel Scharth, 2013. "Realized Volatility Risk," Tinbergen Institute Discussion Papers 13-092/III, Tinbergen Institute.
  44. Kocięcki, Andrzej & Kolasa, Marcin & Rubaszek, Michał, 2012. "A Bayesian method of combining judgmental and model-based density forecasts," Economic Modelling, Elsevier, vol. 29(4), pages 1349-1355.
  45. Hendry, David F & Michael P. Clements, 2002. "Economic Forecasting: Some Lessons from Recent Research," Royal Economic Society Annual Conference 2002 99, Royal Economic Society.
  46. Jakub Nowotarski & Rafal Weron, 2014. "Merging quantile regression with forecast averaging to obtain more accurate interval forecasts of Nord Pool spot prices," HSC Research Reports HSC/14/03, Hugo Steinhaus Center, Wroclaw University of Technology.
  47. Jacobson, Tor & Kindell, Rikard & Lindé, Jesper & Roszbach, Kasper F., 2008. "Firm Default and Aggregate Fluctuations," CEPR Discussion Papers 7083, C.E.P.R. Discussion Papers.
  48. André A. P. Santos & Francisco J. Nogales & Esther Ruiz, 2013. "Comparing Univariate and Multivariate Models to Forecast Portfolio Value-at-Risk," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 11(2), pages 400-441, March.
  49. Borusyak, K., 2011. "Nonlinear Dynamics of the Russian Stock Market in Problems of Risk Management," Journal of the New Economic Association, New Economic Association, issue 11, pages 85-105.
  50. Med Imen Gallali & Raggad Zahraa, 2012. "Evaluation of VaR models' forecasting performance: the case of oil markets," International Journal of Financial Services Management, Inderscience Enterprises Ltd, vol. 5(3), pages 197-215.
  51. Rabeh Khalfaoui & Mohammed Boutahar, 2012. "Portfolio Risk Evaluation An Approach Based on Dynamic Conditional Correlations Models and Wavelet Multi-Resolution Analysis," AMSE Working Papers 1208, Aix-Marseille School of Economics, Marseille, France.
  52. Taylor, James W., 2006. "Density forecasting for the efficient balancing of the generation and consumption of electricity," International Journal of Forecasting, Elsevier, vol. 22(4), pages 707-724.
  53. Mohammed Bouaddi & Jeroen V.K. Rombouts, 2007. "Mixed Exponential Power Asymmetric Conditional Heteroskedasticity," Cahiers de recherche 0749, CIRPEE.
  54. Pesaran, Bahram & Pesaran, M. Hashem, 2010. "Conditional volatility and correlations of weekly returns and the VaR analysis of 2008 stock market crash," Economic Modelling, Elsevier, vol. 27(6), pages 1398-1416, November.
  55. Makoto Takahashi & Toshiaki Watanabe & Yasuhiro Omori, 2014. "Volatility and Quantile Forecasts by Realized Stochastic Volatility Models with Generalized Hyperbolic Distribution," CIRJE F-Series CIRJE-F-921, CIRJE, Faculty of Economics, University of Tokyo.
  56. Cheng, Xixin & Li, W.K. & Yu, Philip L.H. & Zhou, Xuan & Wang, Chao & Lo, P.H., 2011. "Modeling threshold conditional heteroscedasticity with regime-dependent skewness and kurtosis," Computational Statistics & Data Analysis, Elsevier, vol. 55(9), pages 2590-2604, September.
  57. Lúcio Godeiro, Lucas, 2012. "Estimando o VaR (Value-at-Risk) de carteiras via modelos da família GARCH e via Simulação de Monte Carlo
    [Estimating the VaR (Value-at-Risk) of portfolios via GARCH family models and via Monte C
    ," MPRA Paper 45146, University Library of Munich, Germany.
  58. Taylor, Nicholas, 2007. "A note on the importance of overnight information in risk management models," Journal of Banking & Finance, Elsevier, vol. 31(1), pages 161-180, January.
  59. Peter F. Christoffersen & Francis X. Diebold & Til Schuermann, 1998. "Horizon problems and extreme events in financial risk management," Economic Policy Review, Federal Reserve Bank of New York, issue Oct, pages 109-118.
  60. GIOT, Pierre, 2003. "The information content of implied volatility indexes for forecasting volatility and market risk," CORE Discussion Papers 2003027, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  61. Candelon, Bertrand & Joëts, Marc & Tokpavi, Sessi, 2013. "Testing for Granger causality in distribution tails: An application to oil markets integration," Economic Modelling, Elsevier, vol. 31(C), pages 276-285.
  62. repec:dgr:uvatin:2013047 is not listed on IDEAS
  63. Martin Larch & Jo�o Nogueira Martins, 2007. "Fiscal indicators - Proceedings of the the Directorate-General for Economic and Financial Affairs Workshop held on 22 September 2006 in Brussels," European Economy - Economic Papers 297, Directorate General Economic and Monetary Affairs (DG ECFIN), European Commission.
  64. Clements, Michael P., 2008. "Explanations of the inconsistencies in survey respondents'forecasts," The Warwick Economics Research Paper Series (TWERPS) 870, University of Warwick, Department of Economics.
  65. Maheu, John M. & McCurdy, Thomas H., 2000. "Volatility dynamics under duration-dependent mixing," Journal of Empirical Finance, Elsevier, vol. 7(3-4), pages 345-372, November.
  66. Nikoloulopoulos, Aristidis K. & Joe, Harry & Li, Haijun, 2012. "Vine copulas with asymmetric tail dependence and applications to financial return data," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3659-3673.
  67. Konstantinidi, Eirini & Skiadopoulos, George, 2011. "Are VIX futures prices predictable? An empirical investigation," International Journal of Forecasting, Elsevier, vol. 27(2), pages 543-560, April.
  68. Martin Martens & Dick van Dijk & Michiel de Pooter, 2004. "Modeling and Forecasting S&P 500 Volatility: Long Memory, Structural Breaks and Nonlinearity," Tinbergen Institute Discussion Papers 04-067/4, Tinbergen Institute.
  69. Ortobelli, Sergio & Rachev, Svetlozar T. & Fabozzi, Frank J., 2010. "Risk management and dynamic portfolio selection with stable Paretian distributions," Journal of Empirical Finance, Elsevier, vol. 17(2), pages 195-211, March.
  70. Thomakos, Dimitrios D. & Wang, Tao, 2010. "'Optimal' probabilistic and directional predictions of financial returns," Journal of Empirical Finance, Elsevier, vol. 17(1), pages 102-119, January.
  71. 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.
  72. Marcelo Brutti Righi & Paulo Sergio Ceretta, 2013. "Pair Copula Construction based Expected Shortfall estimation," Economics Bulletin, AccessEcon, vol. 33(2), pages 1067-1072.
  73. Jean-Marie Dufour & Abderrahim Taamouti, 2008. "Exact optimal and adaptive inference in regression models under heteroskedasticity and non-normality of unknown forms," Economics Working Papers we086027, Universidad Carlos III, Departamento de Economía.
  74. Jian Wang & Jason J. Wu, 2008. "The Taylor rule and forecast intervals for exchange rates," Globalization and Monetary Policy Institute Working Paper 22, Federal Reserve Bank of Dallas.
  75. Giordani, Paolo & Söderlind, Paul, 2002. "Is there Evidence of Pessimism and Doubt in Subjective Distributions? A Comment on Abel," Working Paper Series in Economics and Finance 519, Stockholm School of Economics, revised 15 Aug 2003.
  76. Riadh Aloui & Mohamed Safouane Ben Aissa & Khuong Nguyen Duc, 2010. "Global Financial Crisis, Extreme Interdependences, and Contagion E§ects: The Role of Economic Structure," Working Papers 15, Development and Policies Research Center (DEPOCEN), Vietnam.
  77. Wagner Piazza Gaglianone & Luiz Renato Lima & Oliver Linton & Daniel Smith, 2010. "Evaluating Value-at-Risk Models via Quantile Regression," NCER Working Paper Series 67, National Centre for Econometric Research.
  78. Sabrina Khanniche, 2009. "Evaluation of Hedge Fund Returns Value at Risk Using GARCH Models," EconomiX Working Papers 2009-46, University of Paris West - Nanterre la Défense, EconomiX.
  79. Massimiliano Marzo & Paolo Zagaglia, 2010. "Volatility forecasting for crude oil futures," Applied Economics Letters, Taylor & Francis Journals, vol. 17(16), pages 1587-1599.
  80. Fantazzini, Dean, 2009. "The effects of misspecified marginals and copulas on computing the value at risk: A Monte Carlo study," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2168-2188, April.
  81. David Ardia & Lukasz Gatarek & Lennart F. Hoogerheide, 2014. "A New Bootstrap Test for the Validity of a Set of Marginal Models for Multiple Dependent Time Series: An Application to Risk Analysis," Tinbergen Institute Discussion Papers 14-028/III, Tinbergen Institute.
  82. Colletaz, Gilbert & Hurlin, Christophe & Pérignon, Christophe, 2013. "The Risk Map: A new tool for validating risk models," Journal of Banking & Finance, Elsevier, vol. 37(10), pages 3843-3854.
  83. Lucio Sarno, 2003. "Nonlinear Exchange Rate Models," IMF Working Papers 03/111, International Monetary Fund.
  84. Siem Jan Koopman & Charles S. Bos, 2002. "Time Series Models with a Common Stochastic Variance for Analysing Economic Time Series," Tinbergen Institute Discussion Papers 02-113/4, Tinbergen Institute.
  85. Gianna Boero & Emanuela Marrocu, 2005. "Evaluating non-linear models on point and interval forecasts: an application with exchange rates," BNL Quarterly Review, Banca Nazionale del Lavoro, vol. 58(232), pages 91-120.
  86. Leccadito, Arturo & Boffelli, Simona & Urga, Giovanni, 2014. "Evaluating the accuracy of value-at-risk forecasts: New multilevel tests," International Journal of Forecasting, Elsevier, vol. 30(2), pages 206-216.
  87. Mapa, Dennis S. & Suaiso, Oliver Q., 2009. "Measuring market risk using extreme value theory," MPRA Paper 21246, University Library of Munich, Germany.
  88. Shamiri, Ahmed & Shaari, Abu Hassan & Isa, Zaidi, 2007. "Practical Volatility Modeling for Financial Market Risk Management," MPRA Paper 9790, University Library of Munich, Germany, revised 15 May 2008.
  89. Arnold Polanski & Evarist Stoja, 2013. "Co-dependence of Extreme Events in High Frequency FX Returns," University of East Anglia Applied and Financial Economics Working Paper Series 040, School of Economics, University of East Anglia, Norwich, UK..
  90. Clements, Michael P. & Galvão, Ana Beatriz & Kim, Jae H., 2008. "Quantile forecasts of daily exchange rate returns from forecasts of realized volatility," Journal of Empirical Finance, Elsevier, vol. 15(4), pages 729-750, September.
  91. Liu, Hung-Chun & Chiang, Shu-Mei & Cheng, Nick Ying-Pin, 2012. "Forecasting the volatility of S&P depositary receipts using GARCH-type models under intraday range-based and return-based proxy measures," International Review of Economics & Finance, Elsevier, vol. 22(1), pages 78-91.
  92. Cifter, Atilla, 2011. "Value-at-risk estimation with wavelet-based extreme value theory: Evidence from emerging markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(12), pages 2356-2367.
  93. GIOT, Pierre & PETITJEAN, Mikael, 2005. "Dynamic asset allocation between stocks and bonds using the Bond-Equity Yield Ratio," CORE Discussion Papers 2005010, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  94. Chen, C.W.S. & Gerlach, R. & Hwang, B.B.K. & McAleer, M.J., 2011. "Forecasting Value-at-Risk Using Nonlinear Regression Quantiles and the Intraday Range," Econometric Institute Research Papers EI 2011-17, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  95. Kyungchul Song, 2009. "Testing Predictive Ability and Power Robustification," PIER Working Paper Archive 09-035, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
  96. Escanciano, Juan Carlos & Pei, Pei, 2012. "Pitfalls in backtesting Historical Simulation VaR models," Journal of Banking & Finance, Elsevier, vol. 36(8), pages 2233-2244.
  97. Gabriela De Raaij & Burkhard Raunig, 2005. "Evaluating density forecasts from models of stock market returns," The European Journal of Finance, Taylor & Francis Journals, vol. 11(2), pages 151-166.
  98. Van Bellegem, Sebastien & von Sachs, Rainer, 2004. "Forecasting economic time series with unconditional time-varying variance," International Journal of Forecasting, Elsevier, vol. 20(4), pages 611-627.
  99. Tsyplakov, Alexander, 2014. "Theoretical guidelines for a partially informed forecast examiner," MPRA Paper 55017, University Library of Munich, Germany.
  100. GIOT, Pierre & PETITJEAN, Mikael, 2006. "The information content of the Bond-Equity Yield Ratio: better than a random walk?," CORE Discussion Papers 2006089, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  101. Tsyplakov, Alexander, 2012. "Assessment of probabilistic forecasts: Proper scoring rules and moments," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 27(3), pages 115-132.
  102. Jeremy Berkowitz, 1999. "A coherent framework for stress-testing," Finance and Economics Discussion Series 1999-29, Board of Governors of the Federal Reserve System (U.S.).
  103. Worapree Maneesoonthorn & Gael M. Martin & Catherine S. Forbes & Simone Grose, 2010. "Probabilistic Forecasts of Volatility and its Risk Premia," Monash Econometrics and Business Statistics Working Papers 22/10, Monash University, Department of Econometrics and Business Statistics.
  104. 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.
  105. Sun, Xiaolei & Li, Jianping & Tang, Ling & Wu, Dengsheng, 2012. "Identifying the risk-return tradeoff and exploring the dynamic risk exposure of country portfolio of the FSU's oil economies," Economic Modelling, Elsevier, vol. 29(6), pages 2494-2503.
  106. 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.
  107. Nickell, Pamela & Perraudin, William & Varotto, Simone, 2007. "Ratings-based credit risk modelling: An empirical analysis," International Review of Financial Analysis, Elsevier, vol. 16(5), pages 434-451.
  108. Mehmet Balcilar & Rangan Gupta & Stephen M. Miller, 2012. "The Out-of-Sample Forecasting Performance of Non-Linear Models of Regional Housing Prices in the US," Working Papers 201226, University of Pretoria, Department of Economics.
  109. Valentina Corradi & Norman Swanson, 2003. "The Block Bootstrap for Parameter Estimation Error In Recursive Estimation Schemes, With Applications to Predictive Evaluation," Departmental Working Papers 200313, Rutgers University, Department of Economics.
  110. Caporin Massimiliano & Paruolo Paolo, 2005. "Multivariate ARCH with spatial effects for stock sector and size," Economics and Quantitative Methods qf0509, Department of Economics, University of Insubria.
  111. Stavros Degiannakis & Christos Floros & Alexandra Livada, 2012. "Evaluating value-at-risk models before and after the financial crisis of 2008: International evidence," Managerial Finance, Emerald Group Publishing, vol. 38(3), pages 436-452, March.
  112. Reeves, Jonathan J., 2005. "Bootstrap prediction intervals for ARCH models," International Journal of Forecasting, Elsevier, vol. 21(2), pages 237-248.
  113. Michael P. Clements & Nick Taylor, 2003. "Evaluating interval forecasts of high-frequency financial data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(4), pages 445-456.
  114. Francis X. Diebold & Jose A. Lopez, 1996. "Forecast Evaluation and Combination," NBER Technical Working Papers 0192, National Bureau of Economic Research, Inc.
  115. repec:wyi:journl:002190 is not listed on IDEAS
  116. Peter F. Christoffersen & Francis X. Diebold, 1997. "How Relevant is Volatility Forecasting for Financial Risk Management?," Center for Financial Institutions Working Papers 97-45, Wharton School Center for Financial Institutions, University of Pennsylvania.
  117. 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.
  118. Valentina Corradi & Norman Swanson, 2004. "Predective Density and Conditional Confidence Interval Accuracy Tests," Departmental Working Papers 200423, Rutgers University, Department of Economics.
  119. G. Boero & E. Marrocu, 2001. "Evaluating non-linear models on point and interval forecasts: an application with exchange rate returns," Working Paper CRENoS 200110, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
  120. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold, 2005. "Roughing it Up: Including Jump Components in the Measurement, Modeling and Forecasting of Return Volatility," NBER Working Papers 11775, National Bureau of Economic Research, Inc.
  121. Dick van Dijk & Philip Hans Franses & Michael P. Clements & Jeremy Smith, 2003. "On SETAR non-linearity and forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 22(5), pages 359-375.
  122. Alexander, Carol & Sheedy, Elizabeth, 2008. "Developing a stress testing framework based on market risk models," Journal of Banking & Finance, Elsevier, vol. 32(10), pages 2220-2236, October.
  123. Andrew J. Patton & Allan Timmermann, 2005. "Testable Implications of Forecast Optimality," STICERD - Econometrics Paper Series /2005/485, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
  124. Lee, Yun Shin & Scholtes, Stefan, 2014. "Empirical prediction intervals revisited," International Journal of Forecasting, Elsevier, vol. 30(2), pages 217-234.
  125. Michael McAleer & Bernardo da Veiga & Suhejla Hoti, 2010. "Value-at-Risk for Country Risk Ratings," Working Papers in Economics 10/29, University of Canterbury, Department of Economics and Finance.
  126. Bontemps, Christian & Meddahi, Nour, 2005. "Testing normality: a GMM approach," Journal of Econometrics, Elsevier, vol. 124(1), pages 149-186, January.
  127. Konstantinidi, Eirini & Skiadopoulos, George & Tzagkaraki, Emilia, 2008. "Can the evolution of implied volatility be forecasted? Evidence from European and US implied volatility indices," Journal of Banking & Finance, Elsevier, vol. 32(11), pages 2401-2411, November.
  128. Giordani, Paolo & Soderlind, Paul, 2003. "Inflation forecast uncertainty," European Economic Review, Elsevier, vol. 47(6), pages 1037-1059, December.
  129. Li, Yushu & Andersson, Jonas, 2014. "A Likelihood Ratio and Markov Chain Based Method to Evaluate Density Forecasting," Discussion Papers 2014/12, Department of Business and Management Science, Norwegian School of Economics.
  130. Goulas, Lambros & Skiadopoulos, George, 2012. "Are freight futures markets efficient? Evidence from IMAREX," International Journal of Forecasting, Elsevier, vol. 28(3), pages 644-659.
  131. Almeida, Caio & Vicente, José, 2009. "Are interest rate options important for the assessment of interest rate risk?," Journal of Banking & Finance, Elsevier, vol. 33(8), pages 1376-1387, August.
  132. Kabaila, Paul & Syuhada, Khreshna, 2010. "The asymptotic efficiency of improved prediction intervals," Statistics & Probability Letters, Elsevier, vol. 80(17-18), pages 1348-1353, September.
  133. Franses, Ph.H.B.F. & Kranendonk, H.C. & Lanser, D., 2007. "On the optimality of expert-adjusted forecasts," Econometric Institute Research Papers EI 2007-38, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  134. Haas, Markus & Krause, Jochen & Paolella, Marc S. & Steude, Sven C., 2013. "Time-varying mixture GARCH models and asymmetric volatility," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 602-623.
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