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Citations for "Testing Density Forecasts, with Applications to Risk Management"

by Berkowitz, Jeremy

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  1. Chang, Kuang-Liang, 2009. "Do macroeconomic variables have regime-dependent effects on stock return dynamics? Evidence from the Markov regime switching model," Economic Modelling, Elsevier, vol. 26(6), pages 1283-1299, November.
  2. 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.
  3. Juan Carlos Escanciano & Zaichao Du, 2015. "Backtesting Expected Shortfall: Accounting for Tail Risk," Caepr Working Papers 2015-001, Center for Applied Economics and Policy Research, Economics Department, Indiana University Bloomington.
  4. Anthony Garratt & James Mitchell & Shaun P. Vahey, 2009. "Measuring output gap uncertainty," Reserve Bank of New Zealand Discussion Paper Series DP2009/15, Reserve Bank of New Zealand.
  5. Massimo Guidolin & Giovanna Nicodano, 2005. "Small Caps in International Equity Portfolios: The Effects of Variance Risk," CeRP Working Papers 41, Center for Research on Pensions and Welfare Policies, Turin (Italy).
  6. Ravazzolo Francesco & Vahey Shaun P., 2014. "Forecast densities for economic aggregates from disaggregate ensembles," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 18(4), pages 15, September.
  7. Vasileios Siakoulis & Ioannis Venetis, 2015. "On inter-arrival times of bond market extreme events. An application to seven European markets," Journal of Economics and Finance, Springer, vol. 39(4), pages 717-741, October.
  8. Alexios Ghalanos & Eduardo Rossi & Giovanni Urga, 2015. "Independent Factor Autoregressive Conditional Density Model," Econometric Reviews, Taylor & Francis Journals, vol. 34(5), pages 594-616, May.
  9. Manzan, Sebastiano & Zerom, Dawit, 2013. "Are macroeconomic variables useful for forecasting the distribution of U.S. inflation?," International Journal of Forecasting, Elsevier, vol. 29(3), pages 469-478.
  10. Erika Gomes-Gon\c{c}alves & Henryk Gzyl & Silvia Mayoral, 2014. "Two maxentropic approaches to determine the probability density of compound risk losses," Papers 1411.5625, arXiv.org, revised Nov 2014.
  11. Ivanova, Vesela & Puigvert Gutiérrez, Josep Maria, 2014. "Interest rate forecasts, state price densities and risk premium from Euribor options," Journal of Banking & Finance, Elsevier, vol. 48(C), pages 210-223.
  12. BAUWENS, Luc & STORTI, Giuseppe, 2007. "A component GARCH model with time varying weights," CORE Discussion Papers 2007019, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  13. Caglayan, Mustafa & Jehan, Zainab & Mouratidis, Kostas, 2012. "Asymmetric monetary policy rules for open economies: Evidence from four countries," MPRA Paper 37401, University Library of Munich, Germany.
  14. 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).
  15. Li, Xiao-Ming & Rose, Lawrence C., 2009. "The tail risk of emerging stock markets," Emerging Markets Review, Elsevier, vol. 10(4), pages 242-256, December.
  16. Kenourgios, Dimitris & Samitas, Aristeidis & Paltalidis, Nikos, 2011. "Financial crises and stock market contagion in a multivariate time-varying asymmetric framework," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 21(1), pages 92-106, February.
  17. Guidolin, Massimo & Timmermann, Allan, 2007. "Asset allocation under multivariate regime switching," Journal of Economic Dynamics and Control, Elsevier, vol. 31(11), pages 3503-3544, November.
  18. Francisco Alonso & Roberto Blanco & Gonzalo Rubio, 2005. "Testing the forecasting performace of IBEX 35 option implied risk neutral densities," Banco de Espa�a Working Papers 0504, Banco de Espa�a.
  19. Christophe Hurlin & Sessi Tokpavi, 2007. "Une Evaluation des Procédures de Backtesting," Working Papers halshs-00159846, HAL.
  20. Marc Saidenberg & Til Schuermann & May, . "The New Basel Capital Accord and Questions for Research," Center for Financial Institutions Working Papers 03-14, Wharton School Center for Financial Institutions, University of Pennsylvania.
  21. 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.
  22. Wong, Woon K., 2010. "Backtesting value-at-risk based on tail losses," Journal of Empirical Finance, Elsevier, vol. 17(3), pages 526-538, June.
  23. Raffaella Giacomini & Barbara Rossi, 2014. "Forecasting in nonstationary environments: What works and what doesn't in reduced-form and structural models," Economics Working Papers 1476, Department of Economics and Business, Universitat Pompeu Fabra.
  24. Roberta Cardani & Alessia Paccagnini & Stefania Villa, 2015. "Forecasting in a DSGE Model with Banking Intermediation: Evidence from the US," Working Papers 292, University of Milano-Bicocca, Department of Economics, revised Feb 2015.
  25. Massimo Guidolin & Carrie Fangzhou Na, 2007. "The economic and statistical value of forecast combinations under regime switching: an application to predictable U.S. returns," Working Papers 2006-059, Federal Reserve Bank of St. Louis.
  26. Francesco Ravazzolo & Shaun P Vahey, 2010. "Measuring Core Inflation in Australia with Disaggregate Ensembles," RBA Annual Conference Volume, in: Renée Fry & Callum Jones & Christopher Kent (ed.), Inflation in an Era of Relative Price Shocks Reserve Bank of Australia.
  27. Tsyplakov, Alexander, 2014. "Theoretical guidelines for a partially informed forecast examiner," MPRA Paper 55017, University Library of Munich, Germany.
  28. Giorgio Valente & Lucio Sarno, 2004. "Empirical Exchange Rate Models and Currency Risk: Some Evidence from Density Forecasts," Working Papers wp04-10, Warwick Business School, Finance Group.
  29. Dijk, D. van & Diks, C.G.H. & Panchenko, V., 2008. "Partial Likelihood-Based Scoring Rules for Evaluating Density Forecasts in Tails," CeNDEF Working Papers 08-03, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
  30. Bruce Mizrach, 2007. "Recovering Probabilistic Information From Options Prices and the Underlying," Departmental Working Papers 200702, Rutgers University, Department of Economics.
  31. Rossi, Barbara & Sekhposyan, Tatevik, 2014. "Evaluating predictive densities of US output growth and inflation in a large macroeconomic data set," International Journal of Forecasting, Elsevier, vol. 30(3), pages 662-682.
  32. Raunig, Burkhard, 2006. "The longer-horizon predictability of German stock market volatility," International Journal of Forecasting, Elsevier, vol. 22(2), pages 363-372.
  33. Weron, Rafał, 2014. "Electricity price forecasting: A review of the state-of-the-art with a look into the future," International Journal of Forecasting, Elsevier, vol. 30(4), pages 1030-1081.
  34. Bedendo, Mascia & Hodges, Stewart D., 2009. "The dynamics of the volatility skew: A Kalman filter approach," Journal of Banking & Finance, Elsevier, vol. 33(6), pages 1156-1165, June.
  35. José Renato Haas Ornelas, 2014. "Assessing the Forecast Ability of Risk-Neutral Densities and Real-World Densities from Emerging Markets Currencies," Working Papers Series 370, Central Bank of Brazil, Research Department.
  36. Refet S. Gürkaynak & Justin Wolfers, 2005. "Macroeconomic derivatives: an initial analysis of market-based macro forecasts, uncertainty, and risk," Working Paper Series 2005-26, Federal Reserve Bank of San Francisco.
  37. 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.
  38. Huurman, Christian & Ravazzolo, Francesco & Zhou, Chen, 2012. "The power of weather," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3793-3807.
  39. Davide Delle Monache & Ivan Petrella, 2014. "Adaptive Models and Heavy Tails," Birkbeck Working Papers in Economics and Finance 1409, Birkbeck, Department of Economics, Mathematics & Statistics.
  40. Weng, Haijie & Trück, Stefan, 2011. "Style analysis and Value-at-Risk of Asia-focused hedge funds," Pacific-Basin Finance Journal, Elsevier, vol. 19(5), pages 491-510, November.
  41. Hilde C. Bjørnland & Francesco Ravazzolo & Leif Anders Thorsrud, 2015. "Forecasting GDP with global components. This time is different," Working Paper 2015/05, Norges Bank.
  42. Andr� Lucas & Xin Zhang, 2014. "Score Driven exponentially Weighted Moving Average and Value-at-Risk Forecasting," Tinbergen Institute Discussion Papers 14-092/IV/DSF77, Tinbergen Institute, revised 09 Sep 2015.
  43. Dick Dijk & Philip Hans Franses, 2003. "Selecting a Nonlinear Time Series Model using Weighted Tests of Equal Forecast Accuracy," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 65(s1), pages 727-744, December.
  44. Trino-Manuel Niguez & Javier Perote, 2004. "Forecasting the density of asset returns," LSE Research Online Documents on Economics 6845, London School of Economics and Political Science, LSE Library.
  45. Philippas, Dionisis & Siriopoulos, Costas, 2013. "Putting the “C” into crisis: Contagion, correlations and copulas on EMU bond markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 27(C), pages 161-176.
  46. Bontemps, Christian & Meddahi, Nour, 2005. "Testing normality: a GMM approach," Journal of Econometrics, Elsevier, vol. 124(1), pages 149-186, January.
  47. Clements, Michael P, 2012. "Subjective and Ex Post Forecast Uncertainty : US Inflation and Output Growth," The Warwick Economics Research Paper Series (TWERPS) 995, University of Warwick, Department of Economics.
  48. Knut Are Aastveit & Karsten R. Gerdrup & Anne Sofie Jore & Leif Anders Thorsrud, 2011. "Nowcasting GDP in Real-Time: A Density Combination Approach," Working Papers 0003, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
  49. Wolters, Maik H., 2013. "Evaluating point and density forecasts of DSGE models," Economics Working Papers 2013-03, Christian-Albrechts-University of Kiel, Department of Economics.
  50. Andres, P. & Harvey, A., 2012. "The Dyanamic Location/Scale Model: with applications to intra-day financial data," Cambridge Working Papers in Economics 1240, Faculty of Economics, University of Cambridge.
  51. BAUWENS , Luc & GIOT, Pierre & GRAMMIG, Joachim & VEREDAS, David, 2000. "A comparison of financial duration models via density forecasts," CORE Discussion Papers 2000060, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  52. Monica Billio & Roberto Casarin & Francesco Ravazzolo & Herman K. van Dijk, 2012. "Time-varying Combinations of Predictive Densities using Nonlinear Filtering," Tinbergen Institute Discussion Papers 12-118/III, Tinbergen Institute.
  53. Juan Carlos Escanciano & Pei Pei, 2012. "Pitfalls in Backtesting Historical Simulation VaR Models," Caepr Working Papers 2012-003, Center for Applied Economics and Policy Research, Economics Department, Indiana University Bloomington.
  54. De Gooijer, Jan G. & Vidiella-i-Anguera, Antoni, 2004. "Forecasting threshold cointegrated systems," International Journal of Forecasting, Elsevier, vol. 20(2), pages 237-253.
  55. Andrea Monticini & Francesco Ravazzolo, 2011. "Forecasting the intraday market price of money," Working Paper 2011/06, Norges Bank.
  56. Chang, Kuang-Liang, 2010. "House price dynamics, conditional higher-order moments, and density forecasts," Economic Modelling, Elsevier, vol. 27(5), pages 1029-1039, September.
  57. Tommaso Proietti & Martyna Marczak & Gianluigi Mazzi, 2015. "EuroMInd-D: A Density Estimate of Monthly Gross Domestic Product for the Euro Area," CEIS Research Paper 340, Tor Vergata University, CEIS, revised 10 Apr 2015.
  58. Aramonte, Sirio & Giudice Rodriguez, Marius del & Wu, Jason, 2013. "Dynamic factor Value-at-Risk for large heteroskedastic portfolios," Journal of Banking & Finance, Elsevier, vol. 37(11), pages 4299-4309.
  59. CHOLLETE, Loran & HEINEN, Andréas & VALDESOGO, Alfonso, 2008. "Modeling international financial returns with a multivariate regime switching copula," CORE Discussion Papers 2008013, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  60. Igor Kheifets, 2014. "Specification Tests for Nonlinear Dynamic Models," Cowles Foundation Discussion Papers 1937, Cowles Foundation for Research in Economics, Yale University, revised Oct 2014.
  61. Anne Sofie Jore & James Mitchell & Shaun Vahey, 2008. "Combining Forecast Densities from VARs with Uncertain Instabilities," Reserve Bank of New Zealand Discussion Paper Series DP2008/18, Reserve Bank of New Zealand.
  62. Kang, Byung Jin & Kim, Tong Suk, 2008. "Empirical risk aversion functions-estimates and assessment of their reliability," International Review of Financial Analysis, Elsevier, vol. 17(5), pages 1123-1138, December.
  63. Wojciech Charemza & Carlos Diaz Vela & Svetlana Makarova, 2013. "Too many skew normal distributions? The practitioner’s perspective," Discussion Papers in Economics 13/07, Department of Economics, University of Leicester.
  64. Raunig, Burkhard, 2008. "The predictability of exchange rate volatility," Economics Letters, Elsevier, vol. 98(2), pages 220-228, February.
  65. Hugo Gerard & Kristoffer Nimark, 2008. "Combining multivariate density forecasts using predictive criteria," Economics Working Papers 1117, Department of Economics and Business, Universitat Pompeu Fabra, revised Oct 2008.
  66. Miguel A. Ferreira & Jose A. Lopez, 2004. "Evaluating interest rate covariance models within a value-at-risk framework," Working Paper Series 2004-03, Federal Reserve Bank of San Francisco.
  67. 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.
  68. Ida Wolden Bache & James Mitchell & Francesco Ravazzolo & Shaun P. Vahey, 2009. "Macro modelling with many models," Working Paper 2009/15, Norges Bank.
  69. Bartram, Söhnke M. & Wang, Yaw-Huei, 2015. "European financial market dependence: An industry analysis," Journal of Banking & Finance, Elsevier, vol. 59(C), pages 146-163.
  70. Liu, Xiaoquan & Shackleton, Mark B. & Taylor, Stephen J. & Xu, Xinzhong, 2007. "Closed-form transformations from risk-neutral to real-world distributions," Journal of Banking & Finance, Elsevier, vol. 31(5), pages 1501-1520, May.
  71. Deschamps, Philippe J., 2012. "Bayesian estimation of generalized hyperbolic skewed student GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3035-3054.
  72. 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.
  73. Tsyplakov, Alexander, 2013. "Evaluation of Probabilistic Forecasts: Proper Scoring Rules and Moments," MPRA Paper 45186, University Library of Munich, Germany.
  74. Siliverstovs, B. & van Dijk, D.J.C., 2003. "Forecasting industrial production with linear, nonlinear, and structural change models," Econometric Institute Research Papers EI 2003-16, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  75. Wagner Piazza Gaglianone & Jaqueline Terra Moura Marins, 2014. "Risk Assessment of the Brazilian FX Rate," Working Papers Series 344, Central Bank of Brazil, Research Department.
  76. repec:ctc:serie1:def10 is not listed on IDEAS
  77. Igor Kheifets, 2014. "Specification Tests for Nonlinear Dynamic Models," Working Papers w0209, Center for Economic and Financial Research (CEFIR).
  78. Bekiros Stelios & Paccagnini Alessia, 2015. "Estimating point and density forecasts for the US economy with a factor-augmented vector autoregressive DSGE model," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 19(2), pages 107-136, April.
  79. Christophe M. Boucher & Jon Danielsson & Patrick S. Kouontchou & Bertrand B. Maillet, 2013. "Risk models–at–risk," LSE Research Online Documents on Economics 59299, London School of Economics and Political Science, LSE Library.
  80. Durham, Garland B., 2006. "Monte Carlo methods for estimating, smoothing, and filtering one- and two-factor stochastic volatility models," Journal of Econometrics, Elsevier, vol. 133(1), pages 273-305, July.
  81. Sean D. Campbell, 2005. "A review of backtesting and backtesting procedures," Finance and Economics Discussion Series 2005-21, Board of Governors of the Federal Reserve System (U.S.).
  82. Todd E. Clark & Michael W. McCracken, 2013. "Evaluating the accuracy of forecasts from vector autoregressions," Working Papers 2013-010, Federal Reserve Bank of St. Louis.
  83. Lucio Sarno, 2003. "Nonlinear Exchange Rate Models: A Selective Overview," IMF Working Papers 03/111, International Monetary Fund.
  84. Christian Kascha & Francesco Ravazzolo, 2008. "Combining inflation density forecasts," Working Paper 2008/22, Norges Bank.
  85. Anthony Garratt & James Mitchell & Shaun P. Vahey & Elizabeth C. Wakerly, 2010. "Real-time Inflation Forecast Densities from Ensemble Phillips Curves," CAMA Working Papers 2010-34, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  86. Haas, Markus & Mittnik, Stefan & Mizrach, Bruce, 2006. "Assessing central bank credibility during the ERM crises: Comparing option and spot market-based forecasts," Journal of Financial Stability, Elsevier, vol. 2(1), pages 28-54, April.
  87. 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.
  88. Haas, Markus & Mittnik, Stefan & Paolella, Marc S., 2002. "Mixed normal conditional heteroskedasticity," CFS Working Paper Series 2002/10, Center for Financial Studies (CFS).
  89. Geweke, John & Amisano, Gianni, 2010. "Comparing and evaluating Bayesian predictive distributions of asset returns," International Journal of Forecasting, Elsevier, vol. 26(2), pages 216-230, April.
  90. Datta, Deepa Dhume & Londono, Juan M. & Ross, Landon J, 2014. "Generating Options-Implied Probability Densities to Understand Oil Market Events," International Finance Discussion Papers 1122, Board of Governors of the Federal Reserve System (U.S.).
  91. Marinela BARBULESCU & Alina HAGIU & Cristina BALDAN, 2015. "Contingencies For Measurement Of The Credit Risk," Scientific Bulletin - Economic Sciences, University of Pitesti, vol. 14(3), pages 60-65.
  92. Bartram, Sohnke M. & Taylor, Stephen J. & Wang, Yaw-Huei, 2007. "The Euro and European financial market dependence," Journal of Banking & Finance, Elsevier, vol. 31(5), pages 1461-1481, May.
  93. Hall, Stephen G. & Mitchell, James, 2007. "Combining density forecasts," International Journal of Forecasting, Elsevier, vol. 23(1), pages 1-13.
  94. 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.
  95. Corradi, Valentina & Swanson, Norman R., 2006. "Predictive density and conditional confidence interval accuracy tests," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 187-228.
  96. Ng, Jason & Forbes, Catherine S. & Martin, Gael M. & McCabe, Brendan P.M., 2013. "Non-parametric estimation of forecast distributions in non-Gaussian, non-linear state space models," International Journal of Forecasting, Elsevier, vol. 29(3), pages 411-430.
  97. Cees Diks & Valentyn Panchenko & Dick Van Dijk, 2011. "Likelihood-based scoring rules for comparing density forecasts in tails," Post-Print hal-00834423, HAL.
  98. Stavros Degiannakis & Pamela Dent & Christos Floros, 2014. "A Monte Carlo Simulation Approach to Forecasting Multi-period Value-at-Risk and Expected Shortfall Using the FIGARCH-skT Specification," Manchester School, University of Manchester, vol. 82(1), pages 71-102, 01.
  99. González-Rivera, Gloria & Yoldas, Emre, 2012. "Autocontour-based evaluation of multivariate predictive densities," International Journal of Forecasting, Elsevier, vol. 28(2), pages 328-342.
  100. Markku Lanne, 2006. "A Mixture Multiplicative Error Model for Realized Volatility," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 4(4), pages 594-616.
  101. 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 1209, University of Nevada, Las Vegas , Department of Economics.
  102. Isao Ishida, 2005. "Scanning Multivariate Conditional Densities with Probability Integral Transforms," CIRJE F-Series CIRJE-F-369, CIRJE, Faculty of Economics, University of Tokyo.
  103. Garland Durham & John Geweke, 2013. "Adaptive Sequential Posterior Simulators for Massively Parallel Computing Environments," Working Paper Series 9, Economics Discipline Group, UTS Business School, University of Technology, Sydney.
  104. Massimo Guidolin & Allan Timmerman, 2005. "Optimal portfolio choice under regime switching, skew and kurtosis preferences," Working Papers 2005-006, Federal Reserve Bank of St. Louis.
  105. Chen, Qian & Gerlach, Richard & Lu, Zudi, 2012. "Bayesian Value-at-Risk and expected shortfall forecasting via the asymmetric Laplace distribution," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3498-3516.
  106. Polanski, Arnold & Stoja, Evarist, 2014. "Co-dependence of extreme events in high frequency FX returns," Journal of International Money and Finance, Elsevier, vol. 44(C), pages 164-178.
  107. Pritsker, Matthew, 2006. "The hidden dangers of historical simulation," Journal of Banking & Finance, Elsevier, vol. 30(2), pages 561-582, February.
  108. Chen, Yi-Hsuan & Tu, Anthony H., 2013. "Estimating hedged portfolio value-at-risk using the conditional copula: An illustration of model risk," International Review of Economics & Finance, Elsevier, vol. 27(C), pages 514-528.
  109. Chang, Kuang-Liang, 2012. "Volatility regimes, asymmetric basis effects and forecasting performance: An empirical investigation of the WTI crude oil futures market," Energy Economics, Elsevier, vol. 34(1), pages 294-306.
  110. Amendola, Alessandra & Christian, Francq, 2009. "Concepts and tools for nonlinear time series modelling," MPRA Paper 15140, University Library of Munich, Germany.
  111. 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.
  112. Markus Haas & Stefan Mittnik & Marc Paolella, 2006. "Modelling and predicting market risk with Laplace-Gaussian mixture distributions," Applied Financial Economics, Taylor & Francis Journals, vol. 16(15), pages 1145-1162.
  113. Massimiliano Marcellino & Mario Porqueddu & Fabrizio Venditti, 2013. "Short-term GDP forecasting with a mixed frequency dynamic factor model with stochastic volatility," Temi di discussione (Economic working papers) 896, Bank of Italy, Economic Research and International Relations Area.
  114. Siakoulis, Vasilios, 2015. "Modeling bank default intensity in the USA using autoregressive duration models," MPRA Paper 64526, University Library of Munich, Germany.
  115. Michal Adam & Piotr Banbula & Michal Markun, 2015. "International Dependence and Contagion across Asset Classes: The Case of Poland," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 65(3), pages 254-270, May.
  116. Degiannakis, Stavros & Floros, Christos, 2013. "Modeling CAC40 volatility using ultra-high frequency data," Research in International Business and Finance, Elsevier, vol. 28(C), pages 68-81.
  117. Clements, Michael P., 2014. "Probability distributions or point predictions? Survey forecasts of US output growth and inflation," International Journal of Forecasting, Elsevier, vol. 30(1), pages 99-117.
  118. 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.
  119. Francisco Peñaranda, 2003. "Evaluation of joint density forecasts of stock and bond returns: predictability and parameter uncertainty," LSE Research Online Documents on Economics 24857, London School of Economics and Political Science, LSE Library.
  120. 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).
  121. 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.
  122. Friedmann, Ralph & Sanddorf-Kohle, Walter G., 2007. "A conditional distribution model for limited stock index returns," Journal of Economic Dynamics and Control, Elsevier, vol. 31(3), pages 721-741, March.
  123. Haas Markus, 2010. "Skew-Normal Mixture and Markov-Switching GARCH Processes," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(4), pages 1-56, September.
  124. Joanna Janczura & Rafał Weron, 2013. "Goodness-of-fit testing for the marginal distribution of regime-switching models with an application to electricity spot prices," AStA Advances in Statistical Analysis, Springer, vol. 97(3), pages 239-270, July.
  125. Anthony Garratt & James Mitchell & Shaun P. Vahey, 2011. "Measuring Output Gap Nowcast Uncertainty," CAMA Working Papers 2011-16, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  126. Peter Christoffersen & Stefano Mazzotta, 2004. "The Informational Content of Over-the-Counter Currency Options," CIRANO Working Papers 2004s-16, CIRANO.
  127. Guidolin, Massimo & Ono, Sadayuki, 2006. "Are the dynamic linkages between the macroeconomy and asset prices time-varying?," Journal of Economics and Business, Elsevier, vol. 58(5-6), pages 480-518.
  128. Leonidas Tsiaras, 2010. "Dynamic Models of Exchange Rate Dependence Using Option Prices and Historical Returns," CREATES Research Papers 2010-35, School of Economics and Management, University of Aarhus.
  129. Dr. James Mitchell, 2008. "Evaluating Density Forecasts: Forecast Combinations, Model Mixtures, Calibration and Sharpness," NIESR Discussion Papers 320, National Institute of Economic and Social Research.
  130. Ida Wolden Bache & Anne Sofie Jore & James Mitchell & Shaun P. Vahey, 2009. "Combining VAR and DSGE forecast densities," Working Paper 2009/23, Norges Bank.
  131. Silva Filho, Osvaldo Candido da & Ziegelmann, Flavio Augusto & Dueker, Michael J., 2012. "Modeling dependence dynamics through copulas with regime switching," Insurance: Mathematics and Economics, Elsevier, vol. 50(3), pages 346-356.
  132. Robert R. Bliss & Nikolaos Panigirtzoglou, 2001. "Recovering risk aversion from options," Working Paper Series WP-01-15, Federal Reserve Bank of Chicago.
  133. Christophe HURLIN & Sessi TOKPAVI, 2006. "Backtesting VaR Accuracy: A Simple and Powerful Test," LEO Working Papers / DR LEO 268, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
  134. Luiz Renato Regis de Oliveira Lima & Wagner Piazza Gaglianone, 2012. "Constructing Optimal Density Forecasts from Point Forecast Combinations," Série Textos para Discussão (Working Papers) 5, Programa de Pós-Graduação em Economia - PPGE, Universidade Federal da Paraíba.
  135. Fawcett, Nicholas & Koerber, Lena & Masolo, Riccardo & Waldron, Matthew, 2015. "Evaluating UK point and density forecasts from an estimated DSGE model: the role of off-model information over the financial crisis," Bank of England working papers 538, Bank of England.
  136. Fabozzi, Frank J. & Leccadito, Arturo & Tunaru, Radu S., 2014. "Extracting market information from equity options with exponential Lévy processes," Journal of Economic Dynamics and Control, Elsevier, vol. 38(C), pages 125-141.
  137. Righi, Marcelo Brutti & Ceretta, Paulo Sergio, 2015. "A comparison of Expected Shortfall estimation models," Journal of Economics and Business, Elsevier, vol. 78(C), pages 14-47.
  138. Monica Billio & Roberto Casarin & Francesco Ravazzolo & Herman K. van Dijk, 2012. "Combining predictive densities using Bayesian filtering with applications to US economic data," Working Papers 2012_16, Department of Economics, University of Venice "Ca' Foscari".
  139. Ziggel, Daniel & Berens, Tobias & Weiß, Gregor N.F. & Wied, Dominik, 2014. "A new set of improved Value-at-Risk backtests," Journal of Banking & Finance, Elsevier, vol. 48(C), pages 29-41.
  140. Sara Cecchetti & Laura Sigalotti, 2013. "Forward-looking robust portfolio selection," Temi di discussione (Economic working papers) 913, Bank of Italy, Economic Research and International Relations Area.
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