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Citations for "A Forecast Comparison of Volatility Models: Does Anything Beat a GARCH(1,1)?"

by Asger Lunde & Peter Reinhard Hansen

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  1. Christian T. Brownlees & Giampiero M. Gallo, 2010. "Comparison of Volatility Measures: a Risk Management Perspective," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 8(1), pages 29-56, Winter.
  2. Valeria V. Lakshina, 2014. "The Fluke Of Stochastic Volatility Versus Garch Inevitability : Which Model Creates Better Forecasts?," HSE Working papers WP BRP 37/FE/2014, National Research University Higher School of Economics.
  3. Radchenko, Stanislav, 2005. "Oil price volatility and the asymmetric response of gasoline prices to oil price increases and decreases," Energy Economics, Elsevier, vol. 27(5), pages 708-730, September.
  4. Stavros Degiannakis & Evdokia Xekalaki, 2007. "Assessing the performance of a prediction error criterion model selection algorithm in the context of ARCH models," Applied Financial Economics, Taylor & Francis Journals, vol. 17(2), pages 149-171.
  5. Lin Zhao & Sweder van Wijnbergen, 2013. "A Real Option Perspective on Valuing Gas Fields," Tinbergen Institute Discussion Papers 13-126/VI/DSF60, Tinbergen Institute.
  6. Christian Conrad, 2007. "Non-negativity Conditions for the Hyperbolic GARCH Model," KOF Working papers 07-162, KOF Swiss Economic Institute, ETH Zurich.
  7. McMillan, David G., 2009. "The confusing time-series behaviour of real exchange rates: Are asymmetries important?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 19(4), pages 692-711, October.
  8. Peter Reinhard Hansen & Asger Lunde & James M. Nason, 2005. "Testing the significance of calendar effects," Working Paper 2005-02, Federal Reserve Bank of Atlanta.
  9. Ardliansyah, Rifqi, 2012. "Stock Market Integration and International Portfolio Diversification between U.S. and ASEAN Equity Markets," MPRA Paper 41958, University Library of Munich, Germany.
  10. Trino-Manuel Ñíguez, 2008. "Volatility and VaR forecasting in the Madrid Stock Exchange," Spanish Economic Review, Springer, vol. 10(3), pages 169-196, September.
  11. Roxana Halbleib & Valeri Voev, 2012. "Forecasting Covariance Matrices: A Mixed Frequency Approach," Working Paper Series of the Department of Economics, University of Konstanz 2012-30, Department of Economics, University of Konstanz.
  12. Charlot, Philippe & Marimoutou, Vêlayoudom, 2014. "On the relationship between the prices of oil and the precious metals: Revisiting with a multivariate regime-switching decision tree," Energy Economics, Elsevier, vol. 44(C), pages 456-467.
  13. Laurent Calvet & Adlai Fisher, 2003. "Regime-Switching and the Estimation of Multifractal Processes," Harvard Institute of Economic Research Working Papers 1999, Harvard - Institute of Economic Research.
  14. Amélie Charles & Olivier Darné, 2014. "Volatility persistence in crude oil markets," Post-Print hal-00940312, HAL.
  15. 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".
  16. Taylor, Nicholas, 2008. "Can idiosyncratic volatility help forecast stock market volatility?," International Journal of Forecasting, Elsevier, vol. 24(3), pages 462-479.
  17. ROMBOUTS, Jeroen V. K. & STENTOFT, Lars & VIOLANTE, Francesco, 2012. "The value of multivariate model sophistication: an application to pricing Dow Jones Industrial Average options," CORE Discussion Papers 2012003, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  18. Olga Efimova & Apostolos Serletis, 2014. "Energy Markets Volatility Modelling using GARCH," Working Papers 2014-39, Department of Economics, University of Calgary, revised 24 Feb 2014.
  19. Olivier Damette & Stéphane Goutte, 2014. "Tobin tax and trading volume tightening: a reassessment," Working Papers halshs-00926805, HAL.
  20. Cordis, Adriana S. & Kirby, Chris, 2014. "Discrete stochastic autoregressive volatility," Journal of Banking & Finance, Elsevier, vol. 43(C), pages 160-178.
  21. Massimiliano Caporin & Michael McAleer, 2011. "Ranking Multivariate GARCH Models by Problem Dimension: An Empirical Evaluation," Working Papers in Economics 11/23, University of Canterbury, Department of Economics and Finance.
  22. Francesco Audrino & Peter Bühlmann, 2009. "Splines for financial volatility," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 71(3), pages 655-670.
  23. Peter Hansen & Asger Lunde, 2003. "Consistent Preordering with an Estimated Criterion Function, with an Application to the Evaluation and Comparison of Volatility Models," Working Papers 2003-01, Brown University, Department of Economics.
  24. Shynkevich, Andrei, 2013. "Time-series momentum as an intra- and inter-industry effect: Implications for market efficiency," Journal of Economics and Business, Elsevier, vol. 69(C), pages 64-85.
  25. Oleg Korenok & Stanislav Radchenko, 2005. "The smooth transition autoregressive target zone model with the Gaussian stochastic volatility and TGARCH error terms with applications," Econometrics 0508015, EconWPA.
  26. Fantazzini, Dean, 2008. "Credit Risk Management," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 12(4), pages 84-137.
  27. David G. McMillan & Mark E. Wohar, 2010. "Stock return predictability and dividend-price ratio: a nonlinear approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 15(4), pages 351-365.
  28. repec:rwi:repape:0243 is not listed on IDEAS
  29. Andrew Patton, 2006. "Volatility Forecast Comparison using Imperfect Volatility Proxies," Research Paper Series 175, Quantitative Finance Research Centre, University of Technology, Sydney.
  30. Rodrigo A. Alfaro & Carmen Gloria Silva, 2008. "Volatilidad de Indices Accionarios: El caso del IPSA," Latin American Journal of Economics-formerly Cuadernos de Economía, Instituto de Economía. Pontificia Universidad Católica de Chile., vol. 45(132), pages 217-233.
  31. Benjamin R. Auer & Horst Rottmann, 2013. "Is there a Friday the 13th Effect in Emerging Asian Stock Markets?," CESifo Working Paper Series 4409, CESifo Group Munich.
  32. Maurício Yoshinori Une & Marcelo Savino Portugal, 2005. "Can fear beat hope? A story of GARCH-in-Mean-Level effects for Emerging Market Country Risks," Econometrics 0509006, EconWPA.
  33. Wong, Woon K. & Tu, Anthony H., 2009. "Market imperfections and the information content of implied and realized volatility," Pacific-Basin Finance Journal, Elsevier, vol. 17(1), pages 58-79, January.
  34. Köksal, Bülent, 2009. "A Comparison of Conditional Volatility Estimators for the ISE National 100 Index Returns," MPRA Paper 30510, University Library of Munich, Germany.
  35. Patton, Andrew J, 2001. "Estimation of Copula Models for Time Series of Possibly Different Length," University of California at San Diego, Economics Working Paper Series qt3fc1c8hw, Department of Economics, UC San Diego.
  36. repec:ebl:ecbull:eb-14-00886 is not listed on IDEAS
  37. Caporin, M. & McAleer, M.J., 2012. "Robust Ranking of Multivariate GARCH Models by Problem Dimension," Econometric Institute Research Papers EI2012-13, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  38. Wei, Yu, 2012. "Forecasting volatility of fuel oil futures in China: GARCH-type, SV or realized volatility models?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(22), pages 5546-5556.
  39. Rubia, Antonio & Sanchis-Marco, Lidia, 2013. "On downside risk predictability through liquidity and trading activity: A dynamic quantile approach," International Journal of Forecasting, Elsevier, vol. 29(1), pages 202-219.
  40. B. Dupoyet & H. R. Fiebig & D. P. Musgrove, 2011. "Arbitrage-free Self-organizing Markets with GARCH Properties: Generating them in the Lab with a Lattice Model," Papers 1112.2379, arXiv.org.
  41. Smith, Daniel R., 2007. "Conditional coskewness and asset pricing," Journal of Empirical Finance, Elsevier, vol. 14(1), pages 91-119, January.
  42. Mapa, Dennis S., 2003. "A Range-Based GARCH Model for Forecasting Volatility," MPRA Paper 21323, University Library of Munich, Germany.
  43. M. Marzo & P. Zagaglia, 2007. "Volatility Forecasting for Crude Oil Futures," Working Papers 599, Dipartimento Scienze Economiche, Universita' di Bologna.
  44. Luc Bauwens & Genaro Sucarrat, 2008. "General to specific modelling of exchange rate volatility : a forecast evaluation," Economics Working Papers we081810, Universidad Carlos III, Departamento de Economía.
  45. Gresnigt, Francine & Kole, Erik & Franses, Philip Hans, 2015. "Interpreting financial market crashes as earthquakes: A new Early Warning System for medium term crashes," Journal of Banking & Finance, Elsevier, vol. 56(C), pages 123-139.
  46. Benavides, Guillermo & Capistrán, Carlos, 2012. "Forecasting exchange rate volatility: The superior performance of conditional combinations of time series and option implied forecasts," Journal of Empirical Finance, Elsevier, vol. 19(5), pages 627-639.
  47. 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.
  48. Tetsuya Takaishi, 2013. "Empirical Analysis of Stochastic Volatility Model by Hybrid Monte Carlo Algorithm," Papers 1305.3184, arXiv.org.
  49. Klar, B. & Lindner, F. & Meintanis, S.G., 2012. "Specification tests for the error distribution in GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3587-3598.
  50. Luger, Richard, 2012. "Finite-sample bootstrap inference in GARCH models with heavy-tailed innovations," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3198-3211.
  51. Rossignolo, Adrian F. & Fethi, Meryem Duygun & Shaban, Mohamed, 2012. "Value-at-Risk models and Basel capital charges," Journal of Financial Stability, Elsevier, vol. 8(4), pages 303-319.
  52. Makoto Takahashi & Yasuhiro Omori & Toshiaki Watanabe, 2007. "Estimating Stochastic Volatility Models Using Daily Returns and Realized Volatility Simultaneously ( Revised in March 2008; Published in "Computational Statistics and Data Analysis", 53-6, 2," CARF F-Series CARF-F-108, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
  53. Weiß, Gregor N.F., 2011. "Are Copula-GoF-tests of any practical use? Empirical evidence for stocks, commodities and FX futures," The Quarterly Review of Economics and Finance, Elsevier, vol. 51(2), pages 173-188, May.
  54. repec:hal:journl:halshs-00259225 is not listed on IDEAS
  55. David E. Rapach & Jack K. Strauss, 2008. "Structural breaks and GARCH models of exchange rate volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(1), pages 65-90.
  56. Hsu, Po-Hsuan & Hsu, Yu-Chin & Kuan, Chung-Ming, 2010. "Testing the predictive ability of technical analysis using a new stepwise test without data snooping bias," Journal of Empirical Finance, Elsevier, vol. 17(3), pages 471-484, June.
  57. Roache, Shaun K. & Rossi, Marco, 2010. "The effects of economic news on commodity prices," The Quarterly Review of Economics and Finance, Elsevier, vol. 50(3), pages 377-385, August.
  58. BOUEZMARNI, Taoufik & ROMBOUTS, Jeroen V. K., 2006. "Nonparametric density estimation for positive time series," CORE Discussion Papers 2006085, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  59. Chevallier, Julien, 2011. "Detecting instability in the volatility of carbon prices," Economics Papers from University Paris Dauphine 123456789/5110, Paris Dauphine University.
  60. Yusaku Nishimura & Ming Men, 2010. "The paradox of China's international stock market co-movement: Evidence from volatility spillover effects between China and G5 stock markets," Journal of Chinese Economic and Foreign Trade Studies, Emerald Group Publishing, vol. 3(3), pages 235-253, December.
  61. Daniele Bianchi & Massimo Guidolin & Francesco Ravazzolo, 2013. "Macroeconomic factors strike back: A Bayesian change-point model of time-varying risk exposures and premia in the U.S. cross-section," Working Paper 2013/19, Norges Bank.
  62. 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.
  63. Belke, Ansgar & Gokus, Christian, 2011. "Volatility Patterns of CDS, Bond and Stock Markets Before and During the Financial Crisis – Evidence from Major Financial Institutions," Ruhr Economic Papers 243, Rheinisch-Westfälisches Institut für Wirtschaftsforschung (RWI), Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
  64. David E. Allen & Michael McAleer & Marcel Scharth, 2014. "Asymmetric Realized Volatility Risk," Tinbergen Institute Discussion Papers 14-075/III, Tinbergen Institute.
  65. R. Khalfaoui & M. Boutahar, 2012. "Portfolio Risk Evaluation: An Approach Based on Dynamic Conditional Correlations Models and Wavelet Multi-Resolution Analysis," Working Papers halshs-00793068, HAL.
  66. Hua, Jian & Manzan, Sebastiano, 2013. "Forecasting the return distribution using high-frequency volatility measures," Journal of Banking & Finance, Elsevier, vol. 37(11), pages 4381-4403.
  67. David E. Allen & Michael McAleer & Marcel Scharth, 2010. "Realized Volatility Risk," Working Papers in Economics 10/26, University of Canterbury, Department of Economics and Finance.
  68. Dupoyet, B. & Fiebig, H.R. & Musgrove, D.P., 2012. "Arbitrage-free self-organizing markets with GARCH properties: Generating them in the lab with a lattice model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(18), pages 4350-4363.
  69. José Curto & José Pinto & Gonçalo Tavares, 2009. "Modeling stock markets’ volatility using GARCH models with Normal, Student’s t and stable Paretian distributions," Statistical Papers, Springer, vol. 50(2), pages 311-321, March.
  70. Prateek Sharma & Swati Sharma, 2015. "Forecasting gains of robust realized variance estimators: evidence from European stock markets," Economics Bulletin, AccessEcon, vol. 35(1), pages 61-69.
  71. de Araújo, André da Silva & Garcia, Maria Teresa Medeiros, 2013. "Risk contagion in the north-western and southern European stock markets," Journal of Economics and Business, Elsevier, vol. 69(C), pages 1-34.
  72. Patton, Andrew J., 2011. "Data-based ranking of realised volatility estimators," Journal of Econometrics, Elsevier, vol. 161(2), pages 284-303, April.
  73. ERIC HILLEBRAND & MArcelo Cunha Medeiros, 2010. "Asymmetries, breaks, and long-range dependence: An estimation framework for daily realized volatility," Textos para discussão 578, Department of Economics PUC-Rio (Brazil).
  74. Takahashi, Makoto & Omori, Yasuhiro & Watanabe, Toshiaki, 2009. "Estimating stochastic volatility models using daily returns and realized volatility simultaneously," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2404-2426, April.
  75. King, Daniel & Botha, Ferdi, 2015. "Modelling stock return volatility dynamics in selected African markets," Economic Modelling, Elsevier, vol. 45(C), pages 50-73.
  76. Michał Adam & Piotr Bańbuła & Michał Markun, 2013. "Dependence and contagion between asset prices in Poland and abroad. A copula approach," National Bank of Poland Working Papers 169, National Bank of Poland, Economic Institute.
  77. Aurea Grané & Helena Veiga, 2010. "Outliers in Garch models and the estimation of risk measures," Statistics and Econometrics Working Papers ws100502, Universidad Carlos III, Departamento de Estadística y Econometría.
  78. Carluccio Bianchi & Alessandro Carta & Dean Fantazzini & Maria Elena De Giuli & Mario A. Maggi, 2009. "A Copula-VAR-X Approach for Industrial Production Modelling and Forecasting," Quaderni di Dipartimento 105, University of Pavia, Department of Economics and Quantitative Methods.
  79. Todd E. Clark & Francesco Ravazzolo, 2012. "The macroeconomic forecasting performance of autoregressive models with alternative specifications of time-varying volatility," Working Paper 2012/09, Norges Bank.
  80. Francq, Christian & Thieu, Le Quyen, 2015. "Qml inference for volatility models with covariates," MPRA Paper 63198, University Library of Munich, Germany.
  81. Shynkevich, Andrei, 2012. "Short-term predictability of equity returns along two style dimensions," Journal of Empirical Finance, Elsevier, vol. 19(5), pages 675-685.
  82. Celso Brunetti & Roberto S. Mariano & Chiara Scotti & Augustine H.H. Tan, 2007. "Markov switching GARCH models of currency turmoil in southeast Asia," International Finance Discussion Papers 889, Board of Governors of the Federal Reserve System (U.S.).
  83. Prono, Todd, 2011. "When A Factor Is Measured with Error: The Role of Conditional Heteroskedasticity in Identifying and Estimating Linear Factor Models," MPRA Paper 33593, University Library of Munich, Germany.
  84. Ting Ting Chen & Tetsuya Takaishi, 2013. "Empirical Study of the GARCH model with Rational Errors," Papers 1312.7057, arXiv.org.
  85. Frank J. Fabozzi & Rosella Giacometti & Naoshi Tsuchida, 2015. "The ICA-based Factor Decomposition of the Eurozone Sovereign CDS Spreads," IMES Discussion Paper Series 15-E-04, Institute for Monetary and Economic Studies, Bank of Japan.
  86. Ole E. Barndorff-Nielsen & Neil Shephard, 2005. "Variation, jumps, market frictions and high frequency data in financial econometrics," Economics Papers 2005-W16, Economics Group, Nuffield College, University of Oxford.
  87. repec:dgr:rugsom:14029-eef is not listed on IDEAS
  88. 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.
  89. Wei, Yu & Wang, Peng, 2008. "Forecasting volatility of SSEC in Chinese stock market using multifractal analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(7), pages 1585-1592.
  90. Laurent, Sébastien & Rombouts, Jeroen V.K. & Violante, Francesco, 2013. "On loss functions and ranking forecasting performances of multivariate volatility models," Journal of Econometrics, Elsevier, vol. 173(1), pages 1-10.
  91. Chung, Sang-Kuck, 2009. "Bivariate mixed normal GARCH models and out-of-sample hedge performances," Finance Research Letters, Elsevier, vol. 6(3), pages 130-137, September.
  92. Shinichiro Shirota & Takayuki Hizu & Yasuhiro Omori, 2013. "Realized Stochastic Volatility with Leverage and Long Memory," CIRJE F-Series CIRJE-F-880, CIRJE, Faculty of Economics, University of Tokyo.
  93. Peter Reinhard Hansen & Asger Lunde & James M. Nason, 2003. "Choosing the best volatility models: the model confidence set approach," Working Paper 2003-28, Federal Reserve Bank of Atlanta.
  94. Lin Zhao & Sweder van Wijnbergen, 2013. "A Real Option Perspective on Valuing Gas Fields," Tinbergen Institute Discussion Papers 13-126/VI/DSF60, Tinbergen Institute.
  95. Mohammadi, Hassan & Su, Lixian, 2010. "International evidence on crude oil price dynamics: Applications of ARIMA-GARCH models," Energy Economics, Elsevier, vol. 32(5), pages 1001-1008, September.
  96. 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.
  97. Friberg, Richard & Huse, Cristian, 2012. "How to use demand systems to evaluate risky projects, with an application to automobile production," MPRA Paper 48906, University Library of Munich, Germany.
  98. MArcelo Carvalho & MArco Aurelio Freire & Marcelo Cunha Medeiros & Leonardo Souza, 2006. "Modeling and forecasting the volatility of Brazilian asset returns," Textos para discussão 530, Department of Economics PUC-Rio (Brazil).
  99. Ardelean, Vlad & Pleier, Thomas, 2013. "Outliers & predicting time series: A comparative study," IWQW Discussion Paper Series 05/2013, Friedrich-Alexander-Universität Erlangen-Nürnberg, Institut für Wirtschaftspolitik und Quantitative Wirtschaftsforschung (IWQW).
  100. BenSaïda, Ahmed, 2015. "The frequency of regime switching in financial market volatility," Journal of Empirical Finance, Elsevier, vol. 32(C), pages 63-79.
  101. Nikolaus Hautsch & Lada M. Kyj & Peter Malec, 2013. "Do High-Frequency Data Improve High-Dimensional Portfolio Allocations?," SFB 649 Discussion Papers SFB649DP2013-014, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  102. Christian Conrad & Menelaos Karanasos & Ning Zeng, 2008. "Multivariate Fractionally Integrated APARCH Modeling of Stock Market Volatility: A multi-country study," Working Papers 0472, University of Heidelberg, Department of Economics, revised Jul 2008.
  103. A.S.K. Wong & P.J.G. Vlaar, 2003. "Modelling time-varying correlations of financial markets," WO Research Memoranda (discontinued) 739, Netherlands Central Bank, Research Department.
  104. Chen, Wang & Wei, Yu & Lang, Qiaoqi & Lin, Yu & Liu, Maojuan, 2014. "Financial market volatility and contagion effect: A copula–multifractal volatility approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 398(C), pages 289-300.
  105. Artis, Michael J & Clavel, Jose Garcia & Hoffmann, Mathias & Nachane, Dilip M, 2007. "Analyzing Strongly Periodic Series in the Frequency Domain: A Comparison of Alternative Approaches with Applications," CEPR Discussion Papers 6517, C.E.P.R. Discussion Papers.
  106. Georges Prat, 2010. "Equity Risk Premium and Time Horizon : What do the U.S. Secular Data Say ?," EconomiX Working Papers 2010-22, University of Paris West - Nanterre la Défense, EconomiX.
  107. Liu, Lily Y. & Patton, Andrew J. & Sheppard, Kevin, 2015. "Does anything beat 5-minute RV? A comparison of realized measures across multiple asset classes," Journal of Econometrics, Elsevier, vol. 187(1), pages 293-311.
  108. Siem Jan Koopman & Andre Lucas & Marcel Scharth, 2012. "Predicting Time-Varying Parameters with Parameter-Driven and Observation-Driven Models," Tinbergen Institute Discussion Papers 12-020/4, Tinbergen Institute.
  109. Mabrouk, Samir & Saadi, Samir, 2012. "Parametric Value-at-Risk analysis: Evidence from stock indices," The Quarterly Review of Economics and Finance, Elsevier, vol. 52(3), pages 305-321.
  110. Ma, Feng & Wei, Yu & Huang, Dengshi & Chen, Yixiang, 2014. "Which is the better forecasting model? A comparison between HAR-RV and multifractality volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 405(C), pages 171-180.
  111. Daniel Smith, 2008. "Testing for structural breaks in GARCH models," Applied Financial Economics, Taylor & Francis Journals, vol. 18(10), pages 845-862.
  112. Elie BOURI, 2011. "An Attempt to Capture Leptokurtic of Returns and to Model Its Volatility: The Case of Beirut Stock Exchange," Review of Economic and Business Studies, Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, issue 8, pages 259-271, December.
  113. Bekaert, Geert & Engstrom, Eric & Ermolov, Andrey, 2015. "Bad environments, good environments: A non-Gaussian asymmetric volatility model," Journal of Econometrics, Elsevier, vol. 186(1), pages 258-275.
  114. Bhattacharyya, Surajit & Saxena, Arunima, 2008. "Stock Futures Introduction & Its Impact on Indian Spot Market," MPRA Paper 15250, University Library of Munich, Germany.
  115. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold, 2003. "Some Like it Smooth, and Some Like it Rough: Untangling Continuous and Jump Components in Measuring, Modeling, and Forecasting Asset Return Volatility," PIER Working Paper Archive 03-025, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 01 Sep 2003.
  116. Helena Veiga, 2006. "Volatility Forecasts: A Continuous Time Model Versus Discrete Time Models1," Statistics and Econometrics Working Papers ws062509, Universidad Carlos III, Departamento de Estadística y Econometría.
  117. Andriosopoulos, Kostas & Doumpos, Michael & Papapostolou, Nikos C. & Pouliasis, Panos K., 2013. "Portfolio optimization and index tracking for the shipping stock and freight markets using evolutionary algorithms," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 52(C), pages 16-34.
  118. David E. Allen & Michael McAleer & Marcel Scharth, 2014. "Asymmetric Realized Volatility Risk," Tinbergen Institute Discussion Papers 14-075/III, Tinbergen Institute.
  119. repec:spr:pharme:v:4:y:2014:i:1:p:71-79 is not listed on IDEAS
  120. Faten Ben Slimane, 2012. "Stock exchange consolidation and return volatility," Managerial Finance, Emerald Group Publishing, vol. 38(6), pages 606-627, May.
  121. Huang, Alex YiHou & Peng, Sheng-Pen & Li, Fangjhy & Ke, Ching-Jie, 2011. "Volatility forecasting of exchange rate by quantile regression," International Review of Economics & Finance, Elsevier, vol. 20(4), pages 591-606, October.
  122. Subbotin, Alexandre, 2009. "Volatility Models: from Conditional Heteroscedasticity to Cascades at Multiple Horizons," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 15(3), pages 94-138.
  123. 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.
  124. Lidan Großmaß, 2014. "Liquidity and the Value at Risk," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), Justus-Liebig University Giessen, Department of Statistics and Economics, vol. 234(5), pages 572-602, September.
  125. Mapa, Dennis S., 2004. "A Forecast Comparison of Financial Volatility Models: GARCH (1,1) is not Enough," MPRA Paper 21028, University Library of Munich, Germany.
  126. Mike So & Rui Xu, 2013. "Forecasting Intraday Volatility and Value-at-Risk with High-Frequency Data," Asia-Pacific Financial Markets, Springer, vol. 20(1), pages 83-111, March.
  127. Rizvi, Syed Kumail Abbas & Naqvi, Bushra, 2009. "Inflation Volatility: An Asian Perspective," MPRA Paper 19489, University Library of Munich, Germany.
  128. Thomas Lee & John Zyren, 2007. "Volatility Relationship between Crude Oil and Petroleum Products," Atlantic Economic Journal, International Atlantic Economic Society, vol. 35(1), pages 97-112, March.
  129. Lin, Xiaoqiang & Chen, Qiang & Tang, Zhenpeng, 2014. "Dynamic hedging strategy in incomplete market: Evidence from Shanghai fuel oil futures market," Economic Modelling, Elsevier, vol. 40(C), pages 81-90.
  130. José Dias Curto & João Tomaz & José Castro Pinto, 2009. "A new approach to bad news effects on volatility: the multiple-sign-volume sensitive regime EGARCH model (MSV-EGARCH)," Portuguese Economic Journal, Springer, vol. 8(1), pages 23-36, April.
  131. Hansen, Peter Reinhard & Lunde, Asger, 2006. "Consistent ranking of volatility models," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 97-121.
  132. repec:hal:journl:halshs-00270719 is not listed on IDEAS
  133. Almeida e Santos Nogueira, R.J. & Basturk, N. & Kaymak, U. & Costa Sousa, J.M., 2013. "Estimation of flexible fuzzy GARCH models for conditional density estimation," ERIM Report Series Research in Management ERS-2013-013-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
  134. Ergun Ermisoglu & Yasin Akcelik & Arif Oduncu & Temel Taskin, 2014. "Effects of additional monetary tightening on exchange rates," Eurasian Economic Review, Eurasia Business and Economics Society, vol. 4(1), pages 71-79, June.
  135. McMillan, David G. & Speight, Alan E.H. & Evans, Kevin P., 2008. "How useful is intraday data for evaluating daily Value-at-Risk?: Evidence from three Euro rates," Journal of Multinational Financial Management, Elsevier, vol. 18(5), pages 488-503, December.
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