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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. Shirota, Shinichiro & Hizu, Takayuki & Omori, Yasuhiro, 2014. "Realized stochastic volatility with leverage and long memory," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 618-641.
  2. Carles Bretó & Helena Veiga, 2011. "Forecasting volatility: does continuous time do better than discrete time?," Statistics and Econometrics Working Papers ws112518, Universidad Carlos III, Departamento de Estadística y Econometría.
  3. Lanne, Markku & Ahoniemi, Katja, 2008. "Implied Volatility with Time-Varying Regime Probabilities," MPRA Paper 23721, University Library of Munich, Germany.
  4. 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.
  5. Chevallier, Julien, 2011. "Detecting instability in the volatility of carbon prices," Energy Economics, Elsevier, vol. 33(1), pages 99-110, January.
  6. Ansgar Belke & Christian Gokus, 2011. "Volatility Patterns of CDS, Bond and Stock Markets Before and During the Financial Crisis – Evidence from Major Financial Institutions," Ruhr Economic Papers 0243, Rheinisch-Westfälisches Institut für Wirtschaftsforschung, Ruhr-Universität Bochum, Universität Dortmund, Universität Duisburg-Essen.
  7. Oleg Korenok & Stanislav Radchenko, 2005. "The smooth transition autoregressive target zone model with the Gaussian stochastic volatility and TGARCH error terms with applications," Working Papers 0505, VCU School of Business, Department of Economics.
  8. Köksal, Bülent, 2009. "A Comparison of Conditional Volatility Estimators for the ISE National 100 Index Returns," MPRA Paper 30510, University Library of Munich, Germany.
  9. 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.
  10. Mapa, Dennis S., 2003. "A Range-Based GARCH Model for Forecasting Volatility," MPRA Paper 21323, University Library of Munich, Germany.
  11. 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.
  12. 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.
  13. Lars Stentoft, 2008. "Option Pricing using Realized Volatility," CREATES Research Papers 2008-13, School of Economics and Management, University of Aarhus.
  14. Patton, Andrew J., 2011. "Volatility forecast comparison using imperfect volatility proxies," Journal of Econometrics, Elsevier, vol. 160(1), pages 246-256, January.
  15. 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.
  16. 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.
  17. David E. Allen & Michael McAleer & Marcel Scharth, 2013. "Realized volatility risk," Documentos de Trabajo del ICAE 2013-26, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
  18. 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.
  19. King, Daniel & Botha, Ferdi, 2015. "Modelling stock return volatility dynamics in selected African markets," Economic Modelling, Elsevier, vol. 45(C), pages 50-73.
  20. Shaun K. Roache & Marco Rossi, 2009. "The Effects of Economic Newson Commodity Prices; Is Gold Just Another Commodity?," IMF Working Papers 09/140, International Monetary Fund.
  21. Faten Ben Slimane, 2012. "Stock exchange consolidation and return volatility," Managerial Finance, Emerald Group Publishing, vol. 38(6), pages 606-627, May.
  22. Peter Hansen & Asger Lunde, 2003. "Testing the Significance of Calendar Effects," Working Papers 2003-03, Brown University, Department of Economics.
  23. 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.
  24. 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.
  25. Omid Sabbaghi, 2011. "The behavior of green exchange-traded funds," Managerial Finance, Emerald Group Publishing, vol. 37(5), pages 426-441, May.
  26. 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.
  27. 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.
  28. 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.
  29. 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.
  30. Brunetti, Celso & Scotti, Chiara & Mariano, Roberto S. & Tan, Augustine H.H., 2008. "Markov switching GARCH models of currency turmoil in Southeast Asia," Emerging Markets Review, Elsevier, vol. 9(2), pages 104-128, June.
  31. McCracken, Michael W., 2004. "Parameter estimation and tests of equal forecast accuracy between non-nested models," International Journal of Forecasting, Elsevier, vol. 20(3), pages 503-514.
  32. Mauro Bernardi & Leopoldo Catania & Lea Petrella, 2014. "Are news important to predict large losses?," Papers 1410.6898, arXiv.org, revised Oct 2014.
  33. 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.
  34. Ahoniemi, Katja & Lanne, Markku, 2013. "Overnight stock returns and realized volatility," International Journal of Forecasting, Elsevier, vol. 29(4), pages 592-604.
  35. Cordis, Adriana S. & Kirby, Chris, 2014. "Discrete stochastic autoregressive volatility," Journal of Banking & Finance, Elsevier, vol. 43(C), pages 160-178.
  36. Simone Bianco & Roberto Ren\'o, 2006. "Unexpected volatility and intraday serial correlation," Papers physics/0610023, arXiv.org.
  37. Francine Gresnigt & Erik Kole & Philip Hans Franses, 2014. "Interpreting Financial Market Crashes as Earthquakes: A New early Warning System for Medium Term Crashes," Tinbergen Institute Discussion Papers 14-067/III, Tinbergen Institute.
  38. 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.
  39. Auer, Benjamin R., 2014. "Daily seasonality in crude oil returns and volatilities," Energy Economics, Elsevier, vol. 43(C), pages 82-88.
  40. 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.
  41. BAUWENS, Luc & SUCARRAT, Genaro, 2006. "General to specific modelling of exchange rate volatility: a forecast evaluation," CORE Discussion Papers 2006021, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  42. 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.
  43. 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.
  44. Patton, Andrew J., 2011. "Data-based ranking of realised volatility estimators," Journal of Econometrics, Elsevier, vol. 161(2), pages 284-303, April.
  45. Alexander Subbotin & Thierry Chauveau & Kateryna Shapovalova, 2009. "Volatility Models : from GARCH to Multi-Horizon Cascades," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00390636, HAL.
  46. 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.
  47. Bouezmarni, Taoufik & Rombouts, Jeroen V.K., 2010. "Nonparametric density estimation for positive time series," Computational Statistics & Data Analysis, Elsevier, vol. 54(2), pages 245-261, February.
  48. Xekalaki, Evdokia & Degiannakis, Stavros, 2005. "Evaluating volatility forecasts in option pricing in the context of a simulated options market," Computational Statistics & Data Analysis, Elsevier, vol. 49(2), pages 611-629, April.
  49. Caporin, Massimiliano & McAleer, Michael, 2014. "Robust ranking of multivariate GARCH models by problem dimension," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 172-185.
  50. Lanne, Markku & Luoto, Jani, 2007. "Robustness of the Risk-Return Relationship in the U.S. Stock Market," MPRA Paper 3879, University Library of Munich, Germany.
  51. Lorenzo Cappiello & Robert F. Engle & Kevin Sheppard, 2006. "Asymmetric Dynamics in the Correlations of Global Equity and Bond Returns," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 4(4), pages 537-572.
  52. 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.
  53. 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.
  54. 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.
  55. 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.
  56. 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.
  57. 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.
  58. 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.
  59. 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.
  60. Prat, Georges, 2013. "Equity risk premium and time horizon: What do the U.S. secular data say?," Economic Modelling, Elsevier, vol. 34(C), pages 76-88.
  61. 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.
  62. 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.
  63. Audrino, Francesco & Camponovo, Lorenzo & Roth, Constantin, 2015. "Testing the lag structure of assets’ realized volatility dynamics," Economics Working Paper Series 1501, University of St. Gallen, School of Economics and Political Science.
  64. 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.
  65. Gozgor, Giray & Nokay, Pinar, 2011. "Comparing forecast performances among volatility estimation methods in the pricing of european type currency options of USD-TL and Euro-TL," MPRA Paper 34369, University Library of Munich, Germany.
  66. David E. Allen & Michael McAleer & Marcel Scharth, 2014. "Asymmetric Realized Volatility Risk," Working Papers in Economics 14/20, University of Canterbury, Department of Economics and Finance.
  67. Jeroen Rombouts & Lars Peter Stentoft & Francesco Violente, 2012. "The Value of Multivariate Model Sophistication: An Application to pricing Dow Jones Industrial Average Options," CIRANO Working Papers 2012s-05, CIRANO.
  68. 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.
  69. Clements, A. & Silvennoinen, A., 2013. "Volatility timing: How best to forecast portfolio exposures," Journal of Empirical Finance, Elsevier, vol. 24(C), pages 108-115.
  70. Fantazzini, Dean, 2008. "Credit Risk Management," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 12(4), pages 84-137.
  71. repec:hal:journl:halshs-00259225 is not listed on IDEAS
  72. 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.
  73. Francq, Christian & Thieu, Le Quyen, 2015. "Qml inference for volatility models with covariates," MPRA Paper 63198, University Library of Munich, Germany.
  74. Adam Clements & Ayesha Scott & Annastiina Silvennoinen, 2013. "On the Benefits of Equicorrelation for Portfolio Allocation," NCER Working Paper Series 99, National Centre for Econometric Research.
  75. Lin Zhao & Sweder van Wijnbergen, 2013. "A Real Option Perspective on Valuing Gas Fields," Tinbergen Institute Discussion Papers 13-126/VI/DSF60, Tinbergen Institute.
  76. 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.
  77. Taylor, Nicholas, 2008. "Can idiosyncratic volatility help forecast stock market volatility?," International Journal of Forecasting, Elsevier, vol. 24(3), pages 462-479.
  78. 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.
  79. 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.
  80. 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.
  81. Stanislav Radchenko, 2004. "Oil price volatility and the asymmetric response of gasoline prices to oil price increases and decreases," Industrial Organization 0408001, EconWPA.
  82. Todd, Prono, 2010. "Simple GMM Estimation of the Semi-Strong GARCH(1,1) Model," MPRA Paper 20034, University Library of Munich, Germany.
  83. Marzo, Massimiliano & Zagaglia, Paolo, 2007. "Volatility forecasting for crude oil futures," Research Papers in Economics 2007:9, Stockholm University, Department of Economics.
  84. 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.
  85. 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.
  86. 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.
  87. Borgsen, Sina & Glaser, Markus, 2005. "Diversifikationseffekte durch Small und Mid Caps?," Sonderforschungsbereich 504 Publications 05-10, Sonderforschungsbereich 504, Universität Mannheim;Sonderforschungsbereich 504, University of Mannheim.
  88. Ting Ting Chen & Tetsuya Takaishi, 2013. "Empirical Study of the GARCH model with Rational Errors," Papers 1312.7057, arXiv.org.
  89. 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.
  90. Sucarrat, Genaro, 2009. "Forecast Evaluation of Explanatory Models of Financial Variability," Economics - The Open-Access, Open-Assessment E-Journal, Kiel Institute for the World Economy, vol. 3, pages 1-33.
  91. Mancino, M.E. & Sanfelici, S., 2008. "Robustness of Fourier estimator of integrated volatility in the presence of microstructure noise," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 2966-2989, February.
  92. 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.
  93. Bhattacharyya, Surajit & Saxena, Arunima, 2008. "Stock Futures Introduction & Its Impact on Indian Spot Market," MPRA Paper 15250, University Library of Munich, Germany.
  94. Gael M. Martin & Andrew Reidy & Jill Wright, 2009. "Does the option market produce superior forecasts of noise-corrected volatility measures?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(1), pages 77-104.
  95. David E. Allen & Michael McAleer & Marcel Scharth, 2014. "Asymmetric Realized Volatility Risk," Tinbergen Institute Discussion Papers 14-075/III, Tinbergen Institute.
  96. Todd E. Clark & Francesco Ravazzolo, 2012. "The macroeconomic forecasting performance of autoregressive models with alternative specifications of time-varying volatility," Working Paper 1218, Federal Reserve Bank of Cleveland.
  97. Shynkevich, Andrei, 2012. "Short-term predictability of equity returns along two style dimensions," Journal of Empirical Finance, Elsevier, vol. 19(5), pages 675-685.
  98. Neil Shephard & Ole E. Barndorff-Nielsen, 2005. "Variation, jumps, market frictions and high frequency data in financial econometrics," Economics Series Working Papers 240, University of Oxford, Department of Economics.
  99. 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".
  100. Christian Conrad, 2007. "Non-negativity Conditions for the Hyperbolic GARCH Model," KOF Working papers 07-162, KOF Swiss Economic Institute, ETH Zurich.
  101. 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).
  102. Philippe Charlot & Vêlayoudom Marimoutou, 2014. "On the relationship between the prices of oil and the precious metals: Revisiting with a multivariate regime-switching decision tree," Working Papers hal-00980125, HAL.
  103. Masato Ubukata & Toshiaki Watanabe, 2013. "Pricing Nikkei 225 Options Using Realized Volatility," Global COE Hi-Stat Discussion Paper Series gd12-273, Institute of Economic Research, Hitotsubashi University.
  104. 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.
  105. Tzouras, Spilios & Anagnostopoulos, Christoforos & McCoy, Emma, 2015. "Financial time series modeling using the Hurst exponent," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 425(C), pages 50-68.
  106. 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.
  107. Charles, Amélie & Darné, Olivier, 2014. "Volatility persistence in crude oil markets," Energy Policy, Elsevier, vol. 65(C), pages 729-742.
  108. Tetsuya Takaishi, 2013. "Empirical Analysis of Stochastic Volatility Model by Hybrid Monte Carlo Algorithm," Papers 1305.3184, arXiv.org.
  109. Shcherba, Alexandr, 2011. "Comparison of VaR estimation methods for different forecasting samples for Russian stocks," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 24(4), pages 58-70.
  110. 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.
  111. Smith, Daniel R., 2007. "Conditional coskewness and asset pricing," Journal of Empirical Finance, Elsevier, vol. 14(1), pages 91-119, January.
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  113. 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).
  114. 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.
  115. Efimova, Olga & Serletis, Apostolos, 2014. "Energy markets volatility modelling using GARCH," Energy Economics, Elsevier, vol. 43(C), pages 264-273.
  116. Guidi, Francesco, 2008. "Volatility and Long Term Relations in Equity Markets: Empirical Evidence from Germany, Switzerland, and the UK," MPRA Paper 11535, University Library of Munich, Germany.
  117. 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.
  118. Jui-Cheng Hung & Ren-Xi Ni & Matthew C. Chang, 2009. "The Information Contents of VIX Index and Range-based Volatility on Volatility Forecasting Performance of S&P 500," Economics Bulletin, AccessEcon, vol. 29(4), pages 2592-2604.
  119. 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.
  120. 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.
  121. Sébastien Laurent & Jeroen Rombouts & Francesco Violente, 2009. "On Loss Functions and Ranking Forecasting Performances of Multivariate Volatility Models," CIRANO Working Papers 2009s-45, CIRANO.
  122. 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.
  123. Andrew Gordon Wilson & David A. Knowles & Zoubin Ghahramani, 2011. "Gaussian Process Regression Networks," Papers 1110.4411, arXiv.org.
  124. María José Rodríguez & Esther Ruiz, 2009. "GARCH models with leverage effect : differences and similarities," Statistics and Econometrics Working Papers ws090302, Universidad Carlos III, Departamento de Estadística y Econometría.
  125. 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.
  126. 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.
  127. 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.
  128. Friberg, Richard & Huse, Cristian, 2012. "How to use demand systems to evaluate risky projects, with an application to automobile production," CEPR Discussion Papers 9266, C.E.P.R. Discussion Papers.
  129. 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.
  130. Andrew Gordon Wilson & Zoubin Ghahramani, 2010. "Copula Processes," Papers 1006.1350, arXiv.org, revised Jun 2010.
  131. Olivier Damette & Stéphane Goutte, 2014. "Tobin tax and trading volume tightening: a reassessment," Working Papers halshs-00926805, HAL.
  132. Rossignolo, Adrián F. & Fethi, Meryem Duygun & Shaban, Mohamed, 2013. "Market crises and Basel capital requirements: Could Basel III have been different? Evidence from Portugal, Ireland, Greece and Spain (PIGS)," Journal of Banking & Finance, Elsevier, vol. 37(5), pages 1323-1339.
  133. 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.
  134. 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.
  135. Charles, Amélie, 2010. "The day-of-the-week effects on the volatility: The role of the asymmetry," European Journal of Operational Research, Elsevier, vol. 202(1), pages 143-152, April.
  136. 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.
  137. 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.
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  151. 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.
  152. Lin Zhao & Sweder van Wijnbergen, 2013. "A Real Option Perspective on Valuing Gas Fields," Tinbergen Institute Discussion Papers 13-126/VI/DSF60, Tinbergen Institute.
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  154. Ghorbel, Ahmed & Trabelsi, Abdelwahed, 2007. "Predictive Performance of Conditional Extreme Value Theory and Conventional Methods in Value at Risk Estimation," MPRA Paper 3963, University Library of Munich, Germany.
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  160. Lestano & Kuper, Gerard H., 2014. "Correlation Dynamics in East Asian Financial Markets," Research Report 14029-EEF, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
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