Forecasting the Value-at-Risk of REITs using realized volatility jump models
Author
Abstract
Suggested Citation
DOI: 10.1016/j.najef.2021.101426
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
References listed on IDEAS
- Giot, Pierre & Laurent, Sebastien, 2004.
"Modelling daily Value-at-Risk using realized volatility and ARCH type models,"
Journal of Empirical Finance, Elsevier, vol. 11(3), pages 379-398, June.
- Giot, P. & Laurent, S.F.J.A., 2001. "Modelling daily value-at-risk using realized volatility and arch type models," Research Memorandum 026, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
- GIOT, Pierre & LAURENT, Sébastien, 2004. "Modelling daily Value-at-Risk using realized volatility and ARCH type models," LIDAM Reprints CORE 1708, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Pierre Giot & Sébastien Laurent, 2002. "Modelling Daily Value-at-Risk Using Realized Volatility and ARCH Type Models," Computing in Economics and Finance 2002 52, Society for Computational Economics.
- Ole E. Barndorff-Nielsen & Neil Shephard, 2006.
"Econometrics of Testing for Jumps in Financial Economics Using Bipower Variation,"
Journal of Financial Econometrics, Oxford University Press, vol. 4(1), pages 1-30.
- Neil Shephard & Ole Barndorff-Nielsen, 2003. "Econometrics of testing for jumps in financial economics using bipower variation," Economics Series Working Papers 2004-FE-01, University of Oxford, Department of Economics.
- Ole E. Barndorff-Nielsen & Neil Shephard, 2004. "Econometrics of testing for jumps in financial economics using bipower variationÂ," OFRC Working Papers Series 2004fe01, Oxford Financial Research Centre.
- Ole E. Barndorff-Nielsen & Neil Shephard, 2003. "Econometrics of testing for jumps in financial economics using bipower variation," Economics Papers 2003-W21, Economics Group, Nuffield College, University of Oxford.
- Paul H. Kupiec, 1995. "Techniques for verifying the accuracy of risk measurement models," Finance and Economics Discussion Series 95-24, Board of Governors of the Federal Reserve System (U.S.).
- Torben G. Andersen & Tim Bollerslev & Francis X. Diebold, 2007.
"Roughing It Up: Including Jump Components in the Measurement, Modeling, and Forecasting of Return Volatility,"
The Review of Economics and Statistics, MIT Press, vol. 89(4), pages 701-720, November.
- 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.
- Torben G. Andersen & Tim Bollerslev & Francis X. Diebold, 2007. "Roughing It Up: Including Jump Components in the Measurement, Modeling and Forecasting of Return Volatility," CREATES Research Papers 2007-18, Department of Economics and Business Economics, Aarhus University.
- Bali, Turan G. & Mo, Hengyong & Tang, Yi, 2008. "The role of autoregressive conditional skewness and kurtosis in the estimation of conditional VaR," Journal of Banking & Finance, Elsevier, vol. 32(2), pages 269-282, February.
- Odusami, Babatunde O., 2021. "Volatility jumps and their determinants in REIT returns," Journal of Economics and Business, Elsevier, vol. 113(C).
- Andersen, Torben G. & Bollerslev, Tim & Huang, Xin, 2011.
"A reduced form framework for modeling volatility of speculative prices based on realized variation measures,"
Journal of Econometrics, Elsevier, vol. 160(1), pages 176-189, January.
- Torben G. Andersen & Tim Bollerslev & Xin Huang, 2007. "A Reduced Form Framework for Modeling Volatility of Speculative Prices based on Realized Variation Measures," CREATES Research Papers 2007-14, Department of Economics and Business Economics, Aarhus University.
- 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.
- Engle, Robert F & Manganelli, Simone, 1999. "CAViaR: Conditional Autoregressive Value at Risk by Regression Quantiles," University of California at San Diego, Economics Working Paper Series qt06m3d6nv, Department of Economics, UC San Diego.
- Robert Engle & Simone Manganelli, 2000. "CAViaR: Conditional Autoregressive Value at Risk by Regression Quantiles," Econometric Society World Congress 2000 Contributed Papers 0841, Econometric Society.
- Amaya, Diego & Christoffersen, Peter & Jacobs, Kris & Vasquez, Aurelio, 2015.
"Does realized skewness predict the cross-section of equity returns?,"
Journal of Financial Economics, Elsevier, vol. 118(1), pages 135-167.
- Diego Amaya & Peter Christoffersen & Kris Jacobs & Aurelio Vasquez, 2013. "Does Realized Skewness Predict the Cross-Section of Equity Returns?," CREATES Research Papers 2013-41, Department of Economics and Business Economics, Aarhus University.
- Fulvio Corsi, 2009. "A Simple Approximate Long-Memory Model of Realized Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 7(2), pages 174-196, Spring.
- Christoffersen, Peter F, 1998. "Evaluating Interval Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 841-862, November.
- Ole E. Barndorff-Nielsen, 2004.
"Power and Bipower Variation with Stochastic Volatility and Jumps,"
Journal of Financial Econometrics, Oxford University Press, vol. 2(1), pages 1-37.
- Ole E. Barndorff-Nielsen & Neil Shephard, 2003. "Power and bipower variation with stochastic volatility and jumps," Economics Papers 2003-W17, Economics Group, Nuffield College, University of Oxford.
- Bjørn Eraker & Michael Johannes & Nicholas Polson, 2003. "The Impact of Jumps in Volatility and Returns," Journal of Finance, American Finance Association, vol. 58(3), pages 1269-1300, June.
- repec:bla:jfinan:v:59:y:2004:i:2:p:755-793 is not listed on IDEAS
- Branger, Nicole & Schlag, Christian & Schneider, Eva, 2008. "Optimal portfolios when volatility can jump," Journal of Banking & Finance, Elsevier, vol. 32(6), pages 1087-1097, June.
- Merton, Robert C., 1976.
"Option pricing when underlying stock returns are discontinuous,"
Journal of Financial Economics, Elsevier, vol. 3(1-2), pages 125-144.
- Merton, Robert C., 1975. "Option pricing when underlying stock returns are discontinuous," Working papers 787-75., Massachusetts Institute of Technology (MIT), Sloan School of Management.
- Suzanne S. Lee, 2012. "Jumps and Information Flow in Financial Markets," The Review of Financial Studies, Society for Financial Studies, vol. 25(2), pages 439-479.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Salisu, Afees A. & Gupta, Rangan & Bouri, Elie, 2023.
"Testing the forecasting power of global economic conditions for the volatility of international REITs using a GARCH-MIDAS approach,"
The Quarterly Review of Economics and Finance, Elsevier, vol. 88(C), pages 303-314.
- Afees A. Salisu & Rangan Gupta & Elie Bouri, 2022. "Testing the Forecasting Power of Global Economic Conditions for the Volatility of International REITs using a GARCH-MIDAS Approach," Working Papers 202211, University of Pretoria, Department of Economics.
- Shixuan Wang & Rangan Gupta & Matteo Bonato & Oguzhan Cepni, 2022. "The Effects of Conventional and Unconventional Monetary Policy Shocks on US REITs Moments: Evidence from VARs with Functional Shocks," Working Papers 202219, University of Pretoria, Department of Economics.
- Song, Yuping & Huang, Jiefei & Zhang, Qichao & Xu, Yang, 2024. "Heterogeneity effect of positive and negative jumps on the realized volatility: Evidence from China," Economic Modelling, Elsevier, vol. 136(C).
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Santos, Douglas G. & Candido, Osvaldo & Tófoli, Paula V., 2022. "Forecasting risk measures using intraday and overnight information," The North American Journal of Economics and Finance, Elsevier, vol. 60(C).
- F. Lilla, 2017. "High Frequency vs. Daily Resolution: the Economic Value of Forecasting Volatility Models - 2nd ed," Working Papers wp1099, Dipartimento Scienze Economiche, Universita' di Bologna.
- F. Lilla, 2016. "High Frequency vs. Daily Resolution: the Economic Value of Forecasting Volatility Models," Working Papers wp1084, Dipartimento Scienze Economiche, Universita' di Bologna.
- Tim Bollerslev & Sophia Zhengzi Li & Viktor Todorov, 2014. "Roughing up Beta: Continuous vs. Discontinuous Betas, and the Cross-Section of Expected Stock Returns," CREATES Research Papers 2014-48, Department of Economics and Business Economics, Aarhus University.
- Bee, Marco & Dupuis, Debbie J. & Trapin, Luca, 2016. "Realizing the extremes: Estimation of tail-risk measures from a high-frequency perspective," Journal of Empirical Finance, Elsevier, vol. 36(C), pages 86-99.
- Maneesoonthorn, Worapree & Martin, Gael M. & Forbes, Catherine S., 2020.
"High-frequency jump tests: Which test should we use?,"
Journal of Econometrics, Elsevier, vol. 219(2), pages 478-487.
- Worapree Maneesoonthorn & Gael M. Martin & Catherine S. Forbes, 2017. "High-Frequency Jump Tests: Which Test Should We Use?," Papers 1708.09520, arXiv.org, revised Jan 2020.
- Worapree Maneesoonthorn & Gael M. Martin & Catherine S. Forbes, 2020. "High-Frequency Jump Tests: Which Test Should We Use?," Monash Econometrics and Business Statistics Working Papers 3/20, Monash University, Department of Econometrics and Business Statistics.
- 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.
- Liu, Yi & Liu, Huifang & Zhang, Lei, 2019. "Modeling and forecasting return jumps using realized variation measures," Economic Modelling, Elsevier, vol. 76(C), pages 63-80.
- Worapree Maneesoonthorn & Gael M. Martin & Catherine S. Forbes, 2017. "Dynamic asset price jumps and the performance of high frequency tests and measures," Monash Econometrics and Business Statistics Working Papers 14/17, Monash University, Department of Econometrics and Business Statistics.
- Barbara Będowska-Sójka, 2018. "Is intraday data useful for forecasting VaR? The evidence from EUR/PLN exchange rate," Risk Management, Palgrave Macmillan, vol. 20(4), pages 326-346, November.
- 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.
- Donggyu Kim & Minseok Shin & Yazhen Wang, 2023.
"Overnight GARCH-Itô Volatility Models,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 41(4), pages 1215-1227, October.
- Donggyu Kim & Minseok Shin & Yazhen Wang, 2021. "Overnight GARCH-It\^o Volatility Models," Papers 2102.13467, arXiv.org, revised Jun 2022.
- Worapree Maneesoonthorn & Gael M Martin & Catherine S Forbes, 2018. "Dynamic price jumps: The performance of high frequency tests and measures, and the robustness of inference," Monash Econometrics and Business Statistics Working Papers 17/18, Monash University, Department of Econometrics and Business Statistics.
- 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.
- Bollerslev, Tim & Li, Sophia Zhengzi & Todorov, Viktor, 2016. "Roughing up beta: Continuous versus discontinuous betas and the cross section of expected stock returns," Journal of Financial Economics, Elsevier, vol. 120(3), pages 464-490.
- Christophe Chorro & Florian Ielpo & Benoît Sévi, 2017. "The contribution of jumps to forecasting the density of returns," Post-Print halshs-01442618, HAL.
- Gkillas, Konstantinos & Gupta, Rangan & Pierdzioch, Christian, 2020.
"Forecasting realized oil-price volatility: The role of financial stress and asymmetric loss,"
Journal of International Money and Finance, Elsevier, vol. 104(C).
- Konstantinos Gkillas & Rangan Gupta & Christian Pierdzioch, 2019. "Forecasting Realized Oil-Price Volatility: The Role of Financial Stress and Asymmetric Loss," Working Papers 201903, University of Pretoria, Department of Economics.
- Maneesoonthorn, Worapree & Martin, Gael M. & Forbes, Catherine S. & Grose, Simone D., 2012.
"Probabilistic forecasts of volatility and its risk premia,"
Journal of Econometrics, Elsevier, vol. 171(2), pages 217-236.
- 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.
- Filip Žikeš & Jozef Baruník, 2016.
"Semi-parametric Conditional Quantile Models for Financial Returns and Realized Volatility,"
Journal of Financial Econometrics, Oxford University Press, vol. 14(1), pages 185-226.
- Filip Zikes & Jozef Barunik, 2013. "Semiparametric Conditional Quantile Models for Financial Returns and Realized Volatility," Papers 1308.4276, arXiv.org.
- Žikeš, Filip & Baruník, Jozef, 2014. "Semiparametric Conditional Quantile Models for Financial Returns and Realized Volatility," FinMaP-Working Papers 20, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
- 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.
- Degiannakis, Stavros & Floros, Christos, 2013. "Modeling CAC40 Volatility Using Ultra-high Frequency Data," MPRA Paper 80445, University Library of Munich, Germany.
More about this item
Keywords
REITs; Real estate; Jumps; Bipower variation; Value-at-Risk;All these keywords.
JEL classification:
- G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ecofin:v:58:y:2021:i:c:s1062940821000589. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/620163 .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.