Prévoir la volatilité d’un actif financier à l’aide d’un modèle à mélange de fréquences
Author
Abstract
Suggested Citation
Download full text from publisher
Other versions of this item:
- Denisa Georgiana Banulescu & Ferrara Laurent & Marsilli Clément, 2019. "Prévoir la volatilité d’un actif financier à l’aide d’un modèle à mélange de fréquences," Working Papers hal-03563168, HAL.
References listed on IDEAS
- Asger Lunde & Peter R. Hansen, 2005.
"A forecast comparison of volatility models: does anything beat a GARCH(1,1)?,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(7), pages 873-889.
- Asger Lunde & Peter Reinhard Hansen, 2001. "A Forecast Comparison of Volatility Models: Does Anything Beat a GARCH(1,1)?," Working Papers 2001-04, Brown University, Department of Economics.
- Wood, Robert A & McInish, Thomas H & Ord, J Keith, 1985. "An Investigation of Transactions Data for NYSE Stocks," Journal of Finance, American Finance Association, vol. 40(3), pages 723-739, July.
- 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.
- Christensen, Kim & Oomen, Roel & Podolskij, Mark, 2010.
"Realised quantile-based estimation of the integrated variance,"
Journal of Econometrics, Elsevier, vol. 159(1), pages 74-98, November.
- Kim Christensen & Roel Oomen & Mark Podolskij, 2009. "Realised Quantile-Based Estimation of the Integrated Variance," CREATES Research Papers 2009-27, Department of Economics and Business Economics, Aarhus University.
- Kim Christensen & Roel Oomen & Mark Podolskij, 2010. "Realised quantile-based estimation of the integrated variance," Post-Print hal-00732538, HAL.
- Ole E. Barndorff-Nielsen & Neil Shephard, 2004. "Econometric Analysis of Realized Covariation: High Frequency Based Covariance, Regression, and Correlation in Financial Economics," Econometrica, Econometric Society, vol. 72(3), pages 885-925, May.
- Laurent Ferrara & Clément Marsilli, 2019.
"Nowcasting global economic growth: A factor‐augmented mixed‐frequency approach,"
The World Economy, Wiley Blackwell, vol. 42(3), pages 846-875, March.
- L. Ferrara & C. Marsilli, 2014. "Nowcasting global economic growth: A factor-augmented mixed-frequency approach," Working papers 515, Banque de France.
- Laurent Ferrara & Clément Marsilli, 2019. "Nowcasting global economic growth: A factor-augmented mixed-frequency approach," Post-Print hal-01636761, HAL.
- Marcellino, Massimiliano & Stock, James H. & Watson, Mark W., 2006.
"A comparison of direct and iterated multistep AR methods for forecasting macroeconomic time series,"
Journal of Econometrics, Elsevier, vol. 135(1-2), pages 499-526.
- Stock, James & Watson, Mark & Marcellino, Massimiliano, 2005. "A Comparison of Direct and Iterated Multistep AR Methods for Forecasting Macroeconomic Time Series," CEPR Discussion Papers 4976, C.E.P.R. Discussion Papers.
- Massimiliano Marcellino & James Stock & Mark Watson, 2005. "A Comparison of Direct and Iterated Multistep AR Methods for Forecasting Macroeconomic Time Series," Working Papers 285, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
- Torben G. Andersen & Tim Bollerslev & Nour Meddahi, 2005. "Correcting the Errors: Volatility Forecast Evaluation Using High-Frequency Data and Realized Volatilities," Econometrica, Econometric Society, vol. 73(1), pages 279-296, January.
- Hansen, Peter Reinhard & Lunde, Asger, 2006. "Consistent ranking of volatility models," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 97-121.
- Andreou, Elena & Ghysels, Eric & Kourtellos, Andros, 2010.
"Regression models with mixed sampling frequencies,"
Journal of Econometrics, Elsevier, vol. 158(2), pages 246-261, October.
- Elena Andreou, Eric Ghysels & Eric Ghysels & Andros Kourtellos, 2007. "Regression Models with Mixed Sampling Frequencies," University of Cyprus Working Papers in Economics 8-2007, University of Cyprus Department of Economics.
- Peter R. Hansen & Asger Lunde & James M. Nason, 2011.
"The Model Confidence Set,"
Econometrica, Econometric Society, vol. 79(2), pages 453-497, March.
- Peter R. Hansen & Asger Lunde & James M. Nason, 2010. "The Model Confidence Set," CREATES Research Papers 2010-76, Department of Economics and Business Economics, Aarhus University.
- Jérôme Lahaye & Sébastien Laurent & Christopher J. Neely, 2011.
"Jumps, cojumps and macro announcements,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(6), pages 893-921, September.
- Jerome Lahaye & Sebastien Laurent & Christopher J. Neely, 2007. "Jumps, cojumps and macro announcements," Working Papers 2007-032, Federal Reserve Bank of St. Louis.
- LAHAYE, Jérôme & LAURENT, Sébastien & NEELY, Christopher J., 2011. "Jumps, cojumps and macro announcements," LIDAM Reprints CORE 2413, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Karim Barhoumi & Olivier Darné & Laurent Ferrara, 2014.
"Dynamic factor models: A review of the literature,"
OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2013(2), pages 73-107.
- Karim Barhoumi & Olivier Darné & Laurent Ferrara, 2013. "Dynamic factor models: A review of the literature," Post-Print hal-01385974, HAL.
- Barhoumi, K. & Darné, O. & Ferrara, L., 2013. "Dynamic Factor Models: A review of the Literature ," Working papers 430, Banque de France.
- Ole E. Barndorff-Nielsen & Peter Reinhard Hansen & Asger Lunde & Neil Shephard, 2008.
"Designing Realized Kernels to Measure the ex post Variation of Equity Prices in the Presence of Noise,"
Econometrica, Econometric Society, vol. 76(6), pages 1481-1536, November.
- Ole E Barndorff-Nielsen & Peter Hansen & Asger Lunde & Neil Shephard, 2006. "Designing realised kernels to measure the ex-post variation of equity prices in the presence of noise," OFRC Working Papers Series 2006fe05, Oxford Financial Research Centre.
- Ole E. Barndorff-Nielsen & Peter Reinhard Hansen & Asger Lunde & Neil Shephard, 2006. "Designing realised kernels to measure the ex-post variation of equity prices in the presence of noise," Economics Papers 2006-W03, Economics Group, Nuffield College, University of Oxford.
- Andersen, Torben G. & Bollerslev, Tim, 1997. "Intraday periodicity and volatility persistence in financial markets," Journal of Empirical Finance, Elsevier, vol. 4(2-3), pages 115-158, June.
- Pierre Guérin & Massimiliano Marcellino, 2013.
"Markov-Switching MIDAS Models,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(1), pages 45-56, January.
- Marcellino, Massimiliano, 2011. "Markov-switching MIDAS models," CEPR Discussion Papers 8234, C.E.P.R. Discussion Papers.
- 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.
- Kvedaras, Virmantas & Zemlys, Vaidotas, 2012. "Testing the functional constraints on parameters in regressions with variables of different frequency," Economics Letters, Elsevier, vol. 116(2), pages 250-254.
- Andersen, Torben G & Bollerslev, Tim, 1998. "Answering the Skeptics: Yes, Standard Volatility Models Do Provide Accurate Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 885-905, November.
- Ole E. Barndorff‐Nielsen & Neil Shephard, 2002.
"Econometric analysis of realized volatility and its use in estimating stochastic volatility models,"
Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(2), pages 253-280, May.
- Ole E. Barndorff-Nielsen & Neil Shephard, 2000. "Econometric analysis of realised volatility and its use in estimating stochastic volatility models," Economics Papers 2001-W4, Economics Group, Nuffield College, University of Oxford, revised 05 Jul 2001.
- Neil Shephard & Ole E. Barndorff-Nielsen & University of Aarhus, 2001. "Econometric Analysis of Realised Volatility and Its Use in Estimating Stochastic Volatility Models," Economics Series Working Papers 71, University of Oxford, Department of Economics.
- 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.
- Sébastien Laurent & Jeroen V.K. Rombouts & Francesco Violante, 2009. "On Loss Functions and Ranking Forecasting Performances of Multivariate Volatility Models," Cahiers de recherche 0948, CIRPEE.
- Sébastien Laurent & Jeroen Rombouts & Francesco Violente, 2009. "On Loss Functions and Ranking Forecasting Performances of Multivariate Volatility Models," CIRANO Working Papers 2009s-45, CIRANO.
- Bates, David S, 1996. "Jumps and Stochastic Volatility: Exchange Rate Processes Implicit in Deutsche Mark Options," The Review of Financial Studies, Society for Financial Studies, vol. 9(1), pages 69-107.
- Tsurumi, Hiroki, 1971. "A Note on Gamma Distributed Lags," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 12(2), pages 317-324, June.
- 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.
- Bollerslev, Tim, 1986.
"Generalized autoregressive conditional heteroskedasticity,"
Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
- Tim Bollerslev, 1986. "Generalized autoregressive conditional heteroskedasticity," EERI Research Paper Series EERI RP 1986/01, Economics and Econometrics Research Institute (EERI), Brussels.
- Denisa Banulescu-Radu & Christophe Hurlin & Bertrand Candelon & Sébastien Laurent, 2016.
"Do We Need High Frequency Data to Forecast Variances?,"
Annals of Economics and Statistics, GENES, issue 123-124, pages 135-174.
- Denisa Banulescu-Radu & Christophe Hurlin & Bertrand Candelon & Sébastien Laurent, 2016. "Do We Need High Frequency Data to Forecast Variances?," Post-Print hal-01448237, HAL.
- Eric Ghysels & Arthur Sinko & Rossen Valkanov, 2007. "MIDAS Regressions: Further Results and New Directions," Econometric Reviews, Taylor & Francis Journals, vol. 26(1), pages 53-90.
- Cecilia Frale & Libero Monteforte, "undated".
"FaMIDAS: A Mixed Frequency Factor Model with MIDAS structure,"
Working Papers
3, Department of the Treasury, Ministry of the Economy and of Finance.
- Cecilia Frale & Libero Monteforte, 2011. "FaMIDAS: A Mixed Frequency Factor Model with MIDAS structure," Temi di discussione (Economic working papers) 788, Bank of Italy, Economic Research and International Relations Area.
- Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2003.
"Modeling and Forecasting Realized Volatility,"
Econometrica, Econometric Society, vol. 71(2), pages 579-625, March.
- Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2001. "Modeling and Forecasting Realized Volatility," Center for Financial Institutions Working Papers 01-01, Wharton School Center for Financial Institutions, University of Pennsylvania.
- Anderson, Torben G. & Bollerslev, Tim & Diebold, Francis X. & Labys, Paul, 2002. "Modeling and Forecasting Realized Volatility," Working Papers 02-12, Duke University, Department of Economics.
- Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2001. "Modeling and Forecasting Realized Volatility," NBER Working Papers 8160, National Bureau of Economic Research, Inc.
- Hamlen, Susan S. & Hamlen, William Jr., 1978. "Harmonic alternatives to the Almon polynomial technique," Journal of Econometrics, Elsevier, vol. 7(1), pages 57-66, February.
- Denisa Banulescu-Radu & Christophe Hurlin & Bertrand Candelon & Sébastien Laurent, 2016.
"Do We Need High Frequency Data to Forecast Variances?,"
Annals of Economics and Statistics, GENES, issue 123-124, pages 135-174.
- Denisa Banulescu-Radu & Christophe Hurlin & Bertrand Candelon & Sébastien Laurent, 2016. "Do We Need High Frequency Data to Forecast Variances?," Post-Print hal-01448237, HAL.
- Denisa Banulescu-Radu & Christophe Hurlin & Sebastien Laurent & Bertrand Candelon, 2016. "Do We Need High Frequency Data to Forecast Variances?," Post-Print hal-03528839, HAL.
- Andersen, Torben G. & Bollerslev, Tim & Diebold, Francis X. & Ebens, Heiko, 2001. "The distribution of realized stock return volatility," Journal of Financial Economics, Elsevier, vol. 61(1), pages 43-76, July.
- repec:hal:journl:peer-00732538 is not listed on IDEAS
- Shiller, Robert J, 1973. "A Distributed Lag Estimator Derived from Smoothness Priors," Econometrica, Econometric Society, vol. 41(4), pages 775-788, July.
- Ghysels, Eric & Santa-Clara, Pedro & Valkanov, Rossen, 2004.
"The MIDAS Touch: Mixed Data Sampling Regression Models,"
University of California at Los Angeles, Anderson Graduate School of Management
qt9mf223rs, Anderson Graduate School of Management, UCLA.
- Eric Ghysels & Pedro Santa-Clara & Rossen Valkanov, 2004. "The MIDAS Touch: Mixed Data Sampling Regression Models," CIRANO Working Papers 2004s-20, CIRANO.
- Patton, Andrew J., 2011.
"Volatility forecast comparison using imperfect volatility proxies,"
Journal of Econometrics, Elsevier, vol. 160(1), pages 246-256, January.
- Andrew Patton, 2006. "Volatility Forecast Comparison using Imperfect Volatility Proxies," Research Paper Series 175, Quantitative Finance Research Centre, University of Technology, Sydney.
- Andreou, Elena & Ghysels, Eric, 2002.
"Rolling-Sample Volatility Estimators: Some New Theoretical, Simulation, and Empirical Results,"
Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 363-376, July.
- Elena Andreou & Eric Ghysels, 2000. "Rolling-Sample Volatility Estimators: Some New Theoretical, Simulation and Empirical Results," CIRANO Working Papers 2000s-19, CIRANO.
- O. E. Barndorff-Nielsen & P. Reinhard Hansen & A. Lunde & N. Shephard, 2009. "Realized kernels in practice: trades and quotes," Econometrics Journal, Royal Economic Society, vol. 12(3), pages 1-32, November.
- Suzanne S. Lee & Per A. Mykland, 2008. "Jumps in Financial Markets: A New Nonparametric Test and Jump Dynamics," The Review of Financial Studies, Society for Financial Studies, vol. 21(6), pages 2535-2563, November.
- Claudia Foroni & Massimiliano Marcellino & Christian Schumacher, 2015. "Unrestricted mixed data sampling (MIDAS): MIDAS regressions with unrestricted lag polynomials," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 178(1), pages 57-82, January.
- Yu-chin Chen & Wen-Jen Tsay, "undated".
"Forecasting Commodity Prices with Mixed-Frequency Data: An OLS-Based Generalized ADL Approach,"
Working Papers
UWEC-2011-06, University of Washington, Department of Economics.
- Yu-chin Chen & Wen-Jen Tsay, 2011. "Forecasting Commodity Prices with Mixed-Frequency Data: An OLS-Based Generalized ADL Approach," IEAS Working Paper : academic research 11-A001, Institute of Economics, Academia Sinica, Taipei, Taiwan, revised May 2011.
- Jim Griffin & Roel Oomen, 2008. "Sampling Returns for Realized Variance Calculations: Tick Time or Transaction Time?," Econometric Reviews, Taylor & Francis Journals, vol. 27(1-3), pages 230-253.
- Corradi, C & Gambetta, G, 1976. "The Estimation of Distributed Lags by Spline Functions," Empirical Economics, Springer, vol. 1(1), pages 41-51.
- Boudt, Kris & Croux, Christophe & Laurent, Sébastien, 2011.
"Robust estimation of intraweek periodicity in volatility and jump detection,"
Journal of Empirical Finance, Elsevier, vol. 18(2), pages 353-367, March.
- BOUDT, Kris & CROUX, Christophe & LAURENT, Sabéastien, 2011. "Robust estimation of intraweek periodicity in volatility and jump detection," LIDAM Reprints CORE 2411, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
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.- Denisa Banulescu-Radu & Christophe Hurlin & Bertrand Candelon & Sébastien Laurent, 2016.
"Do We Need High Frequency Data to Forecast Variances?,"
Annals of Economics and Statistics, GENES, issue 123-124, pages 135-174.
- Denisa Banulescu-Radu & Christophe Hurlin & Bertrand Candelon & Sébastien Laurent, 2016. "Do We Need High Frequency Data to Forecast Variances?," Post-Print hal-01448237, HAL.
- Georgiana-Denisa Banulescu & Bertrand Candelon & Christophe Hurlin & Sébastien Laurent, 2014. "Do We Need Ultra-High Frequency Data to Forecast Variances?," Working Papers halshs-01078158, HAL.
- Elena Ivona Dumitrescu & Georgiana-Denisa Banulescu, 2019.
"Do High-frequency-based Measures Improve Conditional Covariance Forecasts?,"
Post-Print
hal-03331122, HAL.
- Denisa BANULESCU-RADU & Elena Ivona DUMITRESCU, 2019. "Do High-frequency-based Measures Improve Conditional Covariance Forecasts?," LEO Working Papers / DR LEO 2709, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
- Bu, Ruijun & Hizmeri, Rodrigo & Izzeldin, Marwan & Murphy, Anthony & Tsionas, Mike, 2023.
"The contribution of jump signs and activity to forecasting stock price volatility,"
Journal of Empirical Finance, Elsevier, vol. 70(C), pages 144-164.
- , 2019. "The Contribution of Jump Signs and Activity to Forecasting Stock Price Volatility," Working Papers 1902, Federal Reserve Bank of Dallas, revised 17 Dec 2022.
- Ruijun Bu & Rodrigo Hizmeri & Marwan Izzeldin & Anthony Murphy & Mike G. Tsionas, 2021. "The Contribution of Jump Signs and Activity to Forecasting Stock Price Volatility," Working Papers 202109, University of Liverpool, Department of Economics.
- 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.
- Kevin Sheppard & Lily Liu & Andrew J. Patton, 2013. "Does Anything Beat 5-Minute RV? A Comparison of Realized Measures Across Multiple Asset Classes," Economics Series Working Papers 645, University of Oxford, Department of Economics.
- Wang, Chengyang & Nishiyama, Yoshihiko, 2015. "Volatility forecast of stock indices by model averaging using high-frequency data," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 324-337.
- Wang Pu & Yixiang Chen & Feng Ma, 2016. "Forecasting the realized volatility in the Chinese stock market: further evidence," Applied Economics, Taylor & Francis Journals, vol. 48(33), pages 3116-3130, July.
- Li, Jia & Patton, Andrew J., 2018.
"Asymptotic inference about predictive accuracy using high frequency data,"
Journal of Econometrics, Elsevier, vol. 203(2), pages 223-240.
- Jia Li & Andrew J. Patton, 2013. "Asymptotic Inference about Predictive Accuracy Using High Frequency Data," Working Papers 13-27, Duke University, Department of Economics.
- Yusui Tang & Feng Ma & Yaojie Zhang & Yu Wei, 2022. "Forecasting the oil price realized volatility: A multivariate heterogeneous autoregressive model," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 4770-4783, October.
- Patton, Andrew J., 2011. "Data-based ranking of realised volatility estimators," Journal of Econometrics, Elsevier, vol. 161(2), pages 284-303, April.
- Chen, Wang & Lu, Xinjie & Wang, Jiqian, 2022. "Modeling and managing stock market volatility using MRS-MIDAS model," International Review of Economics & Finance, Elsevier, vol. 82(C), pages 625-635.
- Ma, Feng & Li, Yu & Liu, Li & Zhang, Yaojie, 2018. "Are low-frequency data really uninformative? A forecasting combination perspective," The North American Journal of Economics and Finance, Elsevier, vol. 44(C), pages 92-108.
- Christophe Chorro & Florian Ielpo & Benoît Sévi, 2017. "The contribution of jumps to forecasting the density of returns," Post-Print halshs-01442618, HAL.
- Liu, Min & Lee, Chien-Chiang, 2021. "Capturing the dynamics of the China crude oil futures: Markov switching, co-movement, and volatility forecasting," Energy Economics, Elsevier, vol. 103(C).
- Ole E. Barndorff-Nielsen & Neil Shephard, 2005.
"Variation, jumps, market frictions and high frequency data in financial econometrics,"
OFRC Working Papers Series
2005fe08, Oxford Financial Research Centre.
- 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.
- Neil Shephard & Ole E. Barndorff-Nielsen & Department of Mathematical Sciences & University of Aarhus & Denmark, 2005. "Variation, jumps, market frictions and high frequency data in financial econometrics," Economics Series Working Papers 240, University of Oxford, Department of Economics.
- Chun Liu & John M. Maheu, 2009.
"Forecasting realized volatility: a Bayesian model-averaging approach,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(5), pages 709-733.
- Chun Liu & John M Maheu, 2008. "Forecasting Realized Volatility: A Bayesian Model Averaging Approach," Working Papers tecipa-313, University of Toronto, Department of Economics.
- Chorro, Christophe & Ielpo, Florian & Sévi, Benoît, 2020. "The contribution of intraday jumps to forecasting the density of returns," Journal of Economic Dynamics and Control, Elsevier, vol. 113(C).
- Patton, Andrew J. & Sheppard, Kevin, 2009. "Optimal combinations of realised volatility estimators," International Journal of Forecasting, Elsevier, vol. 25(2), pages 218-238.
- 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.
- Liu, Jing & Ma, Feng & Yang, Ke & Zhang, Yaojie, 2018. "Forecasting the oil futures price volatility: Large jumps and small jumps," Energy Economics, Elsevier, vol. 72(C), pages 321-330.
More about this item
Keywords
; Volatilité; Prévision; Mélange de fréquences;All these keywords.
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:leo:wpaper:2710. 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: Sébastien Galanti (email available below). General contact details of provider: https://edirc.repec.org/data/leorlfr.html .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.