Generalized Method of Moment estimation of multivariate multifractal models
Author
Abstract
Suggested Citation
DOI: 10.1016/j.econmod.2016.11.010
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
- Lux, Thomas, 2008.
"The Markov-Switching Multifractal Model of Asset Returns: GMM Estimation and Linear Forecasting of Volatility,"
Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 194-210, April.
- Lux, Thomas, 2004. "The Markov-switching multi-fractal model of asset returns: GMM estimation and linear forecasting of volatility," Economics Working Papers 2004-11, Christian-Albrechts-University of Kiel, Department of Economics.
- Lux, Thomas, 2006. "The Markov-Switching Multifractal Model of asset returns: GMM estimation and linear forecasting of volatility," Economics Working Papers 2006-17, Christian-Albrechts-University of Kiel, Department of Economics.
- Calvet, Laurent E. & Fisher, Adlai J. & Thompson, Samuel B., 2006.
"Volatility comovement: a multifrequency approach,"
Journal of Econometrics, Elsevier, vol. 131(1-2), pages 179-215.
- Laurent E. Calvet & Adlai J. Fisher & Samuel B. Thompson, 2004. "Volatility Comovement: A Multifrequency Approach," NBER Technical Working Papers 0300, National Bureau of Economic Research, Inc.
- Laurent-Emmanuel Calvet & Adlai J. Fisher & Samuel B. Thompson, 2006. "Volatility Comovement: a multifrequency approach," Post-Print hal-00459667, HAL.
- Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
- Lobato, Ignacio N & Savin, N E, 1998.
"Real and Spurious Long-Memory Properties of Stock-Market Data,"
Journal of Business & Economic Statistics, American Statistical Association, vol. 16(3), pages 261-268, July.
- Lobato, I.N. & Savin, N.E., 1996. "Real and Spurious Long Memory Properties of Stock Market Data," Working Papers 96-07, University of Iowa, Department of Economics.
- I.N. Lobato & N.E. Savin, 1996. "Real and Spurious Long Memory Properties of Stock Market Data," Econometrics 9605004, University Library of Munich, Germany, revised 26 Sep 1996.
- Ding, Zhuanxin & Granger, Clive W. J. & Engle, Robert F., 1993. "A long memory property of stock market returns and a new model," Journal of Empirical Finance, Elsevier, vol. 1(1), pages 83-106, June.
- Calvet, Laurent & Fisher, Adlai, 2001.
"Forecasting multifractal volatility,"
Journal of Econometrics, Elsevier, vol. 105(1), pages 27-58, November.
- Laurent Calvet & Adlai Fisher, 1999. "Forecasting Multifractal Volatility," New York University, Leonard N. Stern School Finance Department Working Paper Seires 99-017, New York University, Leonard N. Stern School of Business-.
- Laurent-Emmanuel Calvet & Adlai J. Fisher, 2001. "Forecasting multifractal volatility," Post-Print hal-00477952, HAL.
- Laurent Calvet, 2000. "Forecasting Multifractal Volatility," Harvard Institute of Economic Research Working Papers 1902, Harvard - Institute of Economic Research.
- Luc Bauwens & Sébastien Laurent & Jeroen V. K. Rombouts, 2006.
"Multivariate GARCH models: a survey,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 79-109, January.
- Sébastien Laurent & Luc Bauwens & Jeroen V. K. Rombouts, 2006. "Multivariate GARCH models: a survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 79-109.
- BAUWENS, Luc & LAURENT, Sébastien & ROMBOUTS, Jeroen, 2003. "Multivariate GARCH models: a survey," LIDAM Discussion Papers CORE 2003031, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- BAUWENS, Luc & LAURENT, Sébastien & ROMBOUTS, Jeroen VK, 2006. "Multivariate GARCH models: a survey," LIDAM Reprints CORE 1847, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Thomas Lux, 2004. "Detecting Multifractal Properties In Asset Returns: The Failure Of The "Scaling Estimator"," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 15(04), pages 481-491.
- Lo, Andrew W, 1991.
"Long-Term Memory in Stock Market Prices,"
Econometrica, Econometric Society, vol. 59(5), pages 1279-1313, September.
- Lo, Andrew W. (Andrew Wen-Chuan), 1989. "Long-term memory in stock market prices," Working papers 3014-89., Massachusetts Institute of Technology (MIT), Sloan School of Management.
- Andrew W. Lo, 1989. "Long-term Memory in Stock Market Prices," NBER Working Papers 2984, National Bureau of Economic Research, Inc.
- Tom Doan, "undated". "RSSTATISTIC: RATS procedure to compute R/S Statistic (classical or Lo's modified)," Statistical Software Components RTS00191, Boston College Department of Economics.
- Julien Idier, 2011.
"Long-term vs. short-term comovements in stock markets: the use of Markov-switching multifractal models,"
The European Journal of Finance, Taylor & Francis Journals, vol. 17(1), pages 27-48.
- Idier, J., 2008. "Long term vs. short term comovements in stock markets: the use of Markov-switching multifractal models," Working papers 218, Banque de France.
- Liesenfeld, Roman & Richard, Jean-Francois, 2003. "Univariate and multivariate stochastic volatility models: estimation and diagnostics," Journal of Empirical Finance, Elsevier, vol. 10(4), pages 505-531, September.
- Ramsey, J.B., 2002. "Wavelets in Economics and Finance: Past and Future," Working Papers 02-02, C.V. Starr Center for Applied Economics, New York University.
- Baruník, Jozef & Kočenda, Evžen & Vácha, Lukáš, 2016.
"Gold, oil, and stocks: Dynamic correlations,"
International Review of Economics & Finance, Elsevier, vol. 42(C), pages 186-201.
- Jozef Barunik & Evzen Kocenda & Lukas Vacha, 2013. "Gold, Oil, and Stocks," Papers 1308.0210, arXiv.org, revised Mar 2014.
- Jozef Baruník & Evžen Kocenda & Lukáš Vácha, 2015. "Gold, Oil, and Stocks: Dynamic Correlations," CESifo Working Paper Series 5333, CESifo.
- Baruník, Jozef & Kočenda, Evžen & Vácha, Lukáš, 2014. "Gold, Oil, and Stocks," FinMaP-Working Papers 14, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
- Laurent E. Calvet, 2004.
"How to Forecast Long-Run Volatility: Regime Switching and the Estimation of Multifractal Processes,"
Journal of Financial Econometrics, Oxford University Press, vol. 2(1), pages 49-83.
- Laurent-Emmanuel Calvet & Adlai J. Fisher, 2004. "How to Forecast Long-Run Volatility: Regime Switching and the Estimation of Multifractal Processes," Post-Print hal-00478472, HAL.
- Harvey, David I & Leybourne, Stephen J & Newbold, Paul, 1998. "Tests for Forecast Encompassing," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(2), pages 254-259, April.
- Lobato, Ignacio N & Savin, N E, 1998. "Real and Spurious Long-Memory Properties of Stock-Market Data: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(3), pages 280-283, July.
- Lux, Thomas & Morales-Arias, Leonardo, 2010. "Forecasting volatility under fractality, regime-switching, long memory and student-t innovations," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2676-2692, November.
- Bollerslev, Tim, 1990. "Modelling the Coherence in Short-run Nominal Exchange Rates: A Multivariate Generalized ARCH Model," The Review of Economics and Statistics, MIT Press, vol. 72(3), pages 498-505, August.
- E. Bacry & J. Delour & J. F. Muzy, 2000. "A multivariate multifractal model for return fluctuations," Papers cond-mat/0009260, arXiv.org.
- Gilles Zumbach, 2004. "Volatility processes and volatility forecast with long memory," Quantitative Finance, Taylor & Francis Journals, vol. 4(1), pages 70-86.
- Ramsey James B., 2002. "Wavelets in Economics and Finance: Past and Future," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 6(3), pages 1-29, November.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Lux, Thomas, 2022. "Inference for Nonlinear State Space Models: A Comparison of Different Methods applied to Markov-Switching Multifractal Models," Econometrics and Statistics, Elsevier, vol. 21(C), pages 69-95.
- Sikora, Grzegorz & Michalak, Anna & Bielak, Łukasz & Miśta, Paweł & Wyłomańska, Agnieszka, 2019. "Stochastic modeling of currency exchange rates with novel validation techniques," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 1202-1215.
- Lux, Thomas, 2018. "Inference for nonlinear state space models: A comparison of different methods applied to Markov-switching multifractal models," Economics Working Papers 2018-07, Christian-Albrechts-University of Kiel, Department of Economics.
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.- Liu, Ruipeng & Lux, Thomas, 2010. "Flexible and robust modelling of volatility comovements: a comparison of two multifractal models," Kiel Working Papers 1594, Kiel Institute for the World Economy (IfW Kiel).
- Segnon, Mawuli & Lux, Thomas, 2013. "Multifractal models in finance: Their origin, properties, and applications," Kiel Working Papers 1860, Kiel Institute for the World Economy (IfW Kiel).
- Lux, Thomas & Morales-Arias, Leonardo, 2010. "Relative forecasting performance of volatility models: Monte Carlo evidence," Kiel Working Papers 1582, Kiel Institute for the World Economy (IfW Kiel).
- Lux, Thomas & Alfarano, Simone, 2016. "Financial power laws: Empirical evidence, models, and mechanisms," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 3-18.
- Lux, Thomas & Morales-Arias, Leonardo & Sattarhoff, Cristina, 2011. "A Markov-switching multifractal approach to forecasting realized volatility," Kiel Working Papers 1737, Kiel Institute for the World Economy (IfW Kiel).
- Adnen Ben Nasr & Ahdi Noomen Ajmi & Rangan Gupta, 2014.
"Modelling the volatility of the Dow Jones Islamic Market World Index using a fractionally integrated time-varying GARCH (FITVGARCH) model,"
Applied Financial Economics, Taylor & Francis Journals, vol. 24(14), pages 993-1004, July.
- Adnen Ben Nasr & Ahdi N. Ajmi & Rangan Gupta, 2013. "Modeling the Volatility of the Dow Jones Islamic Market World Index Using a Fractionally Integrated Time Varying GARCH (FITVGARCH) Model," Working Papers 201357, University of Pretoria, Department of Economics.
- Nasr, Adnen Ben & Lux, Thomas & Ajmi, Ahdi Noomen & Gupta, Rangan, 2016.
"Forecasting the volatility of the Dow Jones Islamic Stock Market Index: Long memory vs. regime switching,"
International Review of Economics & Finance, Elsevier, vol. 45(C), pages 559-571.
- Nasr, Adnen Ben & Lux, Thomas & Ajm, Ahdi Noomen & Gupta, Rangan, 2014. "Forecasting the volatility of the dow jones islamic stock market index: Long memory vs. regime switching," Economics Working Papers 2014-07, Christian-Albrechts-University of Kiel, Department of Economics.
- Adnen Ben Nasr & Thomas Lux & Ahdi Noomen Ajmi & Rangan Gupta, 2014. "Forecasting the Volatility of the Dow Jones Islamic Stock Market Index: Long Memory vs. Regime Switching," Working Papers 2014-236, Department of Research, Ipag Business School.
- Adnen Ben Nasr & Thomas Lux & Ahdi N. Ajmi & Rangan Gupta, 2014. "Forecasting the Volatility of the Dow Jones Islamic Stock Market Index: Long Memory vs. Regime Switching," Working Papers 201412, University of Pretoria, Department of Economics.
- Ben Nasr, Adnen & Lux, Thomas & Ajmi, Ahdi Noomen & Gupta, Rangan, 2014. "Forecasting the Volatility of the Dow Jones Islamic Stock Market Index: Long Memory vs. Regime Switching," FinMaP-Working Papers 2, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
- Lux, Thomas & Morales-Arias, Leonardo, 2010. "Forecasting volatility under fractality, regime-switching, long memory and student-t innovations," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2676-2692, November.
- Batten, Jonathan A. & Kinateder, Harald & Wagner, Niklas, 2014. "Multifractality and value-at-risk forecasting of exchange rates," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 401(C), pages 71-81.
- Mawuli Segnon & Stelios Bekiros, 2019. "Forecasting Volatility in Cryptocurrency Markets," CQE Working Papers 7919, Center for Quantitative Economics (CQE), University of Muenster.
- Thomas Lux, 2003.
"The Multi-Fractal Model of Asset Returns:Its Estimation via GMM and Its Use for Volatility Forecasting,"
Computing in Economics and Finance 2003
14, Society for Computational Economics.
- Lux, Thomas, 2003. "The multi-fractal model of asset returns: Its estimation via GMM and its use for volatility forecasting," Economics Working Papers 2003-13, Christian-Albrechts-University of Kiel, Department of Economics.
- Mawuli Segnon & Stelios Bekiros, 2020. "Forecasting volatility in bitcoin market," Annals of Finance, Springer, vol. 16(3), pages 435-462, September.
- Julien Idier, 2011.
"Long-term vs. short-term comovements in stock markets: the use of Markov-switching multifractal models,"
The European Journal of Finance, Taylor & Francis Journals, vol. 17(1), pages 27-48.
- Idier, J., 2008. "Long term vs. short term comovements in stock markets: the use of Markov-switching multifractal models," Working papers 218, Banque de France.
- Lux, Thomas & Morales-Arias, Leonardo, 2009. "Forecasting volatility under fractality, regime-switching, long memory and student-t innovations," Kiel Working Papers 1532, Kiel Institute for the World Economy (IfW Kiel).
- Lux, Thomas, 2008.
"The Markov-Switching Multifractal Model of Asset Returns: GMM Estimation and Linear Forecasting of Volatility,"
Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 194-210, April.
- Lux, Thomas, 2004. "The Markov-switching multi-fractal model of asset returns: GMM estimation and linear forecasting of volatility," Economics Working Papers 2004-11, Christian-Albrechts-University of Kiel, Department of Economics.
- Lux, Thomas, 2006. "The Markov-Switching Multifractal Model of asset returns: GMM estimation and linear forecasting of volatility," Economics Working Papers 2006-17, Christian-Albrechts-University of Kiel, Department of Economics.
- Carmen Broto & Esther Ruiz, 2004.
"Estimation methods for stochastic volatility models: a survey,"
Journal of Economic Surveys, Wiley Blackwell, vol. 18(5), pages 613-649, December.
- Broto, Carmen, 2002. "Estimation methods for stochastic volatility models: a survey," DES - Working Papers. Statistics and Econometrics. WS ws025414, Universidad Carlos III de Madrid. Departamento de EstadÃstica.
- Elena Andreou & Eric Ghysels, 2002.
"Detecting multiple breaks in financial market volatility dynamics,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 579-600.
- Elena Andreou & Eric Ghysels, 2001. "Detecting Mutiple Breaks in Financial Market Volatility Dynamics," CIRANO Working Papers 2001s-65, CIRANO.
- Elena Andreou & Eric Ghysels, 2001. "Detecting Multiple Breaks in Financial Market Volatility Dynamics," University of Cyprus Working Papers in Economics 0202, University of Cyprus Department of Economics.
- Lux, Thomas & Kaizoji, Taisei, 2007.
"Forecasting volatility and volume in the Tokyo Stock Market: Long memory, fractality and regime switching,"
Journal of Economic Dynamics and Control, Elsevier, vol. 31(6), pages 1808-1843, June.
- Lux, Thomas & Kaizoji, Taisei, 2006. "Forecasting volatility and volume in the Tokyo stock market: Long memory, fractality and regime switching," Economics Working Papers 2006-13, Christian-Albrechts-University of Kiel, Department of Economics.
- Lux, Thomas, 2008. "Applications of statistical physics in finance and economics," Kiel Working Papers 1425, Kiel Institute for the World Economy (IfW Kiel).
- Segnon, Mawuli & Lux, Thomas & Gupta, Rangan, 2015.
"Modeling and Forecasting Carbon Dioxide Emission Allowance Spot Price Volatility: Multifractal vs. GARCH-type Volatility Models,"
FinMaP-Working Papers
46, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
- Mawuli Segnon & Thomas Lux & Rangan Gupta, 2015. "Modeling and Forecasting Carbon Dioxide Emission Allowance Spot Price Volatility: Multifractal vs. GARCH-Type Volatility Models," Working Papers 201550, University of Pretoria, Department of Economics.
More about this item
Keywords
Multivariate; Multifractal; Long memory; GMM estimation;All these keywords.
JEL classification:
- C20 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - General
- G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
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:ecmode:v:67:y:2017:i:c:p:136-148. 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/30411 .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.