The UHF-GARCH-Type Model in the Analysis of Intraday Volatility and Price Durations – the Bayesian Approach
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Luc Bauwens & Pierre Giot, 2000.
"The Logarithmic ACD Model: An Application to the Bid-Ask Quote Process of Three NYSE Stocks,"
Annals of Economics and Statistics, GENES, issue 60, pages 117-149.
- BAUWENS, Luc & GIOT, Pierre, 2000. "The logarithmic ACD model: an application to the bid-ask quote process of three NYSE stocks," LIDAM Reprints CORE 1497, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Roman Huptas, 2014. "Bayesian Estimation and Prediction for ACD Models in the Analysis of Trade Durations from the Polish Stock Market," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 6(4), pages 237-273, December.
- Luc Bauwens & Pierre Giot, 2003.
"Asymmetric ACD models: Introducing price information in ACD models,"
Empirical Economics, Springer, vol. 28(4), pages 709-731, November.
- BAUWENS, Luc & GIOT, Pierre, 2003. "Asymmetric ACD models: Introducing price information in ACD models," LIDAM Reprints CORE 1670, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- BAUWENS, Luc & VEREDAS, David, 1999.
"The stochastic conditional duration model: a latent factor model for the analysis of financial durations,"
LIDAM Discussion Papers CORE
1999058, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Luc Bauwens & David Veredas, 2004. "The stochastic conditional duration model: a latent factor model for the analysis of financial durations," ULB Institutional Repository 2013/136234, ULB -- Universite Libre de Bruxelles.
- Hautsch, Nikolaus, 2002. "Modelling Intraday Trading Activity Using Box-Cox-ACD Models," CoFE Discussion Papers 02/05, University of Konstanz, Center of Finance and Econometrics (CoFE).
- Ghysels Eric & Jasiak Joanna, 1998. "GARCH for Irregularly Spaced Financial Data: The ACD-GARCH Model," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 2(4), pages 1-19, January.
- Robert F. Engle & Jeffrey R. Russell, 1998. "Autoregressive Conditional Duration: A New Model for Irregularly Spaced Transaction Data," Econometrica, Econometric Society, vol. 66(5), pages 1127-1162, September.
- Bauwens, Luc & Veredas, David, 2004.
"The stochastic conditional duration model: a latent variable model for the analysis of financial durations,"
Journal of Econometrics, Elsevier, vol. 119(2), pages 381-412, April.
- BAUWENS, Luc & VEREDAS, David, 2004. "The stochastic conditional duration model: a latent variable model for the analysis of financial durations," LIDAM Reprints CORE 1688, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Roll, Richard, 1984. "A Simple Implicit Measure of the Effective Bid-Ask Spread in an Efficient Market," Journal of Finance, American Finance Association, vol. 39(4), pages 1127-1139, September.
- Manganelli, Simone, 2005.
"Duration, volume and volatility impact of trades,"
Journal of Financial Markets, Elsevier, vol. 8(4), pages 377-399, November.
- Manganelli, Simone, 2002. "Duration, volume and volatility impact of trades," Working Paper Series 125, European Central Bank.
- Robert F. Engle, 2000.
"The Econometrics of Ultra-High Frequency Data,"
Econometrica, Econometric Society, vol. 68(1), pages 1-22, January.
- Robert F. Engle, 1996. "The Econometrics of Ultra-High Frequency Data," NBER Working Papers 5816, National Bureau of Economic Research, Inc.
- Giovanni Luca & Giampiero Gallo, 2009.
"Time-Varying Mixing Weights in Mixture Autoregressive Conditional Duration Models,"
Econometric Reviews, Taylor & Francis Journals, vol. 28(1-3), pages 102-120.
- Giovanni De Luca & Giampiero M. Gallo, 2005. "Time-varying Mixing Weights in Mixture Autoregressive Conditional Duration Models," Econometrics Working Papers Archive wp2005_11, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
- Giovanni De Luca & Giampiero Gallo, 2006. "Time-varying Mixing Weights in Mixture Autoregressive Conditional Duration Models," Econometrics Working Papers Archive wp2006_12, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
- Nikolaus Hautsch, 2012. "Econometrics of Financial High-Frequency Data," Springer Books, Springer, number 978-3-642-21925-2, May.
- Alfonso Dufour & Robert F Engle, 2000. "The ACD Model: Predictability of the Time Between Concecutive Trades," ICMA Centre Discussion Papers in Finance icma-dp2000-05, Henley Business School, University of Reading.
- repec:adr:anecst:y:2000:i:60:p:05 is not listed on IDEAS
- Meddahi, Nour & Renault, Eric & Werker, Bas, 2006.
"GARCH and irregularly spaced data,"
Economics Letters, Elsevier, vol. 90(2), pages 200-204, February.
- Meddahi, N. & Renault, E. & Werker, B.J.M., 2003. "GARCH and Irregularly Spaced Data," Discussion Paper 2003-27, Tilburg University, Center for Economic Research.
- Roman Huptas, 2009. "Intraday Seasonality in Analysis of UHF Financial Data: Models and Their Empirical Verification," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 9, pages 128-138.
- Allen, David & Chan, Felix & McAleer, Michael & Peiris, Shelton, 2008. "Finite sample properties of the QMLE for the Log-ACD model: Application to Australian stocks," Journal of Econometrics, Elsevier, vol. 147(1), pages 163-185, November.
- Bauwens, Luc & Giot, Pierre & Grammig, Joachim & Veredas, David, 2004.
"A comparison of financial duration models via density forecasts,"
International Journal of Forecasting, Elsevier, vol. 20(4), pages 589-609.
- BAUWENS , Luc & GIOT, Pierre & GRAMMIG, Joachim & VEREDAS, David, 2000. "A comparison of financial duration models via density forecasts," LIDAM Discussion Papers CORE 2000060, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Luc Bauwens & Pierre Giot & Joachim Grammig & David Veredas, 2004. "A comparison of financial duration models via density forecast," ULB Institutional Repository 2013/136218, ULB -- Universite Libre de Bruxelles.
- BAUWENS, Luc & GIOT, Pierre & GRAMMIG, Joachim & VEREDAS, David, 2004. "A comparison of financial duration models via density forecasts," LIDAM Reprints CORE 1746, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Luc Bauwens & Pierre Giot & Joachim Grammig & David Veredas, 2000. "A Comparison of Financial Duration Models via Density Forecasts," Econometric Society World Congress 2000 Contributed Papers 0810, Econometric Society.
- De Luca, Giovanni & Zuccolotto, Paola, 2006. "Regime-switching Pareto distributions for ACD models," Computational Statistics & Data Analysis, Elsevier, vol. 51(4), pages 2179-2191, December.
- Easley, David & O'Hara, Maureen, 1992. "Time and the Process of Security Price Adjustment," Journal of Finance, American Finance Association, vol. 47(2), pages 576-605, June.
- Joachim Grammig & Kai-Oliver Maurer, 2000. "Non-monotonic hazard functions and the autoregressive conditional duration model," Econometrics Journal, Royal Economic Society, vol. 3(1), pages 16-38.
- Liu, Chun & Maheu, John M., 2012. "Intraday dynamics of volatility and duration: Evidence from Chinese stocks," Pacific-Basin Finance Journal, Elsevier, vol. 20(3), pages 329-348.
- Zhang, Michael Yuanjie & Russell, Jeffrey R. & Tsay, Ruey S., 2001. "A nonlinear autoregressive conditional duration model with applications to financial transaction data," Journal of Econometrics, Elsevier, vol. 104(1), pages 179-207, August.
- Fernandes, Marcelo & Grammig, Joachim, 2006.
"A family of autoregressive conditional duration models,"
Journal of Econometrics, Elsevier, vol. 130(1), pages 1-23, January.
- FERNANDES, Marcelo & GRAMMIG, Joachim, 2001. "A family of autoregressive conditional duration models," LIDAM Discussion Papers CORE 2001036, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Fernandes, Marcelo & Grammig, Joachim, 2003. "A family of autoregressive conditional duration models," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 501, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
- Fernandes, Marcelo & Grammig, Joachim, 2002. "A family of autoregressive conditional duration models," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 440, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Roman Huptas, 2019. "Point forecasting of intraday volume using Bayesian autoregressive conditional volume models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 38(4), pages 293-310, July.
- Vladim'ir Hol'y, 2022. "An Intraday GARCH Model for Discrete Price Changes and Irregularly Spaced Observations," Papers 2211.12376, arXiv.org, revised May 2024.
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.- Roman Huptas, 2014. "Bayesian Estimation and Prediction for ACD Models in the Analysis of Trade Durations from the Polish Stock Market," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 6(4), pages 237-273, December.
- Roman Huptas, 2019. "Point forecasting of intraday volume using Bayesian autoregressive conditional volume models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 38(4), pages 293-310, July.
- repec:bla:jecsur:v:22:y:2008:i:4:p:711-751 is not listed on IDEAS
- Luc Bauwens & Nikolaus Hautsch, 2009.
"Modelling Financial High Frequency Data Using Point Processes,"
Springer Books, in: Thomas Mikosch & Jens-Peter Kreiß & Richard A. Davis & Torben Gustav Andersen (ed.), Handbook of Financial Time Series, chapter 41, pages 953-979,
Springer.
- Luc, BAUWENS & Nikolaus, HAUTSCH, 2006. "Modelling Financial High Frequency Data Using Point Processes," Discussion Papers (ECON - Département des Sciences Economiques) 2006039, Université catholique de Louvain, Département des Sciences Economiques.
- BAUWENS, Luc & HAUTSCH, Nikolaus, 2009. "Modelling financial high frequency data using point processes," LIDAM Reprints CORE 2123, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- BAUWENS, Luc & HAUTSCH, Nikolaus, 2006. "Modelling financial high frequency data using point processes," LIDAM Discussion Papers CORE 2006080, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Bauwens, Luc & Hautsch, Nikolaus, 2007. "Modelling financial high frequency data using point processes," SFB 649 Discussion Papers 2007-066, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
- Wei Sun & Svetlozar Rachev & Frank Fabozzi & Petko Kalev, 2008. "Fractals in trade duration: capturing long-range dependence and heavy tailedness in modeling trade duration," Annals of Finance, Springer, vol. 4(2), pages 217-241, March.
- Dimitrakopoulos, Stefanos & Tsionas, Mike G. & Aknouche, Abdelhakim, 2020. "Ordinal-response models for irregularly spaced transactions: A forecasting exercise," MPRA Paper 103250, University Library of Munich, Germany, revised 01 Oct 2020.
- Trojan, Sebastian, 2014. "Modeling Intraday Stochastic Volatility and Conditional Duration Contemporaneously with Regime Shifts," Economics Working Paper Series 1425, University of St. Gallen, School of Economics and Political Science.
- Xiufeng Yan, 2021. "Autoregressive conditional duration modelling of high frequency data," Papers 2111.02300, arXiv.org.
- Chun Liu & John M Maheu, 2010. "Intraday Dynamics of Volatility and Duration: Evidence from the Chinese Stock Market," Working Papers tecipa-401, University of Toronto, Department of Economics.
- Fernandes, Marcelo & Grammig, Joachim, 2005.
"Nonparametric specification tests for conditional duration models,"
Journal of Econometrics, Elsevier, vol. 127(1), pages 35-68, July.
- Fernandes, M. & Grammig, J., 2000. "Non-Parametric Specification Tests for Conditional Duration Models," Economics Working Papers eco2000/4, European University Institute.
- Fernandes, Marcelo & Grammig, Joachim, 2003. "Nonparametric specification tests for conditional duration models," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 502, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
- Marcelo Fernandes & Joachim Grammig, 2000. "Non-Parametric Specification Tests For Conditional Duration Models," Computing in Economics and Finance 2000 40, Society for Computational Economics.
- Magdalena Osinska & Andrzej Dobrzynski & Yochanan Shachmurove, 2016. "Performance Of American And Russian Joint Stock Companies On Financial Market. A Microstructure Perspective," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 11(4), pages 819-851, December.
- Yiing Fei Tan & Kok Haur Ng & You Beng Koh & Shelton Peiris, 2022. "Modelling Trade Durations Using Dynamic Logarithmic Component ACD Model with Extended Generalised Inverse Gaussian Distribution," Mathematics, MDPI, vol. 10(10), pages 1-20, May.
- Yogo Purwono & Irwan Adi Ekaputra & Zaäfri Ananto Husodo, 2018. "Estimation of Dynamic Mixed Hitting Time Model Using Characteristic Function Based Moments," Computational Economics, Springer;Society for Computational Economics, vol. 51(2), pages 295-321, February.
- Liu, Chun & Maheu, John M., 2012. "Intraday dynamics of volatility and duration: Evidence from Chinese stocks," Pacific-Basin Finance Journal, Elsevier, vol. 20(3), pages 329-348.
- Renault, Eric & van der Heijden, Thijs & Werker, Bas J.M., 2014. "The dynamic mixed hitting-time model for multiple transaction prices and times," Journal of Econometrics, Elsevier, vol. 180(2), pages 233-250.
- Vasileios Siakoulis & Ioannis Venetis, 2015. "On inter-arrival times of bond market extreme events. An application to seven European markets," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 39(4), pages 717-741, October.
- repec:hum:wpaper:sfb649dp2008-047 is not listed on IDEAS
- Pérez-Rodríguez, Jorge V. & Gómez-Déniz, Emilio & Sosvilla-Rivero, Simón, 2021. "Testing unobserved market heterogeneity in financial markets: The case of Banco Popular," The Quarterly Review of Economics and Finance, Elsevier, vol. 79(C), pages 151-160.
- Antonio Cosma & Fausto Galli, 2006.
"A Nonparametric ACD Model,"
LSF Research Working Paper Series
06-10, Luxembourg School of Finance, University of Luxembourg.
- Cosma, Antonio & Galli, Fausto, 2014. "A non parametric ACD model," MPRA Paper 53990, University Library of Munich, Germany.
- COSMA, Antonio & GALLI, Fausto, 2006. "A nonparametric ACD model," LIDAM Discussion Papers CORE 2006067, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Katarzyna Bien-Barkowska, 2011. "Distribution Choice for the Asymmetric ACD Models," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 11, pages 55-72.
- Jorge Pérez-Rodríguez & Emilio Gómez-Déniza & Simón Sosvilla-Rivero, 2019. "“Testing for private information using trade duration models with unobserved market heterogeneity: The case of Banco Popular”," IREA Working Papers 201907, University of Barcelona, Research Institute of Applied Economics, revised Apr 2019.
- Anthony Tay & Christopher Ting & Yiu Kuen Tse & Mitch Warachka, 2007. "Modeling Transaction Data of Trade Direction and Estimation of Probability of Informed Trading," Finance Working Papers 22483, East Asian Bureau of Economic Research.
More about this item
Keywords
; ; ; ; ;JEL classification:
- C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
- C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
- C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
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:psc:journl:v:8:y:2016:i:1:p:1-20. 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: Damian Jelito (email available below). General contact details of provider: http://cejeme.org/ .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.
Printed from https://ideas.repec.org/a/psc/journl/v8y2016i1p1-20.html