Stochastic Conditional Duration Model with Intraday Seasonality and Limit Order Book Information
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- David Veredas & Juan Rodriguez-Poo & Antoni Espasa, 2001.
"On the (Intradaily) Seasonality and Dynamics of a Financial Point Process : A Semiparametric Approach,"
Working Papers
2001-19, Center for Research in Economics and Statistics.
- VEREDAS, David & RODRIGUEZ-POO, Juan & ESPASA, Antoni, 2002. "On the (intradaily) seasonality and dynamics of a financial point process: a semiparametric approach," LIDAM Discussion Papers CORE 2002023, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Veredas, David & Rodríguez Poo, Juan M., 2001. "On the (intradaily) seasonality and dynamics of a financial point process: a semiparametric approach," DES - Working Papers. Statistics and Econometrics. WS ws013321, Universidad Carlos III de Madrid. Departamento de EstadÃstica.
- Strickland, Chris M. & Forbes, Catherine S. & Martin, Gael M., 2006.
"Bayesian analysis of the stochastic conditional duration model,"
Computational Statistics & Data Analysis, Elsevier, vol. 50(9), pages 2247-2267, May.
- Chris M. Strickland & Catherine S. Forbes & Gael M. Martin, 2003. "Bayesian Analysis of the Stochastic Conditional Duration Model," Monash Econometrics and Business Statistics Working Papers 14/03, Monash University, Department of Econometrics and Business Statistics.
- Omori, Yasuhiro & Watanabe, Toshiaki, 2008.
"Block sampler and posterior mode estimation for asymmetric stochastic volatility models,"
Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 2892-2910, February.
- Yasuhiro Omori & Toshiaki Watanabe, 2007. "Block Sampler and Posterior Mode Estimation for Asymmetric Stochastic Volatility Models," CIRJE F-Series CIRJE-F-507, CIRJE, Faculty of Economics, University of Tokyo.
- 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, 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.
- 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.
- 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).
- David J. Spiegelhalter & Nicola G. Best & Bradley P. Carlin & Angelika Van Der Linde, 2002. "Bayesian measures of model complexity and fit," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(4), pages 583-639, October.
- Toshiaki Watanabe, 2004. "A multi-move sampler for estimating non-Gaussian time series models: Comments on Shephard & Pitt (1997)," Biometrika, Biometrika Trust, vol. 91(1), pages 246-248, March.
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.- 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.
- 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.
- McCausland, William J., 2012. "The HESSIAN method: Highly efficient simulation smoothing, in a nutshell," Journal of Econometrics, Elsevier, vol. 168(2), pages 189-206.
- Xiufeng Yan, 2021. "Autoregressive conditional duration modelling of high frequency data," Papers 2111.02300, arXiv.org.
- Zhongxian Men & Tony S. Wirjanto & Adam W. Kolkiewicz, 2016. "A Multiscale Stochastic Conditional Duration Model," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 11(04), pages 1-28, December.
- Xiufeng Yan, 2021. "Multiplicative Component GARCH Model of Intraday Volatility," Papers 2111.02376, arXiv.org.
- Galli, Fausto, 2014. "Stochastic conditonal range, a latent variable model for financial volatility," MPRA Paper 54841, University Library of Munich, Germany.
- Zhongxian Men & Adam W. Kolkiewicz & Tony S. Wirjanto, 2013. "Bayesian Inference of Asymmetric Stochastic Conditional Duration Models," Working Paper series 28_13, Rimini Centre for Economic Analysis.
- Zhongxian Men & Tony S. Wirjanto & Adam W. Kolkiewicz, 2013. "Bayesian Inference of Multiscale Stochastic Conditional Duration Models," Working Paper series 63_13, Rimini Centre for Economic Analysis.
- Ralph D. Snyder & Gael M. Martin & Phillip Gould & Paul D. Feigin, 2007. "An Assessment of Alternative State Space Models for Count Time Series," Monash Econometrics and Business Statistics Working Papers 4/07, Monash University, Department of Econometrics and Business Statistics.
- Galli, Fausto, 2014. "Stochastic conditonal range, a latent variable model for financial volatility," MPRA Paper 54030, University Library of Munich, Germany.
- Bauwens, L. & Galli, F., 2009.
"Efficient importance sampling for ML estimation of SCD models,"
Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 1974-1992, April.
- Luc, BAUWENS & Fausto Galli, 2007. "Efficient importance sampling for ML estimation of SCD models," Discussion Papers (ECON - Département des Sciences Economiques) 2007032, Université catholique de Louvain, Département des Sciences Economiques.
- BAUWENS, Luc & GALLI, Fausto, 2007. "Efficient importance sampling for ML estimation of SCD models," LIDAM Discussion Papers CORE 2007053, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- BAUWENS, Luc & GALLI, Fausto, 2009. "Efficient importance sampling for ML estimation of SCD models," LIDAM Reprints CORE 2088, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- 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.
- Marcelo Fernandes & Joachim Grammig, 2000. "Non-Parametric Specification Tests For Conditional Duration Models," Computing in Economics and Finance 2000 40, Society for Computational Economics.
- 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).
- Strickland, Chris M. & Martin, Gael M. & Forbes, Catherine S., 2008.
"Parameterisation and efficient MCMC estimation of non-Gaussian state space models,"
Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 2911-2930, February.
- Chris M Strickland & Gael Martin & Catherine S Forbes, 2006. "Parameterisation and Efficient MCMC Estimation of Non-Gaussian State Space Models," Monash Econometrics and Business Statistics Working Papers 22/06, Monash University, Department of Econometrics and Business Statistics.
- Siem Jan Koopman & André Lucas & Marcel Scharth, 2016.
"Predicting Time-Varying Parameters with Parameter-Driven and Observation-Driven Models,"
The Review of Economics and Statistics, MIT Press, vol. 98(1), pages 97-110, March.
- 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.
- Bodnar, Taras & Hautsch, Nikolaus, 2012.
"Copula-based dynamic conditional correlation multiplicative error processes,"
SFB 649 Discussion Papers
2012-044, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
- Bodnar, Taras & Hautsch, Nikolaus, 2013. "Copula-based dynamic conditional correlation multiplicative error processes," CFS Working Paper Series 2013/19, Center for Financial Studies (CFS).
- Taras Bodnar & Nikolaus Hautsch, 2012. "Copula-Based Dynamic Conditional Correlation Multiplicative Error Processes," SFB 649 Discussion Papers SFB649DP2012-044, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
- Hautsch, Nikolaus & Jeleskovic, Vahidin, 2008. "Modelling high-frequency volatility and liquidity using multiplicative error models," SFB 649 Discussion Papers 2008-047, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
- repec:hum:wpaper:sfb649dp2008-047 is not listed on IDEAS
- 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.
- Tony S. Wirjanto & Adam W. Kolkiewicz & Zhongxian Men, 2013. "Stochastic Conditional Duration Models with Mixture Processes," Working Paper series 29_13, Rimini Centre for Economic Analysis.
- Fok, Dennis & Paap, Richard & Franses, Philip Hans, 2012.
"Modeling dynamic effects of promotion on interpurchase times,"
Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3055-3069.
- Fok, D. & Paap, R. & Franses, Ph.H.B.F., 2002. "Modeling dynamic effects of promotion on interpurchase times," Econometric Institute Research Papers EI 2002-37, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
More about this item
Keywords
Bayesian inference; Markov chain Monte Carlo; Metropolis–Hastings algorithm; state space model; block sampler;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:gam:jjrfmx:v:15:y:2022:i:10:p:470-:d:944931. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.