Dynamic Bivariate Mixture Models: Modeling the Behavior of Prices and Trading Volume
AbstractBivariate mixture models have been used to explain the stochastic behavior of daily price changes and trading volume on financial markets. In this class of models, price changes and volume follow a mixture of bivariate distributions with the unobservable number of price-relevant information serving as the mixing variable. The time series behavior of this mixture variable determines the dynamics of the price-volume system. In this article, bivariate mixture specifications with a serially correlated mixing variable are estimated by simulated maximum likelihood and analyzed concerning their ability to account for the observed dynamics on financial markets, especially the persistence in the variance of price changes. The results, based on German stock-market data, reveal that the dynamic bivariate mixture models cannot account for the persistence in the price-change variance.
Download InfoTo our knowledge, this item is not available for download. To find whether it is available, there are three options:
1. Check below under "Related research" whether another version of this item is available online.
2. Check on the provider's web page whether it is in fact available.
3. Perform a search for a similarly titled item that would be available.
Bibliographic InfoArticle provided by American Statistical Association in its journal Journal of Business and Economic Statistics.
Volume (Year): 16 (1998)
Issue (Month): 1 (January)
Contact details of provider:
Web page: http://www.amstat.org/publications/jbes/index.cfm?fuseaction=main
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- repec:lan:wpaper:3048 is not listed on IDEAS
- Thierry Ané & Loredana Ureche-Rangau, 2004.
"Does trading volume really explain stock returns volatility?,"
2004-FIN-02, IESEG School of Management.
- Ané, Thierry & Ureche-Rangau, Loredana, 2008. "Does trading volume really explain stock returns volatility?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 18(3), pages 216-235, July.
- Torben G. Andersen & Tim Bollerslev & Per Frederiksen & Morten �rregaard Nielsen, 2010.
"Continuous-time models, realized volatilities, and testable distributional implications for daily stock returns,"
Journal of Applied Econometrics,
John Wiley & Sons, Ltd., vol. 25(2), pages 233-261.
- Torben G. Andersen & Tim Bollerslev & Per Frederiksen & Morten Ørregaard Nielsen, 2008. "Continuous-Time Models, Realized Volatilities, and Testable Distributional Implications for Daily Stock Returns," Working Papers 1173, Queen's University, Department of Economics.
- Torben G. Andersen & Tim Bollerslev & Per Houmann Frederiksen & Morten Ørregaard Nielsen, 2007. "Continuous-Time Models, Realized Volatilities, and Testable Distributional Implications for Daily Stock Returns," CREATES Research Papers 2007-21, School of Economics and Management, University of Aarhus.
- repec:lan:wpaper:3326 is not listed on IDEAS
- Nikolaus Hautsch, 2007.
"Capturing Common Components in High-Frequency Financial Time Series: A Multivariate Stochastic Multiplicative Error Model,"
SFB 649 Discussion Papers
SFB649DP2007-052, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
- Hautsch, Nikolaus, 2008. "Capturing common components in high-frequency financial time series: A multivariate stochastic multiplicative error model," Journal of Economic Dynamics and Control, Elsevier, vol. 32(12), pages 3978-4015, December.
- Hautsch, Nikolaus, 2007. "Capturing common components in high-frequency financial time series: A multivariate stochastic multiplicative error model," CFS Working Paper Series 2007/25, Center for Financial Studies (CFS).
- Junji Shimada & Yoshihiko Tsukuda, 2004. "Estimation of Stochastic Volatility Models : An Approximation to the Nonlinear State Space," Econometric Society 2004 Far Eastern Meetings 611, Econometric Society.
- Marwan Izzeldin, 2007. "Trading volume and the number of trades: a comparative study using high frequency data," Working Papers 584864, Lancaster University Management School, Economics Department.
- Henryk Gurgul & Paweł Majdosz & Roland Mestel, 2007. "Price–volume relations of DAX companies," Financial Markets and Portfolio Management, Springer, vol. 21(3), pages 353-379, September.
- Maciejowska, Katarzyna, 2013. "Assessing the number of components in a normal mixture: an alternative approach," MPRA Paper 50303, University Library of Munich, Germany.
- repec:lan:wpaper:3142 is not listed on IDEAS
- Roland Füss & Michael Bechtel, 2008. "Partisan politics and stock market performance: The effect of expected government partisanship on stock returns in the 2002 German federal election," Public Choice, Springer, vol. 135(3), pages 131-150, June.
- Roman Liesenfeld & Robert C. Jung, 2000. "Stochastic volatility models: conditional normality versus heavy-tailed distributions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(2), pages 137-160.
- Ainhoa Zarraga, 2003. "GMM-based testing procedures of the mixture of distributions model," Applied Financial Economics, Taylor & Francis Journals, vol. 13(11), pages 841-848.
- Pyun, Chong Soo & Lee, Sa Young & Nam, Kiseok, 2000. "Volatility and information flows in emerging equity market: A case of the Korean Stock Exchange," International Review of Financial Analysis, Elsevier, vol. 9(4), pages 405-420.
- Liesenfeld, Roman, 2001. "A generalized bivariate mixture model for stock price volatility and trading volume," Journal of Econometrics, Elsevier, vol. 104(1), pages 141-178, August.
- 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.
- Asai, Manabu & Brugal, Ivan, 2013. "Forecasting volatility via stock return, range, trading volume and spillover effects: The case of Brazil," The North American Journal of Economics and Finance, Elsevier, vol. 25(C), pages 202-213.
- repec:lan:wpaper:3050 is not listed on IDEAS
- Katarzyna Maciejowska, 2010. "Estimation Methods Comparison of SVAR Models with a Mixture of Two Normal Distributions," Central European Journal of Economic Modelling and Econometrics, CEJEME, vol. 2(4), pages 279-314, September.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Christopher F. Baum).
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 references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link 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 profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.