Advanced Search
MyIDEAS: Login to save this paper or follow this series

Capturing common components in high-frequency financial time series: A multivariate stochastic multiplicative error model

Contents:

Author Info

  • Hautsch, Nikolaus

Abstract

We introduce a multivariate multiplicative error model which is driven by componentspecific observation driven dynamics as well as a common latent autoregressive factor. The model is designed to explicitly account for (information driven) common factor dynamics as well as idiosyncratic effects in the processes of highfrequency return volatilities, trade sizes and trading intensities. The model is estimated by simulated maximum likelihood using efficient importance sampling. Analyzing five minutes data from four liquid stocks traded at the New York Stock Exchange, we find that volatilities, volumes and intensities are driven by idiosyncratic dynamics as well as a highly persistent common factor capturing most causal relations and cross-dependencies between the individual variables. This confirms economic theory and suggests more parsimonious specifications of high-dimensional trading processes. It turns out that common shocks affect the return volatility and the trading volume rather than the trading intensity. --

Download Info

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
File URL: http://econstor.eu/bitstream/10419/25526/1/548222150.PDF
Download Restriction: no

Bibliographic Info

Paper provided by Center for Financial Studies (CFS) in its series CFS Working Paper Series with number 2007/25.

as in new window
Length:
Date of creation: 2007
Date of revision:
Handle: RePEc:zbw:cfswop:200725

Contact details of provider:
Postal: House of Finance, Grüneburgplatz 1, HPF H5, D-60323 Frankfurt am Main
Phone: +49 (0)69 798-30050
Fax: +49 (0)69 798-30077
Email:
Web page: http://www.ifk-cfs.de/
More information through EDIRC

Related research

Keywords: Multiplicative Error Models; Common Factor; Efficient Importance Sampling; Intraday Trading Process;

Other versions of this item:

Find related papers by JEL classification:

References

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
as in new window
  1. Robert Engle, 2002. "New frontiers for arch models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., John Wiley & Sons, Ltd., vol. 17(5), pages 425-446.
  2. Fabrizio Cipollini & Robert F. Engle & Giampiero M. Gallo, 2006. "Vector Multiplicative Error Models: Representation and Inference," NBER Technical Working Papers 0331, National Bureau of Economic Research, Inc.
  3. Eric Ghysels & Christian Gourieroux & Joanna Jasiak, 1997. "Stochastic Volatility Duration Models," Working Papers, Centre de Recherche en Economie et Statistique 97-46, Centre de Recherche en Economie et Statistique.
  4. Robert F. Engle & Giampiero M. Gallo, 2003. "A Multiple Indicators Model for Volatility Using Intra-Daily Data," NBER Working Papers 10117, National Bureau of Economic Research, Inc.
  5. Luc Bauwens & Nikolaus Hautsch, 2006. "Stochastic Conditional Intensity Processes," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 4(3), pages 450-493.
  6. Bowsher, Clive G., 2007. "Modelling security market events in continuous time: Intensity based, multivariate point process models," Journal of Econometrics, Elsevier, Elsevier, vol. 141(2), pages 876-912, December.
  7. Manganelli, Simone, 2005. "Duration, volume and volatility impact of trades," Journal of Financial Markets, Elsevier, Elsevier, vol. 8(4), pages 377-399, November.
  8. Nikolaus Hautsch, 2006. "Testing the Conditional Mean Function of Autoregressive Conditional Duration Models," FRU Working Papers, University of Copenhagen. Department of Economics. Finance Research Unit 2006/06, University of Copenhagen. Department of Economics. Finance Research Unit.
  9. 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.
  10. Meddahi, N. & Renault, E. & Werker, B.J.M., 2003. "GARCH and Irregularly Spaced Data," Discussion Paper, Tilburg University, Center for Economic Research 2003-27, Tilburg University, Center for Economic Research.
  11. Grammig, Joachim & Wellner, Marc, 2002. "Modeling the interdependence of volatility and inter-transaction duration processes," Journal of Econometrics, Elsevier, Elsevier, vol. 106(2), pages 369-400, February.
  12. Jean-Francois Richard, 2007. "Efficient High-Dimensional Importance Sampling," Working Papers, University of Pittsburgh, Department of Economics 321, University of Pittsburgh, Department of Economics, revised Jan 2007.
  13. Clark, Peter K, 1973. "A Subordinated Stochastic Process Model with Finite Variance for Speculative Prices," Econometrica, Econometric Society, Econometric Society, vol. 41(1), pages 135-55, January.
  14. Renault, E. & Werker, B.J.M., 2004. "Stochatic Volatility Models with Transaction Time Risk," Discussion Paper, Tilburg University, Center for Economic Research 2004-24, Tilburg University, Center for Economic Research.
  15. Easley, David & O'Hara, Maureen, 1992. " Time and the Process of Security Price Adjustment," Journal of Finance, American Finance Association, American Finance Association, vol. 47(2), pages 576-605, June.
  16. Hasbrouck, Joel, 1991. " Measuring the Information Content of Stock Trades," Journal of Finance, American Finance Association, American Finance Association, vol. 46(1), pages 179-207, March.
  17. repec:cor:louvrp:2023 is not listed on IDEAS
  18. Andersen, Torben G, 1996. " Return Volatility and Trading Volume: An Information Flow Interpretation of Stochastic Volatility," Journal of Finance, American Finance Association, American Finance Association, vol. 51(1), pages 169-204, March.
  19. Foucault, Thierry, 1999. "Order flow composition and trading costs in a dynamic limit order market1," Journal of Financial Markets, Elsevier, Elsevier, vol. 2(2), pages 99-134, May.
  20. Glosten, Lawrence R. & Milgrom, Paul R., 1985. "Bid, ask and transaction prices in a specialist market with heterogeneously informed traders," Journal of Financial Economics, Elsevier, Elsevier, vol. 14(1), pages 71-100, March.
  21. Koopman, Siem Jan & Lucas, Andre & Monteiro, Andre, 2008. "The multi-state latent factor intensity model for credit rating transitions," Journal of Econometrics, Elsevier, Elsevier, vol. 142(1), pages 399-424, January.
  22. Robert F. Engle, 1996. "The Econometrics of Ultra-High Frequency Data," NBER Working Papers 5816, National Bureau of Economic Research, Inc.
  23. Bollerslev, Tim & Jubinski, Dan, 1999. "Equity Trading Volume and Volatility: Latent Information Arrivals and Common Long-Run Dependencies," Journal of Business & Economic Statistics, American Statistical Association, American Statistical Association, vol. 17(1), pages 9-21, January.
  24. Hentschel, Ludger, 1995. "All in the family Nesting symmetric and asymmetric GARCH models," Journal of Financial Economics, Elsevier, Elsevier, vol. 39(1), pages 71-104, September.
  25. Liesenfeld, Roman & Richard, Jean-Francois, 2003. "Univariate and multivariate stochastic volatility models: estimation and diagnostics," Journal of Empirical Finance, Elsevier, Elsevier, vol. 10(4), pages 505-531, September.
  26. BAUWENS, Luc & GALLi, Fausto & GIOT, Pierre, . "The moments of Log-ACD models," CORE Discussion Papers RP, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE) -2023, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  27. Liesenfeld, Roman, 2001. "A generalized bivariate mixture model for stock price volatility and trading volume," Journal of Econometrics, Elsevier, Elsevier, vol. 104(1), pages 141-178, August.
  28. Lamoureux, Christopher G & Lastrapes, William D, 1990. " Heteroskedasticity in Stock Return Data: Volume versus GARCH Effects," Journal of Finance, American Finance Association, American Finance Association, vol. 45(1), pages 221-29, March.
  29. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, Econometric Society, vol. 59(2), pages 347-70, March.
  30. Engle, Robert F & Ng, Victor K, 1993. " Measuring and Testing the Impact of News on Volatility," Journal of Finance, American Finance Association, American Finance Association, vol. 48(5), pages 1749-78, December.
  31. Jones, Charles M. & Kaul, Gautam & Lipson, Marc L., 1994. "Information, trading, and volatility," Journal of Financial Economics, Elsevier, Elsevier, vol. 36(1), pages 127-154, August.
  32. Epps, Thomas W & Epps, Mary Lee, 1976. "The Stochastic Dependence of Security Price Changes and Transaction Volumes: Implications for the Mixture-of-Distributions Hypothesis," Econometrica, Econometric Society, Econometric Society, vol. 44(2), pages 305-21, March.
  33. Tauchen, George E & Pitts, Mark, 1983. "The Price Variability-Volume Relationship on Speculative Markets," Econometrica, Econometric Society, Econometric Society, vol. 51(2), pages 485-505, March.
  34. Alfonso Dufour & Robert F. Engle, 2000. "Time and the Price Impact of a Trade," Journal of Finance, American Finance Association, American Finance Association, vol. 55(6), pages 2467-2498, December.
  35. Liesenfeld, Roman, 1998. "Dynamic Bivariate Mixture Models: Modeling the Behavior of Prices and Trading Volume," Journal of Business & Economic Statistics, American Statistical Association, American Statistical Association, vol. 16(1), pages 101-09, January.
  36. Fernandes, Marcelo & Grammig, Joachim, 2002. "A Family of Autoregressive Conditional Duration Models," Economics Working Papers (Ensaios Economicos da EPGE) 440, FGV/EPGE Escola Brasileira de Economia e Finanças, Getulio Vargas Foundation (Brazil).
  37. Easley, David, et al, 1996. " Liquidity, Information, and Infrequently Traded Stocks," Journal of Finance, American Finance Association, American Finance Association, vol. 51(4), pages 1405-36, September.
  38. Xu, Xiaoqing Eleanor & Wu, Chunchi, 1999. "The intraday relation between return volatility, transactions, and volume," International Review of Economics & Finance, Elsevier, Elsevier, vol. 8(4), pages 375-397, November.
  39. Koop, Gary & Pesaran, M. Hashem & Potter, Simon M., 1996. "Impulse response analysis in nonlinear multivariate models," Journal of Econometrics, Elsevier, Elsevier, vol. 74(1), pages 119-147, September.
  40. Thierry Ané & Hélyette Geman, 2000. "Order Flow, Transaction Clock, and Normality of Asset Returns," Journal of Finance, American Finance Association, American Finance Association, vol. 55(5), pages 2259-2284, October.
  41. Blume, Lawrence & Easley, David & O'Hara, Maureen, 1994. " Market Statistics and Technical Analysis: The Role of Volume," Journal of Finance, American Finance Association, American Finance Association, vol. 49(1), pages 153-81, March.
  42. Anat R. Admati, Paul Pfleiderer, 1988. "A Theory of Intraday Patterns: Volume and Price Variability," Review of Financial Studies, Society for Financial Studies, Society for Financial Studies, vol. 1(1), pages 3-40.
  43. Huang, Roger D. & Masulis, Ronald W., 2003. "Trading activity and stock price volatility: evidence from the London Stock Exchange," Journal of Empirical Finance, Elsevier, Elsevier, vol. 10(3), pages 249-269, May.
  44. Chan, Kalok & Fong, Wai-Ming, 2000. "Trade size, order imbalance, and the volatility-volume relation," Journal of Financial Economics, Elsevier, Elsevier, vol. 57(2), pages 247-273, August.
Full references (including those not matched with items on IDEAS)

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as in new window

Cited by:
  1. Hautsch, Nikolaus & Hess, Dieter E. & Veredas, David, 2011. "The impact of macroeconomic news on quote adjustments, noise, and informational volatility," CFR Working Papers 11-06, University of Cologne, Centre for Financial Research (CFR).
  2. Chen, Fei & Diebold, Francis X. & Schorfheide, Frank, 2013. "A Markov-switching multifractal inter-trade duration model, with application to US equities," Journal of Econometrics, Elsevier, Elsevier, vol. 177(2), pages 320-342.
  3. Groß-Klußmann, Axel & Hautsch, Nikolaus, 2009. "Quantifying high-frequency market reactions to real-time news sentiment announcements," CFS Working Paper Series 2009/31, Center for Financial Studies (CFS).
  4. Matteo Barigozzi & Christian T. Brownlees & Giampiero M. Gallo & David Veredas, 2014. "Disentangling Systematic and Idiosyncratic Dynamics in Panels of Volatility Measures," Econometrics Working Papers Archive, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti" 2014_02, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", revised Feb 2014.
  5. Groß-Klußmann, Axel & Hautsch, Nikolaus, 2011. "When machines read the news: Using automated text analytics to quantify high frequency news-implied market reactions," Journal of Empirical Finance, Elsevier, Elsevier, vol. 18(2), pages 321-340, March.
  6. Bodnar, Taras & Hautsch, Nikolaus, 2013. "Copula-based dynamic conditional correlation multiplicative error processes," CFS Working Paper Series 2013/19, Center for Financial Studies (CFS).

Lists

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

Statistics

Access and download statistics

Corrections

When requesting a correction, please mention this item's handle: RePEc:zbw:cfswop:200725. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (ZBW - German National Library of Economics).

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.