Private Information and High-Frequency Stochastic Volatility
AbstractWe study the eÂ®ect of privately informed traders on measured high frequency price changes and trades in asset markets. We use a standard market microstructure framework where exogenous news is captured by signals that informed agents receive. We show that the entry and exit of informed traders following the arrival of news accounts for high-frequency serial correlation in squared price changes (stochastic volatility) and grades. Because the bid-ask spread of the market specialist tends to shrink as individuals trade and reveal their information, the model also accounts for the empirical observation that high-frequency serial correlation is more pronounced in trades than in squared price changes. A calibration test of the model shows that the features of the market microstructure, without serially correlated news, accounts qualitatively for the serial correlation in the data, but predicts less persistence than is present in the data.
Download InfoIf 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.
Bibliographic InfoPaper provided by Department of Economics, UC Santa Barbara in its series University of California at Santa Barbara, Economics Working Paper Series with number qt00n4h4mw.
Date of creation: 01 Aug 2003
Date of revision:
Contact details of provider:
Postal: 2127 North Hall, Santa Barbara, CA 93106-9210
Phone: (805) 893-3670
Fax: (805) 893-8830
Web page: http://www.escholarship.org/repec/ucsbecon_dwp/
More information through EDIRC
Other versions of this item:
- Kelly David L. & Steigerwald Douglas G, 2004. "Private Information and High-Frequency Stochastic Volatility," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 8(1), pages 1-30, March.
- D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
- G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
- G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
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.:
- Jamsheed Shorish & Stephen Spear, .
"Shaking the Tree: An Agency Theoretic Model of Asset Pricing,"
GSIA Working Papers
2003-E19, Carnegie Mellon University, Tepper School of Business.
- Jamsheed Shorish & Stephen E. Spear, 2005. "Shaking the tree: an agency-theoretic model of asset pricing," Annals of Finance, Springer, vol. 1(1), pages 51-72, 01.
- John Owens & Douglas G. Steigerwald, 2005. "Inferring Information Frequency and Quality," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 3(4), pages 500-524.
- Haan, Wouter J. den & Spear, Scott A., 1998. "Volatility clustering in real interest rates Theory and evidence," Journal of Monetary Economics, Elsevier, vol. 41(3), pages 431-453, May.
- Tauchen, George E & Pitts, Mark, 1983. "The Price Variability-Volume Relationship on Speculative Markets," Econometrica, Econometric Society, vol. 51(2), pages 485-505, March.
- William A. Brock & Blake D. LeBaron, 1995.
"A Dynamic Structural Model for Stock Return Volatility and Trading Volume,"
NBER Working Papers
4988, National Bureau of Economic Research, Inc.
- Brock, William A & LeBaron, Blake D, 1996. "A Dynamic Structural Model for Stock Return Volatility and Trading Volume," The Review of Economics and Statistics, MIT Press, vol. 78(1), pages 94-110, February.
- French, Kenneth R. & Roll, Richard, 1986. "Stock return variances : The arrival of information and the reaction of traders," Journal of Financial Economics, Elsevier, vol. 17(1), pages 5-26, September.
- Robert F. Engle & Victor Ng & Michael Rothschild, 1988.
"Asset Pricing with a Factor Arch Covariance Structure: Empirical Estimates for Treasury Bills,"
NBER Technical Working Papers
0065, National Bureau of Economic Research, Inc.
- Engle, Robert F. & Ng, Victor K. & Rothschild, Michael, 1990. "Asset pricing with a factor-arch covariance structure : Empirical estimates for treasury bills," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 213-237.
- Goodhart, Charles A. E. & O'Hara, Maureen, 1997. "High frequency data in financial markets: Issues and applications," Journal of Empirical Finance, Elsevier, vol. 4(2-3), pages 73-114, June.
- Andersen, Torben G, 1996. " Return Volatility and Trading Volume: An Information Flow Interpretation of Stochastic Volatility," Journal of Finance, American Finance Association, vol. 51(1), pages 169-204, March.
- Epps, Thomas W, 1975. "Security Price Changes and Transaction Volumes: Theory and Evidence," American Economic Review, American Economic Association, vol. 65(4), pages 586-97, September.
- 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, vol. 14(1), pages 71-100, March.
- Lawrence R. Glosten & Paul R. Milgrom, 1983. "Bid, Ask and Transaction Prices in a Specialist Market with Heterogeneously Informed Traders," Discussion Papers 570, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
- 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.
- Clark, Peter K, 1973. "A Subordinated Stochastic Process Model with Finite Variance for Speculative Prices," Econometrica, Econometric Society, vol. 41(1), pages 135-55, January.
- Harris, Lawrence, 1986. "A transaction data study of weekly and intradaily patterns in stock returns," Journal of Financial Economics, Elsevier, vol. 16(1), pages 99-117, May.
- 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.
- Yoichi Otsubo & Bruce Mizrach, 2012.
"The Market Microstructure of the European Climate Exchange,"
LSF Research Working Paper Series
12-7, Luxembourg School of Finance, University of Luxembourg.
- Mizrach, Bruce & Otsubo, Yoichi, 2014. "The market microstructure of the European climate exchange," Journal of Banking & Finance, Elsevier, vol. 39(C), pages 107-116.
- Bruce Mizrach & Yoichi Otsubo, 2010. "The Market Microstructure of the European Climate Exchange," Departmental Working Papers 201005, Rutgers University, Department of Economics.
- Jonathan H. Wright, 2000.
"Log-periodogram estimation of long memory volatility dependencies with conditionally heavy tailed returns,"
International Finance Discussion Papers
685, Board of Governors of the Federal Reserve System (U.S.).
- Jonathan Wright, 2002. "Log-Periodogram Estimation Of Long Memory Volatility Dependencies With Conditionally Heavy Tailed Returns," Econometric Reviews, Taylor & Francis Journals, vol. 21(4), pages 397-417.
- Booth, G. Geoffrey & Gurun, Umit G., 2008. "Volatility clustering and the bid-ask spread: Exchange rate behavior in early Renaissance Florence," Journal of Empirical Finance, Elsevier, vol. 15(1), pages 131-144, January.
- Steigerwald, Doug & Vagnoni, Richard J., 2001. "Option Market Microstructure and Stochastic Volatility," University of California at Santa Barbara, Economics Working Paper Series qt1v2059c2, Department of Economics, UC Santa Barbara.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Lisa Schiff).
If references are entirely missing, you can add them using this form.