An inflated multivariate integer count hurdle model: an application to bid and ask quote dynamics
In this paper we develop a model for the conditional inflated multivariate density of integer count variables with domain Zn. Our modelling framework is based on a copula approach and can be used for a broad set of applications where the primary characteristics of the data are: (i) discrete domain, (ii) the tendency to cluster at certain outcome values and (iii) contemporaneous dependence. These kind of properties can be found for high or ultra-high frequent data describing the trading process on financial markets. We present a straightforward method of sampling from such an inflated multivariate density through the application of an Independence Metropolis-Hastings sampling algorithm. We demonstrate the power of our approach by modelling the conditional bivari- ate density of bid and ask quote changes in a high frequency setup. We show how to derive the implied conditional discrete density of the bid-ask spread, taking quote clusterings (at multiples of 5 ticks) into account.
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Volume (Year): 26 (2011)
Issue (Month): 4 (06)
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- Diebold, Francis X & Gunther, Todd A & Tay, Anthony S, 1998. "Evaluating Density Forecasts with Applications to Financial Risk Management," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 863-83, November.
- Mullahy, John, 1986. "Specification and testing of some modified count data models," Journal of Econometrics, Elsevier, vol. 33(3), pages 341-365, December.
- Asger Lunde & Peter Reinhard Hansen, 2004. "Realized Variance and IID Market Microstructure Noise," Econometric Society 2004 North American Summer Meetings 526, Econometric Society.
- Roel Oomen, 2004.
"Properties of Bias Corrected Realized Variance Under Alternative Sampling Schemes,"
wp04-15, Warwick Business School, Finance Group.
- Roel C. A. Oomen, 2005. "Properties of Bias-Corrected Realized Variance Under Alternative Sampling Schemes," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 3(4), pages 555-577.
- Neil Shephard, 1995. "Generalized linear autoregressions," Economics Papers 8., Economics Group, Nuffield College, University of Oxford.
- Gleason, Kimberly C. & Lee, Chun I. & Mathur, Ike, 2000. "An explanation for the compass rose pattern," Economics Letters, Elsevier, vol. 68(2), pages 127-133, August.
- Christie, William G & Harris, Jeffrey H & Schultz, Paul H, 1994. " Why Did NASDAQ Market Makers Stop Avoiding Odd-Eighth Quotes?," Journal of Finance, American Finance Association, vol. 49(5), pages 1841-60, December.
- A. Colin Cameron & Tong Li & Pravin K. Trivedi & David M. Zimmer, 2004.
"Modeling the Differences in Counted Outcomes using Bivariate Copula Models: with Application to Mismeasured Counts,"
43, University of California, Davis, Department of Economics.
- A. Colin Cameron & Tong Li & Pravin K. Trivedi & David M. Zimmer, 2004. "Modelling the differences in counted outcomes using bivariate copula models with application to mismeasured counts," Econometrics Journal, Royal Economic Society, vol. 7(2), pages 566-584, December.
- Amilon, Henrik, 2003. "GARCH estimation and discrete stock prices: an application to low-priced Australian stocks," Economics Letters, Elsevier, vol. 81(2), pages 215-222, November.
- Christie, William G & Schultz, Paul H, 1994. " Why Do NASDAQ Market Makers Avoid Odd-Eighth Quotes?," Journal of Finance, American Finance Association, vol. 49(5), pages 1813-40, December.
- Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 1999. "(Understanding, Optimizing, Using and Forecasting) Realized Volatility and Correlation," New York University, Leonard N. Stern School Finance Department Working Paper Seires 99-061, New York University, Leonard N. Stern School of Business-.
- Kramer, Walter & Runde, Ralf, 1997. "Chaos and the compass rose," Economics Letters, Elsevier, vol. 54(2), pages 113-118, February.
- Antonios Antoniou & Constantinos E. Vorlow, 2004. "Price Clustering and Discreteness: Is there Chaos behind the Noise?," Papers cond-mat/0407471, arXiv.org.
- Patton, Andrew J, 2001. "Modelling Time-Varying Exchange Rate Dependence Using the Conditional Copula," University of California at San Diego, Economics Working Paper Series qt01q7j1s2, Department of Economics, UC San Diego.
- Fang, Yue, 2002. "The compass rose and random walk tests," Computational Statistics & Data Analysis, Elsevier, vol. 39(3), pages 299-310, May.
- Constantinos E. Vorlow, 2004. "Stock Price Clustering and Discreteness: The "Compass Rose" and Predictability," Papers cond-mat/0408013, arXiv.org.
- Hasbrouck, Joel, 1999. "Security bid/ask dynamics with discreteness and clustering: Simple strategies for modeling and estimation1," Journal of Financial Markets, Elsevier, vol. 2(1), pages 1-28, February.
- Brock, W.A. & Dechert, W.D. & LeBaron, B. & Scheinkman, J.A., 1995. "A Test for Independence Based on the Correlation Dimension," Working papers 9520, Wisconsin Madison - Social Systems.
- Szpiro, George G., 1998. "Tick size, the compass rose and market nanostructure," Journal of Banking & Finance, Elsevier, vol. 22(12), pages 1559-1569, December.
- Hansen, Peter R. & Lunde, Asger, 2006. "Realized Variance and Market Microstructure Noise," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 127-161, April.
- Antoniou, Antonios & Vorlow, Constantinos E., 2005. "Price clustering and discreteness: is there chaos behind the noise?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 348(C), pages 389-403.
- Ball, Clifford A, 1988. " Estimation Bias Induced by Discrete Security Prices," Journal of Finance, American Finance Association, vol. 43(4), pages 841-65, September.
- Harris, Lawrence, 1991. "Stock Price Clustering and Discreteness," Review of Financial Studies, Society for Financial Studies, vol. 4(3), pages 389-415.
- Huang, Roger D & Stoll, Hans R, 1994. "Market Microstructure and Stock Return Predictions," Review of Financial Studies, Society for Financial Studies, vol. 7(1), pages 179-213.
- Roman Liesenfeld & Ingmar Nolte & Winfried Pohlmeier, 2006. "Modelling financial transaction price movements: a dynamic integer count data model," Empirical Economics, Springer, vol. 30(4), pages 795-825, January.
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