Modeling the coupled return-spread high frequency dynamics of large tick assets
Large tick assets, i.e. assets where one tick movement is a significant fraction of the price and bid-ask spread is almost always equal to one tick, display a dynamics in which price changes and spread are strongly coupled. We introduce a Markov-switching modeling approach for price change, where the latent Markov process is the transition between spreads. We then use a finite Markov mixture of logit regressions on past squared returns to describe the dependence of the probability of price changes. The model can thus be seen as a Double Chain Markov Model. We show that the model describes the shape of return distribution at different time aggregations, volatility clustering, and the anomalous decrease of kurtosis of returns. We calibrate our models on Nasdaq stocks and we show that this model reproduces remarkably well the statistical properties of real data.
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.:
- Onnela, Jukka-Pekka & Töyli, Juuso & Kaski, Kimmo, 2009. "Tick size and stock returns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(4), pages 441-454.
- Matthieu Wyart & Jean-Philippe Bouchaud & Julien Kockelkoren & Marc Potters & Michele Vettorazzo, 2008. "Relation between bid-ask spread, impact and volatility in order-driven markets," Quantitative Finance, Taylor & Francis Journals, vol. 8(1), pages 41-57.
- Rydén, Tobias & Teräsvirta, Timo & Åsbrink, Stefan, 1996.
"Stylized Facts of Daily Return Series and the Hidden Markov Model,"
SSE/EFI Working Paper Series in Economics and Finance
117, Stockholm School of Economics.
- Tobias Rydén & Timo Teräsvirta & Stefan Åsbrink, 1998. "Stylized facts of daily return series and the hidden Markov model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 13(3), pages 217-244.
- Fabien Guilbaud & Huyen Pham, 2011. "Optimal High Frequency Trading with limit and market orders," Working Papers hal-00603385, HAL.
- Engel, Charles & Hamilton, James D, 1990. "Long Swings in the Dollar: Are They in the Data and Do Markets Know It?," American Economic Review, American Economic Association, vol. 80(4), pages 689-713, September.
- Szabolcs Mike & J. Doyne Farmer, 2007.
"An empirical behavioral model of liquidity and volatility,"
- Mike, Szabolcs & Farmer, J. Doyne, 2008. "An empirical behavioral model of liquidity and volatility," Journal of Economic Dynamics and Control, Elsevier, vol. 32(1), pages 200-234, January.
- Zolt�n Eisler & Jean-Philippe Bouchaud & Julien Kockelkoren, 2012. "The price impact of order book events: market orders, limit orders and cancellations," Quantitative Finance, Taylor & Francis Journals, vol. 12(9), pages 1395-1419, September.
- Timmermann, Allan, 2000.
"Moments of Markov switching models,"
Journal of Econometrics,
Elsevier, vol. 96(1), pages 75-111, May.
- Laszlo Gillemot & J. Doyne Farmer & Fabrizio Lillo, 2006.
"There's more to volatility than volume,"
Taylor & Francis Journals, vol. 6(5), pages 371-384.
- Christian Y. Robert & Mathieu Rosenbaum, 2011. "A New Approach for the Dynamics of Ultra-High-Frequency Data: The Model with Uncertainty Zones," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 9(2), pages 344-366, Spring.
- L. Randall Wray & Stephanie Bell, 2004. "Introduction," Chapters, in: Credit and State Theories of Money, chapter 1 Edward Elgar.
- Bulla, Jan & Bulla, Ingo, 2006. "Stylized facts of financial time series and hidden semi-Markov models," Computational Statistics & Data Analysis, Elsevier, vol. 51(4), pages 2192-2209, December.
- Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-84, March.
- 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.
When requesting a correction, please mention this item's handle: RePEc:arx:papers:1310.4539. 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: (arXiv administrators)
If references are entirely missing, you can add them using this form.