PhD Seminar in Market Microstructure

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FINC-GB.4192.01 Fall Semester 2011
Stern School of Business, NYU

Professor Joel Hasbrouck
jhasbrou@stern.nyu.edu
http://pages.stern.nyu.edu/~jhasbrou

The class meets T, Th 1:30-3:00 in KMEC 5-75. This is a half-credit course. The first meeting is Tuesday, September 6; the last meeting is Thursday, October 20. There is no class on Thursday, September 29.

The deliverables are the empirical market data exercises (see below) and the final problem set.

Overview

Market microstructure is the subfield of financial economics that deals with the trading mechanisms used for securities. Most of the equilibrium and no-arbitrage results in finance are predicated on the possibility of trade. With real-world mechanisms, though, trading is costly. These costs affect portfolio formation and the pricing of assets. By changing or regulating the mechanism, it may be possible to prevent market failures, reduce trading costs and move closer to first-best equilibria. Moreover, some component of the trading cost is informational. The joint dynamics of prices and trades can yield insights into information that are otherwise difficult to obtain. This course is a survey of modern trading institutions and the economic lines of thought that have proven useful in understanding them.

This is a seminar course and I'll be guiding you through some of the key papers in the field. The deliverables will include a final problem set and an empirical project (see marketDataAnalysis).

Readings

The text for the course is my book Empirical Market Microstructure. New York, Oxford University Press (EMM).

Useful background books in microstructure include:

• Harris, L. E. (2003). Trading and Exchanges. New York, Oxford University Press.
• O'Hara, M. (1995). Market Microstructure Theory. Cambridge, MA, Blackwell Publishers.

Books that cover econometric techniques useful in market microstructure include:

• Durbin, J. and S. J. Koopman (2001). Time Series Analysis by State Space Methods, Oxford University Press.
• Hamilton, J. D. (1994). Time Series Analysis. Princeton, Princeton University Press.
• Hautsch, N. (2004). Modelling Irregularly Spaced Financial Data: Theory and Practice of Dynamic Duration Models, Springer.

Other resources

I recently taught an MBA class (Financial Markets: Structures and Dynamics). This class was shorter, and did not dwell on the economic and statistical properties of market data. But it did cover institutions in some detail. The class web site is at: Financial Markets: Structure and Dynamics.

Topics

Introduction

• The principal themes in market microstructure.
• Class notes, 6 September 2011.

Structural and statistical univariate microstructure models.

• The Roll (1986) model
• EMM, Ch. 3 and 4
• Class notes, 8 September 2011

Sequential trade models of asymmetric information

• EMM Ch. 5 and 6
• Class notes, 13 September 2011
• Spreadsheet SimpleSequentialTradeModel02.xls

Continuous auction (strategic trade) models

• EMM Ch. 7
• Class notes, 15 September 2011
• analyzeTrades (market data program);

The generalized Roll model

• EMM Ch. 8
• Class Notes, 20 September 2011: RollBasicAndGeneralized.
• See the SAS program SimGenRoll (and related files) in the FTP directory

Multivariate microstructure models

• EMM Ch. 9
• Class notes, 22 September 2011: MultivariateMicrostructureModels dpRegression

Cointegrated microstructure models

• EMM Ch. 10

Experimental Markets

• Tuesday, October 4. In-class games on VECONLAB

Limit order markets

• Thursday, October 6
• EMM Chapters 12 & 13
• References are contained in the class notes: LimitDepthI and LimitDepthII

Liquidity and asset pricing

Notes: Liquidity and asset pricing part 1 part 2

Bayesian estimation of microstructure models

• Hasbrouck, J. (2009). Trading costs and returns for US equities: estimating effective costs from daily data. Journal of Finance 64(3): 1445-1477 DOI link: http://dx.doi.org/10.1111/j.1540-6261.2009.01469.x
•  Lesmond, D. A., J. P. Ogden and C. A. Trzcinka (1999). A new estimate of transactions costs. Review of Financial Studies 12(5): 1113-1141 URL: http://www.jstor.org/stable/2645977.

Background

Books on Bayesian estimation

• Geweke, J. (2005). Contemporary Bayesian Statistics and Econometrics. New York, John Wiley and Sons.
• Lancaster, T. (2004). An Introduction to Modern Bayesian Econometrics. Malden, MA, Blackwell Publishing.

Useful articles

• Casella, G. and E. I. George (1992). Explaining the Gibbs Sampler. The American Statistician 46(3): 167-174 URL: http://www.jstor.org/stable/2685208.
• Chib, S. and E. Greenberg (1995). Understanding the Metropolis-Hastings Algorithm. The American Statistician 49(4): 327-335 URL: http://www.jstor.org/stable/2684568.