Craig W. Holden


BU 356C

Office Hours:

Tues-Thurs 2:30-4:00 or feel free to drop by any time!

Office Phone:



Holden web site:

Career Resources:




Welcome to both the theory and empirical analysis of market microstructure!  Market microstructure is a relatively young subdiscipline in finance, yet it has grown rapidly into one of the largest subdisciplines. It has had a profound impact both on the real world and on the academic profession. Indiana University has had a strong tradition in market microstructure in the 1990’s and 2000’s.


I have set three goals for students in this class:

1.      develop a fundamental knowledge of both the theory and empirical analysis of market microstructure,

2.      develop key modeling and empirical design skills by actively using them, and

3.      develop academic writing skills and presentation skills by actively using them.




My approach to teaching involves three key features:


1.      Assignment Preparation. For each class session, there are assigned readings. You are expected to read all of the assigned readings before class.


2.      Class Participation. You are expected to be ready to lead the class discussion on any part of the assigned reading and to generally participate in the class discussion. Some of the time I will ask for volunteers to lead the class discussion and other times I will cold-call students to insure that everyone participates. This is an “active learning” approach, where students are the primary source of classroom learning and interaction.


3.      Learn By Doing. The best way to learn how to do research is to actually do research. The best way to learn how to present your research to others is to actually present your research to others. Therefore, you are expected to do an original research paper and to do a class presentation of your research.






Session Theme and Topics


Assignment Preparation

(1.) Jan 16a, Introduction

·         Syllabus

·         Security Traders and Market Makers

·         Overview to Microstructure Data

·         Downloading TAQ Data using WRDS


Lightly: An Overview of Microstructure Data, NBBO Example

Assignment: F635 Assignment 1: WRDS Web-Form Downloading of Monthly TAQ Data

(2.) Jan 16b, TAQ, NBBO, and Liquidity Measures

·         Using SAS to Access TAQ and Compute the NBBO and Liquidity Measures

·         Liquidity Measures


In depth: Holden and Jacobsen SAS Code for NBBO and Liquidity Measure Computation Update (the docx file is a copy of sas file), F635 Liquidity Measures

Assignment: F635 Assignment 2: WRDS SAS Connect Downloading of Monthly TAQ Data


(3.) Jan 23a, Trade Typing

·         Trade Typing

·         Timing Specifications


In depth: Lee and Ready (1991)

Lightly: Henker and Wang (2006), Pages 162-170


(4.) Jan 23b, Liquidity Measurement Problems

·         Liquidity Measurement Problems


In depth: Holden and Jacobsen (2013)


(5.) Jan 30a, Developing Trends

·         Equity Trading in the 21st Century


In depth: Angel, Harris, and Spatt (2011)



(6.) Jan 30b, The PIN Model

·         The PIN Model

·         Many PIN Applications


In depth: Easley, Kiefer, O’Hara, and Paperman (1996), Pages 1405-1422, Easley, Kiefer, and O’Hara (1997b), Pages 821-822

Lightly: PIN Application Sampler


(7.) Feb 6a, Information Shares

·         Price Discovery by Regional Exchanges

·         Price Discovery in Stock and Option Markets

·         Price Discovery in Stock and Corporate Bond Markets


In depth: Hasbrouck (1995)

Lightly: Chakravarty, Gulen, and Mayhew (2004), Pages 1235, 1241-1246, Mao (2012), Pages 0, 8, 13-15, 33-35


(8.) Feb 6b, Finnish Data and LOB Construction

·         Sensation seeking and overconfidence

·         IQ and performance

·         Constructing the Limit Order Book


In depth: Grinblatt and Keloharju (2009), Pages 549-569, Grinblatt, Keloharju, and Linnainmaa (2012), Pages 339-351

Lightly: Kavajecz (1999), Pages 749-752

(9.) Feb 13a, Matched Samples

·         Testing for Cost Differences


In depth: Davies and Kim (2009)


(10.) Feb 13b, Commonality

·         Kickoff Discussion of Original Research Paper

·         Commonality in Liquidity

·         A Global Perspective

In depth: Chordia, Roll, and Subrahmanyam (2000), Pages 3-15, 24-26, Brockman, Chung, and Perignon (2009), Pages 851-863, 877



(11.) Feb 20a, Discussion of Student-Selected Empirical Articles



(12.) Feb 20b, The Flash Crash

·         The Flash Crash

·         The Impact of High Frequency Trading

In depth: Joint Final Report on the Flash Crash (2010) Pages 1-8, Flash Crash Reports (2010).pptx (PowerPoint slides), Kirilenko, Kyle, Samadi, and Tuzun (2011), Pages 1-5, 10-16, 41-43, 49-62


(13.) Feb 25, Low-Frequency Liquidity Proxies

·         Global Stock Liquidity

·         Bid-Ask Bounce and the Effective Spread


In depth:, Fong, Holden, and Trzcinka (2013), Roll (1984), Pages 1127-1130, 1135-1137

(14.) Feb 27 Corporate Bonds

·         Impact of TRACE on trading costs

·         Exchange vs. OTC trading


In depth: Bessembinder, Maxwell, and Venkataraman (2006), Pages 251-254, 257, 260-280

Lightly: Biais and Green (2007), Pages 1-5, 17-29, 35-37, Figures 1-7


(15.) March 4, Options

·         Multiple Listing and Designated Primary MarketMaker (DPM): Pre-reform Evidence

·         Toward a National Market System


In depth: Mayhew (2002), Pages 931-950, Tables VI – VII, Figures 5-7

Lightly: Battalio, Hatch, and Jennings (2004), Pages 933-936, 943-955


(16.) March 6, Liquidity-adjusted CAPM

·         World Price of Liquidity Risk


In depth: Lee (2011)


(17.) March 11, Behavioral Empirics

·         Buy-sell imbalances on and around round numbers

·         Trading in attention-grabbing stocks


In depth: Bhattacharya, Holden, and Jacobsen (2012), Barber and Odean (2008), Pages 785-789, 797, 800, 802, 804, 806



(18.) March 13, The Experimental Approach

·         How Noise Trading Affects Markets

·         The Make or Take Decision


In depth: Bloomfield, O’Hara, and Saar (2009), Pages 2275-2296, Bloomfield, O’Hara, and Saar (2005), Pages 165-168, 171-188

Spring Break



(19.) March 25, Spread Decomposition

·         Live Exercise in Designing an Empirical Study

·         An Integrated Spread Decomposition Method


In depth: Huang and Stoll (1997), Pages 995-1020


(20.) March 27, Analysis of Order Data

·         Order Dynamics

·         Impact of Opening Up the NYSE LOB

In depth: Ellul, Holden, Jain and Jennings (2007)

Lightly: Boehmer, Saar, and Yu (2005), Pages 783-806



Session Theme and Topics


Assignment Preparation

(21.) April 1, The Single-Period Kyle Model

·         The single-period model


In depth: Kyle (1985), Pages 1315-1320


(22.) April 3, The Multi-Period Kyle Model

·         The multiperiod-period model


In depth: Kyle (1985), Pages 1320-1328, 1334-1335


(23.) April 8, Kyle Extensions and Applications

·         Many informed traders

·         Basket securities


In depth Extension: Holden and Subrahmanyam (1992), Pages 247-262

In depth Application: Subrahmanyam (1991), Pages 17-33, 39

Lightly: F635 Extentions of the Kyle Model


(24.) April 10, Inventory

·         Aversion to inventory risk

·         Arbitrage trading


In depth: Grossman and Miller (1988), Pages 617-619, 622-628

Lightly: Holden (1995), Pages 423-435


(25.) April 15, Limit Order Models

·         Dynamic Limit Order Book

·         Numerical Dynamic Limit Order Book


In depth: Parlour (1998), Pages 789-800

Lightly: Goettler, Parlour, and Rajan (2005), Pages 2149-2161, 2165-2168

(26.) April 17, Optimal Trading Strategy

·         Optimal Trading with Limit Orders on a Dynamic Limit Order Book


In depth: Holden (2013)

(27.) April 22, Research Paper Presentations

·         23-Minute Presentations and 2 Minute Class Discussions



(28.) April 24, Discussion of Student-Selected Theory Articles



(29.) April 29, Market Liquidity and Funding Liquidity

·         Market Liquidity and Funding Liquidity


In depth: Brunnermeier and Pedersen (2009)

(30.) May 1, Behavioral Theory

·         Live Exercise in Designing a Theoretical Study

·         Overconfidence and Attribution Bias

·         The Psychological Theory That Underlies Behavioral Finance


In depth: Daniel, Hirshleifer, Subrahmanyam (1998), Pages 1839-1855

Lightly: Barberis and Thaler (2002), Pages 1, 11-21


(31.) May 6, Orignial Research Paper

·         Round 3 Original Research Paper and Response to the Referee is due at 5:00 p.m.







1.      Grading is done on a curve based on total points for the course. The following items are graded:





Kick Off

Due Date

Assignment 1

Assignment 2

25 points

25 points







Class Participation in the First Half

Class Participation in the Second Half

100 points

100 points







Original Research Paper:

·           Presentation Quality . . . . . .

·           Academic Writing Quality . .

·           Substantive Quality . . . . . . .


  50 points

  75 points

 125 points






Feb 13


May 6, 5:00 pm

Total Points

500 points





2.      I expect you to participate in the class discussion. I record class participation for each student immediately after class.




You are asked to lead two 25-minute class discussions while sitting in your chair (i.e., no PowerPoint) of published or forthcoming articles in market microstructure: an empirical article on February 20 and a theoretical article on April 24. The articles must have been published in the years 2008 to the present or currently be forthcoming in an elite, top-tier finance journal (JF, JFE, RFS, and JFQA) or in the Journal of Financial Markets.


25 minutes is a short amount of time. You need to focus on the big picture. You need to cover the overall motivation, key assumptions, and key results / intuitions. Don't get bogged down in the details and derivations. This is not a presentation, so PowerPoint is not permitted. Instead, you will lead the class discussion from your chair and I will show key article pages on the screen.


Article discussion sign-ups will begin on February 6 after class for the empirical article and April 10 after class for the theoretical article. Please supply a PDF file of each requested article in its final published form from the journal web site (not in its working paper form). Sign-ups will be first-come, first served. The PDF file of each selected article will be distributed to the entire class. Students are expected to give each selected article at least a 20 minute “quick read” prior to the class discussion. A quick read means completely reading the introduction and then selectively reading key parts, such as the assumptions, figures, propositions, data description, or tables.




I have created four zip files containing F635 class reading materials, data documentation, practitioner analysis (Credit Suisse, Rosenblatt, and Goldman Sach’s “Street Smart”), SAS programs, TORQ data, TORQ access programs, career resources, and my library of microstructure articles. These zip files can be downloaded by logging into Oncourse ( and then clicking on the F635 tab, the Resources link, and the individual zip files.





You are to develop an original research paper following the three round process listed below.


Round 1.   Identify one of the papers on the course syllabus (you may skip ahead to one of the papers we have not yet covered) and brainstorm two-to-three possible extensions that could be made to the model or the empirical analysis. The round 1 write-up (limit of one page write-up per extension – can be handwritten if you wish) should specify for each possible extension:

·         what the extension is

·         what is the motivation – why is this an interesting extension?

·         what key result you hope to obtain - what is new? what is surprising?  (Results sell  papers.)

·         the result’s theoretical significance (if any),

·         the result’s empirical significance (if any),

·         the result’s practical significance (if any),

·         the extension’s feasibility, and

·         the extension’s degree of difficulty.


Response 1.  Drop by my office and we will discuss the merits of each possible extension.


Round 2. Do your research. Write up it up in the standard format of an academic paper. The body of the paper (excluding the title page, appendices, tables, or figures) is limited to 10 double-spaced pages with normal size font and one-inch margins all around. The literature review is limited to 1 page in the introduction. Journal space is very limited, so it is a good habit to learn to write your papers with a very tight, efficient use of space.


For empirical work, keep the sample size small and manageable. Microstructure datasets can be huge and there is limited time in the semester. Please spend most of your time analyzing a manageable sample, rather than getting bogged down in bulk processing a giant / unmanagable sample. Let me suggest viewing this project as a pilot study. If you get interesting results on a small scale and wish to pursue it, then you can expand the sample to full size when the course is over.


Submit your paper twice: (1) as a PDF file to and (2) as a Microsoft Word file to the Assignments tab of F635 on Oncourse. If you use Latex, just copy and paste the Tex file into Microsoft Word. Do not use special characters in your file name, such as: \ / ? * “ : < > # % =. The Microsoft Word file will immediately be submitted to the anti-plagiarism tool called Turnitin. This tool will check your paper against everything posted on the internet and against all prior papers submitted at IU and will produce a similarity score for your paper.


Your write up should include:

·         a title page, including the abstract

·         an introduction with motivation and intuition

·         a very brief literature review - focus on the one or two papers that are the most directly relevant

·         to your extension - I want you to focus your effort on your extension and not on reading extra articles.

·         explain hypotheses you are going to test (if empirical)

·         data you are using and ways you cleaned-up the data (if empirical)

·         results in tables (can be in the body or in the back) (if empirical)

·         interpretations of results (if empirical)

·         step-by-step develop and explain the model (if theoretical) -- explain each idea once in math and a second time in words

·         flag key assumptions and results (if theoetical)

·         optional: comparative statics and other ways to milk the model / design for all it is worth (if theoretical)

·         list of possible directions for future research

·         a brief conclusion.


Class Presentation.  Develop a 23 minute, PowerPoint presentation for the class, which will be followed by a 2 minute discussion. Your presentation should explain:

·         what your are research question(s),

·         what is the movtivation for this line of research,

·         what are hypotheses are you going to test (if empirical),

·         what data are you using (if empirical),

·         what are your results to date, and

·         what are your key interpretations / intuitions for your results.

On the presentation date, please come to class a few minutes early and copy your presentation to the Windows Desktop of the classroom computer.


Response 2.   I will add comments on both the substance and exposition in your paper. I will send you an email that I have read your report and asking you to stop by my office. In my office I will provide additional explanation of my comments.


Round 3.   Incorporate a response to my comments. Add any additional results and polish the exposition. Write a one-page "response to the referee" report explaining with terse bullet points how you have responded to my comments and what additional items have been added. Submit your final verision and your response to the referee report as PDF files to You do NOT need to submit round 3 materials to the Assignments tab of Oncourse. Your grade for the research paper substance and academic writing will be based on the Round 3 paper and response to the referee report. 


Important Dates.

March 6

The Round 1 write-up is due.

March 10, 11, or 12

Drop by my office to discuss the merit of each possible extension.

Sunday, April 20 (early submissions are welcome)

The Round 2 PDF paper submission is due.

April 22

Twenty-three minute presentation of your research to the class.

May 6, 5:00 p.m.

The Round 3 PDF paper and response to the referee report submissions are due.




·         Plagiarism is obvious. When a paper is 10 times more sophisticated that what a first or second year doctoral would produce, it is obvious. When a paper’s writing style is 10 times more polished compared that what a first or second year would produce, it is obvious. When a paper uses perfect English grammar compared to what a non-native English speaker would produce, it is obvious.

·         Plagiarism is easy to verify. The Turnitin tool will easily identify plagiarism. But outside of this class, one just has to take a unique sentence from the paper, type it into Google in quotes, and you will instantly get the plagiarized document. The entire published literature, all books, and all working papers are online. So everything worth plagiarizing is in Google’s index.

·         The penalties for plagiarism are severe. Anyone I catch will get an “F” in this class and, most likely, you would be dismissed from the doctoral program.

·         If you are in trouble, talk with me. The most likely context for plagiarism is that someone gets to a deadline and has nothing to turn in. I will understand your situation and will work with you. In the big picture, it is far better to get a lousy grade in one class than to blow-up your career.




WRDS: WRDS Databases, Ways to Use WRDS, The WRDS Microstructure Cloud Manual


Monthly TAQ: TAQ Users Guide 10-2008 edition, TAQ SAS Programming Issues, TAQ Trades Example, TAQ Quotes Example


Daily TAQ: NYSE Daily TAQ Newsletter Announcement, Overview of TAQ and Microstructure Data Platform Daily, TAQ Client Spec v1.0


TORQ: Hasbrouck (1992), Hasbrouck, Sofianos, and Sosebee (1993)


NASDAQ ITCH: NASDAQ TotalView-ITCH Version 4.1 Manual


SEC Disclosure Rules: Summary of New SEC Disclosure Rules


Thomson Reuters Tick History (TRTH): Thomson Reuters Tick History (2010)


Datastream: Datastream: Handle with Care!


TRACE: TRACE User Guide Version 2.0 2008, Dick-Nielsen (2013)


Berkeley Options: Users Guide (1998), Rubinstein and Vijh (1987)




Easley, Kiefer, and O’Hara (1997b) Pg 805, 812, 820, 829;

Easley, Kiefer, and O’Hara, (1996) Pg. 811, 817;

Easley, Kiefer, and O’Hara, (1997a) Pg 159, 167;

Easley, O’Hara, and Paperman (1998) Pg 175;

Easley, O’Hara, and Srinivas (1998) Pg 431, 437-438;

Easley, O’Hara, Saar (2001) Pg 25, 36;

Easley, Hvidkjaer, and O’Hara (2002) Pg 2185;

Easley, Hvidkjaer, and O’Hara (2005) Pg 0;

Lei and Wu (2005) Pg 153, 162;

Agudelo (2006) Pg 1, 11, 39;

Boehmer, Grammig, and Theissen (2006) Pg 0, 23;

Vega (2006), Pg 103, 109;

Kaul, Lei, and Stoffman (2008) Pg 0, 4-5;

Easley, Engle, O’Hara, Wu (2008) Pg 171, 192, 199;

Lei (2010) Pg 0, 12;

Wei, Lin, and Ke (2011) Pg 625;

Akay, Cyree, Griffiths, and Winters (2011) Pg 29;
Zhang (2013) Pg 4, 21, 23.




O’Hara, M., 1998, Market Microstructure Theory, published by Blackwell Publishing Professional


Harris, L., 2003, Trading and Exchanges: Market for Practitioners, published by Oxford University Press


Hasbrouck, J., 2007, Empirical Market Microstructure: The Institutions, Economics, and Econometrics of Security Trading, published by Oxford University Press


Lhabitant, F. and F. Gregoriou, 2007, Stock Market Liquidity, published by John Wiley and Sons, Inc.


Vives, X., 2008, Information and Learning in Markets: The Impact of Market Microstructure, published by Princeton University Press


Kallunki, J., J. Broussard, and E. Boehmer, 2002, Using SAS in Financial Research, published by SAS Press.


Johnson, B., 2010, Algorithmic Trading & DMA, published by 4Myeloma Press


Teall, J., 2013, Financial Trading and Investing, published by Academic Press


Foucault, T., Pagano, M., and Roell, A., 2013, Market Liquidity, Theory, Evidence, and Policy, published by Oxford University Press




Easley, D. and M. O’Hara, 1995, Market Microstructure, in the Handbook of Finance, edited by R.A. Jarrow, V. Maksimovic, and W. T. Ziemba, in the Handbooks in Operations Research and Management Science, North Holland Press.


Calamia, A., 1999, Market Microstructure: Theory and Empirics, University of Rome working paper


Madhavan, A., 2000, Market Microstructure: A Survey, Journal of Financial Markets 3, 205-258.


Stoll, H., 2003, Market Microstructure, Handbook of the Economics of Finance, edited by G.M. Constantinides, M. Harris, and R. Stulz, Elsevier Science B.V.


Biais, B., L. Glosten, and C. Spatt, 2005, Market Microstructure: A Survey of Microfoundations, Empirical Results, and Policy Implications, Journal of Financial Markets 8, 217-264.


Amihud, Y., Mendelson, H., and Pedersen, L., 2006, Liquidity and Asset Prices, Foundations and Trends in Finance 1, 269-364.


Gould, M., M. Porter, S. Williams, M. McDonald, D. Fenn, and Howison, 2011, Limit Order Books, Quantitative Finance, arXiv:1012.0349v2


Vayanos, D. and Wang, J., 2012, Theories of Liquidity, Foundations and Trends in Finance 4, 221-317.


Jones, C., 2013, What Do We Know About High-Frequency Trading? Columbia University working paper.




The Little SAS Book, Fourth Edition, Lora Delwiche and Susan Slaughter, 2008, SAS Press.





Agudelo, D., 2006, Home Advantage vs. Big Fish Effect. Do Local or Foreign Traders Know More About the Indonesian Market?, working paper, Indiana University.


Akay, O., K. Cyree, M. Griffiths, and D. Winters, 2011, What Does PIN Identify? Journal of Financial Markets, 15, 29-46.


Angel, J., L. Harris, and C. Spatt, 2011, Equity Trading in the 21st Century, Quarterly Journal of Finance 1, 1-53.


Barber B. and T. Odean, 2000, Trading is Hazardous to Your Wealth: The Common Stock Investment Performance of Individual Investors, Journal of Finance, 55, 773-806.


Barber B. and T. Odean, 2001, Boys Will Be Boys: Gender, Overconfidence, and Common Stock Investment, Quarterly Journal of Economics 261-292.


Barber B. and T. Odean, 2002, Online Investors: Do the Slow Die First?, Review of Financial Studies 15, 455-487.


Barber B. and T. Odean, 2008, All That Glitters: The Effect of Attention and News on the Buying Behavior of Individual and Institutional Investors, Review of Financial Studies, 21, 785-818.


Barberis, N. and R. Thalor, 2002, A Survey of Behavioral Finance, working paper on SSRN, final paper was published in 2003 in the Handbook of the Economics of Finance, Chap. 18. Elsevier Science, Amsterdam.


Battalio, R., B. Hatch, and R. Jennings, 2004, Toward a National Market System Exist for U.S. Exchange-listed Equity Options, Journal of Finance, 59, 933-962.


Bessembinder, H., W. Maxwell, and K. Venkataraman, 2006, Market Transparency, Liquidity Externalities, and Institutional Trading Costs in Corporate Bonds, Journal of Financial Economics, 82, 251-288.


Bhattacharya, U., C. Holden, and S. Jacobsen, 2011, Penny Wise, Dollar Foolish: Buy-Sell Imbalances On and Around Round Numbers, forthcoming in Management Science.


Biais, B. and R. Green, 2005, The Microstructure of the Bond Market in the 20th Century, Toulouse University working paper.


Bloomfield, R. and M. O’Hara, 1999, Market Transparency: Who Wins and Who Loses?, Review of Financial Studies, 12, 5-35.


Bloomfield, R, M. O’Hara, and G. Saar, 2005, The “make or take” decision in an electronic market: Evidence on the evolution of liquidity, Journal of Financial Economics, 75, 165-199.


Bloomfield, R, M. O’Hara, and G. Saar, 2009, How Noise Trading Affects Markets: An Experimental Analysis, Review of Financial Studies, 22, 2275-2302.


Boehmer, E., G. Saar, and L.Yu, 2002, Lifting The Veil: An Analysis of Pre-Trade Transparency at the NYSE, Journal of Finance, 60, 783-815.


Brockman, P., D. Chung, and C. Perignon, 2009, Commonality in Liquidity: A Global Perspective, Journal of Financial and Quantitative Analysis, 44, 851-882.


Brunnermeier, M., L. Pedersen, 2009, Market Liquidity and Funding Liquidity, Review of Financial Studies, 22, 2201-2238.


Chakravarty, S., H. Gulen, and S. Mayhew, 2004, Informed Trading in Stock and Option Markets, Journal of Finance, 59, 1235-1258.


Chordia, T., R. Roll, and A. Subrahmanyam, 2000, Commonality in Liquidity, Journal of Financial Economics, 56, 3-28.


Daniel, K., D. Hirshleifer, and A. Subrahmanyam, 1998, Investor Pyschology and Security Market Under- and Overreactions, Journal of Finance, 53, 1839-1885.


Davies, R. and S. Kim, 2009, Using Matched Samples to Test for Differences in Trade Execution Costs, forthcoming in the Journal of Financial Markets.


Domowitz, I. and B. Steil, 1998, Automation, Trading Costs, and the Structure of the Trading Services Industry, working paper, Penn State University.


Easley, D., R. Engle, M. O’Hara, and L.Wu, 2008, Time-Varying Arrival Rates of Informed and Uninformed Trades, Journal of Financial Econometrics, 6, 171-207.


Easley, D., S. Hvidkjaer, and M. O’Hara, 2002, Is Information Risk A Determinant of Asset Returns?, Journal of Finance, 57, 2185-2221.


Easley, D., S. Hvidkjaer, and M. O’Hara, 2010, Factoring Information into Returns, Journal of Financial and Quantitative Analysis 45, 239-309.


Easley, D., N. Kiefer, and M. O’Hara, 1996, Cream-Skimming or Profit-Sharing? The Curious Role of Purchased Order Flow, Journal of Finance, 51, 811-833.


Easley, D., N. Kiefer, and M. O’Hara, 1997a, The Information Content of the Trading Process, Journal of Empirical Finance, 4, 159-186.


Easley, D., N. Kiefer, and M. O’Hara, 1997b, One Day in the Life of a Very Common Stock, Review of Financial Studies, 10, 805-835.


Easley, D., N. Kiefer, M. O’Hara, and J. Paperman, 1996, Liquidity, Information, and Infrequently Traded Stocks, Journal of Finance, 51, 1405-1436.


Easley, D. and O’Hara, M., 1987, Price, Trade Size, and Information in Securities Markets, Journal of Financial Economics 19, 69-90.


Easley, D. and M. O'Hara, 1991, Order Form and Information in Securities Markets, Journal of Finance 46, 905-927.


Easley D. and M. O’Hara, 1992, Time and the Process of Security Price Adjustment, Journal of Finance, 47, 577-605.


Easley, D., M. O’Hara, and J. Paperman, 1998, Financial Analysis and Information-Based Trade, Journal of Financial Markets, 1, 175-201.


Easley, D., M. O’Hara, and G. Saar, 2001, How Stock Splits Affect Trading: A Microstructure Approach”, Journal of Financial and Quantitative Analysis, 36, 25-51.


Easley, D., M. O’Hara, and P.S. Srinivas, 1998, Option Volume and Stock Prices: Evidence on Where Informed Traders Trade, Journal of Finance, 53, 431-466.


Edwards, A., L. Harris, and M. Piwowar, 2007, Corporate Bond Market Transaction Costs and Transparency, Journal of Finance, 62, 1421-51.


Ellis, K., R. Michaely, and M. O’Hara, 2000, The Accuracy of Trade Classification Rules: Evidence from NASDAQ, Journal of Financial and Quantitative Analysis 35, 529-551.


Ellul, A., C. Holden, P. Jain, and R. Jennings, 2007, Order Dynamics: Recent Evidence from the NYSE, Journal of Empirical Finance, 14, 636-661.


Flood, M., R. Huisman, K. Koedijk, and R. Mahieu, 1999, Quote Disclosure and Price Discovery in Multiple-Dealer Financial Markets, Review of Financial Studies, 12, 37-59.


Fong, K, C. Holden, and C. Trzcinka, 2013, What are the Best Liquidity Proxies for Global Research?, working paper, Indiana University.


Glosten, L., 1999, Introductory Comments: Bloomfield and O’Hara, and Flood, Huisman, Koedijk, and Mahieu, Review of Financial Studies, 12, 1-3.


Glosten, L. R. and Milgrom, P. R., 1985, Bid, Ask, and Transaction Prices in a Specialist Market With Heterogeneously Informed Traders, Journal of Financial Economics 14, 71-100.             


Goettler, R., C. Parlour, and U.Rajan, 2005, Equilibrium in a Dynamic Limit Order Book, Journal of Finance, 60, 2149-2192.


Gould, M., M. Porter, S. Williams, M. McDonald, D. Fenn, and Howison, 2011, Limit Order Books, Quantitative Finance, arXiv:1012.0349v2


Grinblatt M. and M. Keloharju, 2009, Sensation Seeking, Overconfidence, and Trading Activity, Journal of Finance, 64, 549-578.


Grinblatt, M., M. Keloharju, and J. Linnainmaa, 2012, IQ, Trading Behavior, and Performance, Journal of Financial Economics 104, 339-362.


Grossman, S., and M. Miller, 1988, Liquidity and Market Structure, Journal of Finance, 43, 617-633.


Hasbrouck, 1992, Using the TORQ Database, working paper, New York University.


Hasbrouck, J., 1995, One Security, Many Markets: Determining the Contributions to Price Discovery, Journal of Finance, 50, 1175-1199.


Hasbrouck, J. 2010, The Best Bid and Offer: A Short Note on Programs and Practices, working paper, New York University.


Hasbrock J. and G. Saar, 2010, Low-Latency Trading, working paper, New York University.


Hasbrouck, Sofianos, and Sosebee, 1993, New York Stock Exchange Systems and Trading Procedures, working paper, New York University.


Hasbrouck, J. and G. Sofianos, 1993, The Trade of Market Makers: An Empirical Analysis of NYSE Specialists, Journal of Finance, 48, 1565-1593.


Henker, T., and J. Wang, 2006, On The Imporance of Timing Specifications in Market Microstructure Research, Journal of Financial Markets, 9, 162-179.


Holden, C., 1995, Index Arbitrage as Cross-Sectional Market Making, Journal of Futures Markets, 15, 423-455.


Holden, C., 2013, Optimal Trading with Limit Orders on a Dynamic Limit Order Book, working paper, Indiana University.


Holden, C, and S. Jacobsen, 2012, Liquidity Measurement Problems in Fast, Competitive Markets:

Expensive and Cheap Solutions, working paper, Indiana University.


Holden, C., and A. Subrahmanyam, 1992, Long-lived Private Information and Imperfect Competition,   Journal of Finance, 47, 247-270.


Huang, R. and H. Stoll, 1997, The Components of the Bid-Ask Spread: A General Approach, Review of Financial Studies, 10, 995-1034.


Joint Advisory Committee on Emerging Regulatory Issues, 2010, Findings Regarding the Market Events of May 6, 2010, Report of the Staffs of the CFTC and SEC, Washington, D.C.


Kaul, G., Q., Lei, and N. Stoffman, 2008, AIMing at PIN: Order Flow, Information, and Liquidity, Indiana University working paper.


Kavajecz, K., 1999, A Specialist’s Quoted Depth and the Limit Order Book, Journal of Finance, 54, 747-771.


Kirilenko, A., A. Kyle, M. Samadi, and T. Tuzun, 2011, The Flash Crash: The Impact of High Frequency Trading on an Electronic Market, working paper, University of Maryland.


Kyle, A.S., 1985, Continuous Auctions and Insider Trading, Econometrica 53, 1315-1335.


Lee, C., B. Mucklow, and M. Ready, 1993, Spreads, Depths, and the Impact of Earnings Information,  Review of Financial Studies, 6, 345-374.


Lee, C. and M. Ready, 1991, Inferring Trade Direction From Intraday Data, Journal of Finance, 46, 733-746.


Lei, Q., 2010, Unveiling the Identity of PIN from the Flash Crash: Illiquidity or Information Asymmetry?, working paper, Southern Methodist University


Lei, Q. and G. Wu, 2005, Time-varying Informed and Uninformed Trading Activities, Journal of Financial Markets, 8, 153-181.


Mao, Y., 2012, Price Discovery in the Stock and Corporate Bond Markets, working paper, Indiana Unversity.


Mayhew, S., 2002, Competition, Market Structure, and Bid-Ask Spreads in Stock Option Markets, Journal of Finance 57, 931-958.


Parlour, C., 1998, Price Dynamics in a Limit Order Market, Review of Financial Studies, 11, 789-816.


Roll, R., 1984, A Simple Implicit Measure of the Effective Bid‑Ask Spread in an Efficient Market, Journal of Finance, 39, 1127‑1139.


Seppi, D., 1997, Liquidity Provision with Limit Orders and a Strategic Specialist, Review of Financial Studies, 10, 103-150.


Subrahmanyam, A., 1991a, A Theory of Trading in Stock Index Futures, Review of Financial Studies, 4, 17-51.


Wei, H., W. Lin, and W. Ke, 2011, A Computing Bias in Estimating the Probability of Informed Trading, Journal of Financial Markets, 14, 625-640.




F635 contributes to achieving the following doctoral program learning goals: (1) comprehensive and intensive disciplinary knowledge, (2) comprehensive and intensive knowledge of research methods, (3) communication of disciplinary research, and (4) evaluations of disciplinary research. The course teaches comprehensive and intensive disciplinary knowledge by teaching the key ideas in the theory and empirical analysis of market microstructure, such as adverse selection, inventory risk, order processing costs, limit order book dynamics, behavioral theory, commonality in liquidity, transparency, the liquidity-adjusted CAPM, linkage vs. fragmentation, etc. The course teaches comprehensive and intensive knowledge of research methods by teaching the key research methods in market microstructure, such as the NBBO, liquidity measures, trading typing, PIN, info shares, limit order book construction, matched samples, spread decomposition, analysis of order data, the experimental approach, etc. and by having student do their own original research paper and providing individual feedback on the substance of their paper. The course teaches the communication of disciplinary research by having students present their own research to the class and by providing individual feedback on the academic writing quality of their paper. The course teaches evaluations of disciplinary research by discussing the strengths and weaknesses of each academic paper that we cover and by having each student lead a discussion of a recently published or forthcoming paper.



Doctoral Program Learning Goals


Goal 1: Comprehensive and Intensive Disciplinary Knowledge      

Students who earn a doctorate degree in business will be able to demonstrate a comprehensive and intensive knowledge of the theories, concepts, frameworks, empirical findings, and controversies in a chosen business discipline.


Goal 2: Comprehensive and Intensive Knowledge of Research Methods   

Students who earn a doctorate degree in business will be able to demonstrate a comprehensive and intensive knowledge of the research methods and analytical techniques applicable to a chosen business discipline.


Goal 3: Communication of Disciplinary Research   

Students who earn a doctorate degree in business will be able to design, conduct, and communicate – in both written and oral formats – original research that makes a substantial contribution to a selected business discipline.


Goal 4: Evaluations of Disciplinary Research         

Students who earn a doctorate degree in business will be able to evaluate research ideas and completed research projects critically, assessing their conceptual and methodological soundness and importance of contribution to existing knowledge in the field.


Goal 5: Teaching       

Students who earn a doctorate degree in business will be able to teach effectively in a selected discipline at the university level.