723-M1040 Security Market Microstructure

723-M1040 Security Market Microstructure
Fall, 2005
Class meet: Room 203, Management Building 2, 2:20-5:20pm, Thursday
Professor Chyi-Mei Chen
3366-1086
cchen@ccms.ntu.edu.tw
This course surveys recent contributions in market microstructure theory.
Market microstructure is the study of the process and outcomes of exchanging
assets under explicit trading rules. With explicitly specified asset trading
mechanisms, optimal trading strategies for different classes of traders are
considered, and the properties of the resulting equilibrium price and volume
are examined.
It will start with a review of the benchmark rational expectations equilibrium
(REE) models (Grossman 1981; Green 1977; Kreps 1977; Hellwig
1980; Admati 1985; Diamond and Verrecchia 1981), and then move on to
the price formation models (Milgrom 1981; Jackson 1991; Kyle 1989). 1 Then
we will look at the classical dealership models (Demsetz 1968; Garman 1976;
Amihud and Mendelson 1980; Stoll 1978; Ho and Stoll 1981; Cohen, Maier,
Schwartz, and Whitcomb 1981), where bid-ask spreads may arise from (i)
the gambler’s ruin problem; (ii) the market power of dealers; (iii) the inventory
uncertainty and price uncertainty facing risk averse dealers; and (iv) the
order types allowed by the trading mechanism.
1 The finance literature suggests that trade can be motivated by either informational
or non-informational motives. Two economic agents may want to trade because they
have different endowments, different attitudes toward risks, or different time preferences.
These are non-informational motives. Two economic agents with the same preferences
and endowments may want to trade because they have different pre-trade beliefs about
the future price and dividend processes of the traded assets. The differences in the pretrade
beliefs may stem from the heterogeneous prior beliefs about the dividend stream
to be distributed by the traded asset ( Harris and Kreps 1978; Morris 1996), from the
different interpretations (differences of opinion) about the statistical relationship between
the intrinsic value of the traded asset and a (public or private) signal, or from the different
private information the agents possess before trading. These are informational motives. It
is by now a well-known theorem in financial economics that different private information
alone cannot generate trade among investors holding the same prior beliefs; see Aumann
(1976) and the no-trade theorems in Kreps (1977) and Milgrom and Stokey (1982). Thus,
a viable theory of asset trading must allow investors to either trade for non-informational
reasons or to have heterogeneous pre-trade beliefs.
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Then it will consider information-based dealership models, for which the
idea dated back to Bagehot (1971) and was first substantiated by Copeland
and Galai (1983). The information-based models have by now considered
both quote-driven and order-driven mechanisms, where the former was originated
by Golsten and Milgrom (1985) and the latter by Kyle (1985). Both
papers have numerous extensions. Easley and O’Hara (1987; 1992), for example,
extend the sequential trading model of Glosten and Milgrom (1985)
to show that high volume tends to be accompanied by large spreads and that
absence of trade has information content for asset pricing. An important
extension is Bernhardt and Hughson (1997), which allows traders to split
orders among dealers. Kyle’s model has been extended by many authors to
allow for utility maximizing liquidity traders (Spiegel and Subrahmanyam
1991), risk averse insiders (Subrahmanyam 1991), imperfectly competitive
insiders (Holden and Subrahmanyam 1992; Back, Cao, and Willard 2000),
super-informed insider (Rochet and Vila 1994), continuously trading (Back
1992), liquidity traders who have discretion about the timing of trade (Admati
and Pfleiderer 1988), and over-confident insiders (Wang 1998), just to
name a few. Back and Baruch (2002) show that with continuous trading, the
two classes of models described above have their equilibria converge.
It will then consider the several theories that aim at explaining some
well-documented patterns in transaction prices and trading volume (Admati
and Pfleiderer 1988, 1989; Foster and Viswanathan 1990; Spiegel and Subrahmanyam
1992; Pagano 1989; Bernhardt and Hughson 2002; Harris and
Raviv 1993; Campbell, Grossman, and Wang 1993; Wang 1993, 1994; Wang
1998; Varian 1985,1987; Huffman 1987; Chen 1992; Chen and Chen 2003). In
particular, trade tends to cluster either geographically or on certain period
of time, and high volume tends to be accompanied by price rise and by large
absolute price change. It will also take a look at block trading (Easley and
O’Hara 1987; Admati and Pfleiderer 1991; Burdett and O’Hara 1987).
It will next consider the role of investors’ trading horizons in leading to
excessive volatility and a tendency to coordinate on fundamental-unrelated
signals. First dynamic REE models (Brown and Jennings 1989; Grundy and
McNichols 1989; Shalen 1993; He and Wang 1995) will be examined. In partially
revealing REE’s, price and volume together can provide information
to the market in much the same way that a sequence of prices does (Wang
1994). It will then ask how short horizon may affect volatility and herding
(Bhushan, Brown, and Mello 1997; Froot, Scharfstein, and Stein 1992;
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Holden and Subrahmanyam 1996; Vives 1995; Spiegle). Essentially, a higher
proportion of short-term traders implies a higher price volatility, but this
emphasis on trading horizons should be contrasted with other explanations
for excessive volatility (see Shiller 1981 and West 1988) that are based on
information asymmetry alone (Wang 1993; Allen and Douglas 1994).
It will then examine the roles of various classes of traders. It will start
with noise traders (Black 1986; DeLong, Shleifer, Summers, and Woldmann
1989, 1990a, 1990b, 1991), and then brokers (Jordan and Morgan 1990; Fishman
and Longstaff 1992), and then financial analysts (Trueman 1994; Hirshleifer,
Subrahmanyam and Titman 1994), and finally exchange specialists
(Glosten 1989; Seppi 1997) and the contrast between specialists and imperfectly
competitive market makers (Madhavan 1992; Leach and Madhavan
1992,1993). Unlike with the Walrasian trading mechanism, in the real world,
price discovery is an important issue, and from this perspective a monopolistic
specialist may be preferred (Leach and Madhavan 1993; Madhavan and
Panchapagesan 2000).
It will then consider the possible economic causes for market crash (Grossman
1988; Gennotte and Leland 1990; Jacklin, Kleidon, and Pfleiderer 1992;
Romer 1993; Hong and Stein 1999).
It will next consider the interactions between the underlying asset market
and the derivative asset markets (Biais and Hillion 1994; Kumar, Sarin, and
Shastri 1992; Brennan and Cao 1996; Cao 1999; Bessembinder and Seguin
1992; Back 1993; Subrahmanyam 1991; Chen, Hsieh, and Szu 2001; Bossaerts
on insiders trading portfolios).
Then various market features will be considered. This includes discrete
pricing (Anshuman and Kalay 1998; Bernhardt and Hughson 1996; Harris
1991), a limit set of order forms (Easley and O’Hara 1991; Chakravarty and
Holden 1995; Han and Chen 2000), mandatory trade disclosure regulation
(Madhavan 1995; Han and Chen 2003; Fishman and Hagerty 1995), one or
multiple market makers (Leach and Madhavan 1992,1993), short sale constraints
(Diamond and Verrecchia 1987), call or continuous markets (Madhavan
1992), transparency (Bikhchandani and Huang 1989; Chen, Hsu and
Wang 2003; Madhavan 1995; Glosten 1999; Bloomfield and O’Hara 1999;
Flood, Huisman, Koedijk and Mahieu 1999), and price limits (Chen 1994;
Kodres and O’Brien 1994).
Then, it will consider market manipulation by uninformed traders (Kumar
and Seppi 1992; Allen and Gale 1992) and by informed traders (Vila
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1986; Benabou and Laroque 1992).
Then it will consider models that involve trade occurring in more than
one market (Chowdhry and Nanda 1991; Biais 1993; Leach and Madhavan
1993, Pagano 1989b; Subrahmanyam 1991).
Finally, we will review the pros and cons of insider trading from the
society’s perspective (Leland 1992, Manove 1989; Laffont and Maskin 1990;
Ausubel 1990; Bagnoli and Khanna 1992; Fischer 1992; Khanna, Slezak, and
Bradley 1994; Bernhardt, Hollifield, and Hughson 1995; Faure-Grimaud and
Gromb 1999).
Students are responsible for presenting part of the listed articles below.
• 9/22 Introduction and the REE Models. Lecture note.
• 9/29 1. Inventory Models.
1. Amihud, Y. and H. Mendelson, 1980, Dealership Market: Market
Making with Inventory, JFE 8, 31-53.
2. Cohen, K., S. Maier, R. Schwartz, and D. Whitcomb, 1981, Transaction
Costs, Order Placement Strategy, and Existence of Bid-Ask
Spread, JPE 89, 287-305.
3. Demsetz, H., 1968, The Cost of Transacting, OJE 82, 33-53.
4. Garman, M., 1976, Market Microstructure, JFE 3, 257-275.
5. Ho, T. and H. Stoll, 1981, Optimal Dealer Pricing under Transactions
and Return Uncertainty, JFE 9, 47-73.
6. Stoll, H., 1978, The Supply of Dealer Services in Securities Markets,
JF 33, 1131-1151.
• 9/29 2. Information-Based Models.
1. Copeland, T. and D. Galai, 1983, Information Effects and the
Bid-Ask Spread, JF 38, 1457-1469.
2. Easley, D. and M. O’Hara, 1987, Price, Trade Size, and Information
in Securities Markets, JFE 19, 69-90.
3. Glosten, L. and P. Milgrom, 1985, Bid, Ask, and Transction Prices
in a Specialist Market with Heterogeneously Informed Traders,
JFE 13, 71-100.
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4. Kyle, A., 1985, Continuous Auctions and Insider Trading, Econometrica
53, 1315-1336.
• 10/6 1. Insider Trading.
1. Back, K., 1992, Insider Trading in Continuous Time, RFS 5, 387-
410.
2. Kyle, A., 1985, Continuous Auctions and Insider Trading, Econometrica
53, 1315-1336.
• 10/13 2. Multiple Insiders.
1. Back, K., Cao, H., and G. Willard, 2000, Imperfect competition
among informed traders, Journal of Finance 55, 2117V2155.
2. Holden, C.W. and A. Subrahmanyam, 1992, Long-Lived Private
Information and Imperfect Competition, JF 47, 247-270.
3. Kyle, A., 1989, Informed Speculation with Imperfect Competition,
RES 56, 317-355.
• 10/20 Uninformed Traders.
1. Admati, A. and P. Pfleiderer, 1988, A Theory of Intraday Patterns:
Volume and Price Variability, RFS 1, 3-40.
2. Admati, A. and P. Pfleiderer, 1989, Divide and Conquer: A Theory
of Intraday and Day-of-the-Week Mean Effects, RFS 2, 189-
224.
3. Foster, F. and S. Viswanathan, 1990, A Theory of the Intraday
Variations in Volume, Variance and Trading Costs in Securities
Markets, RFS 3, 593-624.
4. Spiegel, M. and A. Subrahmanyam, 1992, Informed Speculation
and Hedging in a Noncompetitive Securities Market, RFS 5, 307-
330.
• 10/27 Technical Analysis.
1. Brown, D. and R. Jennings, 1989, On Technical Analysis, RFS 2,
527-552.
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2. Lo, A., H. Mamaysky, and J. Wang, 2000, Foundations of technical
analysis: computational algorithms, statistical inference, and
empirical implementation, JF, 55, 1705-1765.
3. Neftci, S., 1991, Naive trading rules in financial markets and
Weiner-Kolmogorov prediction theory: a study of technical analysis,
JB, 64, 549-571.
• 11/3 Trading Volume and Price Adjustment.
1. Harris, M. and A. Raviv, 1993, Differences of Opinion Make a
Horse Race, RFS 6, 473-506.
2. Wang, J., 1994, A Model of Competitive Stock Trading Volume,
JPE 102, 127-168.
3. Easley, D. and M. O’Hara, 1992, Time and the Process and Security
Price Adjustment, JF 47, 577-606.
4. Grundy, B. and M. McNichols, 1989, Trade and Revelation of
Information Through Prices and Direct Disclosure, RFS 2, 495-
526.
• 11/10 Block trading.
1. Admati, A. and P. Pfleiderer, 1991, Sunshine Trading and Financial
Market Equilibrium, RFS 4, 443-482.
2. Burdett, K. and M. O’Hara, 1987, Building Blocks: An Introduction
to Block Trading, J. Banking and Finance 11, 193-212.
3. Grossman, S., 1990, The Information Role of Unstairs and Downstairs
Trading, working paper, Wharton.
• 11/17 Market Viability,
1. Glosten, L., 1989, Insider Trading, Liquidity, and the Role of Monopolist
Specialist, JB 62, 211-236.
2. Madhavan, A., 1992, Trading Mechanisms in Securities Markets,
JF 47, 607-642.
• 11/24 Market Crash.
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1. Gennotte, G. and H. Leland, 1990, Market Liquidity, Hedges and
Crashes, AER 80, 999-1021.
2. Grossman, S., 1988, An Analysis of the Implications for Stock
and Futures: Price Volatility of Program Trading and Dynamic
Hedging Strategies, JB 61, 275-298.
3. Jacklin, C., A. Kleidon, and P. Pfleiderer, 1992, Underestimation
of Portfolio Insurance and the Crash of October 1987, RFS 5,
35-63.
• 12/1 Trading via Multiple Markets.
1. Brennan, M., and H. Cao, 1996, Information, trade, and derivative
securities, RFS, 9, 163-208.
2. Chowdhry, B. and V. Nanda, 1991, Multi-Market Trading and
Market Liquidity, RFS 3, 483-511.
3. Madhavan, A., 1995, Consolidation, fragmentation, and the disclosure
of trading information, RFS, 8, 579-603.
• 12/8, 12/15 Imperfections and Market Volatility.
1. Anshuman, V.R. and A. Kalay, 1998, Market making with discrete
prices, RFS, 11, 81-109.
2. Chakravarty, S., 1995, An integrated model of market and limit
orders, Journal of Financial Intermediation, vol. 4.
3. Diamond, D. and R. Verrecchia, 1987, Constraints on Short-Selling
and Asset Price Adjustments to Private Information, JFE 18, 277-
311.
4. Ferris, S., and S. Don Chance, 1988, Margin requirements and
stock price volatility, Economic Letters, 28, 251-254.
5. Flavin, M., 1983, Excess volatility in financial markets: a reassessment
of the empirical evidence, J. Political Economy, 91, 929-956.
6. Hsieh, D. and M. Miller, 1990, Margin requirements and stock
price volatility, JF, 45, 3-29.
7. Kodres, L. and D. O’Brien, 1994, The Existence of Pareto Superior
Price Limits, American Economic Review, 84, 919-932.
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8. Kupiec, P. and S. Sharpe, 1991, Animal spirits, margin requirements,
and stock price volatility, JF, 46, 717-731.
• 12/22 Short Horizon.
1. Vives, X., 1995, Short-term investment and the informational efficiency
of the market, RFS, 8, 125-160.
2. Stein, J., 1988, Takeover threats and managerial myopia, J. Political
Economy, 96, 61-79.
3. Stein, J., 1989, Efficient capital markets, inefficient firms: a model
of myopic corporate behavior, QJE, 654-669.
4. Bhushan, R., D. Brown, and A. Mello, 1991, Investor horizon and
noise in asset prices, working paper, MIT.
5. Shleifer, A., and R. Vishny, 1990, Equilibrium short horizons of
investors as firms, AER, 80, 148-153.
6. Narayanan, M., 1985, Observability and the payback criterion, J.
Business, 58, 309-323.
7. Faure-Grimaud, A., and D. Gromb, 1999, Trading, voice and exit
over the firm’s life cycle, working paper, MIT.
8. Holden, C., and A. Subrahmanyam, 1996, Risk aversion, liquidity,
and endogenous short horizon, RFS, 9, 691-722.
• 12/29 Empirical Evidence for Volume.
1. Gallant, A., P. Rossi, and G. Tauchen, 1992, Stock prices and
volume, RFS, 5, 199-242.
2. Jain, P., and G. Joh, 1988, The dependence between hourly prices
and trading volume, JFQA, 23, 269-283.
3. McInish, T., and R. Wood, 1992, An analysis of intraday patterns
in bid/ask spreads for NYSE stocks, JF, 47, 753-764.
4. McInish, T., and R. Wood, 1995, Hidden limit orders on the
NYSE, J. Portfolio Management, 19-26.
5. Karpoff, J., 1987, The relationship between price changes and
trading volume: a survey, JFQA, 22, 109-126.
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6. Gerety, M., and J. H. Mulherin, 1994, Price formation on stock
exchanges: the evolution of trading within the day, RFS, 7, 609-
629.
7. Kumar, R., A. Sarin, and K. Shastri, 1992, The behavior of option
price around large block transactions in the underlying security,
JF, 47, 879-889.
8. Blume, M., A. C. Mackinlay, and B. Terker, 1989, Order imbalances
and stock price movements on October 19 and 20, 1987, JF,
44, 827-.
• 1/5 Herding.
1. Hirshleifer, D., A. Subrahmanyam, and S. Titman, 1994, Security
analysis and trading patterns when some investors receive information
before others, JF, 49, 1665-1697.
2. Scharfstein, D. and J. Stein, 1990, Herd behavior and investment,
AER, 80, 465-479.
3. Bikhchandani, S., D. Hirshleifer, and I. Welch, , A theory of fads,
fashion, custom, and cultural change as information cascades, J.
Political Economy, 100, 992-1026.
4. Banerjee, A., 1992, A simple model of herd behavior, QJE, 107,
797-818.
• 1/12 Final Exam.
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