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Competition for Order Flow and the Theory of Global Games pp 59–101Cite as

Competition for Order Flow in Market Microstructure Theory

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Abstract

The purpose of this chapter is to examine to what extent current theoretic market microstructure research provides answers to the questions raised in the previous chapter. The research area known as market microstructure theory has experienced strong growth over the last three decades. Theoretical, empirical and experimental work covers numerous heterogeneous aspects and issues. The focus of this chapter will lie in the theoretical research that analyzes competition for order flow between markets with different structures, in particular between electronic auction and dealer markets and their implications for market performance and quality.250

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Reference

  1. For a detailed survey of the existing theoretical research, major results and concepts, and a general perspective on the development and evolution of market microstructure theory see O’Hara (1995); For a comprehensive review including theoretical, empirical, and experimental studies see Madhavan (2000); For a review of major theoretical research see Hirth (1998); Cohen, Maier, Schwartz and Withcomb (1986) provide a survey of the early literature.

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  2. See Spulber (1999), p. ix

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  3. See Hirth (1998), p. 1

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  4. See O’Hara (1995), p. 1; Madhavan (2000) defines market microstructure as the “area of finance that is concerned with the process by which investors’ latent demands are translated ultimately into transactions”, Madhavan (2000), p. 205 f

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  5. Frankel, Galli, and Giovanni (1996) and Lyons (2000) provide a detailed overview of the market microstructure of foreign exchange markets, Freixas and Rochet (1997) give a detailed overview of the microstructure of banking. Spulber (1999) examines the market microstructure literature on the theory of firms as intermediaries.

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  6. As suggested by Madhavan (2000), p. 207; For other classification criteria see O’Hara (1995) and Hirth (1998).

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  7. See O’Hara (1995), p. 6

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  8. The Walrasian auctioneer aggregates traders’ supply and demand and sets the market-clearing price. For the description of a Walrasian auction see, for example, O’Hara (1995), p. 4

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  9. For example, commissions, taxes, order handling and clearing costs, trading restrictions, communication costs, etc., see Schwartz (1988), p. 11, 247

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  10. See O’Hara (1995), p. 4 ff, Madhavan (2000), p. 209, Schwartz (1988), p. 10 f

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  11. If information is symmetric and trading frictions are negligible, prices simply reflect expected values, see Madhavan (2000), p. 208; For an brief overview of the informational efficiency of securities markets see, for example, Schwartz (1988), p. 270 ff

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  12. Madhavan (2000), p. 209

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  13. This classification follows Hirth (1998). p. 2 ff; The definition of the basic terms follows the widely accepted notation if not noted differently.

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  14. See, for example, Glosten/Milgrom (1985), Easley/O’Hara (1987), Pagano (1989)

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  15. See Schwartz (1988), p. 271 f

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  16. Hirth (1998) distinguishes between information A, B and C. Information A is exogenous information about, for example, dividend payments or the liquidation value of the asset. Information B is exogenous information which determines the valuation of the asset such as traders’ preferences and endowments. Information C is endogenous information in the sense described above. Market endogenous information plays an important role with regard to the transparency of a market. The more market endogenous information is revealed, the more transparent the market becomes, see Hirth (1998), p. 2 f

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  17. If this were not the case no one would have an incentive to acquire information, see Schwartz (1988), p. 281

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  18. See O’Hara (1995), p. 91, Hirth (1998), p. 3 f

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  19. See Schwartz (1988), p. 17 f; Both theoretical and empirical research on limit order books has currently grown significantly. Angel (1991), Glosten (1994), Harris (1994), Angel (1995), Chakravarty and Holden (1995), Seppi (1997), Parlour (1998), Viswanathan and Wang (1998), Kumar and Seppi (2000), among others, have developed theoretical models of limit order books. Empirical analyses of the limit order book are presented by, among others, Bias, Hillion and Spatt (1995), Hamao and Hasbrouck (1995), Harris and Hasbrouck (1996), Handa and Schwartz (1996), Kavajecz (1998), Ahn, Bae and Chan (1999), Chung, Van Ness and Van Ness (1999).

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  20. Hybrid market structures combine elements of the dealer market and the auction market, for example, the New York Stock Exchange, where the specialist acts as a broker and as a dealer, see, for example, O’Hara (1995), p. 8, Schwartz (1988), p. 389; For an overview of the functions/services provided by dealers and dealers’ costs see Schwartz (1988), p. 389 ff, Weston (2000), p. 7 ff; Dem-setz (1968) considers the dealer as a provider of immediacy with the bid-ask-spread being his compensation for providing this service. Garman (1976) presents a model of a monopoly dealer’s price setting, adjusting the spread to respond to fluctuations in his inventory level. Stoll (1978), Amihud and Mendelson (1980), Ho and Stoll (1981), among others, present a dynamic version of Garman’s (1976) dealer pricing model. Another area of research, beginning with Bagehot [pseud.] (1971), explains the existence of a dealer spread as a result of the existence of informational asymmetries. Influential models in this area have been developed, among many others, by Copeland and Galai (1983), Glosten and Milgrom (1985), and Easley and O’Hara (1987), see for a more detailed overview of these models Madhavan (2000), p. 212 ff, Hirth (1998), p. 20 ff, or O’Hara (1995), chapter 2 and 3 for a detailed description of these models

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  21. For example, OTC market makers are dealers and exchange market makers such as the NYSE specialist are both agents and dealers.

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  22. See, for example, Hirth (1998), p. 5, Madhavan (2000), p. 224

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  23. See Cohen/Maier/Schwartz/Withcomb (1986), p. 13 f, Madhavan (2000), p. 224

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  24. If the dealer in the dealer market has the obligation to quote continuously bid and ask spreads, the dealer market is a continuous market while the auction market may be either periodic or continuous. For more details see Schwartz (1988), p. 20 ff, Cohen/Maier/Schwartz/Withcomb (1986), p. 12, Hirth (1998), p. 5

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  25. Orders may be displayed only at the midpoint of the bid-ask-spread, or the best bid (ask) or the best and the second best bid (ask) quotation are displayed. Limit orders may be displayed in a public or open limit order book, or access to the book may be restricted to selected market participants. In a call market, orders may not be displayed until the market is called. Board trading systems post orders so that they can be seen by all market participants on the floor, see Schwartz (1988), p. 24 ff, for more details

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  26. See Madhavan (2000), p. 224, O’Hara (1995), p. 252 ff, 260 ff

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  27. See Madhavan (2000), p. 224

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  28. See section II2.3.2

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  29. See among others, Securities and Exchange Commission (2000a), Levitt (1999a)

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  30. In 1975, the U.S. Congress mandated the SEC to facilitate the establishment of an NMS, see section 113.2, to address market fragmentation. At the same time, assurance of fair competition among brokers, dealers, exchanges and other markets was an additional goal that was assumed to be consistent with the objective to establish a NMS, see Securities and Exchange Commission (1992), p. 2075 f; The historical debate has mainly focused on off-board trading restrictions such as the NYSE Rule 390, see section 113.2.3.2, and the establishment of intermarket linkages such as the ITS or the CQS, see section 113.2. Post changes in the securities market structures were motivated by the desire to strengthen competition based on the belief of the efficiency of competitive markets, for an overview of the history of the debate see Cohen/Maier/SchwartzNVithcomb (1986), p. 151 ff; In 1992, the SEC announced the undertaking of a study of the structure of the U.S. equity markets and asked for comments on the issues of market fragmentation, see Securities and Exchange Commission (1992); In 1999, SEC chairman Levitt called for a public dialogue on how technology may remove fragmentation without stifling competition, see Levitt (1999a); In February 2000, the SEC again requested comment on issues relating to market fragmentation, see Securities and Exchange Commission (2000a); For theoretical analyses of the fragmentation versus consolidation issue see sections II12.2.2 and II13

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  31. Keynes (1930), p. 67

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  32. See, for example, O’Hara (1995), p. 216, Hasbrouck/Schwartz (1988), p. 10, Schwartz (1988), p. 356, Pagano (1989), p. 255

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  33. The ‘liquidity ratio’ is defined as the ratio of average dollar volume over the average price change in some time period. For a discussion of the limitations of this measure see Grossman/Miller (1988), p. 630 ff; Kyle (1985) uses the order flow needed to move prices one unit as a measure of liquidity.

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  34. See Schwartz (1988), p. 356 f

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  35. See Grossman/Miller (1988), p. 629, Hasbrouck/Schwartz (1988), p. 10 f, O’Hara (1995), p. 217; For more details see next section

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  36. See Garman (1976), Stoll (1978), Amihud/Mendelson (1980), Ho/Stoll (1981)

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  37. See Grossman/Miller (1988) for details

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  38. Liquidity arises because some market participants are willing to hold a suboptimal portfolio for a certain price. This is in line with earlier models that analyze the dealer’s bid ask spread and investigate the dealer’s role as a provider of immediacy, see footnote 285.

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  39. For details on Pagano’s (1989) model see section 1113.2

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  40. For further examples see Madhavan (2000), p. 226

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  41. Kyle (1984) investigates the effect of multiple informed traders on market behavior. Kyle (1985) presents a model with a single informed trader and a number of uninformed noise traders trading with competitive market makers acting as order processors, setting market-clearing prices. The focus of the model is the analysis of the informed traders trading decision to maximize his value of private information and how information is incorporated into asset prices across time Kyle (1985) shows that if liquidity is increased in a market, the informed trader increases his trade quantity that offsets beneficial effects on prices. Thus, there can be no liquidity differences across markets, see O’Hara (1995), p. 227

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  42. Admati and Pfleiderer’s (1988) model is a variant of the Kyle (1984) model, see Admati/Pfleiderer (1988) for details

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  43. See Chowdhry/Nanda (1991) for details

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  44. See Schwartz (1988), p. 426 ff, 465 ff, as well as Cohen, Maier, Schwartz, and Withcomb (1986), p. 150 distinguish between spatial and temporal consolidation. The latter stands for the accumulation of orders over a certain period of time; The fragmentation versus (geographical) consolidation of orders debate is analogous to the question why traders favor continuous trading despite strong arguments for periodic trading, i.e. the temporal consolidation, see Madhavan (2000), p. 226, and Madhavan (2000), p. 231 for an overview of the empirical evidence; This thesis focuses on the geographical consolidation of order flow.

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  45. See footnotes 13 and 14 of this thesis; Real markets lie between the two extremes of a totally consolidated and a highly fragmented market. For example, see section 113.2, the national and regional exchanges in the U.S. are linked by the ITS. Securities and Exchange Commission (2000a) summarizes some statistical data on fragmentation. The market for listed securities in the U.S. is considerably less fragmented than the market for Nasdaq equities. In September 1999, 74.4% of trades in NYSE listed equities were executed on the NYSE, and 68.7% of trades in Amex listed securities were executed on the Amex. In contrast, there was an average of 11.4 market makers per Nasdaq issue; See also section 113.1 for the market share of ATSs in the Nasdaq market.

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  46. See Madhavan (2000), p. 225

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  47. See footnote 279 of this thesis

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  48. The competition between dealers or market centers may be viewed as interdealer competition, in contrast to intermarket competition that applies to a broader competition between rival market centers competing for listing or different products, see Cohen/Maier/Schwartz/Withcomb (1986), p. 162 f, Schwartz (1988), p. 426 f; As this thesis concentrates on intermarket competition, fragmentation in this context is understood as resulting from intermarket competition.

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  49. See Cohen/Maier/Schwartz/Withcomb (1986), p. 151 ff, Schwartz (1988), p. 427 f

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  50. See Cohen/Maier/Schwartz/withcomb (1986), p. 157 ff, Schwartz (1988), p. 429 ff, for a detailed discussion of these issues, see also Securities and Exchange Commission (1992) and Securities and Exchange Commission (2000d) for an overview of market structure issues relating to fragmentation

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  51. The price priority rule assures that buyers (sellers) who are willing to pay (accept) the highest (lowest) price for their order receive execution first, and that market order buyers (sellers) buy (sell) at the lowest (highest) current market price. The second trading priority rule determines the sequence at which orders that have been submitted at the same price are executed. Common rules include the 357 See in detail section IV3 time priority, size priority, or pro rata execution of all orders, see Schwartz (1988), p. 18

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  52. Consolidation of order flow information has two dimensions: the physical consolidation and the consolidation of information other than orders and prices, e.g. the mood on the floor, see Cohen/Maier/Schwartz/Withcomb (1986), p. 160

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  53. See Madhavan (2000), p. 226

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  54. See O’Hara (1995), p. 269, von Heusinger (2000)

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  55. See section 112.3.2

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  56. See Securities and Exchange Commission (1992), p. 2076, O’Hara (1995), p. 269 f on the problem of free riding of the price discovery process; Hasbrouck (1995) shows that the primary market is often the only source of price discovery while the satellite market simply matches quotes.

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  57. For early theoretical analysis see, for example, Ho/Stoll (1983), for empirical evidence see, for example Hamilton (1979), see also Cohen/Maier/Schwartz/Withcomb (1986), p. 162 f

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  58. See also Cohen/Maier/Schwartz/Withcomb (1986), p. 163 f

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  59. See Cohen/Maier/Schwartz/Withcomb (1986), p. 151 ff, Schwartz (1988), p. 427 f, O’Hara (1995), p. 269 f

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  60. See Schwartz (1988), p. 433 f

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  61. For details see Mendelson (1987)

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  62. This result is analogous to the “revenue equivalence theorem” in auction theory that says that, under certain conditions, expected revenues of the seller are the same in Dutch and English auction. Biais (1993) argues that Dutch auctions are similar to the fragmented market, where agents cannot observe the competitors’ bid, and English auctions are similar to consolidated markets. Modeling assumptions allow Biais (1993) to obtain revenue equivalence. For details see Biais (1993), p. 173 f

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  63. For details see Biais (1993)

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  64. For details see Madhavan (1995); See Madhavan (2000), p. 227 f, 231 f, as well as O’Hara (1995), p. 233 ff for an overview of the analysis of fragmentation occurring from off-market trading

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  65. For example, see Mendelson (1997), Biais (1993), Madhavan (1995) in section 1112.2.2; Pagano and Röell (1996) compare several trading systems with different degrees of transparency in isolation and find that uninformed traders’ costs are higher in dealer markets; Other models that focus on the comparison of trading costs in markets with different trading mechanisms include, for example, Kyle (1985) who shows that noise traders’ losses in continuous markets are as twice as high than in a single auction market. Pagano and Röell (1992) find that trading costs are highest in dealer markets and lowest in call markets, see also Theissen (2000), p. 336, Hirth (1998), p. 24 ff, for an overview; For an overview on empirical work comparing different trading mechanisms in isolation that focus on market liquidity, measured by the size of the bid-ask-spread, see Theissen (2000), p. 336 ff

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  66. See footnote 297; According to this distinction, models of category (i) are models of interdealer competition. Models of competition among market makers belonging to category (i) have been developed, among others, by Ho and Stoll (1983). Refer to O’Hara (1995) p. 44 ff, or Hirth (1998), p. 20 ff for an overview of related research. Models analyzing competition between identical markets, that are models of category (ii), are presented by, among others, Pagano (1989), Chowdhry and Nanda (1991), and Parlour and Seppi (1998). Pagano (1989) shows that trade consolidates into one single market if markets are identical, see also section 1113.2; Similar to Pagano (1989), Chowdhry and Nanda (1991) analyze the co-existence of multiple markets and consider how the ability of traders to choose where to trade and how this affects the functioning and the liquidity of the markets, see also section II12.1.2. Parlour and Seppi (1998) consider competition between two pure limit order markets and two hybrid specialist/limit order markets. In the case of two pure limit order markets, multiple equilibria exist depending on the traders’ preferencing rules. In the case of two hybrid markets, a symmetric coexistence equilibrium always exists, see section II13.5

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  67. There are a couple of models in which traders can choose to submit limit orders or market orders to one single market where orders of both types are matched against each other. Models of this class, however, do not analyze multi-market trading and, thus, are not further discussed in this context. For example, Chakravarty and Holden (1995), Handa and Schwartz (1996), Parlour (1998), Foucault (1998), Kumar and Seppi (2000), endogenously model the decision which order type to use and provide insight into the liquidity provision in hybrid structures. In an earlier model, Cohen, Maier, Schwartz and Withcomb (1981) analyze the choice between market and limit orders assuming an exogenously given probability of limit orders execution.

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  68. While Glosten (1994) and Parlour and Seppi (1998) assume the existence of different types of traders who either demand or supply liquidity these models assume the existence of only one type of traders submitting market orders. In the models of Gehrig (1993) and Hendershott and Mendelson (2000) there is also an intermediary as a provider of liquidity.

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  69. See section II12.1.2 for the model of Chowdhry and Nanda (1991) in brief

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  70. This section draws from the original paper. For details refer to the original paper, see Pagano (1989), p.255–274; A brief summary of the first two parts of the analysis is also presented by O’Hara (1995), p. 223 ff

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  71. See section II12.1

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  72. See Pagano (1989), p. 261

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  73. Pagano (1989), p. 261

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  74. See Pagano (1989), Proposition 1, p. 262

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  75. See Pagano (1989), Proposition 2, p. 262 f

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  76. Ëmay be determined by the marginal cost of searching, see Pagano (1989), p. 265

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  77. See Pagano (1989), Proposition 5, p. 267

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  78. While Pagano’s (1989) model completely disregards asymmetric information considerations, Chowdhry and Nanda (1991) examine a market where some traders have informational advantages. They show that multiple markets co-exist and that one market emerges as the dominant market that attracts informed traders. However, the co-existence of multiple markets is based on the assumption that a fraction of small traders cannot choose where to trade but that these traders are assigned to different markets. Thus, there will always be order flow in each market. If all small traders were able to make the choice where to trade, it is likely that trading would concentrate in one single market which confirms Pagano’s (1989) conclusions., see also O’Hara (1995), p. 231 f

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  79. See Pagano (1989), Proposition 6, p. 272 f

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  80. The following section is a summary of Gehrig (1993). For a more formal introduction to the model refer to the Appendix, for details refer to the original paper, see Gehrig (1993), p. 97–120; A summary of the model is also presented by Spulber (1999), p. 118 ff

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  81. If λ = 1, the search market is fully efficient. Gehrig (1993) considers the special case in which the numbers of traders on both sides of the search market are equal. If there are more traders on one side of the market, agents on the short side of the market would be matched with probability a; agent on the long side of the market with probability less than A, adjusted by the relative number of traders on the long side, see Gehrig (1993), p. 104

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  82. See Gehrig (1993), Definition 1, p. 106

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  83. See Gehrig (1993), Proposition 1, p. 108

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  84. See Gehrig (1993), Proposition 2, p. 108

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  85. See Gehrig (1993), Proposition 3, p. 112

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  86. Yavas (1992) is closely related to Gehrig (1993), however, this model assumes that traders who do not find a trading partner in the search market are matched by the intermediary with probability one, thus, there is no risk of trading opportunities to be lost. See Hirth (1998) for a brief summary, see Yavas (1992) for details.

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  87. This section draws from the original paper. More details are presented in the Appendix; For technical details and proofs refer to the original paper, see Hendershott and Mendelson (2000), p. 2071–2115

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  88. The performance of a crossing network has not been studied before, however, Mendelson (1982, 1985, 1987) analyzes a related market structure, a clearing house.

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  89. After trading, all market participants have better information about the asset’s value with an expected sas posterior volatility óv p < óv , see HendershotUMendelson (2000), p. 2075

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  90. See Hendershott/Mendelson (2000), p. 2075; As the focus of this section lies on the competition between the two markets the analysis of the dealers’ pricing behavior is not presented here; For the analysis see Hendershott/Mendelson (2000), p. 2077 ff

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  91. The purpose of this section is to present the basic idea of the model of the interaction between the CN and the DM, thus, the performance analysis of the CN in the presence of informed traders is not presented here; For details see Hendershott/Mendelson (2000), p. 2085 if

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  92. See Hendershott/Mendelson (2000), Proposition 3, p. 2081

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  93. Su, -ce strictly increases in û while (24) with o = F(û) decreases in ù. g(û) increases in û for lower values of û, reaches its maximum, and decreases in û for larger values of 6. Thus, for sufficiently small c there exist two solutions to g(û) = co.

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  94. See Hendershott/Mendelson (2000), p. 2083 for a graphical illustration

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  95. Proposition 4 summarizes these results, see Hendershott/Mendelson (2000), p. 2084; Hendershott and Mendelson (2000) extend their analysis of the CN in isolation by assuming the existence of informed traders. Informed traders affect the probability of order execution. The effect, however, depends on whether informed traders are on the same side of the market as liquidity traders or on the opposite side of the market. The conditional probability of order execution is higher if informed traders are on the opposite side of the market. The equilibrium condition with insider trading is similar to the condition in the absence of informed traders; it differs in that it takes into account the liquidity traders’ expected adverse selection cost from informed trading. Hendershott and Mendelson (2000) find that a CN with informed trading is less attractive to liquidity traders, see Hendershott/Mendelson (2000), p. 2085 ff

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  96. See Hendershott/Mendelson (2000), Proposition 7, p. 2092

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  97. See Hendershott/Mendelson (2000), Proposition 8, p. 2093 f

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  98. See Hendershott/Mendelson (2000), Proposition 9, p. 2094 f, for the calculation of the number of dealers and spread conditional on liquidity traders’ strategies

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  99. See Hendershott/Mendelson (2000), Proposition 10, p. 2095

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  100. See Hendershott/Mendelson (2000), Proposition 11, p. 2095 f

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  101. Hendershott/Mendelson’s (2000) Propositions 7 and 9, p. 2092, 2094, characterize the equilibrium.

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  102. For details on the sensitivity and special cases analyses, see Hendershott/Mendelson (2000), p. 2097 ff

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  103. See Hendershott/Mendelson (2000), Proposition 15, p. 2101

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  104. See Hendershott/Mendelson (2000), Proposition 16, p. 2101

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  105. Glosten (1994) does not endogenize the decision to submit a limit or a market order. Handa and Schwartz (1996) extend his model and derive the trader’s decision whether to trade via limit or market order endogenously.

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  106. This has been analyzed by Seppi (1997).

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  107. Since the equilibrium in Proposition 2 of Gehrig (1993), p. 108 f, weakly dominates all other equilibria it is selected as the prevailing equilibrium, see Gehrig (1993), p. 111

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Dönges, J.A. (2001). Competition for Order Flow in Market Microstructure Theory. In: Competition for Order Flow and the Theory of Global Games. Deutscher Universitätsverlag, Wiesbaden. https://doi.org/10.1007/978-3-663-07734-3_3

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  • DOI: https://doi.org/10.1007/978-3-663-07734-3_3

  • Publisher Name: Deutscher Universitätsverlag, Wiesbaden

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