Academic Research on Market Maker When the underwriter is themarket maker: An examination of trading in the IPO aftermarket, Ellis, K., Michaely, R., & O'hara, M. (2000). The Journal of Finance,55(3), 1039-1074. This paper examines aftermarket trading of underwriters and unaffiliated market makers in the threemonth period after an IPO. The study finds that the lead underwriter is always the dominant market maker; he takes substantial inventory positions in the aftermarket trading, and comanagers play a negligible role in aftermarket trading. When the underwriter is themarket maker: An examination of trading in the IPO aftermarket, Huang, R. D. (2002). The Journal of Finance,57(3), 1285-1319. This paper examines aftermarket trading of underwriters and unaffiliated market makers in the threemonth period after an IPO. The authors find that the lead underwriter is always the dominant market maker; he takes substantial inventory positions in the aftermarket trading, and comanagers play a negligible role in aftermarket trading. Time variation in liquidity: The role ofmarketmakerinventories and revenues, ComertonForde, C., Hendershott, T., Jones, C. M., Moulton, P. C., & Seasholes, M. S. (2010). The Journal of Finance,65(1), 295-331. This paper shows that marketmaker balance sheet and income statement variables explain time variation in liquidity, suggesting liquiditysupplier financing constraints matter. Using 11 years of NYSE specialist inventory positions and trading revenues, the authors find that aggregate marketlevel and specialist firmlevel spreads widen when specialists have large positions or lose money. The objective of this study is to show that compared to low volatility stocks, the liquidity of high volatility stocks is more sensitive to inventories and losses. Heterogeneous beliefs, risk, and learning in a simple asset-pricing model with amarket maker, Chiarella, C., & He, X. Z. (2003). Macroeconomic Dynamics,7(4), 503-536. This paper studies the dynamics of a simple discounted present-value asset-pricing model where agents have different risk attitudes and follow different expectation formation schemes for the price distribution. In particular, the paper concentrates on models of fundamentalists and trend followers who follow recursive geometric-decay (learning) processes (GDP) with both finite and infinite memory. Market makerinventories and stock prices, Hendershott, T., & Seasholes, M. S. (2007). American Economic Review,97(2), 210-214. This paper examines daily inventory/asset price dynamics using 11 years of NYSE specialist data. The study shows that specialists positions are negatively correlated with past price changes and positively correlated with subsequent changes. It also proposes that specialist inventories can be used to predict return continuations over a one-day horizon. The value of the designatedmarket maker, Venkataraman, K., & Waisburd, A. C. (2007). Journal of Financial and Quantitative Analysis,42(3), 735-758. This study examines the questions raised on proliferation of electronic limit order books operating without dealers raises regarding the need for intermediaries with affirmative obligations to maintain markets. In this study, a simple model of dealer participation is developed, and tested using a sample of less liquid firms that trade on the Paris Bourse. The results indicate that firms with designated dealers exhibit better market quality, and that younger firms, smaller firms, and less volatile firms choose a designated dealer. A comparison of transaction costs between competitivemarket makerand specialist market structures, Neal, R. (1992). Journal of Business, 317-334. This study compares bid-ask spreads for equity options in two market structures: the American Stock Exchange (AMEX) specialist structure and the Chicago Board Options Exchange (CBOE) competitive market maker structure. The study shows that when trading volume is low, the specialist structure is associated with significantly smaller spreads, and as volume rises, this difference appears to diminish. Comparison of trust sources of an onlinemarket-makerin the e-marketplace: Buyer's and seller's perspectives, Kim, M. S., & Ahn, J. H. (2006).Journal of Computer Information Systems,47(1), 84-94. This literature investigates the concept and degree of trust exhibited by Internet Users in Electronic Marketplaces, and online forums. In this study, the authors test and analyze trust-building models for buyers and sellers with LISREL using survey data. The results show that the buyer's and sellers trust in a market-maker is positively related to the length of their relationship to the market-maker, reputation of the market-maker, and some of the characteristics of the website hosted by the market-maker. The central bank as themarket-makerof last resort: from lender of last resort tomarket-makerof last resort, Buiter, W., & Sibert, A. (2008). The First Global Financial Crisis of the 21st Century,171. Market makeractivity on Nasdaq: Implications for trading volume, Gould, J. F., & Kleidon, A. W. (1994). Stan. JL Bus. & Fin.,1, 11. This article demonstrate how investors trading volume can be accurately measured using publicly available Nasdaq intraday transaction records that identify transactions in a particular stock, from the point of view of a Nasdaq Market maker. It also explains the structure of trading, and the rules of reporting trades on Nasdaq, using simple examples. The impact ofmarket makercompetition on NASDAQ spreads, Klock, M., & McCormick, D. T. (1999). Financial Review,34(4), 55-73.This study utilizes a comprehensive database containing monthly information on the number of market makers for about 5,288 Nasdaq securities over an eightyear period to investigate the impact of competition on spreads. This paper aims to show the impact of market marker competition on NASDAQ spreads. A practical liquidity-sensitive automatedmarket maker, Othman, A., Pennock, D. M., Reeves, D. M., & Sandholm, T. (2013). ACM Transactions on Economics and Computation,1(3), 14.This article analyses the reasons behind the failures of Automatic Market Markers. Findings show that these markers fails because they are unable to adapt to liquidity, and they run at a deficit. In this article, the authors construct a market maker that is both sensitive to liquidity and can run at a profit.