Price competition between informed limit order submitters and professional market makers allows us to capture tradeoffs between informed limit and market orders in a methodologically simple way. We apply our model to study maker-taker fees a prevalent, but controversial exchange fee system that pays a maker rebate for liquidity provision and levies a taker fee for liquidity removal. When maker-taker fees are passed through to all traders, only the total exchange fee per transaction has an economic impact, consistent with maker literature. However, when investors pay only the average exchange fee through a flat fee per transaction as is common practice in the industry maker-taker fees have an impact beyond that of a change in the total fee. An increase in the maker rebate lowers trading costs, increases trading volume, improves welfare, but decreases market participation by investors. We also thank participants at the WFA Meeting, the NFA Meeting, the 6th Erasmus Liquidity Conference, the 8th Annual Central Bank Workshop on the Microstructure of Financial Markets, the TADC-LBS Meeting, the CEA Meeting, and HEC Paris for their helpful comments. Equity trading is now highly automated: To improve the trading terms, or liquidity, offered in their limit order books, many exchanges provide cash incentives for executed limit orders. These incentives, together with advances in technology, have facilitated the entry of a new type of professional liquidity provider: In this paper, we propose a parsimonious model to study these decisions in the new trading environment, namely, in a limit order book where professional traders act as de facto market makers. Crucially, the model captures tradeoffs between market and limit orders in presence of private information. We then apply our model to study the role that cash incentives for liquidity provision play in the fees markets. Exchanges that pay cash rebates to limit order traders that provide, or make, liquidity typically levy higher fees to remove, or take liquidity on fees of market orders. This practice trading referred to as maker-taker pricing, 3 and it has been a contentious issue in regulatory and policy debates on market structure. Angel, Harris, and Spatt and Colliard and Foucault argue that maker-taker fees affect trading only through the total fee that is retained by the exchange, and that in the absence of regulatory and market frictions, the split of this fee into a maker rebate and a taker fee fees irrelevant. If a maker rebate is introduced in competitive markets, the bid-ask spread will decline by twice the maker rebate. Provided the exchange finances the maker rebate by an increase in the taker fee, the takers cum-fee trading costs, i. As a practical matter, however, many long-term investors do not pay taker fees directly and do not receive maker rebates but instead pay a flat fee per trade to their broker, while professional liquidity providers incur per-trade exchange fees and rebates. We investigate this variant on maker-taker pricing by applying trading model to a setting where we assume that investors trading only the average maker-taker fee. Existing models typically either study markets where all available liquidity is provided by competitive market makers or assume that all traders strategically choose between supplying and demanding liquidity and low they have temporal market power in liquidity provision. When liquidity providers have market power, a limit order submitter must optimally choose the limit order price, while accounting for the impact of the price choice on the probability of the trading order execution. The resulting dynamic optimization problem is especially difficult with informed liquidity provision, as the limit order price may reveal the liquidity provider s private information. In this paper, we build on Kaniel and Liu to provide a model of informed 4 See, e. See also the survey by Parlour and Seppi for further discussion. Traders who we refer to as investors are either informed or uninformed, and trade with market and limit orders; when submitting a limit order, investors compete with uninformed market makers. Price competition in liquidity provision latency potentially informed investors and uninformed market makers is a key methodological insight in our paper it allows us to circumvent the complexity of the optimization problem, because all limit orders are posted at prices that yield zero-profits to professional liquidity providers. Our setup captures the professional liquidity providers advantage in interpreting market data, such as trades and quotes. In practice, the monitoring advantage comes at a cost and professional liquidity providers are arguably at a disadvantage relative to humans or sophisticated algorithms when processing more complex information, such as news reports. We capture this difference in information processing skills by allowing some investors an informational advantage with respect to the security s fundamental value. Investors who are not informed have private valuations e. Investors with extreme valuations optimally choose to submit market orders, investors with moderate valuations submit limit orders, and investors with valuations close to the public expectation of the security s value abstain from trading. Changes in exogenous market factors e. When investors pay a flat fee in a maker-taker pricing environment, 5 Assuming that traders have liquidity needs is common practice in the literature on trading with asymmetric information, to avoid the no-trade result of Milgrom and Stokey ; modelling these needs as private valuations allows use to derive welfare implications. Consequently, the probability of a market order submission increases, and so does the trading volume. This would lead to limit paying taker fees more frequently and consequently charging investors a higher flat fee. We support this intuition numerically and find further that the increase in the flat fee is more than offset by the decline in the bid-ask spread. For a fixed total exchange fee, investors overall trading costs thus decline with an increase in the maker rebate. The marginal submitter of a market order then requires weaker information, and the price impact of a trade declines. To analyze the impact of maker-taker fees on welfare, we follow Bessembinder, Hao, and Lemmon and define a social welfare measure to reflect allocative efficiency. Specifically, with each trade, the social gains latency trade increase by the difference between the buyer s and the seller s private valuations, fees of differences in trading fees, and we define the social welfare to be the expected social gains per period. We find numerically that, for a fixed total exchange fee, the welfare increases in the maker rebate, provided the maker rebate is not too large. Limit order provision by investors is inefficient for two reasons. First, an investor who submits a limit order risks non-execution of his own order. Second, this investor possibly imposes a negative externality on the previous period investor if the earlier investor submitted a limit order on the opposite side, then that order does not execute. In the presence of professional liquidity providers who collect some of 6 When the maker rebate is sufficiently large, the spread becomes sufficiently small, and, in equilibrium, investors choose to trade exclusively with market orders. Any further increase in the maker rebate that is financed by an increase in low taker fee leads to a decline in the quoted spreads, but yields no further economically meaningful implications. Our paper is most closely related to Colliard and Foucault and Foucault, Kadan, and Kandelwho theoretically analyze the impact of maker-taker fees. Colliard and Foucault study trader behavior in a model where symmetrically informed traders choose between limit and market orders. They show that, absent frictions, the split between maker and taker fees has no economic impact, and they focus on the impact of the total fee charged by an exchange. Foucault, Kadan, and Kandel arguethatinthepresence ofaminimumticksize, limitorderbookprices may not adjust sufficiently to compensate traders for changes in the split between maker and taker fees. They then show that exchanges may use maker-taker pricing to balance supply and demand of liquidity, trading traders exogenously act as makers or and. Skjeltorp, Sojli, and Taker support theoretical predictions of Foucault, Kadan, and Kandel empirically, using exogenous changes in maker-taker fee structure and a technological shock for liquidity takers. Rosu finds that the prediction of Colliard and Foucault on the neutrality of the and of the total fees holds in presence of asymmetric information. Our predictions on spreads, price impact, and volume, and the prediction of Colliard and Foucault are supported empirically by Malinova informed Parkwho study the impact of the introduction of maker rebates on the Toronto Stock Exchange. Our work is also closely linked to Degryse, Achter, and Wuytswho study the impact of the post-trade clearing and settlement fees. In their model, the clearing house may set a flat fee for all trades or impose different fees, depending on whether a trade was internalized. They find that the fee structure affects the welfare of market participants, and that the optimal structure depends on the size of the clearing fee. The maker-taker pricing model is related to the payment for order flow model, see, e. Our analysis of a limit order market with competitive informed liquidity provision to the broader theoretical literature on specialist and limit order markets, see, e. We complement the theoretical literature that focuses on the trading strategies of professional liquidity providers, see e. Trading is conducted via limit order book. Investors choose limit posting a limit and to trade at pre-specified prices and submitting a market order to trade immediately with a previously posted limit order. Additionally, we assume the presence of professional liquidity providers, who choose to act as market makers, and to only submit limit orders. These traders possess a monitoring 7 See also the survey by Parlour and Seppi for further related papers. We assume that they are uninformed and that they have no liquidity needs. Professional liquidity providers compete in the sense of Bertrand competition, are continuously present in the market, and ensure that the limit order book is always full. There is a single risky security limit an unknown liquidation value. Function g is symmetric and zero on [0,1]. There is a continuum of risk-neutral investors. At each period t, a single investor randomly arrives at the market. Upon entering the market, the investor is either informed about the fundamental value or endowed with liquidity needs. An investor can submit an order upon arrival and only then. He can buy or sell a single unit round lot of the risky security, or abstain from trading. Similarly for the decision to sell. An investor may submit at most one order, and upon the order s execution or cancellation the investor leaves the market forever. There is continuum of professional liquidity providers who are always present in the market. They hold a monitoring advantage over investors and react to changes in the limit order book quicker than other market participants. These traders act as market makers and post limit orders in response to changes in the limit order book. They compete in prices in the sense of Bertrand competition. Professional liquidity providers are risk-neutral, they fees not receive any information about the security s fundamental value, and they do not have liquidity needs. The Limit Order Book. Trading is organized via limit order book, which is comprised of limit orders. Limit orders last for one period. Arguably, this simplifying assumption is particularly realistic in presence of professional liquidity providers, as investors with lower monitoring intensities may fear that their orders become stale and will be picked off by the professional liquidity providers. Professional liquidity providers ensure that the limit order book is always full by submitting a limit order when there is no standing limit order on the buy or the sell side. The limit order book thus always contains one buy limit order and one sell limit order, upon arrival of an investor in period t. A trade occurs in period t when the investor that arrives in period t chooses to submit a market order. The limit order book is maintained by an exchange that charges time-invariant fees for executing orders. The focus of this paper is on maker-taker fees, which depend on the order type market or limitbut do not depend on whether an order is a buy or a sell. To simplify the exposition, in the current version we assume that the total exchange fee per transaction is 0 and focus on the split of this 8. Professional liquidity providers receive maker rebates for executed limit orders. We study two settings. In the first, investors pay the taker fees and maker rebates on a trade-by-trade basis. In the second, flat-fee setting, investors only pay latency average maker-taker fee, through a flat fee per transaction. Our flat-fee setting reflects a common practice in the industry: Investors and professional liquidity providers observe the history of transactions as well as limit order low and maker. We denote thehistory oftradesandquotes upto but notincluding periodtby H t. The structure of the model is common knowledge among all market participants, but an investor s liquidity needs and his knowledge of an innovation maker the fundamental value are private. Professional Liquidity Provider Information. Professional liquidity providers are able to detect whether a newly posted limit order stems from an investor maker liquidity and informational needs or from other professional liquidity providers. This assumption ensures that the model is tractable. We believe that it is consistent with reality, because professional, fees high-frequency, liquidity providers are allegedly good at identifying, for instance, larger institutional orders. Further, within our model, professional liquidity providers react virtually instantaneously to changes in the limit order book compared maker other traderswhereas investors who trade for liquidity and informational reasons arrive at discrete time intervals consequently, limit orders that are posted by professional liquidity providers are identified by the reaction time. Finally, from a technical perspective, this assumption is equivalent to assuming presence of a single professional liquidity provider who chooses to act competitively. We model intraday trading. Periods are measured in discrete units denoted by t. Each period marks the arrival of an investor. At the beginning of any period t, and limit order book is full in the sense that it contains one buy limit order and one sell limit order. This investor posts a limit or a market order, or abstains from trading. When a market order is posted, it executes against a limit order that was posted in period t 1, and the investor leaves the market forever. The limit order book immediately reacts to the information contained in the period t market order and the professional liquidity providers post limit orders to buy and sell. As with market orders, the limit order book reacts to the information contained in the period t limit order, with a professional liquidity provider posting a limit order on the opposite side of the book. The payoff to an investor who buys one unit of the security in period t is given by the difference between the security s fundamental value in period t, V t, and the price that the investor paid for this unit; similarly for a sell decision. We normalize the payoff to a non-executed order to 0. Investors are risk neutral, and they aim to taker their expected payoffs. The period t investor has the following expected payoffs to submitting, respectively, a market buy order to trade 12 The assumption that limit orders last for a single period is common in the literature, see, e. We focus on the intraday trading, and we assume no discounting. Payoffs to sell orders are analogous. Professional Liquidity Provider Payoffs. A professional liquidity provider observes the period t investor s action before posting her period t limit order. Moreover, she will post a limit buy order in period t only if the period t investor does not post a buy limit order. All Pay Maker-Taker Fees In this section, we assume latency maker rebates and taker fees are passed through to all market participants on a per-trade basis. We look for an equilibrium, in which maker liquidity providers post competitive limit orders and make zero profits, in expectation. We denote the equilibrium bid and ask prices in period t by bid t and ask t, respectively, and we use MB t and MS t denote, respectively, the period t investor s decisions to submit a market buy order price ask t and a market sell order at price bid t. The professional liquidity provider payoffs, given by taker 4then imply the following competitive equilibrium pricing rules, for the maker rebate f: Investor Actions with Competitive Liquidity Provision. We focus on investor choices to buy; sell decisions are analogous. An investor can choose to submit a market order or a limit order, and, if he chooses to submit a limit order, technically, he and also choose the limit price. We search for an equilibrium where professional liquidity providers ensure that bid and ask prices are set competitively and equal the expected security value, conditional on the information available to latency liquidity providers. An investor s choice of the limit price is thus mute, since a limit order that Because an investor is always able to obtain a zero profit by abstaining from trade, we restrict attention to limit orders posted at the competitive, equilibrium prices. Formally, the zero probability of execution for limit orders posted at non-competitive prices is achieved by defining appropriate beliefs of market participants, regarding the information content of a limit order that is posted at an out-of-the-equilibrium price e. The appropriate definition of out-of-equilibrium beliefs is frequently necessary to formally describe equilibria with asymmetric information. To see the role of these beliefs in our model, observe first that when an order is posted at the prescribed, competitive equilibrium price, market participants derive the order s information content by Bayes Rule, using their knowledge of equilibrium strategies. The knowledge of equilibrium strategies, however, does not help market participants to assess the information content of an order that cannot occur in equilibrium instead, traders assess such an order s information content using out-of-the-equilibrium beliefs. We describe these beliefs in Appendix A, and we focus on prices and actions that occur in equilibrium in the main text. Because innovations to the fundamental are independent across periods, all market participants interpret the transaction history in the same manner. The above insight, together with conditions 7 - 8 on the equilibrium bid and ask prices, allows us to rewrite investor payoffs, given by expressions 2 - 3 as: Equations 11 - 12 illustrate, in particular, that investor payoffs are independent of the exchange fees, provided the total exchange fee is 0. In the Internet Appendix, we further show that, for fees non-zero exchange fee, the levels of maker the rebate and the taker fee only affect investor payoffs through the total exchange fee, consistent with Colliard and Foucault Proposition 1 Independence of the Maker-Taker Split For a fixed total exchange fee, investors equilibrium strategies and payoffs do not depend on the split of the total fee into maker and limit fees. Investor Equilibrium Decision Rules. An investor submits an order to buy if, conditional on his information and on informed submission of his order, his expected profits are non-negative. Moreover, conditional on the decision to trade, an investor chooses the order type that maximizes his expected profits. An investor abstains from trading if he expects to make negative profits from all order types. Expressions trading - 12 illustrate that the period t investor payoffs, conditional on the order s execution, are determined by this investor s informational advantage with respect to the period t innovation to the fundamental value relative to the informed Our model is stationary, and in what follows, we restrict attention to investor decision rules taker are independent of the history but are solely governed by an investor s private valuation or his knowledge of the innovation to the security s value. When the decision rules in period t are independent of the history H t, the public expectation limit the period t innovation, conditional on the period t investor s action, does not depend on the history either. Expressions 11 - 12 reveal that neither do investor equilibrium payoffs. Our setup is thus internally consistent in informed sense that the assumed stationarity of the investor decision rules latency not preclude investors from maximizing their payoffs. We thus focus on decision rules with respect to this sum, which we refer to as investor s valuation. We focus on equilibria where investors use both limit and Lemma 1 Informativeness of Trades and Quotes In an equilibrium where investors use both limit and market orders, both trades and investors limit orders contain fees about the security s fundamental value; a buy order increases the expectation of the security s value and a sell order decreases it. Lemma 2 Equilibrium Market and Limit Order Submission In any equilibrium with symmetric time-invariant maker, investors use threshold strategies: To understand the intuition behind Lemma 2, observe first that, conditional on order execution, an investor s payoff is determined, loosely, by the advantage that his valuation provides relative to the information revealed by his order trading expressions 11 - Second, since market orders enjoy guaranteed execution, whereas limit orders do not, for limit orders to be submitted in equilibrium, the payoff to an executed limit order must exceed that of an executed market order. In such an equilibrium, trading roles are pre-defined and maker-taker fees have no economic impact. For this ranking of price impacts to occur, investors who submit limit orders must, on average, observe lower values of the innovation than investors who submit market buy orders. With symmetric distributions of both, the innovations and investor private values, we arrive at the previous lemma. And decisions aretakenfor ordersto sell. Investors with valuations of z M and z L are marginal, in the sense that the investor with the valuation z M is indifferent between submitting a market buy order and a limit buy order, and the investor with the valuation z L is indifferent between submitting a limit buy order and abstaining from trading. Given thresholds z M and z L, these expectations and probabilities are well-defined and can be written out explicitly, The choice of notation for the public expectation of the security s value recognizes that this expectation coincides with a transaction price trading period t 1 when such a transaction occurs. Since the innovations are distributed symmetrically around 0, the public expectation of the period t value of the security at the very beginning of period t, E[V t H t ], also equals p t 1. In the absence of fees, the informed spread is positive as long as market orders are informative. When f 0, however, this is no longer the case. We prove the following existence theorem in Appendix A: These threshold values constitute an equilibrium in a setting taker investors pay maker-taker fees on a per-trade basis, for any history H t, given competitive equilibrium prices, bid t and ask t in 16 - 17for the following trader decision rules, if condition 20 is satisfied. Investors sell decisions are symmetric to buy decisions. Investors Pay Flat Fees We now study the market where investors pay only the average taker fee, through a flat fee per trade. Long-term investors typically trade through a broker, and the flat-fee setting reflects a common practice by brokers of levying a flat fee per trade on their clients. Conditional upon a transaction, the exchange fee incurred by the broker is the taker fee f for the period t investor s market order with certainty plus, if this order low against the period t 1 investor s limit order, the broker will receive the maker rebate f. The expected fee f MS t per investor that the exchange receives from the broker upon an execution of a market sell order in period t is given by: As in Section 2, we focus on an equilibrium where investors use stationary, timeinvariant threshold strategies with respect to their valuation z t. Consequently, the expected per-investor fee does not depend on the type of the market order or on the period t. Investor payoffs, however, are affected by the flat fee f. The split between the taker fee and the maker rebate will thus be economically relevant in this setting. In particular, when the maker rebate is positive, brokers always set a positive flat fee despite the zero total fee. The presence of professional liquidity providers ensures that market orders always execute, whereas limit orders only execute when another investor submits a market order. Professional liquidity providers must capture a fraction of the maker rebates, leaving investors to pay a positive exchange fee. Lemma 3 Flat Fee The average exchange fee per investor trade f is positive when the maker rebate is positive, and it is negative when the maker rebate is negative. Our further results on the flat fee setting are numerical. Specifically, we look for an equilibrium where investors use threshold rules that are symmetric and that do not depend on the history, such that investors with most extreme valuations trade with market orders, investors with moderate valuations trade with limit orders, and investors with valuations around 0 abstain from trading. The equilibrium indifference conditions are analogous to conditions 14 - 15except that they are adjusted for the exchange fees, using 25 - The quoted bid-ask spread is the difference between the ask and bid prices. The cum-fee spread additionally accounts for the fee paid by a submitter of a market order; this fee is the taker fee in the all pay maker-taker fees setting and the flat fee f in the flat fee setting. We measure market participation by the probability that an investor does not abstain from submitting an order, and we measure trading volume by the probability that an investor submits a market order since market orders always execute in our setting. Theorem 1 implies the following result for the setting where fees market participants pay maker-taker fees per-trade. If it were not unique, we would focus on the one that delivers the smallest bid-ask spread in equilibrium. All Pay Maker Taker Fees In an equilibrium of the symmetric fee setting, thresholds z M and z L, market participation, trading volume, and cum-fee bid-ask spreads are independent of f. Quoted bid askspreads decline in f. Trading Volume and Market Participation. Equations 23 - 24which define investor payoffs in the flat fee setting, illustrate that, ceteris paribus, an increase in the maker rebate provides investors with incentives to switch from limit to market orders. All else equal, such an increase will decrease the spread, thus increasing the payoff to market orders and simultaneously reducing the payoff to limit orders. In contrast to the all-pay maker-taker fee setting, however, changes in the bid-ask spread are not offset by the changes in investor fees because the flat fee charged by brokers does not depend on the order type. Since trade occurs in our model when a market order is submitted, an increase in the probability of a market order implies an increase in trading volume. The impact on investors who were previously indifferent between submitting a limit order and abstaining from trading is more complex. On the one hand, ceteris paribus, as traders increase their usage of market orders, limit orders are submitted by less informed traders, the price impact of a limit order maker, and limit orders become more attractive. On the other hand, an increase in the maker rebate leads to a decline in the bid-ask spread, making limit order prices less attractive to investors who do not receive the rebate. Numerical simulations reveal that the latter effect dominates in our setting; that is, market participation declines. What happens when the maker rebate is very large? As the taker fee and the maker rebate increase, threshold z M decreases and threshold z L increases. When the maker rebate is sufficiently high relative to the spreada limit order yields negative profits to investors in expectation, because they do not receive maker rebates. When this happens, professional liquidity providers become the only submitters of limit As a consequence, the flat fee equals the taker fee. The marginal submitter of a market order is then exactly indifferent between submitting a market order and abstaining from trading, and he earns zero expected profits. As with the all pay maker-taker fees setting, an fees fails to exist when the maker rebate is so large that the bid-ask spread becomes nonpositive. Consequently, as the maker fee f increases from 0, quoted spreads widen. Investors pay a flat fee in this case, the fee is negative, so they receive a flat positive rebatetherefore market orders become less attractive to them and limit orders become more attractive. Intuitively, when the maker fee is positive and high f is low and negativethe Financial Markets Itay Goldstein Wharton School, University of Pennsylvania 1 Trading and Price Formation This line of the literature analyzes the formation of prices in financial markets in a setting. The Effect of Maker-Taker Fees on Investor Order Choice and Execution Quality in U. Stock Markets Shawn M. O Donoghue October 30, Abstract Equity exchanges competing for orders are using new pricing. Trading Fees and Efficiency in Limit Order Markets. Jean-Edouard Colliard Paris School of Economics 48 boulevard Jourdan Paris, France colliard pse. The Microstructure of Financial Markets, trading Jong and Rindi Financial Market Microstructure Theory Based on de Jong and Rindi, Chapters 2 5 Frank de Jong Tilburg University 1 Determinants of the. Toxic Arbitrage Thierry Foucault Roman Kozhan Wing Wah Tham Abstract Arbitrage opportunities arise when new information affects the price of one security because dealers in other related securities are. Pricing Liquidity in Electronic Markets Foresight Driver Review Foresight Horizon Scanning Centre, Government Office for Science Contents Executive summary Trading Fees and Effi ciency in Limit Order Markets. Market Power and Efficiency in Card Payment Systems: Cabral New York University and CEPR November 1 Introduction Beginning with their seminal paper. A new model of a market maker M. Cheung Master s thesis Economics and Informatics Specialisation in Computational Economics and Finance Erasmus University Rotterdam, the Netherlands January 6. Do retail traders suffer from high frequency traders? Katya Malinova, Andreas Park, Ryan Riordan November 15, Millions in Milliseconds Monday, June 03, The Effects of Make and Take Fees in Experimental Markets Vince Bourke and David Porter Economic Science Institute Chapman University Abstract: We conduct a series of experiments to examine the effects. Chapter 7 Sealed-bid Auctions An auction is a procedure used for selling and buying items by offering them up for bid. Auctions are often used to sell objects that have a variable price for example oil. Goal Market Maker Pricing and Information about Prospective Order Flow EIEF October 9 Use a risk averse market making model to investigate. Online Appendix Feedback Effects, Asymmetric Trading, and the Limits to Arbitrage Alex Edmans LBS, NBER, CEPR, and ECGI Itay Goldstein Wharton Wei Jiang Columbia May 8, 05 A Proofs of Propositions and. A Theory trading Intraday Patterns: Volume and Price Variability Anat R. Admati Paul Pfleiderer Stanford University This article develops a theory in which concentrated-trading patterns arise endogenously as. Decimalization and market liquidity Craig H. Furfine On January 29, 21, the New York Stock Exchange NYSE implemented decimalization. Beginning on limit Monday, stocks began to be priced in dollars and. Journal of Financial Economics 45 3 8 Symposium on market microstructure: Focus on Nasdaq Informed. William Schwert William E. Simon Graduate School of Business Administration, University of Rochester. News Trading and Speed Thierry Foucault, Johan Hombert, and Ioanid Rosu HEC High Frequency Trading Conference Plan Plan 1. Introduction - Research questions 2. Is news trading different? Institutional tut Finance Financial Crises, Risk Management and Liquidity Markus K. Dong BeomChoi Taker University 1 Market Making Limit Orders Limit order price contingent. MARKET STRUCTURE AND INSIDER TRADING WASSIM DAHER AND LEONARD J. 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Regulatory priorities for capital formation and growth. How aggressive are high frequency traders? Empirical Comparison Janyl Jumadinova, Prithviraj Dasgupta Computer Science Department University of Nebraska, Omaha, NEUSA E-mail: September 29, Can Brokers Have it All? Fast Trading and Prop Trading B. Moinas Toulouse School of Economics December 11, Market Microstructure Confronting many viewpoints 3 New market organization, new financial. Aggressiveness in Investor Order Submission Strategy in the Absence of Trading: Evidence from the Market Preopening Period. Michael Bowe Stuart Hyde Ike Johnson Preliminary draft: Not for quotation Abstract. HFT and the Hidden Cost of Deep Liquidity In this essay we present evidence that high-frequency traders HFTs profits come at the expense of investors. In competing to earn spreads and exchange rebates. A Memo on Competitive Equilibriums and Trade in Insurance Markets Nathaniel Hendren January, Abstract Both Akerlof and Rothschild and Stiglitz show that. We analyze trading potential conflict of interest between. Equilibrium in Competitive Insurance Markets: An Essay informed the Economic latency Imperfect Information By: Michael Rothschild and Joseph Stiglitz Presented by Benjamin S. Barber IV, Xiaoshu Bei, Zhi Chen, Shaiobi. The Financial Review 40 Price Movement Effects on the State of the Electronic Limit-Order Book Yue-cheong Chan Hong Kong Polytechnic University Abstract This paper investigates public-trader. Problem Set Foundations of Financial Markets Instructor: Erin Smith Summer 20 Due date: Beginning of class, May 3. Research Summary Saltuk Ozerturk A. Latency on Information Acquisition in Markets and Agency Issues Between Investors and Financial Intermediaries An important dimension of the workings of financial markets. The Transfer Price Problem A. Short-sale Constraints, Bid-Ask Spreads, and Information Acquisition Hong Liu Yajun Wang November 15, Olin Business School, Washington University in St. Louis and CAFR, liuh wustl. Primary market is a market for new securities. Income Tax Valuation Insights Buyers and Sellers of an S Corporation Should Consider the Section Election Robert P. Schweihs There are a variety of factors that buyers and sellers consider when deciding. Equilibrium High Frequency Trading B. Moinas Fifth Annual Conference of the Paul Woolley Centre for the Study of Capital Market Dysfunctionality London, June What s High Frequency. ECON Game Theory Lecture Notes Auctions Luca Anderlini Spring These notes have been used before. If you can still spot any errors or have any suggestions for improvement, please let me know. OPTION PRICING Options are contingency contracts that specify payoffs if stock prices reach specified levels. A call option is the right to buy a stock at a specified price, X, called the strike price. Chapter 8 And This chapter examines the causes and consequences of inflation. Although the presentation differs somewhat from that. SLICE ORDER IN TASE Low TO HIDE? Mack Robinson College of Business Georgia State University Atlanta, GA August 21, ABSTRACT. Start display at page:. Download "Informed Trading and Maker-Taker Fees in a Low-Latency Limit Order Market". Heather Jennings 1 years ago Views: Wharton Limit, University of Pennsylvania Financial Markets Itay Goldstein Wharton School, University of Pennsylvania 1 Trading and Price Formation This line of the literature analyzes the formation of prices in financial markets in a setting More information. The Effect of Maker-Taker Fees on Investor Order Choice and. Execution Quality in U. Stock Markets The Effect of Maker-Taker Fees on Investor Order Choice and Execution Quality in U. O Donoghue October 30, Abstract Equity exchanges competing for orders are using new pricing More information. Financial Market Microstructure Theory The Microstructure of Financial Markets, de Jong and Rindi Financial Market Microstructure Theory Based on de Jong and Rindi, Chapters 2 5 Frank de Jong Tilburg University 1 Determinants of the More information. Abstract Toxic Arbitrage Thierry Foucault Roman Kozhan Wing Wah Tham Abstract Arbitrage opportunities arise when new information affects the price of one security because dealers in other related securities are More information. Pricing Liquidity in Electronic Markets Pricing Liquidity in Electronic Markets Foresight Driver Review Foresight Horizon Scanning Centre, Government Office for Science Contents Executive summary A Comment on Rochet and Tirole Market Power and Efficiency in Card Payment Systems: Cabral New York University and CEPR November 1 Introduction Beginning with their seminal paper, More information. A new model of a and maker A new model of a market maker M. Cheung Master s thesis Economics and Informatics Specialisation in Computational Economics and Finance Erasmus University Fees, the Netherlands January 6, More information. The Effects of Make and Take Fees in Experimental Markets The Effects of Make and Take Fees in Experimental Markets Vince Maker and David Porter Economic Science Institute Chapman University Abstract: We conduct a series of experiments to examine the effects More information. Sealed-bid Auctions Chapter taker Sealed-bid Auctions An auction is a procedure used for selling and buying items by offering them up for bid. Auctions are often used to sell objects that have a variable price for example oil More information. Goal Market Maker Pricing and Information about Prospective Order Flow Goal Market Maker Pricing and Information about Prospective Order Flow EIEF October 9 Use a risk averse market making model to investigate. Online Appendix Informed Effects, Asymmetric Trading, and the Limits to Arbitrage Online Appendix Feedback Effects, Asymmetric Trading, and the Limits to Arbitrage Alex Edmans LBS, NBER, CEPR, and ECGI Itay Goldstein Wharton Wei Jiang Columbia May 8, 05 A Proofs of Propositions and More information. Volume and Price Variability A Theory of Intraday Patterns: Admati Paul Pfleiderer Stanford University This article develops a theory in which concentrated-trading patterns arise endogenously as More information. Decimalization and low liquidity Decimalization and market liquidity Craig H. Beginning on that Monday, stocks began to be priced in dollars and More information. Symposium on market taker Focus on Nasdaq Journal of Financial Economics 45 3 8 Symposium on market microstructure: Simon Graduate School of Business Administration, University of Rochester, More information. News Trading and Speed News Trading and Speed Thierry Foucault, Johan Hombert, and Ioanid Rosu HEC High Frequency Trading Conference Plan Plan 1. Brunnermeier Institutional tut Finance Financial Crises, Risk Management and Liquidity Markus K. Dong BeomChoi Princeton University 1 Market Making Limit Orders Limit order price contingent More information. MARKET STRUCTURE AND INSIDER TRADING. Insider Trading, Stock prices, Correlated signals, Kyle model MARKET STRUCTURE AND INSIDER TRADING WASSIM DAHER AND LEONARD J. In this paper we examine the real and financial effects of two insiders trading in a static Jain Mirman model Henceforth More information. The Term Structure of Interest Rates, Spot Rates, and Yield to Maturity Chapter 5 How to Value Bonds and Stocks 5A-1 Appendix 5A The Term Structure of Interest Rates, Spot Rates, and Yield to Maturity In the main body of this chapter, we have assumed that the interest rate More information. An Interactive Exercise Market Microstructure: An Interactive Exercise Jeff Donaldson, University of Tampa Donald Flagg, University of Tampa Latency Although a lecture on microstructure serves to initiate the inspiration of More information. Sharing Online Advertising Maker with Consumers Sharing Online Advertising Revenue with Consumers Yiling Chen 2, Arpita Ghosh 1, Preston McAfee 1, and David Pennock 1 1 Yahoo! Forthcoming in the Encyclopedia of Quantitative Finance ABSTRACT 1 Specialist Markets Forthcoming in the Encyclopedia of Quantitative Finance ABSTRACT The specialist market system is defined as a hybrid market structure that includes an auction component e. The Impact of Competition and Information on Intraday Trading The Impact of Competition and Information on Intraday Trading Katya Malinova and Andreas Park University of Toronto April 5, Abstract In a dynamic model limit financial market trading multiple heterogeneously More information. Momentum Traders in the Housing Market: Survey Evidence and a Search Model Federal Reserve Bank of Informed Research Department Staff Report March Momentum Traders in the Housing Market: Survey Evidence and a Search Model Monika Piazzesi Stanford University and National More information. Financial Markets and Institutions Abridged 10 th Edition Financial Markets and Institutions Abridged 10 th Edition by Jeff Madura 1 12 Market Microstructure and Strategies Chapter Objectives describe the common types of stock transactions explain how stock transactions More information. January 13 Abstract We examine whether high-frequency traders HFT increase the transaction costs of slower institutional More information. Review of Basic Options Concepts and Terminology Review of Basic Options Concepts and Terminology March 24, 1 Introduction The purchase of an options contract gives the buyer the right to buy call options contract or sell put options contract some More information. Asymmetric Information 2 Asymmetric nformation 2 John Y. A Theory of Capital Structure, Price Impact, and Long-Run Stock Returns under Heterogeneous Beliefs A Theory informed Capital Structure, Price Impact, and Long-Run Stock Returns under Heterogeneous Beliefs Onur Bayar College of Business, University of Texas at San Antonio Thomas J. Chemmanur Carroll School More information. Sin Taxes and Health Subsidies Optimal Paternalism: High frequency trading High frequency trading And Biais Toulouse School of Economics Presentation low for the European Institute of Financial Regulation Paris, Sept Outline 1 Description 2 Motivation for HFT More information. THE EQUITY OPTIONS STRATEGY GUIDE THE EQUITY OPTIONS STRATEGY GUIDE APRIL Table low Contents Taker 2 Option Terms and Concepts 4 What is an Option? Frequent Batch Auctions FIA PTG Whiteboard: As an advocate for data-driven decision-making, More information. Wharton School, University of Pennsylvania Capital Structure Itay Goldstein Wharton School, University of Pennsylvania 1 Debt and Equity There are two main types of financing: The practice of using computer software More information. Monika Piazzesi and Martin Schneider Momentum traders in the housing market: The first part presents More information. Execution Costs of Exchange Traded Funds ETFs MARKET INSIGHTS Execution Costs of Exchange Traded Funds ETFs By Jagjeev Dosanjh, Daniel Joseph and Vito Mollica August Edition 37 in association with THE COMPANY ASX is a multi-asset class, vertically More information. Notes on the Kyle Model Finance A. Notes on the Informed Model These notes consider the single-period model in Kyle Continuous Auctions and Insider Trading, Econometrica 15, More information. Online and Offline Selling in Limit Order Markets Online and Offline Selling in Limit Order Markets Kevin L. Completely automated electronic More information. 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Stock market simulation with ambient variables and multiple agents Stock market simulation with ambient variables and multiple agents Paolo Giani Cei 0. Economics, VU station B More information. A person who believes that the price of a particular security or the market as a whole will go lower. More generally, it refers More information. Credible Discovery, Settlement, and Negative Expected Value Suits Credible iscovery, Settlement, and Negative Expected Value Suits Warren F. This paper introduces the option to conduct discovery into a model of low bargaining More information. The Blurring of Traditional Definitions Technology and Liquidity Provision: November 3, Joel Hasbrouck and Gideon Saar are from the Stern School of Informed, More information. Mao YE University of Illinois, College of Business Abstract This paper examines More information. A Comparison of US and China. April 30, Session 5 Joel Hasbrouck www. Empirical Comparison Electronic Market-Makers: Can Brokers Have it All? Fast Trading and Prop Trading Fast Trading and Prop Trading B. Moinas Toulouse School of Economics December 11, Market Microstructure Confronting many viewpoints 3 New market organization, new financial More information. Not for quotation Maker More information. HFT and the Hidden Cost of Deep Liquidity HFT and the Hidden Cost of Deep Liquidity In this essay we present evidence that high-frequency traders HFTs profits come at the expense of investors. In competing to earn spreads and exchange rebates More information. A Memo on Competitive Equilibriums and Trade in Insurance Limit Unraveling versus Unraveling: A Memo on Competitive Equilibriums and Trade in Insurance Markets Nathaniel Hendren January, Abstract Both Akerlof and Rothschild and Stiglitz show that More information. We analyze the potential conflict of interest between More information. An Essay on the Economic of Imperfect Information Equilibrium in Competitive Insurance Markets: Barber IV, Xiaoshu Bei, Zhi Chen, Shaiobi More information. This working paper More information. Price Movement Effects on the State of the Electronic Limit-Order Book The Financial Review 40 Price Movement Effects on the State of the Electronic Limit-Order Book Yue-cheong Chan Hong Kong Polytechnic University Abstract This paper investigates public-trader More information. Problem Set 1 Foundations of Financial Markets Instructor: Erin Smith Summer Due date: Beginning of class, May 31 Problem Set Foundations of Financial Markets Instructor: Research Summary Saltuk Ozerturk Research Summary Saltuk Ozerturk A. Research on Information Acquisition in Markets and Agency Issues Between Investors and Financial Intermediaries An important dimension of the workings of financial markets More information. Short-sale Constraints, Taker Spreads, and Information Acquisition Short-sale Constraints, Bid-Ask Spreads, and Information Acquisition Hong Liu Yajun Wang November 15, Olin Business School, Washington University in St. When firms need to raise capital, they may issue securities to the public by investment bankers. Secondary market is More information. Buyers and Sellers of an S Corporation Should Consider the Section Election Income Tax Valuation Insights Buyers and Sellers of an S Corporation Should Consider the Section Election Robert P. Schweihs There are a variety of factors latency buyers and sellers consider when deciding More information. Equilibrium High Frequency Trading Equilibrium High Frequency Trading B. Moinas Fifth Annual Conference of the Paul Woolley Centre for the Study of Capital Market Dysfunctionality London, June What s High Frequency More information. For banks, More information. ECON Game Theory. Luca Anderlini Spring ECON Game Theory Lecture Notes Auctions Luca Anderlini Spring These notes have been used before. FINANCIAL ECONOMICS OPTION PRICING OPTION PRICING Options are contingency contracts that specify payoffs if stock prices reach specified levels. Although the presentation differs somewhat from that More information. Mack Taker College of Business Georgia State University Trading, GA August 21, ABSTRACT More information.
The Top Secret Trade Deal You Need to Know About
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