We analyze the impact of time series dependence in market microstructure noise on the properties of estimators of the integrated volatility of an asset price based on data sampled at frequencies high enough for that noise to be a dominant consideration. We show that combining two time scales for that purpose will work even when the noise exhibits time series dependence, analyze in that context a refinement of this approach based on multiple time scales, and compare empirically our different estimators to the standard realized volatility.

Stanford University for helpful comments and suggestions. We are especially grateful to Michael Fleming for sharing numerous insights on the Treasury market. Hendershott gratefully acknowledges support from the National This paper examines the choice of trading venue by dealers in U.S. Treasury securities to determine what services, if any, human intermediaries provide that are difficult or impossible to replicate in a fully automated trading system. When a Treasury security goes “off the run ” its trading volume drops by more than 90%. This decline in trading volume, which is unrelated to the underlying market microstructure, allows us to examine the pure matching function of intermediaries in financial markets. When trading is thin, an intermediary’s knowledge of the market and its participants may uncover hidden liquidity that facilitates quicker and more efficient matching of customer orders. Thus, our model predicts that human intermediaries will attract a greater market share when the level of trading volume is low. Consistent with this prediction, the market share of fully electronic intermediates falls Electronic trading systems have been steadily increasing their share of securities trading in almost all financial markets. As the amount of automation in financial markets increases, it is

for the considerable amount of time they have spent discussing this topic with me; the Zell Center for Risk Research for its financial support; and the many faculty members and PhD students at the Kellogg School of Management, Northwestern University and at the Northwestern University School of Law for assistance on this paper. Please contact the author before In this paper I examine the impact of high frequency trading (HFT) on the U.S. equities market. I analyze a unique dataset to study the strategies utilized by high frequency traders (HFTs), their profitability, and their relationship with characteristics of the overall market, including liquidity, price discovery, and volatility. The 26 HFT firms in the dataset participate in 68.5 % of the dollar-volume traded. I find the following key results: (1) HFTs tend to follow a price reversal strategy driven by order imbalances, (2) HFTs earn gross trading profits of approximately $2.8 billion annually, (3) HFTs do not seem to systematically engage in a non-HFTr anticipatory trading strategy, (4) HFTs ’ strategies are more correlated with each other than are non-HFTs’, (5) HFTs ’ trading levels change only moderately as volatility increases, (6) HFTs add substantially to the price discovery process, (7) HFTs provide the best bid and offer quotes for a significant portion of the trading day and do so strategically so as to avoid informed traders, but provide only one-fourth as much book depth as non-HFTs, and (8) HFTs

This paper uses unique data from the London Stock Exchange to examine how the anonymity and liquidity of alternative trading venues affect dealers ’ decisions about where to place interdealer trades. During the period we study, dealers could place non-anonymous trades with each other in the public market or use one of four anonymous and private brokered trading systems. Contrary to intuition and some theory, we find adverse selection is less prevalent in the anonymous brokered markets. We hypothesize and document that this pattern can be explained by the way dealers “price ” the adverse selection risk inherent in trading with other dealers. We also discuss how our findings may bear on the increasing fragmentation of securities markets. In this paper we ask why London dealers use more than one trading venue to trade with one another. We argue that the presence of multiple trading venues allows dealers to price better the adverse selection risk present in interdealer trades. In particular, differences in the exclusivity, liquidity, anonymity, and post-trade transparency of each system permit a more efficient sorting of interdealer trades than if

The Internet reduces the cost of exchanging information. Electronic markets exploit this opportunity to enable investors to place quotes at very little cost and compete with incumbent trading systems. Does this quasi--free entry situation lead to competitive liquidity supply? We analyze trades and order placement on Nasdaq and a competing electronic order book, Island. While Island traders often undercut Nasdaq quotes, they undercut each other much less frequently. The coarse tick size prevailing on Nasdaq in 2000 was considerably reduced in 2001, while the Island tick remained very thin. This resulted in tighter spreads on both markets. These findings are inconsistent with the perfect competition hypothesis, under which Island traders should undercut each others as much as Nasdaq quotes, and quote zero-profits spreads, unaffected by a drop in the Nasdaq tick. We also estimate and test a theoretical model of competition in limit orders, and find that Island limit orders earned rents in 2000, but not in 2001. Our findings suggest that perfect competition cannot be taken for granted, even in modern financial markets, and that competition among markets complements competition among traders.

This paper examines the interaction between a stock exchange and a crossing network (dark pool) in which buy and sell orders are passively matched using the price set by the stock exchange. The results show that the crossing network harms price discovery and the relative lack of revealed information most strongly a¤ects stocks with high uncertainty in their funda-mental values. However, the crossing network may reduce the severity of the adverse selection problem in the exchange and increase its liquidity. I …nd that an increase in the uncertainty of the fundamental value of the asset increases the transaction costs in both markets, but stocks with higher fundamental value uncertainty are more likely to have higher market shares in the crossing network. In contrast to the results from previous studies, I …nd that an increase in liquidity trading in the crossing network may decrease execution probability. The impact of di¤erent allocation rules in the crossing network on market outcomes is also examined. JEL Classi…cation: G10 G20

Using order book information from the Australian Stock Exchange (ASX), we examine whether (and to what extent) the order book affects investors ’ order placement strategies. We find that the top of the book always affects order sub-missions, cancellations, and amendments, and the rest of the book mostly affects order cancellations and amendments. The previously documented order submis-sion aggressiveness, given a crowded first step of the book, persists to other price steps and is found in order amendments and cancellations along the book. Finally, investors tend to fill in the large price gaps in the book by submitting or amending orders. JEL Classification: G10, G11, G19 I.

This paper presents preliminary findings and is being distributed to economists and other interested readers solely to stimulate discussion and elicit comments. The views expressed in the paper are those of the authors and are not necessarily reflective of views at the Federal Reserve Bank of New York or the Federal Reserve System. Any errors or omissions are the responsibility of the authors.

Abstract This paper is an empirical investigation of the ways in which …nancial exchanges compete, through the lens of the competition that took place over ten years between two derivatives exchanges. We propose and bring to the data a new model of exchange membership that allows for intermediation and dual membership. Our panel dataset contains traders' membership status at each exchange together with trader characteristics, regulatory controls, and pricing, marketing and product portfolio strategies by each exchange over time. We document several dimensions of heterogeneity across traders that a¤ect competition. We …nd that horizontal di¤erentiation between the two exchanges dominates the vertical di¤erentiation induced by liquidity e¤ects. This phenomenon, which we interpret as the result of intermediation, reduces the importance of liquidity as a determinant of exchange competition and rationalizes the coexistence of di¤erent exchanges trading the same products. Keywords: Platform competition, network e¤ects, intermediation, multi-homing. PARTIALLY REVISED TEXT, INCOMPLETE This paper supersedes an earlier draft distributed under the title "How and When do Markets Tip? Lessons from the Battle of the Bund". We have accumulated a debt to many people during this project. We are very grateful to Eurex and LIFFE for giving us access to their archives, and especially to Stefan Engels (Eurex) and Stuart Sloan (LIFFE) for tracking the data and coordinating the collection at these exchanges. We are also grateful to the executives at Eurex and LIFFE and to the other industry participants who shared their time and knowledge about the industry and events. We thank John Asker, Bruno Biais, Fany Declerck, Jean-Pierre Dubé, Liran Einav, Philippe Février, Shane Greenstein, Jerry Hausman, Rebecca Henderson, Patrick Legros, Aviv Nevo, Felix Oberholzer-Gee, Richard Schmalensee, Andrew Sweeting, Glen Weyl as well as seminar and conference audiences for their comments and suggestions. Last but not least,

Common wisdom has it that competition between trading platforms in securities markets benefits investors because it forces platforms to charge smaller fees. We challenge this view by showing that a decrease in trading fees can impair investors ’ expected welfare in limit order markets. Indeed, a decrease in trading fees can induce investors to strategically post limit orders with a smaller execution probability, in order to earn a greater surplus in case of execution. Hence, a decrease in trading fees yields larger gains from trade when a trade takes place but it can reduce the likelihood of a trade in the first place. The model has testable implications for the effects of a change in trading fees and their breakdown between investors submitting limit orders (makers) and market orders (takers) on limit order fill rates and various measures of bid-ask spreads.