The impact of iceberg orders in limit order books

We examine the impact of iceberg orders on the price and order flow dynamics in limit order books. Iceberg orders allow traders to simultaneously hide a large portion of their order size and signal their interest in trading to the market. We show that when the market learns about iceberg orders they tend to strongly attract market orders consistent with iceberg orders facilitating the search for latent liquidity. The greater the fraction of an iceberg order that is executed the smaller its price impact consistent with liquidity rather than informed trading. The presence of iceberg orders is associated with increased trading consistent with a positive liquidity externality, but the reduced order book transparency associated with iceberg orders also creates an adverse selection cost for limit orders that may partly offset any gains. --Hidden Liquidity,Iceberg Orders,Limit Order Markets,Transparency

The Role of Mortgage Brokers in the Subprime Crisis

Prior to the subprime crisis, mortgage brokers originated about 65% of all subprime mortgages. Yet little is known about their behavior during the runup to the crisis. Using data from New Century Financial Corporation, we find that brokers earned an average revenue of $5,300 per funded loan. We decompose the broker revenues into a cost and a profit component and find evidence consistent with brokers having market power. The profits earned are different for different types of loans and vary with borrower, broker, regulation and neighborhood characteristics. We relate the broker profits to the subsequent performance of the loans and show that brokers earned high profits on loans that turned out to be riskier ex post.

You Can’t Always Get What You Want: Trade-size Clustering and Quantity Choice in Liquidity”,

Abstract This paper examines whether investors care more about trading their exact quantity demands at some times than at others. Using a new data set of foreign-exchange transactions, I find that customers trade more precise quantities at quarter-end, as evidenced by less trade-size clustering. Customers trade more odd lots and fewer round lots, while the number of trades and total volume are not significantly changed. I also find that the price impact of order flow is greater when customers care more about trading precise quantities. This work sheds new light on trade-size clustering and offers a potential explanation for time-series and cross-sectional variations in common liquidity measures. JEL classification: D4; G12; G1

Co-movements of index options and futures quotes

We report evidence that the co-movements of index options and index futures quotes differ sharply from perfect correlation in periods with option trades. In half-hour intervals with (without) option trades 25% (12%) of call option quote changes have either the opposite sign or are larger in magnitude than the corresponding index futures quote changes. We calibrate a stochastic volatility model that allows for trade and no-trade periods using real data and simulate the joint co-movements of index quotes and option quotes in this model. We show that for trade intervals the observed co-movements differ from the benchmark case established by our simulations approximately three times too often. We provide empirical evidence that market microstructure effects - specifically, stale quotes and aggressive quotes - explain the majority of the deviations from the benchmark. Our findings are relevant for techniques that use estimates of local co-movements as inputs to price or hedge options.Options High-frequency data Market Microstructure Hedge ratio

Co-Movements of Index Options and Futures Quotes

We report evidence that the co-movements of index options and index futures quotes differ sharply from perfect correlation in periods with option trades. In half-hour intervals with (without) option trades 25% (12%) of call option quote changes have either the opposite sign or are larger in magnitude than the corresponding index futures quote changes. We calibrate a stochastic volatility model that allows for trade and no-trade periods using real data and simulate the joint co-movements of index quotes and option quotes in this model. We show that for trade intervals the observed co-movements differ from the benchmark case established by our simulations approximately three times too often. We provide empirical evidence that market microstructure effects - specifically, stale quotes and aggressive quotes - explain the majority of the deviations from the benchmark. Our findings are relevant for techniques that use estimates of local co-movements as inputs to price or hedge options

An Empirical Analysis of the Trading Structure at the Stockholm Stock Exchange

This paper describes and analyzes the trading structure at the Stockholm Stock Exchange. In the empirical part, we report stylized facts based on intraday transaction and order book data, focusing on the intraday behavior of returns, trading activity, order palcement and bid/ask spread, on the importance of the tick size and finally on some characteristics of the limit order book. Our main empirical conclusions are that a) the indraday U-chape in trading activity found in earlier U.S. studies on the whole also pertains to the Stockholm Stock Exchange, b) the limit order placement also followas an intraday U-shape, c) there is no distinct intraday pattern in returns, d) the volatility and bid/ask spread seems to be higher at the beginning of the trading day, e) the tick size is economically important, and f) the price impact of an order is a non-linear function of its quantity, implying price inelastic demand and supply.Market microstructure; stock market; trading systems; limit order book

Market Making with Costly Monitoring: An Analysis of the SOES Controversy

This article presents a model of information monitoring and market making in a dealership market. We model how intensively dealers monitor public information to avoid being picked off by professional day traders when monitoring is costly. Price competition among dealers is hampered by their incentives to share monitoring costs. The risk of being picked off by the day traders makes dealers more competitive. The interaction between these effects determines whether a firm quote rule improves trading costs and price discovery. Our empirical results support the prediction that professional day traders prefer stocks with small spreads, but offer less support for the prediction that their trading leads to wider spreads. Copyright 2003, Oxford University Press.

Empirical Analysis of Limit Order Markets

We analyse order placement strategies in a limit order market, using data on the order flow from the Stockholm Stock Exchange. Traders submitting market or limit orders trade off the order price against both the execution probability and the winner’s curse risk associated with different order choices. The optimal order strategy is characterized by a monotone function, which maps the liquidity demand of the investors into their order choice. We develop and implement a semiparametric test of this monotonicity property, and find no evidence against the monotonicity property for buy orders or sell orders. We do find evidence against the hypothesis that the trader’s decision to be a buyer or a seller depends only on the trading profits available in the limit order book. We estimate that traders submitting market buy orders have private valuations that exceed the asset value by 2.3% on average and receive an average payoff of at least 1.8% of the asset value. Traders submitting limit buy orders at the price below the best ask quote have private valuations between 0.1% and 2.3% above the asset value and earn an average payoff of between 0.3% and 1.8% of the asset value. Although the distribution of liquidity demand does not depend on conditioning information, conditioning information helps us to predict the composition of the order flow in our data. These findings imply that variation in the composition of the order flow can be explained by empirical variation in the relative profitability of alternative order choices and movements in the common value of the asset.Auctions; Electronic Trading Systems; Limit Order Markets; Semiparametric Estimation

Estimating the Gains From Trade in Limit Order Markets

We present a method for identifying and estimating the gains from trade in limit order markets and provide new empirical evidence that the limit order market is a good market design. The gains from trade in our model arise because traders have different valuations for the stock. We use observations on the traders’ order submissions and the execution and cancellation histories of the traders’ order submissions to estimate the distribution of traders’ unobserved valuations for the stock. We use the parameter estimates for our model to compute the current gains from trade in the limit order market and the gains from trade that the traders would attain in a perfectly liquid market.allocative efficiency; discrete choice; gains from trade; limit order markets