Screen Information, Trader Activity, and Bid-Ask Spreads in a Limit Order Market (original) (raw)
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Order flow and the bid-ask spread: An empirical probability model of screen-based trading
Journal of Economic Dynamics and Control, 1997
A probabilistic framework for the analysis of screen-based trading activity is presented. Probability functions are derived for the stationary distributions of the best bid and offer, conditional on the order flows. By identifying the unobservable order and acceptance flows, our estimation method permits the prediction of the stationary distributions of other market statistics. A test is proposed that allows a comparison of predicted and sample bid-ask spread distributions taking parameter estimation error into account. The methodology is applied to the screen-based interbank foreign exchange market, using continuously recorded quotes on the Deutschemark/US dollar exchange rate.
Limit orders and the bid–ask spread
Journal of Financial Economics, 1999
We examine the role of limit-order traders and specialists in the market-making process. We find that a large portion of posted bid-ask quotes originates from the limit-order book without direct participation by specialists, and that competition between traders and specialists has a significant impact on the bid-ask spread. Specialists' spreads are widest at the open, narrow until late morning, and then level off. The U-shaped intraday pattern of spreads largely reflects the intraday variation in spreads established by limit-order traders. Lastly, the intraday variation in limit-order spreads is significantly related to the intraday variation in limit-order placements and executions. for useful comments and discussions. We are solely responsible for any errors.
The components of the bid–ask spread in a limit-order market: evidence from the Tokyo Stock Exchange
Journal of Empirical Finance, 2002
This paper analyzes the components of the bid-ask spread in the limit-order book of the Tokyo Stock Exchange (TSE). While the behavior of spread components in U.S. markets has been extensively studied, little is known about the spread components in a pure limit-order market. We find that both the adverse selection and order handling cost components of the TSE exhibit U-shape patterns independently, in contrast to the findings of Madhavan, Richardson, and Roomans (1997) for U.S. stocks. On the TSE, there does not exist an upstairs market that allows large trades to be prenegotiated or certified as on the New York Stock Exchange (NYSE). This feature of the TSE provides a valuable opportunity to examine the relationship between trade size and spread components. Our results show that the adverse selection cost increases with trade size while order handling cost decreases with it.
SSRN Electronic Journal, 2000
The behaviour of limit order quotes and trading activity are studied using a unique and rich database that includes the identity of market participants from a fully automated derivatives market. The analysis is performed using transactions records for three aggregated trader types and three trade identifiers, with trades stamped in milliseconds for the SXF, the equity futures contract of the Montreal Exchange. The identifiers distinguish trades between principals; agency based trades, as well as transactions that are conducted for risk management as opposed to speculative purposes. Agency related trades are shown to represent the largest amount of trading activity relative to other account types. Over 90% of trades in this electronic market are limit orders. The limit order book, especially the depth 1 order, has a dominant role in providing liquidity and in explaining market participants' trading behaviour. Participants in the SXF reference their trades to the best limit order depth. Hence, investors with large positions or investors who want to build a large position have to strategically split large orders to close/build their position, according to the depth of the best limit order, to ameliorate price impact and information leakage effects. In addition, the results show that traditionally measured spreads have no relationship with trading costs.
Order handling rules, tick size, and the intraday pattern of bid–ask spreads for Nasdaq stocks
Journal of Financial Markets, 2001
In this study we perform a before-and-after analysis of intraday variation in bid}ask spreads surrounding two recent Nasdaq market reforms. We "nd that spreads declined signi"cantly after the order handling rule changes and the magnitude of the decline is largest during midday. The results are consistent with our conjecture that, like on the NYSE, limit-order traders on Nasdaq play a signi"cant role in the quote-setting process. Our empirical results also show that the magnitude of the spread reduction associated with the tick-size change is largest (smallest) during the last ("rst) hour of trading. We interpret these results using inventory and information models of the spread. 2001 Elsevier Science B.V. All rights reserved. JEL classixcation: G14; G18 1386-4181/01/$ -see front matter 2001 Elsevier Science B.V. All rights reserved. PII: S 1 3 8 6 -4 1 8 1 ( 0 0 ) 0 0 0 2 1 -5
Liquidity Beyond the Inside Spread: Measuring and Using Information in the Limit Order Book
SSRN Electronic Journal, 2000
World equity markets increasingly convert to electronic trading, in many cases adopting the format of a pure electronic order book without intermediaries. A distinguishing feature of this format is that a high proportion of available liquidity is committed (displayed) rather than implicit or hidden. We examine the properties of a measure of liquidity, the Cost of Round Trip trade (CRT), which aggregates the status of the limit order book at any moment in time for a specific transaction size. CRT, which measures the ex ante committed liquidity immediately available in the market, complements the effective spread, which measures the ex post combination of the committed and hidden liquidity available over a period of time. We use data from the Toronto Stock Exchange to compare CRT to the quoted and effective spreads, and estimate its ability to predict the subsequent trading activity. While we propose CRT as a research tool, we also advocate its use by exchanges to indicate to investors the level of committed liquidity.
The information content of the limit order book: evidence from NYSE specialist trading decisions
Journal of Financial Markets, 2005
Specialists compete with limit order traders to provide liquidity at the New York Stock Exchange. Since specialists see all system limit orders, they enjoy a unique advantage in this competition. We examine whether the limit order book is informative about future price changes and whether specialists use this information when trading. Our analyses consider three actions specialists can take when a market order arrives: stop the order, immediately fill the order at the quoted price, or immediately fill the order at an improved price. Using SuperDOT limit orders in the TORQ database, we find that the limit order book is informative, especially about short-term price movements. We also find that the specialist uses this information in a way that favors him (and sometimes the floor community) over the limit order traders. The results are more evident for active stocks where the competition between specialists and limit order traders is more intense. We also show that specialists in lower-priced stocks are less likely to initiate such actions because of the binding tick size.
An Intraday Examination of the Components of the Bid-Ask Spread
The Financial Review, 2002
Using transactions data for a sample of NYSE stocks, we decompose the bid-ask spread (BAS) into order-processing (OP) and asymmetric information (AI) components using the techniques of George, and . demonstrate that the intraday behavior of BASs can be explained by variables measuring activity, competition, risk, and information. We investigate whether these variables explain the behavior of the OP and AI components of the spread over the trading day. We conclude that, on balance, the variables that determine the aggregate BAS also determine its intraday components.