The information content of an open limit‐order book

Abstract

Using data from the Australian Stock Exchange, the authors assess the information content of an open limit-order book with a particular focus on the incremental information contained in the limit orders behind the best bid and offer. The authors find that the order book is moderately informative-its contribution to price discovery is approximately 22%. The remaining 78% is from the best bid and offer prices on the book and the last transaction price. Furthermore, the authors find that order imbalances between the demand and supply schedules along the book are significantly related to future short-term returns, even after controlling for the autocorrelations in return, the inside spread, and the trade imbalance.Although the information content of a limit-order book has been the subject of an active debate in the price discovery literature, there has been no consensus about whether or not the order book is informative. On the one hand, Glosten (1994), Rock (1996), and Seppi (1997) incorporated informed traders into their models, assuming that they favor and actively submit market orders. This suggests that the order book beyond the best bid and offer contains little, if any, information. On the other hand, several recent studies suggest that the order book is informative. Using an experimental design, Bloomfield, O'Hara, and Saar (2005) found that in an electronic market, informed traders submit more limit orders than market orders. Using SuperDot limit orders in the TORQ database, Harris and Panchapagesan (2005) showed that the order book is informative, and that New York Stock Exchange (NYSE) specialists use the book information in ways that favor them over the limit-order traders. Kaniel and Liu (2006) showed that informed traders prefer limit orders, and that limit orders convey more information than market orders when the private information is long-lived.Regarding the question of whether pre-trade transparency facilitates price discovery, the extant literature offers mixed evidence. Baruch (2005) provided a theoretical model showing that an open limit-order book improves liquidity and information efficiency of prices. Consistent with this prediction, Boehmer, Saar, and Yu (2005) found that the deviations of transaction prices from the efficient prices became smaller after the NYSE's adoption of the open book system. In contrast, Madhavan, Potter, and Weaver (2005) found larger spreads and higher volatility after the Toronto Stock Exchange disseminated the top four price levels of the limit-order book in April 1990.This study is part of the emerging literature on the information content of the limit-order book. The authors are particularly interested in the incremental information content of the book, over and above the information traditionally available in a dealer market: i.e., the best bid and offer prices along with their respective depths. Using order-book information from the Australian Stock Exchange (ASX), the authors empirically assess the information content of an open limit-order book from two pers...

The Impact of Iceberg Orders in Limit Order Books

“…Cao, Hansch, and Wang (2009) find that future prices to some extent can be predicted based on visible information in the order book and an experimental study by Bloomfield, O'Hara, and Saar (2005) shows that informed traders may often use limit orders providing a rational for an informative limit order book. Our evidence shows that other order book information including the hidden volume from iceberg orders and the history of order book updates also 4 helps predict both future prices and quantities.…”

Order Aggressiveness on the ASX Market

“…The method of categorizing price aggressiveness applied by Cao, Hansch and Wang (2004) is based on the priority in execution and described as follows: (1) market orders (immediately executed at the best available price) or marketable limit orders (limit orders at prices better than the best price standing on the opposite side of the market) which consume liquidity on the opposite side of the market; (2) best limit orders placed at prices better than the existing best price and therefore improve the current best bid or offer (3) best limit orders placed at the existing best price; (4) off-best orders placed within three ticks of the best price; (5) off-best orders placed more than three ticks away from the best price; and (6) the cancellation of a limit order that removes liquidity from the book without a transaction. The descriptive statistics of price aggressiveness on the ASX market are documented in section 5 in detail.…”

“…However, some results such as relative depth do not support our hypothesis, and the reason may lie on that traders believe that limit orders outside the best bid and ask are not so informative and simply ignore them. Other explanations include that monitoring and analyzing the book is costly or traders are overconfident and give little weight to order book information and other traders' strategy, relatively to their own assessment of the stock's true value, as stated by Cao et al (2004). Besides, there exists a difference of the effects of explanatory variables on a cross-sectional level to some degree, indicating that some economic relations may hold individually.…”

“…Their results indicate that the bid-ask spread, depth at the best price, price changes in the last five minutes and order imbalance are major determinants for traders to choose between market and limit orders. Cao et al (2004) employ a more comprehensive dataset, covering 21 constituent stocks from the ASX-20 index to study the order submission strategies of traders using an Ordered Probit modeling approach. They provide evidence to confirm that traders use the available information on the state of the limit order book, including spread, depths on the same and opposite sides, when developing their order submission strategies.…”

Two Shades of Opacity: Hidden Orders versus Dark Trading

“…To the extreme, parasitic traders may engage in predatory strategies aimed at exploiting other traders' orders (Brunnermeier and Pedersen, 2005). Moreover, limit orders can contain fundamental information and therefore impact prices (see, e.g., Kaniel and Liu, 2006;Cao, Hansch, and Wang, 2009). Transparency therefore goes hand in hand with increased exposure costs for traders.…”