Market structure, informational efficiency and liquidity: An experimental comparison of auction and dealer markets

We report the results of 18 market experiments that were conducted in order to compare the call market, the continuous auction and the dealer market. Transaction prices in the call and continuous auction markets are much more efficient than prices in the dealer markets. The call market shows a tendency towards underreaction to new information. Execution costs are lowest in the call market and highest in the dealer market. The trading volume and Roll's (Journal of Finance (1984) 1127–1139) serial covariance estimator are inappropriate measures of execution costs in the present context. The relation between private signals, trading decisions and trading profits is analyzed.     

Pricing behavior in an off-hours computerized market

Automated markets are becoming increasingly widespread, and their efficiency properties are of corresponding concern to regulators and exchange policy makers. Many systems are implemented in settings characterized by a distinct lack of liquidity, however, often by design. We evaluate the performance of such a market, the GLOBEX overnight trading system, in absolute terms and relative to a liquid benchmark, the floor market of the Chicago Mercantile Exchange (CME). Our results with respect to bid–ask spreads and adverse selection suggest that the nature of the environment is an important determinant of market performance, but that an automated market can operate well in a relatively illiquid setting. Price clustering, indicative of a lack of pricing efficiency, is prevalent on the automated system, but price resolution improves as trading frequency increases.     

Limit order book,anonymity and market liquidity: evidence from the Sydney Futures Exchange

This study examines the impact of the removal of broker mnemonics on the Sydney Futures Exchange. Early research finds that a decrease in transparency reduces liquidity in the market, whereas more recent research finds that reduced transparency improves market quality. Results of the present study indicate an improvement in liquidity after the removal of broker mnemonics. There is a significant increase in quoted depth and trading volume, and a significant decrease in quoted spreads in the 90 day Bank Accepted Bill, 3 year Treasury Bond and 10 year Treasury Bond Futures. This improvement in liquidity is robust to the length of the event window around the structural change and trading in a control market.     

Optimal execution of open-market stock repurchase programs

This paper formalizes the following intuition about open-market share repurchases. Firms do open-market share repurchases to return free cash, which would otherwise be wasted. However, when the firm goes to buy its own shares with this cash, it has inside information and hence the actual execution is characterized by adverse selection. The market knows that the firm has inside information, and consequently the ask price is high to compensate for this adverse selection problem. This implies that, all else equal, the greater the adverse selection problem compared to the cash waste problem, the higher the ask price, and, therefore, the wider the bid–ask spread and the lower the share repurchase completion rate. We test this implication on a sample of U.S. firms and report evidence consistent with the model.     

The impact of short-selling and margin-buying on liquidity: Evidence from the Chinese stock market

We propose a framework based on limit order book to analyze the impact of short-selling and margin-buying on liquidity. We show that when short-sellers are perceived as informed, adverse selection may lead to uninformed traders withdrawing their limit orders. Given that the Chinese stock market has strong information asymmetry and a high proportion of uninformed traders, we predict that the pilot program launched in March 2010, which lifts restrictions on short-selling and margin-buying for a designated list of stocks, may have a negative impact on liquidity. We perform difference-in-differences tests and show evidence that allowing for short-selling and margin-buying indeed has a significantly negative impact on liquidity for stocks on the designated list. In particular, the negative impact on liquidity is more pronounced for stocks with high information asymmetry. Nevertheless, when short-selling volume dries up due to regulation changes in August 2015, i.e., the “T+1” trading rule on short-selling, we show that consistent with model predictions, lifting restrictions on short-selling and margin-buying has a positive effect on liquidity.     

Impact of a tick size reduction on liquidity: evidence from the Sydney Futures Exchange

This paper examines the impact of a reduction in the minimum price increment on liquidity and execution costs in a futures market setting. In 2006, the Sydney Futures Exchange halved the minimum tick in the 3 Year Commonwealth Treasury Bond Futures. Results indicate that bid‐ask spreads are significantly reduced after the change. Quoted depth, both at the best quotes and visible in the limit order book, is significantly lower after the tick reduction. Further analysis reveals that execution costs are significantly reduced after the change. We conclude that a tick size reduction improves liquidity and reduces execution costs in a futures market setting.     

Adverse selection costs for NASDAQ and NYSE after decimalization

NYSE and NASDAQ completed their decimalization on January 29, 2001 and on April 9, 2001 respectively. In this paper, we compare adverse selection component of the bid–ask spread for NASDAQ and NYSE stocks after decimalization using the data from May 2001 and July 2001. We find that the adverse selection component of the bid–ask spread is significantly lower on NASDAQ than on NYSE, and these differences cannot be attributed to the differences in the characteristics of the stocks traded in the two markets. In addition, we find that the adverse selection costs increase with trade size on NYSE, however there is no monotonic pattern observed for NASDAQ stocks. Lastly, we report that although the order flows arrived in the two markets are significantly different, they can at best explain a small portion of the observed differences in adverse selection costs.     

The dynamics of dealer markets and trading costs

In this study we examine the temporal dynamics of dealer market share and their ramification for competition and trading costs using a large sample of NASDAQ securities. Our results show that although the total market share of the top five dealers is relatively stable over time, there is significant monthly variation in the composition of the top five dealers. We show that market share turbulence among top dealers is another form of competition that narrows bid–ask spreads, especially for stocks with less competitive market structure.     

Latency and liquidity provision in a limit order book

We use a recent, high-quality data set from Nasdaq to perform an empirical analysis of order flow in a limit order book before and after the arrival of a market order. For each of the stocks that we study, we identify a sequence of distinct phases across which the net flow of orders differs considerably. We note that some of our results are consistent with the widely reported phenomenon of stimulated refill, but that others are not. We therefore propose alternative mechanical and strategic motivations for the behaviour that we observe. Based on our findings, we argue that strategic liquidity providers consider both adverse selection and expected waiting costs when deciding how to act.     

Commonalities in the order book

This paper uses data from one of the most important European stock markets and shows that, in line with predictions from theoretical market microstructure, a small number of latent factors captures most of the variation in stock specific order books. We show that these order book commonalities are much stronger than liquidity commonality across stocks. The result that bid and ask side as well as the visible and hidden parts of the order book exhibit quite specific dynamics is interpreted as evidence that open order book markets attract a heterogeneous trader population in terms of asset valuations and impatience. Quantifying the informational content of the extracted factors with respect to the evolution of the asset price, we find that the factor information shares are highest (about 10%) for less frequently traded stocks. We also show that the informational content of hidden orders is limited.

Market microstructure: A review from down under

The early automation of the Australian and New Zealand financial markets provided researchers with access to high‐frequency data to undertake extensive empirical market microstructure research. We use this anniversary edition of Accounting and Finance to review some of this research and to discuss the development of the Australian and New Zealand markets since their automation. We identify issues currently facing the markets and highlight potential areas for future research. The paper also provides a review of market microstructure theory on inventory control models and asymmetric information models.     

The dynamics of ex-ante weighted spread: an empirical analysis

We model the evolution of the ex-ante weighted spread (EWS) embedded in an open Limit Order Book (LOB) and investigate the impact of observed market-related variables on the spread. Our modeling involves decomposing the joint distribution of the weighted spread into simple and interpretable distributions. Our main results have several implications: (i) EWS features high persistence in autocorrelation; (ii) lower-level LOB remains liquid even after a high trade imbalance; (iii) lower- and higher-level LOB react to temporal spread change and trade imbalance in different ways; and (iv) both trade durations and quote durations have seasonality effects. We also show, through a simple high frequency trading exercise, that the use of the model can be economically important. Further, our model provides an estimation of market resilience.     

Optimal execution strategies in limit order books with general shape functions

We consider optimal execution strategies for block market orders placed in a limit order book (LOB). We build on the resilience model proposed by Obizhaeva and Wang (2005 Obizhaeva, A and Wang, J. 2005. Optimal trading strategy and supply/demand dynamics, Preprint Available online at: http://www.rhsmith.umd.edu/faculty/obizhaeva/OW060408.pdf (accessed 16 February 2009)[Crossref] , [Google Scholar]) but allow for a general shape of the LOB defined via a given density function. Thus, we can allow for empirically observed LOB shapes and obtain a nonlinear price impact of market orders. We distinguish two possibilities for modelling the resilience of the LOB after a large market order: the exponential recovery of the number of limit orders, i.e. of the volume of the LOB, or the exponential recovery of the bid–ask spread. We consider both of these resilience modes and, in each case, derive explicit optimal execution strategies in discrete time. Applying our results to a block-shaped LOB, we obtain a new closed-form representation for the optimal strategy of a risk-neutral investor, which explicitly solves the recursive scheme given in Obizhaeva and Wang (2005 Obizhaeva, A and Wang, J. 2005. Optimal trading strategy and supply/demand dynamics, Preprint Available online at: http://www.rhsmith.umd.edu/faculty/obizhaeva/OW060408.pdf (accessed 16 February 2009)[Crossref] , [Google Scholar]). We also provide some evidence for the robustness of optimal strategies with respect to the choice of the shape function and the resilience-type.     

The submission of limit orders or market orders: The role of timing and information in the Reuters D2000-2 system

Recent work in the market microstructure literature suggests that the speed with which orders arrive in the market impacts traders' order submission decisions. In this study we use an asymmetric autoregressive conditional duration (ACD) model to empirically investigate the influence on the submission of limit and market orders of changes in the time between the past submissions of different types of orders, changes in the slope of the limit order book, and changes in price uncertainty. We find that the expected time between the arrivals of successive orders in the foreign exchange market depends on the previous type of order submitted and the slope on both sides of the order book. Price uncertainty (volatility) plays a secondary role after accounting for the impact of changes in the slope of the order book. Lastly, we find that there are fundamental changes in the level of information contained in the submission of orders at the opening and closing of markets.     

Speed of convergence to market efficiency for NYSE-listed foreign stocks

This paper contributes to the cross-listing literature by documenting the speed of convergence to market efficiency for foreign stocks listed on the NYSE. We find that, on average, it takes 30–60 minutes for a foreign stock to achieve market efficiency. For a comparable US stock, it takes only 10–15 minutes. The significant difference between foreign and US stocks remains robust when the speed is measured by the number of transactions rather than in calendar time. After relevant firm characteristics are controlled for, the time that it takes for foreign stocks to reach efficiency is significantly negatively related to the quality of their home country institutions. We find that one possible channel through which institutions affect the speed is through their impact on information asymmetry.     

Reduced form modeling of limit order markets

This paper proposes a parametric approach for stochastic modeling of limit order markets. The models are obtained by augmenting classical perfectly liquid market models with a few additional risk factors that describe liquidity properties of the order book. The resulting models are easy to calibrate and to analyse using standard techniques for multivariate stochastic processes. Despite their simplicity, the models are able to capture several properties that have been found in microstructural analysis of limit order markets. Calibration of a continuous-time three-factor model to Copenhagen Stock Exchange data exhibits, for example, mean reversion in liquidity as well as the so-called crowding out effect, which influences subsequent mid-price moves. Our dynamic models are also well suited for analysing market resilience after liquidity shocks.     

More on a statistical analysis of log-periodic precursors to financial crashes

In this paper, we extend the existing empirical evidence on the relationship between the state of the limit order book (LOB) and order choice. Our contribution is twofold: first, we propose a sequential ordered probit (SOP) model which allows studying patient and impatient traders’ choices separately; second, we consider two pieces of LOB information, the best quotes and the book beyond the best quotes. We find that both pieces of LOB information explain the degree of patience of an incoming trader and, afterwards, its order choice. Nonetheless, the best quotes concentrate most of the explanatory power of the LOB. The shape of the book beyond the best quotes is crucial in explaining the aggressiveness of patient (limit order) traders, while impatient (market order) traders base their decisions primarily on the best quotes. Patient traders’ choices depend more on the state of the LOB on the same side of the market, while impatient traders mostly look at the state of the LOB on the opposite side. The aggressiveness of both types of traders augments with the inside spread. However, patient (impatient) traders submit more (less) aggressive limit (market) orders when the depth of the own (opposite) best quote and the length of the own (opposite) side of the book increase. We also find that higher depth away from the best ask (bid) quote may signal that this quote is ‘too low (high)’, causing incoming impatient buyers (sellers) to be more aggressive and incoming patient sellers (buyers) to be more conservative.     

The information content of a limit order book: The case of an FX market

In this paper we examine the question of whether knowledge of the information contained in a limit order book helps to provide economic value in a simple trading scheme. Given the greater information content of the order book, over simple price information, it might naturally be expected that the order book would dominate. Using Dollar Sterling tick data, we find that despite the in-sample statistical significance of variables describing the structure of the limit order book in explaining tick-by-tick returns, they do not consistently add significant economic value out-of-sample. We show this using a simple linear model to determine trading activity, as well as a model-free genetic algorithm based on price, order flow, and order book information. We also find that the profitability of all trading rules based on genetic algorithms dropped substantially in 2008 compared to 2003 data.     

A liquidity-based model for asset price bubbles

We provide a new liquidity-based model for financial asset price bubbles that explains bubble formation and bubble bursting. The martingale approach to modeling price bubbles assumes that the asset's market price process is exogenous and the fundamental price, the expected future cash flows under a martingale measure, is endogenous. In contrast, we define the asset's fundamental price process exogenously and asset price bubbles are endogenously determined by market trading activity. This enables us to generate a model that explains both bubble formation and bubble bursting. In our model, the quantity impact of trading activity on the fundamental price process—liquidity risk—is what generates price bubbles. We study the conditions under which asset price bubbles are consistent with no arbitrage opportunities and we relate our definition of the fundamental price process to the classical definition.     

Modelling the shape of the limit order book

This article develops a parsimonious way to use the shape of the limit order book to produce an estimate of the asset price. The posited model captures and describes the evolution of the distribution of limit orders on the bid and ask sides of the LOB during the trading session and provides estimates of the execution asset price over time. The performance of the model is evaluated against some existing standards from the market microstructure literature during the trading session. Empirical evidence on listed companies confirm a strong contribution of our methodology to the innovation in asset prices, according to the information share coefficients. We also document a significant improvement relative to the Hasbrouck [J. Finance, 1991, 46, 179–207] model when our model estimates are included as regressors.