Empirical Market Microstructure Research Articles

Introduction to the 2018 Hal White Memorial Lecture

Every year the Society for Financial Econometrics celebrates the fundamental contributions to econometric theory and practice made by our late colleague and friend Hal White. Central to these celebrations is a lecture presented by an established scholar during a plenary session of the Society’s Annual Conference. This lecture is subsequently published in the journal. The 2018 Hal White Memorial Lecture was given by Joel Hasbrouck based on the paper “Price Discovery in High Resolution.” The lecture, followed by four commentaries and a re-joinder, form the content of this issue of the journal. Joel Hasbrouck’s lecture focuses on a key area in empirical market microstructure which seeks to understand the granular properties of pricing dynamics from the identification of appropriate price innovations and the separation of permanent from transient price impact effects. The lecture addresses this issue by proposing and estimating at resolutions from sub-milliseconds to one second a Vector Error...

The Multivariate Kyle Model: More is Different

We reconsider the multivariate Kyle model in a risk-neutral setting with a single, perfectly informed rational insider and a rational competitive market maker, setting the price of $n$ securities. We prove the unicity of a symmetric, positive definite solution for the impact matrix and provide insights on its interpretation. We explore its implications from the perspective of empirical market microstructure and argue that it provides a sensible inference procedure to cure some pathologies encountered in recent attempts to calibrate cross-impact matrices. As an illustration, we determine the empirical cross-impact matrix of US Treasuries and compare the results with recent alternative calibration methods.

Intra-market commonality in liquidity: new evidence from the Polish stock exchange

Research background: Empirical market microstructure research has recently shifted its focus from the examination of liquidity of individual securities towards analyses of the common determinants and components of liquidity. The identification of commonality in liquidity emerged as a new and fast growing strand of the literature on liquidity. However, the results around the world are ambiguous and rather depend on a specific stock market.
 Purpose of the article: The aim of this study is to explore intra-market commonality in liquidity on the Warsaw Stock Exchange (WSE) by using daily proxies of six liquidity estimates: percentage relative spread, percentage realized spread, percentage price impact, percentage order ratio, modified turnover, and modified version of the Amihud measure. The sample covers a period from January 2005 to December 2016. The database contains the group of eighty-six WSE-listed companies.
 Methods: The research hypothesis that there is commonality in liquidity on the Polish stock market is tested. The OLS with the HAC covariance matrix estimation and the GARCH-type models are employed to infer the patterns of liquidity co-movements on the WSE. Moreover, because the sample period is quite long, the stability of the empirical results by time period is examined. Seven 6-year time windows are utilized in the study.
 Findings & Value added: The regression results reveal weak evidence of co-movements in liquidity on the WSE, regardless of the choice of the liquidity proxy. Furthermore, the robustness tests based on the time rolling-window approach do not unambiguously support the research hypothesis that there is commonality in liquidity on the Polish stock market. To the best of the author?s knowledge, the empirical findings presented here are novel and have not been reported in the literature thus far.

The Multivariate Kyle Model: More is Different

We reconsider the multivariate Kyle model in a risk-neutral setting with a single, perfectly informed rational insider and a rational competitive market maker, setting the price of n correlated securities. We prove the unicity of a symmetric, positive definite solution for the impact matrix and provide insights on its interpretation. We explore its implications from the perspective of empirical market microstructure, and argue that it provides a sensible inference procedure to cure some pathologies encountered in recent attempts to calibrate cross-impact matrices. As an illustration, we determine the empirical cross impact matrix of US Treasuries, and compare the results with recent alternative calibration methods.

Testing weak exogeneity in multiplicative error models

Empirical market microstructure literature widely employs the non-linear and non-Gaussian multiplicative error class of models (MEMs) in modelling the dynamics of trading duration and financial marks. It routinely maintains the weak exogeneity of duration vis-à-vis marks in estimations. However, microstructure theory states that trade duration, volume and transaction prices are simultaneously determined. We propose Lagrange-multiplier (LM) tests for weak exogeneity for the MEMs. Our LM tests are extensions of the weak exogeneity tests applicable to VAR or VECM models with Gaussian distributions. Empirical assessments show that (i) weak exogeneity is widely rejected by the data in the MEMs and (ii) the failure of weak exogeneity seriously biases parameter estimates. We hope our tests will be of interest in future empirical applications.

Any Silver Linings? The London Silver Fixing's Impact on Public Silver Markets Before and After the Introduction of Contemporaneous Futures Trading.

Since 1897 the London Silver Fixing has conducted a daily auction which, to this day, sets the daily benchmark price for the precious metal. This private pricing club functions alongside active public markets for silver, including the physical spot and futures markets. This empirical market microstructure study analyses publicly traded silver instruments to assess the impact the fixing has on public markets. The study spans fourteen years of fixings, from January 2000 to December 2013, which includes the introduction of contemporaneous silver futures trading in late 2006. It finds statistically significantly lower prices around the time of the fixing in both spot and futures markets, elevated levels of trade volume and price volatility immediately following the fixing’s start, well before the conclusion of the fixing and the publication of its outcome. Further, it finds statistically significant return advantages in the four minutes following the start of the fixing for informed traders while no significant returns follow the publication of the fixing outcome. Trades in the opening minutes of the fixing are highly predictive of the price direction of the fixings. The size and significance of these results increase after the introduction of contemporaneous futures trading.

The Impact of High-Frequency Trading on Stock Market Liquidity Measures

For the highly traded S&P 500 exchange traded fund SPY, we find that, over time, transaction size has been decreasing while the number of consecutive buy or sell transactions has been increasing due to the increased prevalence of high frequency trading and order splitting. Collapsing sequences of buy or sell transactions into single transactions produces a time series that has a time-stationary distribution and is more tractable for empirical market microstructure models. If sequences are not collapsed, measures of illiquidity are underestimated, implying that increased high-frequency trading may not necessarily be associated with improved liquidity.

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.

Short sales and trade classification algorithms

This paper demonstrates that short sales are often misclassified as buyer-initiated by the Lee–Ready and other commonly used trade classification algorithms. This result is due in part to regulations which require that short sales be executed on an uptick or zero-uptick. In addition, while the literature considers “immediacy premiums” in determining trade direction, it ignores the often larger borrowing premiums that short sellers must pay. Since short sales constitute approximately 30% of all trade volume on U.S. exchanges, these results are important to the empirical market microstructure literature, as well as to measures that rely upon trade classification, such as the probability of informed trading (PIN) metric.

Empirical market microstructure: An analysis of the BRL/US$ exchange rate market

This article provides an analysis of empirical microstructure for the BRL/US$ exchange rate market using high-frequency bid and ask quote data. The aims of the article are to verify the importance of the presence of asymmetric information in price dynamics, to build a model for the price discovery process and to analyze the empirical determinants of the spread between bid and ask through a conditional model that captures an asymmetric response to the spread regarding past information. The asymmetric information hypothesis is tested through a nonparametric test of conditional independence for the Markov property. A model for price discovery is built using a vector error correction between bid and ask, controlling for duration and volatility. As a result of this vector, we build an equilibrium spread deviation series, and we show that the conditional distribution of equilibrium spread deviations responds asymmetrically to the spread changes and expected conditional volatilities and durations. This is made by using the quantilogram and a quantile autoregression as tools for modeling the asymmetry effects. We relate the findings to some facts presented in the theoretical literature on market microstructure.

Short Sales and Trade Classification Algorithms

This paper demonstrates that the Lee-Ready and other commonly used trade classification algorithms classify short sales as buyer-initiated significantly more than 50% of the time. This result is due in part to regulations which require short sales be executed on an uptick or zero-uptick. In addition, while the literature considers immediacy premiums in determining trade direction, they ignore the often larger borrowing premiums which short sellers must pay. Since short sales constitute approximately 30% of all trade volume on U.S. exchanges, these results are important to the empirical market microstructure literature as well as to measures that rely upon trade classification, such as the probability of informed trading (PIN) metric.

On the importance of timing specifications in market microstructure research

This paper highlights the importance of timing specifications in empirical market microstructure studies. Small changes in the data matching process and the timing specification of economic variables can significantly alter the outcomes of empirical research. Using the methodology developed by Lee and Ready [1991. Journal of Finance 46(2) 733–746], we show that their “5-second rule” is not appropriate for matching quotes with transactions for NYSE stocks in the TAQ data set, and the prevailing quotes are the ones immediately before the trades. We demonstrate the significance of the timing specifications of economic variables using the Huang and Stoll [1997. Review of Financial Studies 10, 995–1034] spread decomposition model. Seemingly minor variations from the theoretical model result in severe biases in the estimated parameters. Correcting the timing errors provide much more realistic spread component estimates than those achieved in the literature.

Persistence in Limit Order Flow

I find that limit order submission is not random. The probability of observing a limit sell (buy) order is highest after another limit sell (buy) order. This first-order positive serial correlation in the order flow cannot be explained by theories offered in the current literature. I find that the positive serial correlation is due largely to order splitting and the undercutting behavior among limit order traders. Controlling for these two effects explains up to 72 percent of the positive serial correlation. I also show that the failure to account for these two effects may cloud the results of some empirical market microstructure studies.

On the Importance of Timing Specifications in Market Microstructure Research

This paper highlights the importance of timing specifications in empirical market microstructure studies. Small changes in the data matching process and the timing specification of economic variables can significantly alter the outcomes of empirical research. Using the methodology developed by Lee and Ready (1991), we find that their 5-second rule is no longer appropriate for matching quotes with transactions for NYSE stocks in the TAQ data set. Quotes should be delayed one second when matched with transactions. We demonstrate the significance of the timing specifications of economic variables using the Huang and Stoll (1997) spread decomposition model. Seemingly minor variations from the theoretical model result in severe biases in the estimated parameters. Correcting the timing errors provide much more realistic spread component estimates than those achieved in the literature.

Competition on the London Stock Exchange

This paper investigates the determinants of the level of competition on the order–driven market organised by the London Stock Exchange. In contrast to previous empirical market microstructure studies, we treat the level of competition as an endogenous variable. The statistical nature of the measures of competitive activity used in this paper necessitate use of a count regression model. Using a sample 50 stocks, we find that users of the system tend to follow the lead of other users (termed the ‘herding effect’) and that competition is greater during the period when the US exchanges are open (termed the ‘US effect’). In addition, the level of competition is positively related to the bid–ask spread pertaining to a particular stock (termed the ‘spread effect’). The latter result is most likely due to traders following a strategy where trade immediacy is traded off against price advantage. Finally, we find that the magnitude of the herding effect, the spread effect, and the fit of the count regression models (termed the ‘fit effect’) vary in a predictable manner across the liquidity of stocks.

Price Formation and Transparency on the London Stock Exchange

This paper contributes to the empirical market microstructure literature on the London Stock Exchange (LSE) by producing model-based estimates of the spread and its components. The paper applies the same approach to test for changes in the determinants of price formation following the January 1996 change in the market's publication rules. The results suggest that order-processing costs are a far more important determinant of the LSE spread than the literature has so far presumed. Consistent with existing research findings, no discernible effect of post-trade transparency on market liquidity was found.