Corwin-Schultz bid-ask spread estimator in the Brazilian stock market.
| Autor | Ripamonti, Alexandre |
| Cargo | Report |
Introduction
Comprehending how information is obtained and disseminated is essential to understand how economies function (Rosser, 2003) as well as how it affects price movements (Cuthbertson & Nitzche, 2004; Muth, 1961).
Information asymmetry occurs when one trader has more or better information than another, and this asymmetry influences market equilibrium (Akerlof, 1970) the informed traders' orders bring information to the stock prices, improving the information's quality of other traders, throughout the signalling issues (Spence, 1973), thus showing that competition in markets with imperfect information is more complex than assumed in classical economics. This complexity is because competitors may limit their customers' purchases and competitive equilibria are not Pareto optimal (Rothschild & Stiglitz, 1976). In particular, for stock markets, as Grossman and Stiglitz (1980) show, the only way for informed traders to earn abnormal returns is to take better positions than uninformed ones, because trade activity causes private information to influence prices, although imperfectly.
However, asymmetric information occurs in the trading activity of stock markets along with order processing and inventory holding costs, and sometimes it could be difficult to distinguish between them, but the effects of adverse selection/asymmetric information have been found to be a significant part of the spread between bid-ask quotes (Huang & Stoll, 1997). The behaviour of these components is quite different as well. Adverse selection has been found to increase when earnings announcements are expected, but order processing and inventory holding have been found to decrease (Krinsky & Lee, 1996).
Minardi, Sanvicente, and Monteiro (2006) showed the absence of order processing and inventory holding costs and the presence of asymmetric information costs in the Brazilian stock market. Therefore, for the present study, we directly treat bid-ask spread as asymmetric information.
Furthermore, this study considers that asset prices are driven by equality between purchase and sales flows rather than demand and supply issues. Therefore, we use an information-based model, focusing on asymmetric information and assuming that market makers cannot observe the origin of orders (Bailey, 2005).
In this study, we investigate the validity of the bid-ask spread estimator (Corwin & Schultz, 2012a) as an easy-to-compute and alternative measure of asymmetric information in the Brazilian stock market. The relevance of this type of research model increases because the high-frequency data used to obtain another measure of asymmetric information (pin score) have only been recently available (Easley, Hvidkjaer, & O'Hara, 2002; Martins & Paulo, 2013).
Minardi et al. (2006) developed and tested a measure for bid-ask spread in the Brazilian stock market from 1998 to 2003. Their findings showed that bid-ask spread is correlated negatively with liquidity and positively with return. They analysed data of the biggest firms using correlation and ordinary least squares (OLS) estimation methods.
In this study, we analyse the aggregate daily high and low stock price data of the most traded shares on the Brazilian stock market from 1986 to 2014. The Corwin-Schultz measures of asymmetric information are stationary and can be forecast using single-equation dynamic modelling (Granger, 1981). The aggregate data are obtained from the weighted average of the firm-level Ibovespa components' data for the second quarter of 2014.
The results are consistent with those of other studies examining the same market (Martins, Paulo, & Albuquerque, 2013) and market microstructure theory (Easley et al., 2002). The measures are sensitive to different periods, industries, and listing segments and have a time-varying cointegration vector with firm-level characteristics.
The remainder of this paper is structured as follows. The next section presents the theoretical framework comprising the market microstructure theory, the probability of information-based trading measure (PIN) score, and Corwin-Schultz issues. The third section describes the sample and the timeseries techniques applied. The fourth section presents and discusses the findings, and the final section presents the main implications and concluding remarks.
Theoretical Framework
Market microstructure
Hasbrouck (2007) identified the electronic limit order book, asymmetric information, and linear time-series analysis as the prominent trading approaches used to study financial securities or market microstructure. Madhavan (2000) conceptualizes market microstructure as the financial area pertaining to the process by which the latent demands of investors ultimately translate into transactions. The author clarifies the importance of market microstructure and informational economics and identifies the links between the former and the fields of investment, financing, and capital structure. For market microstructure theory, asset prices need not reflect the full-information expectation values due to a variety of frictions driven by the rapid structural, technological, and regulatory changes affecting the securities industry world-wide. Hasbrouck (2007) argues that only the minute or second horizon is relevant from the point of view of microstructure perspective of stock prices. He also alleges there are two main types of asymmetric information models: sequential trade models (trader randomly selected) and strategic trade models (single informed agent trades multiple trades and reveals some private information).
Roll (1984) presented a method to infer the effective bid-ask spread that requires only the securities time-series' prices, assuming market efficiency and stationarity of observed price changes. The effective bid-ask spread can be estimated with the Equation Spread = 2[square root of -cov], where 'cov' is the first-order serial covariance of price changes. This method came to be known as the Roll serial covariance bid-ask estimator, following Harris (1990), who examined its statistical properties and argued that Roll's method has a small sample estimator bias whereas French and Roll's (1986) adjusted-variance estimator is unbiased but noisy. The latter method was proposed by French and Roll (1986) while examining the greater variances in trading hour than non-trading hour returns. Glosten and Milgron (1985) believed that bid-ask spread implies a divergence between the observed and realizable returns and that the observed returns are approximately the realizable returns plus what the uninformed anticipate when losing to insiders. Glosten and Harris (1988) proposed, estimated, and cross-validated a two-component asymmetric information spread model, while decomposing the bid-ask spread into asymmetric information and inventory costs components. They found the spread to be a function of trade size.
Hasbrouck (1988) examined the effects of asymmetric information and inventory control on the relation between trades and quote revisions, and found substantial information on trade and strong evidence that large trades conveyed more information than small trades. Hasbrouck (1996) further examined the information on automated orders by using an econometric model capturing the joint behaviour of automated orders and the return on stock index futures, and found that orders contain information useful in predicting stock returns beyond the information contained in the reported trades. In another paper, Hasbrouck (1999) proposed a dynamic bid-ask quotes model incorporating the microstructure effects arising from the manner in which security is traded, such as the stochastic cost of market-making, discreteness, and clustering, using Gibbs sampler as a convenient estimation vehicle.
Hasbrouck and Seppi (2001) found that bid-ask spread and quote sizes help explain the time variation in trade impacts, and that existing common factors can explain the common variation in signed and absolute returns. Hasbrouck and Saar (2009) examined a limit order book during a month and observed that about 37% of the limit orders are cancelled within two seconds of submission, suggesting the traders search for liquidity.
Roll and Subrahmanyam (2010) found that competition among market makers lead to an increasing right-skewed distribution of bid-ask spreads and such spreads are associated to institutional holdings and the quantity of analysts that follow the company. Roll, Schwartz, and Subrahmanyam (2014) found a strong association among options trading, short interest rate, term structure and credit spreads, concluding the relevance of informational role of options.
Hasbrouck and Saar (2013) proposed the RunsInProcess, a measure of low-latency activity used to investigate the impact of high-frequency trading on the market environment using publicly available data, suggesting that the millisecond environment constitutes a fundamental change from the manner in which stock markets operated.
PIN score
Easley, Kiefer, and O'Hara (1997) developed the PIN, which is now standard in the literature. This measure uses the price, lagged price, and number of buys and sells to identify the importance of buy and sell trade in model specification and show how such a model can be used in a well-defined statistical framework to guide empirical work (Easley, Kiefer, & O'Hara, 1997). The paper followed Easley and O 'Hara's (1992) findings that trade time affects prices, with the time between trades affecting the spreads of security prices and volume affecting the speed of price adjustment. The definition of trade direction followed Lee and Ready's (1991) algorithm.
Easley, Hvidkjaer, and O'Hara (2002) used Easley et al.'s (1997) PIN model to incorporate obtained estimates into a Fama-French asset-pricing framework, and found that such information does affect asset pricing. Hasbrouck (1991) suggested the asymmetric information is negatively associated to the size of...
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