Decimal Pricing and Information-Based Trading: Tick Size and Informational Efficiency of Asset Price

Abstract:  In this study we analyze the effect of tick size on information-based trading. Although prior studies provide extensive evidence on the effect of tick size on market quality measures such as spreads, depths, and return volatility, there is little evidence as to the effect of tick size on the informational efficiency of asset price. Our results indicate that the probability of information-based trading during the post-decimal period is significantly greater than the corresponding figure during the pre-decimal period. We also show that the increase in information-based trading after decimalization cannot be attributed to concurrent changes in stock attributes. We interpret our findings as evidence that the smaller tick size under penny pricing encourages information-based trading and thereby raises the informational efficiency of asset price.     

Information-based stock trading and managerial incentives: evidence from China's stock market

This paper uses stock price informativeness, or information-based stock trading, to help explain the pay–performance sensitivity (PPS) of chief executive officer (CEO) compensation in China's listed firms. We argue that higher stock price informativeness, which we measure by the probability of informed trading, helps and encourages shareholders to incentivize the top management team based on stock market performance. The regression results support our argument and show that a higher level of stock price informativeness is associated with higher CEO PPSs. Moreover, the impact of stock price informativeness on CEO incentives is stronger for privately controlled listed firms than it is for state-controlled listed firms. The results also hold when information asymmetry is approximated by the accuracy and dispersion of the earnings forecasts made by financial analysts.     

Liquidity,Information, and Infrequently Traded Stocks

This article investigates whether differences in information-based trading can explain observed differences in spreads for active and infrequently traded stocks. Using a new empirical technique, we estimate the risk of information-based trading for a sample of New York Stock Exchange (NYSE) listed stocks. We use the information in trade data to determine how frequently new information occurs, the composition of trading when it does, and the depth of the market for different volume-decile stocks. Our most important empirical result is that the probability of information-based trading is lower for high volume stocks. Using regressions, we provide evidence of the economic importance of information-based trading on spreads.     

Information-Based Trading and Price Improvement

Abstract:  In this study we test the information hypothesis of price improvement. Our results show that price improvement is negatively related to both the probability of information-based trading and the price impact of trades. We interpret these results as evidence that liquidity providers selectively offer price improvements according to the information content of trades. We also show that liquidity providers offer greater (and more frequent) price improvements when they are at the NBBO, and for stocks with wider spreads, fewer trades, or smaller trade sizes relative to the quoted depth. Buyer-initiated trades receive smaller (larger) price improvements than seller-initiated trades on the NYSE (NASDAQ).     

Disclosure regulation and information risk

The present paper examines the impact of the Corporations Law Reform Act 1994 on information-based trading in Australian Stock Exchange-listed stocks. Results show that information-based trading is higher in the post-reform period, particularly for lower capitalization stocks. Further analysis shows that this is caused by a fall in turnover and rise in the number of slow trading days. After controlling for these factors, the reform is found to have no impact on information-based trading. Interestingly, the volume of price-sensitive disclosures is found to have no impact on either the level of information-based trading or market spreads.     

Information diffusion in electronic and floor trading

The attractiveness of floor trading versus anonymous electronic trading systems for traders is analysed. We hypothesize that in times of low information intensity, the insight into the order book of the electronic trading system provides more valuable information than floor trading, but in times of high information intensity, this is not true. Thus, the electronic system's market share in trading volume should decline when information intensity increases. This hypothesis is tested by DTB and LIFFE data on Bund-Future trading in the period 1991 to 1995. In the first years of trading, the DTB's market share is inversely related to price volatility and trading volume as proxies for information intensity. In recent years, this relation fades away; this can be explained by the high frequency of transactions which implies a steady flow of information on transactions.     

Order preferencing, adverse-selection costs, and the probability of information-based trading

Although prior studies offer various conjectures on the causes and consequences of order preferencing, there is only limited empirical evidence. In this study, we show that the extent of order preferencing is significantly and negatively related to both the adverse-selection component of the spread and the probability of information-based trading. This result is consistent with the prediction of the clientele-pricing hypothesis that dealers (brokers) selectively purchase (internalize) orders based on information content. Our results suggest that order preferencing may not be as harmful as some researchers have suggested and offer some rationale for its prevalence in securities markets with heterogeneously informed traders. JEL Classification G18 · G19     

The PIN anomaly around M&A announcements

The probability of information-based trading (PIN) introduced by Easley and O’Hara (1987) has been increasingly used in empirical research in finance. We investigate its behavior around a sample of merger and acquisition announcements that took place on Euronext Paris between 1995 and 2000. The behavior of the PIN seems to be in contradiction with clear evidence of information leakages in our sample during the pre-event period. We investigate the reasons for its unusual behavior and raise some concerns about its use as an information-based trading indicator, at least around major corporate events.     

Dealer attention,the speed of quote adjustment to information,and net dealer revenue

Using trade and quote data from the NYSE, we examine the relation between dealer attention, dealer revenue, and the probability of informed trade. We find that dealer revenue net of losses to better-informed traders in NYSE stocks is positively related to the speed at which quotes adjust to full information levels. The speed of quote adjustment is faster for stocks with greater dealer attention, as measured by a stock’s relative prominence at its post and panel location on the NYSE floor. The level of dealer attention in turn is positively related to a stock’s probability of information-based trading. The results are consistent with a theoretical model we derive in which dealers trade multiple securities and must optimally allocate their limited attention to monitoring order flow to minimize losses to better-informed traders.     

Liquidity costs: Screen-based trading versus open outcry

The results reported in this paper challenge the popular belief that screen-based trading offered lower liquidity costs than the open-outcry approach during its first year of side-by-side operation in the U.S. financial derivatives market. Using time and sales data from the Chicago Board of Trade (CBOT) market profile data series, effective bid-ask spreads are estimated on the basis of daily and intraday measures of the Thompson-Waller and Smith-Whaley estimators. We find liquidity costs on the screen-based system vary with time and the level of floor trading activity. In particular, a one-tick market is observed just before the opening of the Chicago trading floor (6:30 to 7:30 am). However, subsequent intraday spreads exhibit the familiar “reverse J-shaped pattern”—highest following the opening of floor trading, declining until afternoon, and then increasing until close. Meanwhile, daily spread estimates average almost a quarter-tick higher on the screen-based market relative to the one-tick spread commonly associated with open outcry. This relationship remained robust across sample time-series and conservative price-change specifications. Since the study was conducted, electronic trading has become the predominant exchange medium for financial derivatives at the CBOT, following the example set in Europe's traditional futures exchanges, e.g. France's Matif, Germany's Deutsche Bourse and the U.K.'s Liffe.     

What does PIN identify? Evidence from the T-bill market

The probability of informed trading (PIN) measure has been increasingly used in empirical research in finance. However, there is a growing debate as to whether PIN measures information-based or liquidity-based trading. We contribute to the discussion by estimating PIN using transaction data for one-month T-bills. Our PIN estimates exceed those reported for equities, despite it being unlikely that the probability of informed trading is higher in T-bills than equities. We conclude that PIN identifies trading clusters and that the source of the clustering depends on the economics of the market. The economics of the T-bill market suggest discretionary liquidity traders are the likely source of the clustering.     

The Inter-Temporal Behavior of Informed and Uninformed Traders

The purpose of this study is to investigate the inter-temporal trading behavior of informed and uninformed investors. We estimate a variation of the market microstructure model developed in Easley, Keifer, O'Hara, and Paperman (1996) and document the day-of-the-week pattern in informed and uninformed trading, as well as the probability of an information event and the probability of bad news. Using bootstrapped distributions, we show that the probability of trading against informed investors follows a U-shape pattern from Monday to Friday. Cross-sectional regression results suggest that inter-temporal patterns between informed and uninformed traders can generate observed patterns in liquidity provision costs.     

Algorithmic trading and block ownership initiation: An information perspective

This paper examines the impact of algorithmic trading (AT) on investors' incentives to initiate block ownership in U.S. public companies. We find that a one standard deviation change in AT activity reduces the block ownership initiation likelihood by 3.5%. Using the SEC's randomised tick size pilot experiment in 2016 as a negative shock to AT, we show that the effect of AT on block ownership initiation is causal. Further evidence supports the information-hindering explanation that AT discourages sophisticated investors from acquiring information, which results in a decrease in block ownership initiation. We find that the effect of AT is more pronounced among information-sensitive investors and that institutional investors reduce their information-gathering activities in AT-targeted stocks. Additional tests exploring information-based trading behaviour in the presence of AT provide strong evidence to support the explanation of information-hindering, and our results hold across a battery of robustness tests.     

Are Liquidity and Information Risks Priced in the Treasury Bond Market?

We provide a comprehensive empirical analysis of the effects of liquidity and information risks on expected returns of Treasury bonds. We focus on the systematic liquidity risk of Pastor and Stambaugh as opposed to the traditional microstructure-based measures of liquidity. Information risk is measured by the probability of information-based trading (PIN). We document a strong positive relation between expected Treasury returns and liquidity and information risks, controlling for the effects of other systematic risk factors and bond characteristics. This relation is robust to many empirical specifications and a wide variety of traditional liquidity and informed trading proxies.     

The magnet effect of price limits: A logit approach

We investigate the magnet effect of price limits using transaction data from the Taiwan Stock Exchange. A logit model incorporates explanatory variables from microstructure literature and reveals that the conditional probability of a price increase (decrease) increases significantly when the price approaches the upper (lower) price limit, in support of the magnet effect. Our approach recognizes when the magnet effect starts to emerge and identifies possible determinants of magnet effect. The probability of information-based trading has a significant impact on the magnet effect for lower price limits.     

With or without you: market quality of floor trading when screen trading closes early

Most stock markets are characterized by a number of parallel operating trading systems which interact intensively with each other. Usually, smaller trading platforms take the leading domestic main market as a benchmark in the price discovery process and for closing open trading positions. But what happens if the smaller trading systems suddenly have to act without this benchmark platform? We examine the effects of the reduction of the daily business hours of a screen based main trading system while a parallel floor based trading system keeps on operating. We provide evidence that liquidity improves while informed trading and informational efficiency of prices decrease at the floor based trading system as a result of the no longer operating main market. While prior research on parallel trading focuses on changes due to a growing number of trading venues, we present the first evidence on market effects when the main trading platform reduces trading hours.     

Information-based trading,price impact of trades,and trade autocorrelation

In this study we show that both the price impact of trades and serial correlation in trade direction are positively and significantly related to the probability of information-based trading (PIN). The positive relation remains significant even after controlling for the effects of stock attributes. Higher trading activity (i.e., shorter intervals between trades) induces both larger price impact and stronger positive serial correlation in trade direction. The effect of time interval between trades on quote revision is stronger for stocks with higher PIN values. These results provide direct empirical support for the information models of trade and quote revision.     

Does Greater Market Transparency Reduce Information Asymmetry?

This research aims to determine whether the degree of asymmetric information decreases with greater pre-trade transparency in the Taiwan stock market. We used the probability of informed trading based on the Markov regime-switching model in an order-driven auction market to investigate this topic. Information asymmetry showed no conspicuous variations with greater transparency. However, after further grouping, the empirical results revealed that increased transparency facilitated a decrease in information asymmetry in the sub-samples, which originally exhibited greater information asymmetry. In addition, the intraday patterns of probability of informed trading revealed that greater transparency facilitates decreased market information asymmetry after opening.     

Quality of PIN estimates and the PIN-return relationship

This paper provides new evidence concerning the probability of informed trading (PIN) and the PIN-return relationship. We take measures to overcome known estimation biases and improve the quality of quarterly PIN estimates. We use the average of a firm’s PIN estimates in four consecutive quarters to smooth out the effect of seasonal variation in trading activities. We find that when high-quality PIN estimates are used, the Fama–MacBeth cross-sectional regressions show stronger evidence for the positive PIN-return relationship than documented in the prior literature. This finding is robust to controls for the January, liquidity, and momentum effects.     

TSFDC: A trading strategy based on forecasting directional change

Directional Change (DC) is a technique to summarize price movements in a financial market. According to the DC concept, data is sampled only when the magnitude of price change is significant according to the investor. In this paper, we develop a contrarian trading strategy named TSFDC. TSFDC is based on a forecasting model which aims to predict the change of the direction of market's trend under the DC context. We examine the profitability, risk and risk‐adjusted return of TSFDC in the FX market using eight currency pairs. The results suggest that TSFDC outperforms the buy and hold approach and another DC‐based trading strategy.