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.     

Estimating the probability of informed trading—does trade misclassification matter?

Easley et al. [1996. Journal of Finance 51, 1405–1436] have proposed an empirical methodology to estimate the probability of informed trading (PIN). This approach has been employed in a wide range of applications in market microstructure, corporate finance, and asset pricing. To estimate the model, a researcher only needs the number of buyer- and seller-initiated trades. This information, however, is generally unobservable and has to be inferred from trade-classification algorithms, which are known to be inaccurate. In this paper, we show analytically that inaccurate trade classification leads to downward-biased PIN estimates and that the magnitude of the bias is related to a security's trading intensity. Simulation results and empirical evidence based on order and transaction data from the New York Stock Exchange are consistent with this argument. We propose a data-based adjustment procedure that substantially reduces the misclassification bias.     

An improved estimation method and empirical properties of the probability of informed trading

We report evidence that boundary solutions can cause a bias in the estimate of the probability of informed trading (PIN). We develop an algorithm to overcome this bias and use it to estimate PIN for nearly 80,000 stock-quarters between 1993 and 2004. We obtain two sets of PIN estimates by using the factorized likelihood functions in both [Easley et al., 2010] and [Lin and Ke, 2011], respectively. We find that the estimate based on the EHO factorization is systematically smaller than the estimate based on the LK factorization, meaning that there is a downward bias associated with the EHO factorization. In addition, we find that boundary solutions appear with a very high frequency when the LK factorization is used. Thus it is necessary to use the LK factorization together with the algorithm in this paper. At last, we document several interesting empirical properties of PIN.     

Adverse-Selection Costs and the Probability of Information-Based Trading

Prior studies offer various empirical models to decompose the observed bid‐ask spread into the adverse‐selection and transitory (order‐processing and inventory‐holding) components. There is limited evidence, however, on whether the spread components estimated from these models indeed measure what they purport to measure. In this study, we show that the estimates of the adverse‐selection component given by these models are positively and significantly related to the probability of information‐based trading (PIN), after controlling for the endogeneity of the PIN and other stock attributes. These results provide direct empirical support for the spread component models examined in the present study.     

Does the Probability of Informed Trading Model Fit Empirical Data?

The probability of informed trading (PIN) is used widely as a measure of information asymmetry. Relatively little work has appeared on how well PIN models fit empirical trade data. We reveal structural limitations in PIN models by examining their marginal distributions and dependence structures represented by copulas. We develop a distribution-free test of the goodness-of-fit of PIN models. Our results indicate that estimated PIN models have generally poor fit to actual trade data. These results suggest that researchers should be cautious when PIN estimates are plugged into empirical models as explanatory variables.     

Information asymmetry in warrants and their underlying stocks on the stock exchange of Thailand

This paper examines the informational role of warrants based on the unique order data from the Stock Exchange of Thailand, where both warrants and stocks are traded under the same market structure and where warrants are as liquid as stocks. The estimated probability of informed trading (PIN) in warrants is found to be statistically higher than their underlying stocks regardless of order submission type and order size. The PIN explains a substantial portion of the cross-sectional variation in the opening spread beyond trading volume and minimum tick size. We find evidence that a signed warrant trade contains information about the future stock price and that warrants with a higher PIN have greater predictive powers.     

Probability of information-based trading and the January effect

We investigate the seasonality in the probability of information-based trading (PIN)–return relationship, the ‘January PIN effect’. We find that on average stock returns decrease with PIN in January, in contrast to other calendar months. This pattern is more apparent for small stocks. We argue that this seasonality is related to the January effect. According to the analysis, the December selling pressure associated with the January effect decreases in PIN, especially for small stocks. This suggests that when the price bounces back in January, low-PIN stocks will exhibit a larger return within a small stock group, leading to the negative PIN–return pattern. Furthermore, this seasonality is not the same as other January anomalies associated with momentum and idiosyncratic risk.     

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.     

Is information risk priced for NASDAQ-listed stocks?

Easley et al. (J Finance 57:2185–2221, 2002), building upon the asset pricing model of Fama and French (J Finance 47:427–465, 1992), show that the probability of informed trading (PIN) is a determinant of asset returns for NYSE-listed securities. We extend this work by examining whether the PIN is a predictive factor for NASDAQ stocks, as many studies document significant differences between NYSE and NASDAQ listed securities. In the process we examine whether the use of PIN is appropriate for NASDAQ-listed securities. We find that PIN and certain stock characteristics correlate differently for our sample of NASDAQ stocks than that of Easley et al. sample of NYSE stocks. We also determine that the risk of informed trading is only weakly priced for NASDAQ stocks. Contrary to Easley et al. we do not find evidence that excess returns increases as PIN increases.     

Does eliminating the Form 20-F reconciliation from IFRS to U.S. GAAP have capital market consequences?

This paper investigates the capital market consequences of the SEC's decision to eliminate the reconciliation requirement for cross-listed companies following International Financial Reporting Standards (IFRS). We find no evidence that the elimination has a negative impact on firms' market liquidity or probability of informed trading (PIN). We also find no evidence of a significant impact on cost of equity, analyst forecasts, institutional ownership, stock price efficiency and synchronicity. Moreover, IFRS users do not increase disclosure frequency nor supply the reconciliation voluntarily. Our results do not support the argument that eliminating the reconciliation results in information loss or greater information asymmetry.     

Does information vault Niagara Falls? Cross-listed trading in New York and Toronto

We document differential private information in cross-border asset pricing using the probability of informed trading (PIN) for Canadian shares traded on both sides of Niagara Falls. Relative to the New York Stock Exchange (NYSE), the Toronto Stock Exchange (TSX) has more informed trades and a larger information share. This cross-border information imbalance is associated with small but positive price premiums in New York as predicted by a model. The dynamics of these premiums depends on trade informativeness. Lastly, the PIN for TSX trading typically rises upon cross-listing on the NYSE, which is consistent with the negative event-study response.     

Trading costs for listed options: The implications for market efficiency

This paper reexamines the anomalous evidence concerning the efficiency of the listed options exchanges. We focus on the structure of trading costs in that market, and note several costs which generally have been ignored, the largest of which is the bid-ask spread. When we adjust the published trading rules for our estimates of these trading costs, the reported abnormal returns are eliminated.     

A faster estimation method for the probability of informed trading using hierarchical agglomerative clustering

The probability of informed trading (PIN) is a commonly used market microstructure measure for detecting the level of information asymmetry. Estimating PIN can be problematic due to corner solutions, local maxima and floating point exceptions (FPE). Yan and Zhang [J. Bank. Finance, 2012, 36, 454–467] show that whilst factorization can solve FPE, boundary solutions appear frequently in maximum likelihood estimation for PIN. A grid search initial value algorithm is suggested to overcome this problem. We present a faster method for reducing the likelihood of boundary solutions and local maxima based on hierarchical agglomerative clustering (HAC). We show that HAC can be used to determine an accurate and fast starting value approximation for PIN. This assists the maximum likelihood estimation process in both speed and accuracy.     

The probability of informed trading and mergers and acquisitions

This paper investigates the role of the probability of informed trading (PIN) in mergers and acquisitions (M&A). We show that acquirers with higher PINs use more cash to finance their deals due to their higher cost of equity, and acquirers use more equity financing when acquiring targets with higher PINs to share the information risk with the target shareholders. We also find that acquirers and targets with higher PINs both experience higher announcement returns when cash financing is used, indicating that PINs are priced in the M&A market.     

The Role of Stock Size and Trading Intensity in the Magnitude of the "Interval Effect" in Beta Estimation: Empirical Evidence from the Polish Capital Market

In this paper, we present empirical evidence about the "interval effect" in estimation of beta parameters for stocks listed on the Warsaw Stock Exchange. We analyze models constructed for the returns calculated using intervals of different length—that is, 1, 5, 10, and 21 trading days (corresponding to, roughly, 1 day, 1 week, 2 weeks, and 1 month, respectively). In the cases in which heteroskedasticity was present, we estimated ARCH models. The results indicate that the estimates of betas for the same stock differ considerably when various return intervals are used. We further explore the source of differences in betas for every stock by investigating the relations between them and such factors as stock size and its trading intensity. The empirical results provide evidence that a statistically significant relationship exists between these two characteristics of stocks. This finding has important practical implications for beta estimation in practice.     

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.     

Corporate Events,Trading Activity,and the Estimation of Systematic Risk: Evidence From Equity Offerings and Share Repurchases

We investigate the relation between trading activity, the measurement of security returns, and the evolution of security prices by examining estimates of systematic risk surrounding equity offerings and share repurchases. In contrast to prior studies, we find no evidence of changes in systematic risk following either equity offerings or share repurchases after correcting for biases caused by infrequent trading and price adjustment delays. Moreover, changes in ordinary least squares beta estimates are significantly related to contemporaneous changes in trading activity. Our results have implications for studies interested in the properties of security returns, particularly those examining periods in which trading activity changes.     

Female insiders' ethics and trading profitability

We provide the evidence of ethical differences between female and male top managers and insiders in conducting profitable trades with their own company stocks. Using a large sample of Chinese insider trading activities, we find that female insiders trade less profitably, which can be attributed to their higher ethical values. This relationship is robust for various profitability measures and holds after addressing potential endogeneity bias. We also provide evidence that our findings are not explained by female insiders' informational disadvantage, risk aversion, managerial ability, trading experience or concerns for differential legal consequences. Our study provides a more direct evidence on the ethical differences in gender in the context of insider trading.     

Does information risk affect the implied cost of equity capital? An analysis of PIN and adjusted PIN

Using a unique dataset of Korean listed companies for which trade initiators are correctly identifiable, we estimate bias-free PIN (probability of informed trading) that is no longer subject to the trade misspecification problem and test whether it is related to expected returns. Unlike prior studies, we find that bias-free AdjPIN, the adjusted PIN purged of a liquidity component, is positively related to implied cost of equity. Our findings suggest that the errors in PIN variables hamper a proper identification of PIN pricing in prior studies.     

The Interim Trading Skills of Institutional Investors

Using a large proprietary database of institutional trades, this paper examines the interim (intraquarter) trading skills of institutional investors. We find strong evidence that institutional investors earn significant abnormal returns on their trades within the trading quarter and that interim trading performance is persistent. After transactions costs, our estimates suggest that interim trading skills contribute between 20 and 26 basis points per year to the average fund's abnormal performance. Our findings also indicate that any trading skills documented by previous studies that use quarterly data are biased downwards because of their inability to account for interim trades.