Endogenous informed trading in the presence of trading costs: Theory and evidence

The basic premise of the model we propose is that market frictions (trading costs) force traders with market-wide information to strategically choose which securities to trade in. We study the effect of recognizing trading costs on the choices of informed traders and the resulting statistical properties of security prices. Specifically, we show that (1) stocks with intermediate β's have the least informative prices, even though they are traded by the greatest number of informed traders; (2) for high β securities, the contemporaneous correlation of prices is close to the correlation in fundamental values; (3) a security with a higher β, higher volume of liquidity trading and lower idiosyncratic variance is more likely to lead another security. With market capitalization as a proxy for the level of liquidity trading, these specific predictions of the model on the lead–lag relationship are also shown to be strongly supported by the data.     

Investor protection, adverse selection, and the probability of informed trading

The purpose of this study is to investigate the relation between investor protection, adverse selection, and the probability of informed trading. Previous research has established a direct relation between investor protection and firm liquidity, measured by bid-ask spreads and depths. In this study, we test the hypothesis that adverse selection is the mechanism through which poor investor protection leads to higher costs of liquidity. The Hong Kong equity market provides a unique opportunity to compare adverse selection differences across distinct investor protection environments, holding constant the trading platform and currency. Using various bid-ask spread decomposition models and probability of informed trading estimates, we confirm the hypothesized relation between investor protection quality and adverse selection costs. These findings contribute to the literature by establishing one of the links in the chain connecting investor protection to firm valuation.

Adverse selection,brokerage coverage,and trading activity on the Tokyo Stock Exchange

Limit-order trading mechanisms, corporate ownership structure, and incentive structures in the Japanese brokerage industry differ from those in the US in several important ways. This paper exploits these differences to examine the joint and cross-sectional determinants of adverse selection costs, brokerage coverage, and trading activity for a large sample of Japanese firms traded on the Tokyo Stock Exchange. We find that adverse selection costs are associated with firm characteristics but not with ownership characteristics, which implies that adverse selection costs are affected by inside trading rather than inside holdings. We also find that while brokerage coverage reduces adverse selection costs, higher adverse selection costs lead more brokerage firms to enter the market because of the greater profit potential. Finally, we find that causality also runs both ways between brokerage coverage and trading volume: brokerage coverage increases trading volume and trading volume increases brokerage coverage.     

Cross-market informed trading in the CDS and option markets

This paper analyzes how informed traders balance leverage and liquidity in making cross-market trading decisions. Our findings are three-fold. Using daily data on the actively traded North American CDX Investment Grade and High Yield indexes from 2010 to 2017, first, we find robust evidence that, when the credit default swap (CDS) market is illiquid, informed traders do not hesitate to exploit their information advantage in the option market, and this manifests mainly for negative credit news. Second, we find that informed trading occurs predominantly in the option market for low-rated firms due to high adverse selection risk in the CDS market. Third, there is strong evidence of informed trading taking place in the CDS market for financial firms and we argue that this is due to the interdealer network through which CDS dealers obtain private information about other financial firms and their privileged position as market makers to be able to disguise their informed trades as ordinary market-making activities. Finally, we propose re-thinking market efficiency and how to advance it in a direction which does not privilege a small circle of financiers or create monopoly while keeping the markets liquid and tranquil at all times.     

Optimal informed trading in the foreign exchange market

We formulate a market microstructure model of exchange determination that we employ to investigate the impact of informed trading on exchange rates and on foreign exchange (FX) market conditions. With our formulation, we show how strategic informed agents influence exchange rates via both the portfolio-balance and information effects. We outline the connection which exists between the private value of information, market efficiency, liquidity and exchange rate volatility. Our model is also consistent with recent empirical research on the micro-structure of FX markets.     

Adverse selection costs,trading activity and price discovery in the NYSE: An empirical analysis

This paper studies the role that trading activity plays in the price discovery process of a NYSE-listed stock. We measure the expected information content of each trade by estimating its permanent price impact. It depends on observable trade features and market conditions. We also estimate the time required for quotes to incorporate all the information content of a particular trade. Our results show that price discovery is faster after risky trades and also at the extreme intervals of the session. The quote adjustment to trade-related shocks is progressive and this causes risk persistency and unusual short-term market conditions.     

The implied intra-day probability of informed trading

The paper develops a methodology for estimating the intra-day probability of informed trading for NYSE stocks, implied by the specialist’s quotes and depths. The time series pattern of our measure (PROBINF) in an intra-day analysis around earnings announcements is consistent with previous findings and with expectations regarding informed trading. Moreover, we find that PROBINF exhibits a strong and robust relationship with PIN, the level of insider trading and with measures of the price impact of trades. Our methodology complements the one developed in Easley et al. (J Financ 51(3):811–833, 1996a, J Financ 51(4):1405–1436, b), as it can be used to measure short term changes in informed trading and information asymmetry around events such as merger and acquisition announcements, share repurchases, stock splits, dividend announcements and index additions and deletions.     

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 impact of informed trading on corporate liquidity

The purpose of this paper is to analyze the impact of informed trading on corporate liquidity. Although theory posits an inverse relation between informed trading and firm liquidity, there is relatively little evidence on precisely how this relation is established or maintained. The trading model of Easley et al. (J. Finance 51 (1996) 1405) is employed to estimate the probability of informed trading and to identify specific days of informed trading using posterior probabilities. The results show that corporate liquidity, both in terms of spreads and depths, is a decreasing function of the probability of informed trading. The main finding is that spreads narrow and depths increase on actual information days even after controlling for variations in price, volume, and volatility.     

A computing bias in estimating the probability of informed trading

This study identifies a factor that leads to a bias in estimating the probability of informed trading (PIN), a widely-used microstructure measure. It is shown that, along with the numerical maximization of the likelihood function for PIN, the floating-point exception (i.e., overflow or underflow) may eliminate feasible solutions to the actual parameters in the optimization problem. Approximately 44% of PIN estimates for recent stock market data may have been subject to a downward bias that is more pronounced for active stocks than for inactive stocks. This study develops a remedy to mitigate the resulting bias.     

Complete markets,informed trading and equity option introductions

This paper proposes and tests a new hypothesis concerning the price impact of option introductions on the underlying asset. We argue that the leverage properties of options induce a higher level of informed trading in the aggregate market (underlying plus derivative), resulting in excess listing-day price movements in the newly optioned equity. Using an alternative dataset, our results suggest that this may be an explanation for the observed positive than negative excess listing-day returns of US optioned stocks over the past thirty years.     

Security price formation and informed trading with constrained short selling

Short sale orders account for a substantial portion of trading volume in recent years. This paper develops a sequential trade model with constrained short selling to derive the effect on prices when the market maker can observe short selling in the order flow. The model predicts that market quotes will adjust differently to short sales and regular sales. Furthermore, the model shows that the probability of informed trading is impacted both by the level of short sale constraints and the intensity of actual short sale trades. Simulation evidence confirms that estimates of the probability of informed trade are improved when accounting for past short selling activity. The results demonstrate the information benefits of short selling transparency.

     

Dancing in the dark: post-trade anonymity,liquidity and informed trading

We analyze the impact of post-trade anonymity on liquidity and informed trading in an order driven stock market. The German stock market introduced the Central Counterparty (CCP) in March 2003 for German equities traded on its anonymous electronic trading platform Xetra leading to a major change in its existing transparency regime. Before the introduction trader IDs were revealed to the counterparties of a trade, with the introduction of the CCP even after the transaction the traders remain anonymous. Previous theoretical and empirical research documents that pre-trade anonymity results in increased liquidity, while results on post-trade anonymity are mixed. We find a significant increase in liquidity measured through a reduction of 25% in implicit transaction costs. We also document that the arrival rate of informed traders is reduced in the anonymous setting. Following recent findings of Bloomfield et al. (J Finan Econ 75:165–199, 2005) that informed traders take on the role of liquidity providers we interpret our findings as indication that informed traders change their behavior in providing liquidity more aggressively in an anonymous environment.     

Family control,multiple institutional block-holders,and informed trading

This paper investigates how large family shareholders and institutional block-holders jointly influence informed trading and firm valuation in the Hong Kong stock market. It combines market microstructure research with studies on the governance roles of multiple block-holders and finds that institutional block-holders rely on their relative controlling power vis-à-vis family owners to mitigate problems associated with informed trading. They also use their ownership rights to improve the structure of informed trading. However, these governance roles are predominantly exercised by pressure-resistant institutional block-holders. Informed trading reduces firm valuation, while an improvement in its structure increases valuation. Therefore, the governance roles of controlling families and pressure-resistant institutional block-holders may have different implications in terms of investors’ perceptions of private information risk.     

Earnings announcements,private information,and strategic informed trading

In this paper, we estimate and test a multi-period model of strategic informed trading developed by Foster and Viswanathan [Foster, F.-D., Viswanathan, S., 1996. Strategic trading when agents forecast the forecasts of others, J. Finance 51, 1437–1478]. We employ the GMM using intertemporal patterns of price, trading volume and market depth, leading up to the earnings announcements made by NYSE firms. We find that multiple informed traders with heterogeneous private signals trade prior to the announcements. In addition, by comparing the results from daily and intra-day estimations, we find that the number of informed traders increases while the intensity of liquidity trading decreases, and that the adverse selection problem becomes more pronounced as the announcements approach.     

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 and the financial accelerator

Many economists believe that credit market distortions create a financial accelerator which destabilizes the economy. This paper shows that when credit market distortions arise from adverse selection they sometimes stabilize the economy rather than destabilize it. The stabilizing forces are closely related to forces that cause overinvestment in static models. When investment projects are equity financed, or when contracts are written optimally, the distortions always stabilize the economy. Thus, stabilizing equilibria are a robust feature of the model. The empirical distinction between accelerator and stabilizer equilibria is subtle. Many empirical tests are unable to distinguish between accelerator and stabilizer equilibria.     

Heterogeneously informed trading and the stock market efficiency during the COVID-19 pandemic

This study investigates the U.S. stock market efficiency from the symmetric and asymmetric perspectives during the COVID-19 pandemic. We explore that the pandemic boosts (hurts) the information role of symmetrically (asymmetrically) informed trading. Specifically, we find that the epidemic outbreak and infection scale strengthen (weaken) the stock return reaction to symmetrically (asymmetrically) informed trading. Evidence also indicates that the effect of symmetrically (asymmetrically) informed trading on stocks' permanent price shocks and price informational efficiency is enhanced (impaired) during the pandemic. Moreover, all these effects are consistently more intensive to informed buys.     

The characteristics of informed trading: Implications for asset pricing

This paper investigates the linkage of microstructure, accounting, and asset pricing. We determine the relationship between firm characteristics as captured by accounting and market data and a firm's probability of private information-based trade (PIN) as estimated from trade data. This allows us to determine what types of firms have high information risk. We then use these data to create an instrument for PIN, the PPIN, which we can estimate from firm-specific data. We show that PPINs have explanatory power for the cross-section of asset returns in long sample tests. We also investigate whether information risk vitiates the influence of other variables on asset returns. We develop a PPIN factor and show that it dominates the Amihud factor in asset returns. Our results provide strong support for information risk affecting asset returns in long sample tests.     

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.