We introduce a novel perspective on private information, specifically microstructure-based private information, to unravel how institutional investors predict stock returns. Using tick-by-tick transaction data from the Chinese stock market, we find that in retail-dominated markets, institutional investors positively predict stock returns, consistent with findings from institution-dominated markets. However, in contrast to the traditional view that institutional investors primarily rely on value-based private information, our results indicate that microstructure-based private information contributes almost as much to their predictive power as value-based private information does, with both components jointly accounting for approximately two-thirds of the total predictive power of institutional order flow. This finding reveals that retail investors’ trading activities significantly impact institutional investors, naturally forcing them to balance firm value information with microstructure information, thus profoundly influencing the price discovery process in the stock market.

Using Chinese data, we find that analysts’ earnings forecasts are more accurate and less biased when analysts are socially connected with the company’s signatory auditor. We also find that forecast performance improves following mandatory auditor rotations that result in new analyst-auditor connections and declines following mandatory rotations that terminate existing connections. We further find that our results become stronger when the information that auditors possess is likely to be more useful to analysts, that connected analysts have better career outcomes than unconnected analysts, and that investors and other analysts are more responsive to forecast revisions issued by connected analysts. Finally, we find that connected auditors provide higher quality audits to their connected clients and are more likely to retain those clients. Overall, our findings are consistent with connected analysts benefitting from private information obtained from their social connections with auditors by providing better earnings forecasts, and in turn, with auditors benefitting from information they receive from connected analysts by delivering higher quality audits that improve client retention.

Bank stress tests can be an effective information disclosure policy in persuading stakeholders to avoid “attacking” a bank, thereby decreasing the probability of bank failure during distress. This paper studies stress test design along two dimensions: strength and frequency, assuming stakeholders are privately informed and move sequentially. We characterize all robustly persuasive stress tests that ensure all bank stakeholders disregard private information and coordinate actions perfectly based on test results (“pass” or “fail”). Our ffndings indicate that more frequent stress tests can substitute for increased test strength in making the stress test result robustly persuasive. We then identify the optimal stress test policy and investigate how the optimal frequency and strength depend on macroeconomic conditions, bank idiosyncratic characteristics, and endogenous maturity choices of banks. Finally, we discuss how other regulatory measures may complement the stress test policy.

This paper examines whether sell-side analysts struggle to cope with macroeconomic uncertainty. We find that analysts issue more accurate earnings forecasts when facing higher economic policy uncertainty, which conflicts with the conclusions in the US. We provide a novel explanation for this finding and exclude the view that forecast accuracy improvement comes from analysts’ efforts to actively collect private information through site visits. Further evidence supports that heuristic cognitive bias and emotional framing effect hold back analysts’ tendency to optimism in China, resulting in higher forecast accuracy. As to why Chinese analysts do not work harder but issue more accurate forecasts, we suggest that it is mainly due to the different market regimes faced by analysts in the two countries. Our study sheds light on how macroeconomic uncertainty affects analysts’ unethical behavior and explains the cognitive processes involved.

It has been long that literature in financial academics focuses mainly on price and return but much less on trading volume. In the past twenty years, it has already linked both price and trading volume to economic fundamentals, and explored the behavioral implications of trading volume such as investor’s attitude toward risks, overconfidence, disagreement, and attention etc. However, what is surprising is how little we really know about trading volume. Here we show that trading volume probability represents the frequency of market crowd’s trading action in terms of behavior analysis, and test two adaptive hypotheses relevant to the volume uncertainty associated with price in China stock market. The empirical work reveals that market crowd trade a stock in efficient adaptation except for simple heuristics, gradually tend to achieve agreement on an outcome or an asset price widely on a trading day, and generate such a stationary equilibrium price very often in interaction and competition among themselves no matter whether it is highly overestimated or underestimated. This suggests that asset prices include not only a fundamental value but also private information, speculative, sentiment, attention, gamble, and entertainment values etc. Moreover, market crowd adapt to gain and loss by trading volume increase or decrease significantly in interaction with environment in any two consecutive trading days. Our results demonstrate how interaction between information and news, the trading action, and return outcomes in the three-term feedback loop produces excessive trading volume which includes various internal and external causes. Finally, we reconcile market dynamics and crowd’s trading behaviors in a unified framework by Shi’s price-volume differential equation in stock market where, we assume, investors derive a liquidity utility expressed in terms of trading wealth which is equal to the sum of a probability weighting utility and a reversal utility in reference to an outcome. JEL Classifications: G12, G02, D83 （长期以来，金融学术领域里的文献只注重价格和收益率，却较少研究交易量。在最近的二十年里，金融学术文献已经开始研究价格和交易量两者与经济基本量之间的相互关系，并且探讨交易量的行为内涵，例如投资者对风险的态度、过度自信、不同观点以及关注程度等等。然而，我们还是对交易量的认识知之甚少。本文根据行为分析，用交易量概率来表示市场群体的交易频率，并且通过我国股市来实证检验涉及交易量与价格之间不确定关系的两种适应性假说。实证结果表明：市场群体在每日交易的时间窗口内除了采用简单的经验法则之外，同时还采用有效的适应性方式来从事股票交易，并且逐步倾向于形成一个结果和认同的资产价格；无论该资产价格是否明显地被高估或低估，市场群体在相互作用和竞争的过程中往往能够形成这样一个稳态的均衡价格。这表明了资产价格不仅包含了基本价值同时还包含了非公开信息、投机、情绪、关注、赌博和娱乐等价值。此外，在任意两个连续交易日之间，市场群体在与市场环境的相互作用过程中，通过交易量的增加或减少来有效地适应盈亏。我们的研究结果说明了在由信息、交易与收益结果三项构成的反馈环中，它们之间的相互作用是如何导致了过度交易的，这其中包含了导致过度交易的各种内外因素。最后，我们假设股票市场中的投资者是通过交易财富来产生流动性效用，它等于概率加权效用与相对于结果为参照系的反转效用之和，从而推导出Shi氏价-量微分方程，将市场动力学行为与群体交易行为协调在一个统一的框架体系。）

It has been long that literature in financial academics focuses mainly on price and return but much less on trading volume. In the past twenty years, it has already linked both price and trading volume to economic fundamentals, and explored the behavioral implications of trading volume such as investor’s attitude toward risks, overconfidence, disagreement, and attention etc. However, what is surprising is how little we really know about trading volume. Here we show that trading volume probability represents the frequency of market crowd’s trading action in terms of behavior analysis, and test two crowd’s trading behavioral hypotheses relevant to the volume uncertainty associated with price in China stock market. The empirical work reveals that market crowd trade in simple heuristics and efficient adaptation, gradually tend to achieve agreement on an outcome or an asset price widely on a trading day, and generate such a stationary equilibrium price very often in interaction among themselves no matter whether it is highly overestimated or underestimated, suggesting that asset prices include not only a fundamental value but also private information, speculative, sentiment, gamble, and entertainment values etc. In addition, market crowd adapt to gain and loss by trading volume increase or decrease significantly in interaction with environment in any two consecutive trading days. Our results demonstrate how interaction between information and news, the trading action, and return outcomes in the three-term feedback loop produces excessive trading volume which includes various internal and external causes. Finally, we reconcile market dynamics and crowd’s trading behaviors in a unified framework by Shi’s price-volume differential equation in stock market where, we assume, investors derive a liquidity utility expressed in terms of trading wealth which is equal to the sum of a probability weighting utility and a reversal utility in reference to an outcome. JEL Classifications: G12, G02, D83 (长期以来，金融学术领域里的文献只注重价格和收益率，却较少研究交易量。在最近的二十年里，金融学术文献已经开始研究价格和交易量两者与经济基本量之间的相互关系，并且探讨交易量的行为内涵，例如投资者对风险的态度、过度自信、不同观点以及关注程度等等。然而，我们还是对交易量的认识知之甚少。本文根据行为分析，用交易量概率来表示市场群体的交易频率，并且通过我国股市来实证检验交易量与价格之间不确定关系中关于群体交易行为的两个基本假说。实证结果表明：市场群体在每日交易的时间窗口内采用简单的经验法则和有效的适应方式来从事交易，并且总是逐步地倾向于形成一个结果和认同的资产价格；无论该资产价格是否明显地被高估或低估，市场群体在相互作用的过程中往往能够形成这样一个稳态的均衡价格，这表明了资产价格不仅包含基本价值同时还包含非公开信息、投机、情绪、赌博和娱乐等价值。此外，在任意两个连续交易日之间，市场群体在与市场环境的相互作用过程中，通过交易量的增加或减少来有效地适应盈亏。我们的研究结果说明了在由信息、交易与收益结果三项构成的反馈环中，它们之间的相互作用是如何导致了过度交易的，这其中包含了导致过度交易的各种内外因素。最后，我们假设股票市场中的投资者是通过交易财富来产生流动性效用，它等于概率加权效用与相对于结果为参照系的反转效用之和，从而推导出Shi氏价-量微分方程，将市场动力学行为与群体交易行为协调在一个统一的框架体系。)

Using block trades data on the Shanghai Stock Exchange (SSE) from 2003 – 2009, we study the pricing mechanisms of block buys and sells. We show that block trades are priced at discount (premium) for sells (buys). The discount/ premium varies depending on the characteristics of the stocks traded, the complexity of the trades, and also on whether the trades are internalized. We also study permanent and temporary price impact of the trades. As expected, seller-initiated trades do not seem to be information related as there is no significant information content. On the contrary, the prices decline after buyer-initiated trades, suggesting that buyers do not possess private information which leads to a permanent shift in prices. Temporary price impacts of all trades are large in magnitude and statistically significant, reflecting compensation for locating counterparties and the cost of negotiating terms. This suggests that the information platform on SSE for locating counterparties is yet to be fully developed to help reduce the transaction cost of block trades.

In this paper, we test the relationship between information asymmetry and acquisition premium in the mergers and acquisitions of the emerging market firms. Based on a sample of the domestic and cross-border acquisitions in twenty emerging countries between 1990 and 2007, we found a strong positive relationship between the acquisition premium paid to the target firms and the level of information asymmetry of the target firms. In addition, we found that higher level of information asymmetry leads to less cash payment and higher propensity of acquiring majority control (>50%) in the target firms. This evidence supports the theory that acquiring majority control is important in high asymmetric information environment. Thus, the higher the information asymmetry the higher is the premium paid by bidding firms in order to obtain majority control in the target firms. In addition, target firms with high information asymmetry have more valuable private information resources that are not accessible to the public investors. Acquiring firms may pay higher premium for such valuable information resources. The hypothesis is supported by the evidence of both the domestic and the cross-border acquisitions in the emerging markets.

We examine the dynamic relation between return and volume of individual stocks in Russia and other emerging markets. In a simple model in which investors trade to share risk or speculate on private information, Llorente, Michaely, Saar, and Wang (2001) show that returns generated by risk-sharing trades tend to reverse themselves while returns generated by private information trades tend to continue themselves. We apply this theoretical framework to analyze the relation between daily volume and first-order return autocorrelation for individual stocks traded in Russia and other emerging markets. We find strong evidence of return continuation following high volume days, suggesting the presence of private information trading in emerging markets. Using corporate announcement data from Russia, we discover that the private information trading is especially strong around major corporate event dates. In addition, we find stocks in countries that enforce insider-trading law and provide better investor protection exhibit less private information trading. These results suggest a possible measure of “information asymmetry” for ranking emerging market stocks.

In this paper, we develop a methodology to identify money managers who have private information about future asset returns. The methodology does not rely on a specific risk model, such as the Sharpe ratio, CAPM, or APT. Instead, it relies on the observation that returns generated by managers with private information cannot be replicated by those without it. Using managers’ trading records, we develop distribution-free tests that can identify such managers. We show that our approach is general with regard to the nature of private information the managers may have, and with regard to the trading strategies they may follow.