An experiment of social learning with endogenous timing

In this paper, we experimentally investigate a social learning model with endogenous timing. Specifically, we focus on a model, in which two subjects are supposed to make a binary decision. One alternative is a safe action with a fixed payoff, while the other alternative is a risky action. The subjects can make their decisions in three stages. The safe action is reversible, but the risky action is not. A subject who delays his decision can observe the decision of the other subject in the earlier stages, and as a result, acquire more information. We show that players do delay their decisions in order to obtain more information. Furthermore, they delay especially when their private information does not particularly support the risky action. We also find evidence which suggests that risk aversion plays an important role in timing decisions, often leading to ex post inefficient outcomes.     

信息披露与内部人股票交易获利策略——以六起内部人股票交易为基础的案例研究

本文以近期A股市场内部人股票交易活跃的六家公司为例,通过考查信息披露与内部人股票交易间的关系,解释内部人股票交易的获利策略。研究发现,在允许内部人交易本公司股票的情况下,信息披露与内部人股票交易关系密切,内部人存在利用私有信息和策略性信息披露两类获利策略。信息权力是内部人股票交易的获利基础,公司业绩是影响内部人股票交易获利策略选择的重要因素,而法律诉讼风险并没有对我国内部人股票交易和信息披露产生明显约束作用。这些发现对完善我国资本市场内部人股票交易行为规范具有一定借鉴意义。     

Do Managers Trade on Public or Private Information? Evidence from Fundamental Valuations

Using accounting-based (residual income) valuations, this study examines the extent to which abnormal returns after insider share trades are explained by private information versus mispricing of public information. For a sample of insider trades in the Netherlands (1999–2008), I find that managers' share purchase decisions are associated with positive future abnormal returns as well as equity undervaluation. Even though undervaluation results in predictable price increases, positive abnormal returns following purchases persist after controlling for fundamental valuations. Thus, this study provides evidence on the sources of managers' personal trading gains and suggests that positive abnormal returns after insider share purchases reflect both private information and managers' responses to market mispricing of public information.     

Inferring the private information content of trades: a regime‐switching approach

This paper presents an empirical model for inferring the private information content of trades at the transaction level. The trade‐indicator model of Glosten and Harris ( 1988 ) is extended to a two‐state regime‐switching setting, and the model is estimated using tick‐by‐tick data from the New York Stock Exchange (NYSE). The specialist is found to react in accordance with the proposed model. Bid–ask quotes set after the execution of a trade reflect the conjectured information content of that particular trade. Based on the estimated model four empirical results emerge: (a) the suggested regime‐switching model fit data well; (b) the reverse J‐shaped pattern of intra‐daily quoted spreads is shown to agree with the clustering of costs incurred by the specialist through trading with better‐informed agents; (c) on average 9% of all trades are found to reveal private: information to the specialist; (d) results regarding the trading volume of informed traders support the stealth trading hypothesis suggested by Barclay and Warner ( 1993 ). Copyright © 2003 John Wiley & Sons, Ltd.     

Private information in futures markets: An experimental study

This paper presents the results of an experimental study on how people use their private information to estimate the “fair” futures price and how the quality of this information affects the traders' behavior and desire to trade. It finds that subjects are able to use their information correctly and that their desire to rely on it depends positively on the information precision. It shows that subjects are able to recognize that they are expected to lose money on futures trading when other traders have better quality information. However, subjects failed to recognize the symmetry of the futures contracts.     

Fake news

This analysis uses Twitter stock and options prices sampled at a 30 s frequency around the fake news announcement, of a bid for a controlling stake in Twitter stock, to investigate how noise trading and informed trading is disseminated into equity and option markets. We find reaction to the fake news occurred in the equity market, and the option market reacted with a delay. This differs from many analyses of actual news events, which found informed traders prefer the options market, and information from their trades then leaks into the equity market. We conclude uninformed traders, and those aware of the hoax, prefer to trade in equity over option markets. This result has implications for isolating informed trading around actual news events.     

Structural estimation of behavioral heterogeneity

We develop a behavioral asset pricing model in which agents trade in a market with information friction. Profit‐maximizing agents switch between trading strategies in response to dynamic market conditions. Owing to noisy private information about the fundamental value, the agents form different evaluations about heterogeneous strategies. We exploit a thin set—a small sub‐population—to point identify this nonlinear model, and estimate the structural parameters using extended method of moments. Based on the estimated parameters, the model produces return time series that emulate the moments of the real data. These results are robust across different sample periods and estimation methods.     

An equilibrium model of insider trading in continuous time

We study a Bayesian–Nash equilibrium model of insider trading in continuous time. The supply of the risky asset is assumed to be stochastic. This supply can be interpreted as noise from nonrational traders (noise traders). A rational informed investor (the insider) has private information on the growth rate of the dividend flow rewarded by the risky asset. She is risk averse and maximizes her inter-temporal utility rate over an infinite time-horizon. The market is cleared by a risk neutral market maker who sets the price of the risky asset competitively as the conditional present value of future dividends, given the information supplied by the dividend history and the cumulative order flow. Due to the presence of noise traders, the market demand does not fully reveal the insider’s private information, which slowly becomes incorporated in prices. An interesting result of the paper is that a nonstandard linear filtering procedure gives an a priori form for the equilibrium strategy to be postulated. We show the existence of a stationary linear equilibrium where the insider acts strategically by taking advantage of the camouflage provided by the noise which affects the market maker’s estimates on private information. In this equilibrium, we find that the insider’s returns on the stock are uncorrelated over long periods of time. Finally, we show that the instantaneous variance of the price under asymmetric information lies between the instantaneous variance of the price under complete and incomplete information. The converse inequalities hold true for the unconditional variance of the price.     

On the Evolution of Overconfidence and Entrepreneurs

This paper explains why seemingly irrational overconfident behavior can persist. Information aggregation is poor in groups in which most individuals herd. By ignoring the herd, the actions of overconfident individuals ("entrepreneurs") convey their private information. However, entrepreneurs make mistakes and thus die more frequently. The socially optimal proportion of entrepreneurs trades off the positive information externality against high attrition rates of entrepreneurs, and depends on the size of the group, on the degree of overconfidence, and on the accuracy of individuals' private information. The stationary distribution trades off the fitness of the group against the fitness of overconfident individuals.     

Noise Trading and the Management of Operational Risk; Firms,Traders and Irrationality in Financial Markets*

abstract Efficient market models cannot explain the high level of trading in financial markets in terms of asset portfolio adjustment. It is presumed that much of this excessive trading is irrational ‘noise’ trading. A corollary is that there must either be irrational traders in the market or rational traders with irrational aberrations. The paper reviews the various attempts to explain noise trading in the finance literature, concluding that the persistence of irrationality is not well explained. Data from a study of 118 traders in four large investment banks are presented to advance reasons why traders might seek to trade more frequently than financial models predict. The argument is advanced that trades do not simply occur in order to generate profit, but it does not follow that such trading is irrational. Trading may generate information, accelerate learning, create commitments and enhance social capital, all of which sustain traders' long term survival in the market. The paper treats noise trading as a form of operational risk facing firms operating in financial markets and discusses approaches to the management of such risk.     

Information dissemination in an experimentally based agent-based stock market

This paper builds an agent-based model to reproduce the results of an experimental stock market that studies how the market aggregates private information. The aim is to use experiments and agent-based modeling to analyze the trading behavior in experimental stock markets. Using the experimental environment and results, it is possible to formulate a hypothesis about the subjects’ behavior and thereby formalize (algorithmically) the trading behavior in an agent-based model. This may lead to a better understanding of how the market converges to an equilibrium and of the mechanism that allows dissemination of private information in the market.     

Strategic real options under asymmetric information

This paper studies the effect of private information on the capital allocation decisions of firms who operate under imperfect competition. I analyze two interactive firms, one with private information and the other without, who must decide when to undertake an irreversible and uncertain investment decision. Traditional non-strategic models of irreversible investment under uncertainty involve a single decision maker and result in an optimal period of delay before the investment is undertaken. In a strategic setting, firms must balance their desire to delay against competitive advantages from early investment. I find that an equilibrium may not exist within the standard continuous framework when the private information is over revenues. Moreover, when an equilibrium does exist the competitive pressures from the uninformed firm are weak. This is in contrast to existing models with asymmetric information over costs, where an equilibrium always exists and the competitive pressures remain strong (Hsu and Lambrecht, 2007). This work shows that the investment timing decision, and thus the value of the private information, is highly sensitive to the nature of incomplete information.     

Extreme returns and intensity of trading

Asymmetric information models of market microstructure claim that variables such as trading intensity are proxies for latent information on the value of financial assets. We consider the interval‐valued time series (ITS) of low/high returns and explore the relationship between these extreme returns and the intensity of trading. We assume that the returns (or prices) are generated by a latent process with some unknown conditional density. At each period of time, from this density, we have some random draws (trades) and the lowest and highest returns are the realized extreme observations of the latent process over the sample of draws. In this context, we propose a semiparametric model of extreme returns that exploits the results provided by extreme value theory. If properly centered and standardized extremes have well‐defined limiting distributions, the conditional mean of extreme returns is a nonlinear function of the conditional moments of the latent process and of the conditional intensity of the process that governs the number of draws. We implement a two‐step estimation procedure. First, we estimate parametrically the regressors that will enter into the nonlinear function, and in a second step we estimate nonparametrically the conditional mean of extreme returns as a function of the generated regressors. Unlike current models for ITS, the proposed semiparametric model is robust to misspecification of the conditional density of the latent process. We fit several nonlinear and linear models to the 5‐minute and 1‐minute low/high returns to seven major banks and technology stocks, and find that the nonlinear specification is superior to the current linear models and that the conditional volatility of the latent process and the conditional intensity of the trading process are major drivers of the dynamics of extreme returns.     

Investor heterogeneity and commonality in stock return and liquidity

This paper examines how the trading activities of different investor types are related to common return and liquidity movements. Using a unique dataset, we decompose the daily return and liquidity of individual stocks into price impact components attributable to trades of institutional investors and retail investors. We then investigate the variation of each component relative to market-wide return and liquidity. We show that institutional trades contribute more than retail trades to liquidity commonality. However, retail trades contribute more strongly to return co-movement. The incremental contribution of retail trades to the co-variability of stock returns is more pronounced for firms with high information asymmetry.     

Information interaction,behavioral synchronization and asset market volatility

This paper focuses on the synchronization of trading behavior caused by interactions among traders. The study begins with an agent-based model in which most agents make investment decisions based on three types of information (neighbor, public and private information) according to their heterogeneous personal preferences. Considering the influence of the social relationship network in reality, traders in our model are connected by a complex network. We use four different types of networks. The simulated results of this model reproduce several stylized facts about the asset market. Simulated results show that when preference of traders for neighbor information increases, the level of trust among traders will gradually increase and then there will be a “leap” at a certain point. The mutual trust among traders is achieved through coupling effect in the network. Moreover, with the frequent synchronization of traders’ behavior, extreme phenomena in financial markets will emerge. In addition, our numerical simulations show that when the average degree of network is higher, behavioral synchronization will emerge at a lower level of dependence on neighbor information. The degree distribution of the network will also have a significant influence on the convergence processes of behavioral synchronization. The more heterogeneous the degree distribution is, the easier the behavioral synchronization process will occur. In our simulations, the mode of agent behavior expectation will also enhance the effect of network structure to behavioral synchronization. Finally, this paper affirms the important role of public information and learning mechanism (expectation formation mode) in the process of behavioral synchronization.     

Informational cascades with endogenous prices: The role of risk aversion

In this paper, we show that long run market informational inefficiency and informational cascades can easily happen when trades occur at market clearing prices. We consider a sequential trade model where: (i) the investors’ set of actions is discrete; (ii) dealers and investors differ in risk aversion; (iii) investors’ information is bounded. We show that informational cascade occurs as soon as traders’ beliefs do not differ too sharply. Thus, prices cannot fully incorporate the private information dispersed in the economy.     

An analysis of the opening mechanisms of Exchange Traded Fund markets

We examine the opening of Exchange Traded Fund (ETF) markets in a multimarket trading environment. We find that the opening trades on the American Stock Exchange (AMEX) are the most costly. This result is consistent with the market power hypothesis which suggests that the specialists use their informational advantage about the order imbalance at the open or take advantage of the inelastic demand at the open by imposing wider spreads. We also find that the transparent opening mechanisms of the New York Stock Exchange (NYSE) and Electronic Communication Networks (ECNs) enable them to facilitate greater price discovery at the opening and to have more efficient opening prices. This result implies that the transparency effect dominates the market power effect. Further, we find that peripheral markets do not passively free ride on information revealed through the AMEX because their opening trades contribute significantly to the price discovery process.     

Optimal coordination mechanisms in generalized principal–agent problems

The general principal–agent problem is formulated, in which agents have both private information and private decisions, unobservable to the principal. It is shown that the principal can restrict himself to incentive-compatible direct coordination mechanisms, in which agents report their information to the principal, who then recommends to them decisions forming a correlated equilibrium. In the finite case, optimal coordination mechanisms can be found by linear programming. Some basic issues relating to systems with many principals are also discussed. Non-cooperative equilibria between interacting principals do not necessarily exist, so quasi-equilibria are defined and shown to exist.     

How do experienced traders respond to inflows of inexperienced traders? An experimental analysis

We conducted asset market experiments where one experienced subject interacts with five inexperienced subjects to investigate how experienced subjects change their price forecasts and trading behavior when faced with strategic uncertainty caused by inflows of inexperienced subjects. Only half the experienced subjects initially forecasted prices deviating more from the fundamental values in the market with five inexperienced subjects than in the final round of the experiment in which they had previously participated. Furthermore, the majority of our experienced subjects did not change their trading behavior. Many experienced subjects act as price stabilizers when the inflow of inexperienced subjects is not associated with other changes in market conditions.     

Structural holes, innovation and the distribution of ideas

We model knowledge diffusion in a population of agents situated on a network, interacting only over direct ties. Some agents are by nature traders, others are by nature “givers”: traders demand a quid pro quo for information transfer; givers do not. We are interested in efficiency of diffusion and explore the interplay between the structure of the population (proportion of traders), the network structure (clustering, path length and degree distribution), and the scarcity of knowledge. We find that at the global level, trading (as opposed to giving) reduces efficiency. At the individual level, highly connected agents do well when knowledge is scarce, agents in clustered neighbourhoods do well when it is abundant. The latter finding is connected to the debate on structural holes and social capital.