Price Revelation from Insider Trading: Evidence from Hacked Earnings News

From 2010 to 2015, a group of traders illegally accessed earnings information before their public release by hacking several newswire services. We use this scheme as a natural experiment to investigate how informed investors select among private signals and how efficiently financial markets incorporate private information contained in trades into prices. We construct a measure of qualitative information using machine learning and find that the hackers traded on both qualitative and quantitative signals. The hackers’ trading caused 15% more of the earnings news to be incorporated in prices before their public release. Liquidity providers responded to the hackers’ trades by widening spreads.

The Condorcet Jury Theorem with Information Acquisition

We analyze a committee decision in which individuals with common preferences are uncertain which of two alternatives is better for them. Members can acquire costly information. Private signals and information choice are both continuous. As is consistent with Down’s rational ignorance hypothesis, each member acquires less information in a larger committee and tends to acquire zero information when the committee size goes to infinity. However, with more members, a larger committee can gather more aggregate information in equilibrium. The aggregate information is infinite with the size going to infinity if and only if marginal cost at “zero information acquisition” is zero. When the marginal cost at “zero information acquisition” is positive, the probability of making an appropriate decision tends to be less than one.

Chromosome X-wide Analysis of Positive Selection in Human Populations: Common and Private Signals of Selection and its Impact on Inactivated Genes and Enhancers

The ability of detecting adaptive (positive) selection in the genome has opened the possibility of understanding the genetic basis of population-specific adaptations genome-wide. Here, we present the analysis of recent selective sweeps, specifically in the X chromosome, in human populations from the third phase of the 1,000 Genomes Project using three different haplotype-based statistics. We describe instances of recent positive selection that fit the criteria of hard or soft sweeps, and detect a higher number of events among sub-Saharan Africans than non-Africans (Europe and East Asia). A global enrichment of neural-related processes is observed and numerous genes related to fertility appear among the top candidates, reflecting the importance of reproduction in human evolution. Commonalities with previously reported genes under positive selection are found, while particularly strong new signals are reported in specific populations or shared across different continental groups. We report an enrichment of signals in genes that escape X chromosome inactivation, which may contribute to the differentiation between sexes. We also provide evidence of a widespread presence of soft-sweep-like signatures across the chromosome and a global enrichment of highly scoring regions that overlap potential regulatory elements. Among these, enhancers-like signatures seem to present putative signals of positive selection which might be in concordance with selection in their target genes. Also, particularly strong signals appear in regulatory regions that show differential activities, which might point to population-specific regulatory adaptations.

Chromosome X-wide analysis of positive selection in human populations: from common and private signals to selection impact on inactivated genes and enhancers-like signatures

The ability of detecting adaptive (positive) selection in the genome has opened the possibility of understanding the genetic bases of population-specific adaptations genome-wide. Here we present the analysis of recent selective sweeps specifically in the X chromosome in different human populations from the third phase of the 1000 Genomes Project using three different haplotype-based statistics. We describe numerous instances of genes under recent positive selection that fit the regimes of hard and soft sweeps, showing a higher amount of detectable sweeps in sub-Saharan Africans than in non-Africans (Europe and East Asia). A global enrichment is seen in neural-related processes while numerous genes related to fertility appear among the top candidates, reflecting the importance of reproduction in human evolution. Commonalities with previously reported genes under positive selection are found, while particularly strong new signals are reported in specific populations or shared across different continental groups. We report an enrichment of signals in genes that escape X chromosome inactivation, which may contribute to the differentiation between sexes. We also provide evidence of a widespread presence of soft-sweep-like signatures across the chromosome and a global enrichment of highly scoring regions that overlap potential regulatory elements. Among these, enhancers-like signatures seem to present putative signals of positive selection that might be in concordance with selection in their target genes. Also, particularly strong signals appear in regulatory regions that show differential activities, which might point to population-specific regulatory adaptations.

Common-Value Public Goods and Informational Social Dilemmas

We experimentally examine private information and communication in a public goods environment with uncertain returns. We consider a common-value public goods game in which the return to contribution is either high or low. Before contributing, three players observe private signals correlated with the return and send cheap talk messages to one another. There are social gains from truthfulness, but a private incentive to exaggerate. We compare treatments with and without cheap talk, finding that communication is largely truthful and increases efficiency. In further treatments, we increase the incentive to exaggerate and find reduced truthfulness and smaller gains from communication. (JEL C72, D82, D83, H41)

Hidden Experts in the Crowd: Using Meta-Predictions to Leverage Expertise in Single-Question Prediction Problems

Modern forecasting algorithms use the wisdom of crowds to produce forecasts better than those of the best identifiable expert. However, these algorithms may be inaccurate when crowds are systematically biased or when expertise varies substantially across forecasters. Recent work has shown that meta-predictions—a forecast of the average forecasts of others—can be used to correct for biases even when no external information, such as forecasters’ past performance, is available. We explore whether meta-predictions can also be used to improve forecasts by identifying and leveraging the expertise of forecasters. We develop a confidence-based version of the Surprisingly Popular algorithm proposed by Prelec, Seung, and McCoy. As with the original algorithm, our new algorithm is robust to bias. However, unlike the original algorithm, our version is predicted to always weight forecasters with more informative private signals more than forecasters with less informative ones. In a series of experiments, we find that the modified algorithm does a better job in weighting informed forecasters than the original algorithm and show that individuals who are correct more often on similar decision problems contribute more to the final decision than other forecasters. Empirically, the modified algorithm outperforms the original algorithm for a set of 500 decision problems. This paper was accepted by Yan Chen, decision analysis.

Simple bets to elicit private signals

This paper introduces two simple betting mechanisms—top‐flop and threshold betting—to elicit unverifiable information from crowds. Agents are offered bets on the rating of an item about which they received a private signal versus that of a random item. We characterize conditions for the chosen bet to reveal the agents' private signal even if the underlying ratings are biased. We further provide microeconomic foundations of the ratings, which are endogenously determined by the actions of other agents in a game setting. Our mechanisms relax standard assumptions of the literature, such as common prior, and homogeneous and risk neutral agents.

Social Connectivity, Media Bias, and Correlation Neglect*

A biased newspaper aims to persuade voters to vote for the government. Voters are uncertain about the government’s competence. Each voter receives the newspaper’s report as well as independent private signals about the competence. Voters then exchange messages containing this information on social media and form posterior beliefs, neglecting correlation among messages. We show that greater social connectivity increases the probability of an efficient voting outcome if the prior favours the government; otherwise, efficiency decreases. The probability of an efficient outcome remains strictly below one even when connectivity becomes large, implying a failure of the Condorcet jury theorem.

Learning from prices: information aggregation and accumulation in an asset market

Can prices convey information about the fundamental value of an asset? This paper considers this problem in relation to the dynamic properties of the fundamental (whether it is constant or time-varying) and the structure of information available to agents. Risk-averse traders receive two potential signals each period: one exogenous and private and the other, prices, endogenous and public. Prices aggregate private information but include aggregate noise. Information can accumulate over time both through endogenous and exogenous signals. With a constant fundamental, the precision of both private and public cumulative information increases over time but agents put progressively more weight on the endogenous signals, asymptotically disregarding private ones. If the fundamental is time-varying, the use of past private signals complicates the role of prices as a source of information, since it introduces endogenous serial correlation in the price signal and cross-correlation between it and innovations in the fundamental. A modified version of the Kalman filter can still be used to extract information from prices and results show that the precision of the endogenous signals converges to a constant, with both private and public information used at all times.