Information, market power and welfare

We study a financial market in which agents with interdependent values bid for a risky asset. Some agents are privately informed of their own value for the asset while others seek to infer it from the equilibrium price. Due to adverse selection, uninformed agents are less willing than the informed to provide liquidity, and engage in greater bid shading when prices are more informative. While increased participation by informed agents leads to perfect competition in the limit, the market remains illiquid to some degree even with free entry of uninformed traders. The incentive to produce information is increasing in market size and is maximal in a perfectly competitive economy. Price informativeness, on the other hand, is independent of market size. Curtailing information production by one group can reduce adverse selection, and improve liquidity and welfare for all agents

Convergence of random sleep algorithms for optimal consensus

a b s t r a c t In this paper, we propose a random sleep algorithm for a network to cooperatively find a point within the intersection of some convex sets, each of which is known only to a particular node. At each step, each node first chooses to project its own set or not at random by a Bernoulli decision independently. When a node has chosen to project its set, we assume that it can detect only the projection direction rather than the exact projection point, based on which the node obtains an estimate for the projection point. Then the agents update their states by averaging the estimates with their neighbors. Under directed and time-varying communication graph, sufficient and/or necessary stepsize conditions are presented for the considered algorithm converging to a consensus within the intersection set

Information aggregation in a financial market with general signal structure

We study a financial market with asymmetric, multidimensional trader signals that have general correlation structure. Each of a continuum of traders belongs to one of finitely many “information groups.” There is a multidimensional aggregate signal for each group. Each trader observes an idiosyncratic signal about the fundamental, built from this group signal. Correlations across group signals are arbitrary. Several existing models serve as special cases, and new applications become possible. We establish existence and regularity of linear equilibrium, and demonstrate that the equilibrium price aggregates information perfectly as noise trade vanishes

Information, market power and welfare

We study the market for a risky asset in which traders are heterogeneous both in terms of their value for the asset and the information that they have about this value. Traders behave strategically and use the equilibrium price to extract information that is relevant to them. Due to adverse selection, uninformed traders are less willing than the informed to provide liquidity. We evaluate the impact of a change in the size or composition of the investor population on price informativeness, liquidity and welfare, with applications to the rise of passive investing and the adoption of ESG standards

How Is Leadership Related to Employee Self-concept?

In the field of leadership research, the relationship between leadership styles and follower self-concept was of great interests to researchers. The purpose of this study is to investigate how leadership styles such as transformational leadership, passive leadership and leader-member exchange (LMX) relate to employee self-concept. A total of 585 valid responses were collected from hotel front line employees in mainland China. The results showed that the effect of transformational leadership on self-concept was mainly mediated by LMX. The strong direct effects of LMX on levels of self-concept were also identified in this study. Theoretical and practical implications were provided based on the results of this study

Network flows as least squares solvers for linear equations

This paper presents a first-order continuous-time distributed step-size algorithm for computing the least squares solution to a linear equation over networks. Given the uniqueness of the solution and nonintegrable step size, the convergence results are provided for fixed graphs. For the nonunique solution and square integrable step size, the convergence is shown for constantly connected switching graphs. We also validate the results and illustrate possible impacts on the convergence speed using a few numerical examples