Cladistic Asset Pricing

了解资产价格如何响应不同知情代理人之间的战略相互作用是有效监管证券市场的重要要求，但这种现象尚未得到很好的理解和建模。拟议的研究将探讨股票市场的行为，当有投机交易者谁拥有的信息是不可用的市场作为一个整体。在这样的环境中，人们希望确定信息不同的代理人之间的战略相互作用如何随着时间的推移影响市场价格、数量和利润。在许多情况下，投机交易者对一家公司的价值有私人信息，随着时间的推移，他们将不断地获得新的、长期存在的信息。例如，公司内部人士不仅掌握当前和过去的收益信息；他们可能会知道有关公司盈利的新信息。投资者也常常只关注少数股票或研究范围狭窄的行业。他们积累的专业知识使他们能够更好地在学习后立即评估信息，以及将来信息到达时进行评估。该行业尚未开发出一种方法，可以分析当多个代理反复访问私人信息时的均衡结果；更不用说在这样的环境中描述结果了。拟议的研究将开发新的方法，可以追溯包括当前和过去的信息。该模型的主要创新之处在于假设每个个体接收到的信息是一个AR(1)过程，从而允许一个均衡解。这个结果使得回答几个问题成为可能，例如：知情的代理人如何使用当前和过去的信号，以及当前和过去价格中的信息，来确定每个日期的交易量？均衡价格动态的结果是什么？这些方法的范围使探索资产市场理论中的核心问题成为可能，例如：知情代理人之间的竞争对战略交易和均衡价格动态的影响；竞争加剧是否以及何时会通过价格导致更多信息被披露，以及这与信息的“年龄”有何关系；信息结构如何影响策略交易行为、定价和信息披露；当一些交易者比其他人更了解情况时的市场特征；一种资产的信息对其他资产的价格和订单流动动态的影响；以及合谋对价格和订单流动的影响，以及如何通过实证检测这种合谋。该方法易于操作，可广泛用于研究股票交易模型，以及分析信息体现在价格中的各种经济模型。

Understanding how asset prices respond to strategic interplay among differentially informed agents is an important requirement for efficient regulation security markets, yet this phenomenon is not well understood and modeled. The proposed research will explore the behavior of stock markets when there are speculative traders who possess information that is not available to the market as a whole. In such an environment, one wishes to determine how the strategic interplay between differentially-informed agents affects market prices, volume and profits over time.In many of the contexts in which speculative traders have private information about a firm's value, they will continue to have access to new, long-lived information over the time on a recurring basis. For example, corporate insiders will not only have information about current and past earnings; they likely will be privy to new information about earnings. Investors, too, often focus on a small number of stocks or narrow sectors on which to do research. Their accumulated expertise leaves them better situated to evaluate the information both immediately after they learn it, and when it arrives in the future.The profession has not developed a methodology that can analyze equilibrium outcomes when multiple agents have recurring access to private information; much less characterize outcomes in such environments. The proposed research will develop new methods that can tractably encompass both current and past information. The main innovation in the model is to assume that the information received by each individual as an AR(1) process, thus allowing for an equilibrium solution. This results then makes it possible to answer several questions, such as: How do informed agents use current and past signals, and the information in current and past prices, to determine how much to trade at each date? What are the consequences for equilibrium price dynamics?The scope of the methods makes it possible to explore the central issues in the theory of asset markets such as: the effect of competition among informed agents on strategic trading and equilibrium price dynamics; whether and when increased competition leads to more information being revealed through price, and how this is related to the 'age' of the information; how the structure of the information affects the strategic trading behavior, pricing and information revelation; characteristics of market when some traders are better informed than others; the effects of information about one asset on the prices and dynamics of order flows of other assets; and the effects of collusion on price and order flows, and ways to detect such collusion empirically.The methodology is tractable enough to be broadly used to study equity trading models, as well as the analyses of a broad range of economic models in which information is embodied in prices.