摘要翻译：
本文对基于信息的资产定价进行了概述。在这种方法中，资产是由其现金流结构定义的。假定市场可以获得有关未来现金流量的“部分”信息。每一个现金流都是由一系列独立的市场因素决定的，这些因素被称为X-因素。市场过滤是由一组信息过程产生的，每一个信息过程都带有关于X因子之一的信息，并最终揭示X因子。每个信息过程都有两个术语，其中一个包含关于相关x因子的“信号”，另一个代表“市场噪音”。资产的价格是由风险中性度量中的现金流贴现预期给出的，条件是市场提供的信息。当市场噪声用布朗桥建模时，人们可以构造资产价格的显式公式，以及期权和衍生品价格和希腊语的半解析表达式。特别是，期权价格数据可以用来确定隐含在信息过程定义中的信息流率参数。模型框架的一个结果是随机波动性和相关过程的一个特定方案。不是将波动性和相关性模型强加于一组资产的动态上，而是能够从涉及相关现金流的更原始的假设中推导出资产价格变动的波动性和相关性的动态。论文最后考察了涉及信息不对称的情况。我们为知情交易者提供了一个简单的模型，并展示了如何将其作为所谓统计套利的基础。最后，我们考虑了具有多个代理的异质市场中的价格形成问题。
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英文标题：
《Modelling Information Flows in Financial Markets》
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作者：
Dorje C. Brody, Lane P. Hughston, Andrea Macrina
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最新提交年份：
2010
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分类信息：

一级分类：Quantitative Finance        数量金融学
二级分类：Pricing of Securities        证券定价
分类描述：Valuation and hedging of financial securities, their derivatives, and structured products
金融证券及其衍生产品和结构化产品的估值和套期保值
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一级分类：Mathematics        数学
二级分类：Probability        概率
分类描述：Theory and applications of probability and stochastic processes: e.g. central limit theorems, large deviations, stochastic differential equations, models from statistical mechanics, queuing theory
概率论与随机过程的理论与应用：例如中心极限定理，大偏差，随机微分方程，统计力学模型，排队论
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英文摘要：
  This paper presents an overview of information-based asset pricing. In this approach, an asset is defined by its cash-flow structure. The market is assumed to have access to "partial" information about future cash flows. Each cash flow is determined by a collection of independent market factors called X-factors. The market filtration is generated by a set of information processes, each of which carries information about one of the X-factors, and eventually reveals the X-factor. Each information process has two terms, one of which contains a "signal" about the associated X-factor, and the other of which represents "market noise". The price of an asset is given by the expectation of the discounted cash flows in the risk-neutral measure, conditional on the information provided by the market. When the market noise is modelled by a Brownian bridge one is able to construct explicit formulae for asset prices, as well as semi-analytic expressions for the prices and greeks of options and derivatives. In particular, option price data can be used to determine the information flow-rate parameters implicit in the definitions of the information processes. One consequence of the modelling framework is a specific scheme of stochastic volatility and correlation processes. Instead of imposing a volatility and correlation model upon the dynamics of a set of assets, one is able to deduce the dynamics of the volatilities and correlations of the asset price movements from more primitive assumptions involving the associated cash flows. The paper concludes with an examination of situations involving asymmetric information. We present a simple model for informed traders and show how this can be used as a basis for so-called statistical arbitrage. Finally, we consider the problem of price formation in a heterogeneous market with multiple agents.
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PDF链接：
https://arxiv.org/pdf/1004.4822