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Stochastic equilibrium. Learning by exponential smoothing.

机译:随机平衡。通过指数平滑学习。

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摘要

This article considers three standard asset pricing models with adaptive agents and stochastic dividends. The models only differ in the parameters to be estimated. We assume that only limited information is used to construct estimators. Therefore, parameters are not estimated consistently. More precisely, we assume that the parameters are estimated by exponential smoothing, where past parameters are down-weighted and the weight of recent observations does not decrease with time. This situation is familiar for applications in finance. Even if time series of volatile stocks or bonds are available for a long time, only recent data is used in the analysis. In this situation the prices do not converge and remain a random variable. This raises the question how to describe equilibrium behavior with stochastic prices. However, prices can reveal properties such as ergodicity, such that the law of the price process converges to a stationary law, which provides a natural and useful extension of the idea of equilibrium behavior of an economic system for a stochastic setup. It is this implied law of the price process that we investigate in this paper. We provide conditions for the ergodicity and analyze the stationary distribution. (author's abstract)
机译:本文考虑了具有自适应代理和随机股利的三种标准资产定价模型。这些模型仅在要估计的参数上有所不同。我们假设仅使用有限的信息来构造估计量。因此,不能一致地估计参数。更准确地说,我们假设参数是通过指数平滑法估算的,其中过去的参数权重较低,而最近观测值的权重不会随时间减少。这种情况对于金融中的应用是很熟悉的。即使长期存在波动性股票或债券的时间序列,分析中也仅使用最新数据。在这种情况下,价格不会收敛,而是保持随机变量。这就提出了一个问题,即如何用随机价格来描述均衡行为。但是,价格可以揭示诸如遍历性之类的属性,从而使价格过程的定律收敛于平稳的定律,从而为随机系统的经济系统均衡行为的思想提供了自然而有用的扩展。我们在本文中研究的就是价格过程的这种隐含规律。我们为遍历提供条件并分析平稳分布。 (作者的摘要)

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  • 年度 2000
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