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On the specification of noise in two agent-based asset pricing models

机译：关于两种基于代理的资产定价模型中的噪声规范

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The paper is concerned with two recent agent-based models of speculative dynamics from the literature, one by Gaunersdorfer and Hommes (2007) and the other by He and Li (2007). At short as well as long lags, both of them display an autocorrelation structure in absolute and squared returns that comes fairly close to that of real data at a daily frequency. The note argues that these long memory effects are to be ascribed to the stochastic specification of the price equation, which despite the wide fluctuations in these models fails to normalize the price shocks. Under an appropriate respecification, the long memory completely disappears. It is subsequently shown that an alternative introduction of randomness, which may be called structural stochastic volatility, can restore the original properties and even improves upon them.
机译：本文关注的是来自文献的两个最近的基于主体的投机动力学模型，一个是Gaunersdorfer和Hommes（2007），另一个是He和Li（2007）。无论是短期还是长期滞后，它们两个都以绝对和平方的回报显示出自相关结构，这与每天的实际数据相当接近。该说明认为，这些长期记忆效应应归因于价格方程的随机性规范，尽管这些模型的波动很大，但未能使价格冲击正常化。在适当的重新指定下，长记忆将完全消失。随后表明，随机性的另一种引入（可以称为结构随机波动性）可以恢复原始属性，甚至可以改善原始属性。

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