Estimation of an Adaptive Stock Market Model with Heterogeneous Agents
Estimation of an Adaptive Stock Market Model with Heterogeneous Agents
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DOI：
10.2139/ssrn.938693
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发表时间：
2006-10
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影响因子：
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通讯作者：
Henrik Amilon
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文献类型：
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作者：
Henrik Amilon
基于理性预期和同质性的标准经济模型在解释金融市场的复杂性和波动性方面存在问题。最近，有界理性和异质代理模型被开发出来，模拟收益被发现呈现出各种风格化的事实，如波动率聚集和厚尾。在这里，我们感兴趣的是所提出的模型能否很好地解释真实数据中的所有属性，而不是一次只解释一个或几个属性。因此，我们利用有效的矩方法和极大似然法对这类模型的一些简单版本进行了适当的估计，并将结果与实际数据和更传统的计量经济模型进行了比较。我们发现了两个主要发现。首先，与早期模拟中发现的观测数据的相似性至关重要地依赖于对噪声项的某种不切实际的建模。其次，当更恰当地引入随机性时，我们发现这些模型能够产生一些风格化的事实，但总体上拟合程度很差。
Standard economic models based on rational expectations and homogeneity have problems explaining the complex and volatile nature of financial markets. Recently, boundedly rational and heterogeneous agent models have been developed and simulated returns are found to exhibit various stylized facts, such as volatility clustering and fat tails. Here, we are interested in how well the proposed models can explain all the properties seen in real data, not just one or a few at a time. Hence, we do a proper estimation of some simple versions of such a model by the use of efficient method of moments and maximum likelihood and compare the results to real data and more traditional econometric models. We discover two main findings. First, the similarities with observed data found in earlier simulations rely crucially on a somewhat unrealistic modeling of the noise term. Second, when the stochastic is more properly introduced we find that the models are able to generate some stylized facts, but that the fit generally is quite poor.