Estimation of an Adaptive Stock Market Model with Heterogeneous Agents

Henrik Amilon ()
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Henrik Amilon: European Central Bank, Postal: Postfach 16 03 19, D-60066 Frankfurt am Main, Germany

No 177, Working Paper Series from Sveriges Riksbank (Central Bank of Sweden)

Abstract: 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.

Keywords: Efficient method of moments; heterogeneous expectations; bounded rationality; evolutionary dynamics; adaptive beliefs (search for similar items in EconPapers)
JEL-codes: C13 C15 C32 C51 G12 (search for similar items in EconPapers)
Pages: 31 pages
Date: 2005-01-01
New Economics Papers: this item is included in nep-cbe, nep-cmp and nep-fin
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Related works:
Journal Article: Estimation of an adaptive stock market model with heterogeneous agents (2008)
Working Paper: Estimation of an Adaptive Stock Market Model with Heterogeneous Agents (2003)
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Persistent link: https://EconPapers.repec.org/RePEc:hhs:rbnkwp:0177

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