Heterogeneous Agents and Long Horizon Features of Asset Prices

Blake Lebaron ()

No 63, Working Papers from Brandeis University, Department of Economics and International Business School

Abstract: Heterogeneous agent models for financial markets have provided explanations for many empirical regularities of relatively high frequency (hourly/daily) financial time series. They have been much quieter when it comes to longer range features. This paper examines a simplified computational heterogeneous agent model in the context of various longer range time series properties for equity returns. The model is compared to a specially created long range data set, and is found to perform well in terms of replicating features, and even revealing some aspects of the data that have not been well quantified to date. By matching empirical properties at both short and long horizons this sets a higher standard in terms of validation which this model is able to match.

Keywords: Learning; Asset Pricing; Financial Time Series; Evolution; Memory (search for similar items in EconPapers)
Pages: 48 pages
Date: 2013-07, Revised 2013-09
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Citations: View citations in EconPapers (1)

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http://www.brandeis.edu/economics/RePEc/brd/doc/Brandeis_WP63.pdf First version, 2013 (application/pdf)

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Persistent link: https://EconPapers.repec.org/RePEc:brd:wpaper:63

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