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Heterogeneous beliefs and asset price dynamics: a survey of recent evidence

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  • Saskia ter Ellen

    (Norges Bank (Central Bank of Norway))

  • Willem F.C. Verschoor

    (Vrije Universiteit Amsterdam)

Abstract

This paper reviews the empirical literature on heterogeneous beliefs and asset price dynamics that challenges the traditional rational agent framework. Emphasis is given to the validation and estimation of (dynamic) heterogeneous agent models that have their roots in the agent-based literature. Heterogeneous agent models perform well in describing, explaining, and often forecasting asset markets dynamics, such as equities, foreign exchange, credit, housing, derivatives, and commodities. Our survey suggests that heterogeneous agent models have the ability to produce important stylised facts observed in financial time series and to replicate important episodes of financial turmoil.

Suggested Citation

  • Saskia ter Ellen & Willem F.C. Verschoor, 2017. "Heterogeneous beliefs and asset price dynamics: a survey of recent evidence," Working Paper 2017/22, Norges Bank.
  • Handle: RePEc:bno:worpap:2017_22
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    6. Mirza Faizan Ahmed, 2019. "Estimating proportion of noise traders and asset prices," Business Review, School of Economics and Social Sciences, IBA Karachi, vol. 14(2), pages 1-12, July-Dece.
    7. Filippo Gusella & Giorgio Ricchiuti, 2021. "State Space Model to Detect Cycles in Heterogeneous Agents Models," Working Papers - Economics wp2021_10.rdf, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
    8. Luca Guerrini & Akio Matsumoto & Ferenc Szidarovszky, 2018. "A heterogeneous agent model of asset price dynamics with two time delays," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 41(2), pages 379-397, November.
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    10. Lyócsa, Štefan & Výrost, Tomáš & Plíhal, Tomáš, 2021. "A tale of tails : New evidence on the growth-return nexus," Finance Research Letters, Elsevier, vol. 38(C).
    11. Filippo Gusella & Giorgio Ricchiuti, 2022. "A State-Space Approach for Time-Series Prediction of an Heterogeneous Agent Model," Working Papers - Economics wp2022_20.rdf, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.

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