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Disposition effect and multi-asset market dynamics

Disposition effect and multi-asset market dynamics Asset pricing dynamics in a multi-asset framework when investors’ trading exhibits the disposition effect is studied. The purpose of this paper is to explore asset pricing dynamics and the switching behavior among multiple assets.Design/methodology/approachThe dynamics of complex financial markets can be best explored by following agent-based modeling approach. The artificial financial market is populated with traders following two heterogeneous trading strategies: the technical and the fundamental trading rules. By simulation, the switching behavior among multiple assets is investigated.FindingsThe proposed framework can explain important stylized facts in financial time series, such as random walk price dynamics, bubbles and crashes, fat-tailed return distributions, absence of autocorrelation in raw returns, persistent long memory of volatility, excess volatility, volatility clustering and power-law tails. In addition, asset returns possess fractal structure and self-similarity features; though the switching behavior is only allowed among the asset markets.Practical implicationsThe model demonstrates stylized facts of most real financial markets. Thereafter, the proposed model can serve as a testbed for policy makers, scholars and investors.Originality/valueTo the best of knowledge, no research has been conducted to introduce the disposition effect to a multi-asset agent-based model. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Review of Behavioral Finance Emerald Publishing

Disposition effect and multi-asset market dynamics

Ezzat, Heba M.
Review of Behavioral Finance , Volume 11 (2): 21 – Jun 24, 2019
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21 pages

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Publisher
Emerald Publishing
Copyright
© Emerald Publishing Limited
ISSN
1940-5979
DOI
10.1108/rbf-01-2018-0003
Publisher site
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Abstract

Asset pricing dynamics in a multi-asset framework when investors’ trading exhibits the disposition effect is studied. The purpose of this paper is to explore asset pricing dynamics and the switching behavior among multiple assets.Design/methodology/approachThe dynamics of complex financial markets can be best explored by following agent-based modeling approach. The artificial financial market is populated with traders following two heterogeneous trading strategies: the technical and the fundamental trading rules. By simulation, the switching behavior among multiple assets is investigated.FindingsThe proposed framework can explain important stylized facts in financial time series, such as random walk price dynamics, bubbles and crashes, fat-tailed return distributions, absence of autocorrelation in raw returns, persistent long memory of volatility, excess volatility, volatility clustering and power-law tails. In addition, asset returns possess fractal structure and self-similarity features; though the switching behavior is only allowed among the asset markets.Practical implicationsThe model demonstrates stylized facts of most real financial markets. Thereafter, the proposed model can serve as a testbed for policy makers, scholars and investors.Originality/valueTo the best of knowledge, no research has been conducted to introduce the disposition effect to a multi-asset agent-based model.

Journal

Review of Behavioral Finance – Emerald Publishing

Published: Jun 24, 2019

Keywords: Agent-based model; Financial markets; Bounded rationality; Fractals and scaling; Power-law distributions

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