A pseudo-Bayesian model in financial decision making with implications to market volatility, under- and overreaction

Kin Lam; Taisheng Liu; Wing Keung WONG

doi:10.1016/j.ejor.2009.07.005

A pseudo-Bayesian model in financial decision making with implications to market volatility, under- and overreaction

Kin Lam, Taisheng Liu, Wing Keung WONG^*

^*Corresponding author for this work

Research output: Contribution to journal › Journal article › peer-review

57 Citations (Scopus)

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Abstract

This paper develops a model of weight assignments using a pseudo-Bayesian approach that reflects investors' behavioral biases. In this parsimonious model of investor sentiment, weights induced by investors' conservative and representative heuristics are assigned to observations of the earning shocks of stock prices. Such weight assignments enable us to provide a quantitative link between some market anomalies and investors' behavioral biases. The seriousness of an anomaly can be quantitatively assessed by investigating into its dependency on weights. New results other than the short-run underreaction and long-run overreaction can be derived and new hypotheses can be formed.

Original language	English
Pages (from-to)	166-175
Number of pages	10
Journal	European Journal of Operational Research
Volume	203
Issue number	1
DOIs	https://doi.org/10.1016/j.ejor.2009.07.005
Publication status	Published - 16 May 2010

Scopus Subject Areas

General Computer Science
Modelling and Simulation
Management Science and Operations Research
Information Systems and Management

User-Defined Keywords

Bayesian model
Overreaction
Representative and conservative heuristics
Stock price
Stock return
Underreaction

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10.1016/j.ejor.2009.07.005

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Cite this

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abstract = "This paper develops a model of weight assignments using a pseudo-Bayesian approach that reflects investors' behavioral biases. In this parsimonious model of investor sentiment, weights induced by investors' conservative and representative heuristics are assigned to observations of the earning shocks of stock prices. Such weight assignments enable us to provide a quantitative link between some market anomalies and investors' behavioral biases. The seriousness of an anomaly can be quantitatively assessed by investigating into its dependency on weights. New results other than the short-run underreaction and long-run overreaction can be derived and new hypotheses can be formed.",

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author = "Kin Lam and Taisheng Liu and WONG, {Wing Keung}",

note = "Funding Information: The authors are grateful to Professor Lorenzo Peccati and anonymous referees for substantive comments that have significantly improved this manuscript. The third author would like to thank Professors Robert B. Miller and Howard E. Thompson for their continuous guidance and encouragement. The research is partially supported by the Grant No. 200908 from Hong Kong Research Grants Council. ",

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N2 - This paper develops a model of weight assignments using a pseudo-Bayesian approach that reflects investors' behavioral biases. In this parsimonious model of investor sentiment, weights induced by investors' conservative and representative heuristics are assigned to observations of the earning shocks of stock prices. Such weight assignments enable us to provide a quantitative link between some market anomalies and investors' behavioral biases. The seriousness of an anomaly can be quantitatively assessed by investigating into its dependency on weights. New results other than the short-run underreaction and long-run overreaction can be derived and new hypotheses can be formed.

AB - This paper develops a model of weight assignments using a pseudo-Bayesian approach that reflects investors' behavioral biases. In this parsimonious model of investor sentiment, weights induced by investors' conservative and representative heuristics are assigned to observations of the earning shocks of stock prices. Such weight assignments enable us to provide a quantitative link between some market anomalies and investors' behavioral biases. The seriousness of an anomaly can be quantitatively assessed by investigating into its dependency on weights. New results other than the short-run underreaction and long-run overreaction can be derived and new hypotheses can be formed.

KW - Bayesian model

KW - Overreaction

KW - Representative and conservative heuristics

KW - Stock price

KW - Stock return

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A pseudo-Bayesian model in financial decision making with implications to market volatility, under- and overreaction

Abstract

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