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Application of Structural Equation Modeling in Behavioral Finance: A Study on the Disposition Effect

In: HANDBOOK OF FINANCIAL ECONOMETRICS, MATHEMATICS, STATISTICS, AND MACHINE LEARNING

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  • Hsin-Hue Chang

Abstract

Studies on behavioral finance argue that cognitive/emotional biases could influence investors’ decisions and result in the disposition effect, wherein investors have the tendency to sell winning stocks too early and hold losing stocks too long. In this regard, this study proposes a conceptual model to examine the relationship among cognitive/emotional biases, the disposition effect, and investment performance. Cognitive/emotional biases mainly consist of mental accounting, regret avoidance, and self-control. Furthermore, this study examines whether gender and marital status moderate the relationship between these biases and the disposition effect by collecting quantitative data through a questionnaire survey and employing a structural equation modeling (SEM) approach to execute the estimation procedure. The results of this study show that mental accounting has the most significant influence on the disposition effect, which implies that prospect theory is an alternative to expected utility theory in accounting for investor’s behavior. The findings of moderating analysis indicate that female investors display a larger disposition effect than male investors.

Suggested Citation

  • Hsin-Hue Chang, 2020. "Application of Structural Equation Modeling in Behavioral Finance: A Study on the Disposition Effect," World Scientific Book Chapters, in: Cheng Few Lee & John C Lee (ed.), HANDBOOK OF FINANCIAL ECONOMETRICS, MATHEMATICS, STATISTICS, AND MACHINE LEARNING, chapter 16, pages 603-626, World Scientific Publishing Co. Pte. Ltd..
  • Handle: RePEc:wsi:wschap:9789811202391_0016
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    Cited by:

    1. Tai-Yuen Hon & Massoud Moslehpour & Kai-Yin Woo, 2021. "Review on Behavioral Finance with Empirical Evidence," Advances in Decision Sciences, Asia University, Taiwan, vol. 25(4), pages 15-41, December.

    More about this item

    Keywords

    Financial Econometrics; Financial Mathematics; Financial Statistics; Financial Technology; Machine Learning; Covariance Regression; Cluster Effect; Option Bound; Dynamic Capital Budgeting; Big Data;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

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