Investors’ Heterogeneous Preferences for Structured Financial Products in China: The Impact of Demographic Characteristics
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How to Cite

Han, X. ., & Liu, W. . (2022). Investors’ Heterogeneous Preferences for Structured Financial Products in China: The Impact of Demographic Characteristics. Review of Business Management, 24(3). https://doi.org/10.7819/rbgn.v24i3.4187

Abstract

Purpose – Structured financial products (SPs) have become very popular with retail investors in recent years. Investors’ preferences play a critical role when investing in SPs. The objective of this study is to understand SP investment behavior by investigating Chinese investors’ heterogeneous preferences for choosing wealth management products (WMPs) with certain attributes.
Theoretical framework – Investors with different demographic characteristics show different preferences in their SP investments.
Design/methodology/approach – We employ the choice experiment (CE) method and examine preference heterogeneity using the multinomial logit (MNL) and the mixed logit (MXL) models.
Findings – (i) The attributes of small bank, minimum amount, non-guaranteed floating return and guaranteed floating return significantly affect the choice when purchasing WMPs. (ii) There are significant heterogeneous preferences for minimum amount. (iii) These four characters are the sources of heterogeneous preferences for minimum amount.
Practical & social implications of research – This information can contribute to understanding the heterogeneous preferences of investors, which can help in designing marketable WMPs to target different kinds of investors.
Originality/value – The main contribution of the research is it examines investors’ heterogeneous preferences for SPs. The study provides empirical evidence of which attributes of structured products significantly affect investor preferences. It also reveals which characteristics of investors affect their heterogeneous preferences.

Keywords: Structured financial products, heterogeneous preferences, choice experiments, mixed logit model, behavior.

https://doi.org/10.7819/rbgn.v24i3.4187
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pdf (Português (Brasil))

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