超越金融基本面的资产定价:亲社会偏好和形象问题的影响

IF 1.9 3区 经济学 Q2 ECONOMICS Journal of Economic Dynamics & Control Pub Date : 2024-11-26 DOI:10.1016/j.jedc.2024.105004
Dragana Draganac , Kelin Lu
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引用次数: 0

摘要

本文研究了两种非财务价值--社会偏好和形象关注--对实验资产市场中社会效益股票定价的影响,并将其与股票财务基本面的影响分离开来。为此,我们设计了一个新颖的实验室资产市场,在这个市场中,股票的基本价值相同,但与非财务价值的关联却各不相同。我们发现,单纯的亲社会偏好对社会效益股票的市场价格影响甚微。然而,形象因素的存在会显著提高社会公益股票的市场价格。此外,在这种情况下,无论个人的非财务价值水平如何,他们都会以高价交易这些股票。为了确定非财务价值在个人层面上对股票估值的影响,我们进行了一项平行的非市场实验,其中纳入了相同的决策因素。在这种非市场环境下,仅亲社会偏好就对股票预订价格产生了积极影响,而形象因素的加入则进一步提高了股票预订价格。
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Pricing asset beyond financial fundamentals: The impact of prosocial preference and image concerns
This paper examines the effects of two non-financial values—prosocial preferences and image concerns—on the pricing of socially beneficial stocks within experimental asset markets, isolating their effect from those of stocks' financial fundamentals. To this end, we designed a novel laboratory asset market where stocks shared the same fundamental value but varied in their associations with non-financial values. We found that prosocial preferences alone have a minimal impact on the market prices of socially beneficial stocks. However, the presence of image concerns significantly raises the market price of socially beneficial stocks. Additionally, under this condition, individuals trade these stocks at high prices regardless of their level of non-financial values. To benchmark the effect of non-financial values on stock valuation at the individual level, we conducted a parallel non-market experiment incorporating the same decision factors. In this non-market setting, prosocial preferences alone positively impacted stock reservation prices, and the addition of image concerns further increased these prices.
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来源期刊
CiteScore
3.10
自引率
10.50%
发文量
199
期刊介绍: The journal provides an outlet for publication of research concerning all theoretical and empirical aspects of economic dynamics and control as well as the development and use of computational methods in economics and finance. Contributions regarding computational methods may include, but are not restricted to, artificial intelligence, databases, decision support systems, genetic algorithms, modelling languages, neural networks, numerical algorithms for optimization, control and equilibria, parallel computing and qualitative reasoning.
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