The role of capital expansion in stock evaluation: A variance decomposition approach

IF 1.9 3区经济学 Q2 ECONOMICS

Journal of Economic Dynamics & Control Pub Date : 2025-05-01 DOI:10.1016/j.jedc.2025.105113

Huixuan Li , Jing Chen , Manling Zhang , Ya Tang

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Abstract

We extend Cohen et al.'s (2003) variance decomposition framework to examine cross-sectional stock valuation drivers across Chinese and U.S. markets by incorporating expected capital expansion as an additional component. Our analysis demonstrates that in China's A-share market, 32.8 percent of cross-sectional valuation dispersion is attributable to future capital expansion. This positive relationship is mirrored in the NASDAQ market but contrasts with the negative effect observed in the NYSE/AMEX market. In particular, capital expansion exhibits strong explanatory power for valuations of small firms, high-tech companies, and firms listed on China's growth-oriented ChiNext and STAR market segments. Our decomposition approach also measures price informativeness—the degree to which stock valuations reflect future cash flows. We find a significant improvement in the price informativeness of China's stock prices since 2005. These findings enhance our understanding of stock pricing dynamics in growth-oriented markets.

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资本扩张在股票评价中的作用：方差分解方法

我们扩展了Cohen等人（2003）的方差分解框架，通过将预期资本扩张作为额外的组成部分来检查中国和美国市场的横截面股票估值驱动因素。我们的分析表明，在中国a股市场，32.8%的横截面估值分散归因于未来的资本扩张。这种积极的关系反映在纳斯达克市场，但与纽约证券交易所/美国证券交易所市场观察到的负面影响形成对比。特别是，资本扩张对小型公司、高科技公司以及在中国成长型创业板和创业板上市的公司的估值具有很强的解释力。我们的分解方法也衡量了价格信息——股票估值反映未来现金流的程度。我们发现，自2005年以来，中国股票价格的价格信息性有了显著提高。这些发现增强了我们对成长型市场股票定价动态的理解。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Economic Dynamics & Control ECONOMICS-

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.