更深入地研究公司特定回报变化与股票回报之间的关系

IF 1.1 Q3 BUSINESS, FINANCE
H. Nguyen, Yihui Lan, Sirimon Treepongkaruna
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引用次数: 0

摘要

目的先前的研究使用了两种衡量公司特定回报变化的指标:绝对和相对的特殊波动性,后者也称为股价非同步性。尽管大多数研究都集中在研究特殊波动性难题上,但作者对这两个指标进行了比较,并进一步研究了非同步性的两个组成部分中的哪一个解释了FSRV和股票回报之间的关联,强调了评估哪一个组成部分驱动股票回报的重要性。设计/方法论/方法作者使用1925年至2016年的美国个股收益率,并基于Fama和French(1993)模型定义了FRSV的两个指标。具体而言,作者将相对测度分解为两个部分:(i)绝对特质波动率和(ii)系统波动率。作者基于高-低、零投资五分之一投资组合排序进行了各种测试,并通过挑选每个组成部分进行了Fama–MacBeth分析。研究结果:作者发现,根据相对特殊波动率或系统波动率排序的投资组合回报为正,但根据绝对特殊波动率排序,回报为负。在使用双重排序方法控制大小、BM和其他风险特征后,结果是稳健的。Fama–MacBeth回归结果表明,相对测度与股票回报率之间的正相关主要是由公司之间的低系统波动异常驱动的。研究结果对控制返回剩余动量、偏度、跳跃和信息离散性具有鲁棒性。独创性/价值外部研究提出了特殊波动性难题和低波动性异常。作者强调了整合这两种研究流的重要性。这项研究增强了对FSRV和横截面股票回报之间关系背后驱动力的理解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A closer look at the relationship between firm-specific return variation and stock returns
PurposePrior studies use two measures of firm-specific return variation (FSRV): idiosyncratic volatility in absolute and relative terms, the latter of which is also termed stock price nonsynchronicity. Whereas most research focuses on investigating the idiosyncratic volatility puzzle, the authors carry out comparison of these two measures and further investigate which of the two constituents of nonsynchronicity explain the association between FSRV and stock returns, emphasising the importance of assessing which component drives stock returns.Design/methodology/approachThe authors use the US individual stock returns from 1925 to 2016 and define the two measures of FRSV based on the Fama and French (1993) model. Specifically, the authors decompose the relative measure into two components: (i) absolute idiosyncratic volatility and (ii) systematic volatility. The authors conduct various tests based on high-minus-low, zero-investment quintile portfolio sorts and perform the Fama–MacBeth analysis by singling out each component.FindingsThe authors find a positive return on the portfolio sorted on relative idiosyncratic volatility or on systematic volatility, but find a negative return sorted on absolute idiosyncratic volatility. The results are robust after controlling for size, BM and other risk characteristics using a double-sorting approach. The Fama–MacBeth regression results show that a positive association between the relative measure and stock returns is driven primarily by the low-systematic-volatility anomaly across firms. The findings are robust to controlling for return residual momentum, skewness, jumps and information discreteness.Originality/valueExtant research posits the idiosyncratic volatility puzzle and the low-volatility anomaly. The authors emphasize the importance of integrating these two streams of research. This study enhances the understanding of the driving force underlying the relationship between FSRV and cross-sectional stock returns.
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来源期刊
CiteScore
6.50
自引率
0.00%
发文量
6
期刊介绍: The objective of the Journal is to publish papers that make a fundamental and substantial contribution to the understanding of accounting phenomena. To this end, the Journal intends to publish papers that (1) synthesize an area of research in a concise and rigorous manner to assist academics and others to gain knowledge and appreciation of diverse research areas or (2) present high quality, multi-method, original research on a broad range of topics relevant to accounting, auditing and taxation. Topical coverage is broad and inclusive covering virtually all aspects of accounting. Consistent with the historical mission of the Journal, it is expected that the lead article of each issue will be a synthesis article on an important research topic. Other manuscripts to be included in a given issue will be a mix of synthesis and original research papers. In addition to traditional research topics and methods, we actively solicit manuscripts of the including, but not limited to, the following: • meta-analyses • field studies • critiques of papers published in other journals • emerging developments in accounting theory • commentaries on current issues • innovative experimental research with strong grounding in cognitive, social or anthropological sciences • creative archival analyses using non-standard methodologies or data sources with strong grounding in various social sciences • book reviews • "idea" papers that don''t fit into other established categories.
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