企业估值的不确定性与横截面错估度量

IF 0.8 Q4 BUSINESS, FINANCE
Giulio Bottazzi, Francesco Cordoni, Giulia Livieri, Stefano Marmi
{"title":"企业估值的不确定性与横截面错估度量","authors":"Giulio Bottazzi,&nbsp;Francesco Cordoni,&nbsp;Giulia Livieri,&nbsp;Stefano Marmi","doi":"10.1007/s10436-022-00423-w","DOIUrl":null,"url":null,"abstract":"<div><p>The degree of uncertainty associated with the value of a company plays a relevant role in valuation analysis. We propose an original and robust methodology for company market valuation, which replaces the traditional point estimate of the conventional Discounted Cash Flow model with a probability distribution of fair values that convey information about both the expected value of the company and its intrinsic uncertainty. Our methodology depends on two main ingredients: an econometric model for company revenues and a set of firm-specific balance sheet relations that are estimated using historical data. We explore the effectiveness and scope of our methodology through a series of statistical exercises on publicly traded U.S. companies. At the firm level, we show that the fair value distribution derived with our methodology constitutes a reliable predictor of the company’s future abnormal returns. At the market level, we show that a long-short valuation (LSV) factor, built using buy-sell recommendations based on the fair value distribution, contains information not accessible through the traditional market factors. The LSV factor significantly increases the explanatory and the predictive power of factor models estimated on portfolios and individual stock returns.</p></div>","PeriodicalId":45289,"journal":{"name":"Annals of Finance","volume":null,"pages":null},"PeriodicalIF":0.8000,"publicationDate":"2023-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10436-022-00423-w.pdf","citationCount":"1","resultStr":"{\"title\":\"Uncertainty in firm valuation and a cross-sectional misvaluation measure\",\"authors\":\"Giulio Bottazzi,&nbsp;Francesco Cordoni,&nbsp;Giulia Livieri,&nbsp;Stefano Marmi\",\"doi\":\"10.1007/s10436-022-00423-w\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>The degree of uncertainty associated with the value of a company plays a relevant role in valuation analysis. We propose an original and robust methodology for company market valuation, which replaces the traditional point estimate of the conventional Discounted Cash Flow model with a probability distribution of fair values that convey information about both the expected value of the company and its intrinsic uncertainty. Our methodology depends on two main ingredients: an econometric model for company revenues and a set of firm-specific balance sheet relations that are estimated using historical data. We explore the effectiveness and scope of our methodology through a series of statistical exercises on publicly traded U.S. companies. At the firm level, we show that the fair value distribution derived with our methodology constitutes a reliable predictor of the company’s future abnormal returns. At the market level, we show that a long-short valuation (LSV) factor, built using buy-sell recommendations based on the fair value distribution, contains information not accessible through the traditional market factors. The LSV factor significantly increases the explanatory and the predictive power of factor models estimated on portfolios and individual stock returns.</p></div>\",\"PeriodicalId\":45289,\"journal\":{\"name\":\"Annals of Finance\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.8000,\"publicationDate\":\"2023-01-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://link.springer.com/content/pdf/10.1007/s10436-022-00423-w.pdf\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Annals of Finance\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s10436-022-00423-w\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"BUSINESS, FINANCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annals of Finance","FirstCategoryId":"1085","ListUrlMain":"https://link.springer.com/article/10.1007/s10436-022-00423-w","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
引用次数: 1

摘要

与公司价值相关的不确定性程度在估值分析中起着相关作用。我们提出了一种新颖而稳健的公司市场估值方法,该方法用公允价值的概率分布取代了传统贴现现金流模型的传统点估计,该分布传达了有关公司预期价值及其内在不确定性的信息。我们的方法取决于两个主要因素:一个是公司收入的计量经济模型,另一个是使用历史数据估计的一组特定于公司的资产负债表关系。我们通过对美国上市公司的一系列统计练习来探索我们方法的有效性和范围。在公司层面,我们表明,用我们的方法得出的公允价值分布构成了公司未来异常回报的可靠预测指标。在市场层面,我们发现,使用基于公允价值分布的买卖建议构建的长短期估值(LSV)因子包含传统市场因子无法获取的信息。LSV因子显著提高了因子模型对投资组合和个股回报的解释力和预测力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Uncertainty in firm valuation and a cross-sectional misvaluation measure

Uncertainty in firm valuation and a cross-sectional misvaluation measure

The degree of uncertainty associated with the value of a company plays a relevant role in valuation analysis. We propose an original and robust methodology for company market valuation, which replaces the traditional point estimate of the conventional Discounted Cash Flow model with a probability distribution of fair values that convey information about both the expected value of the company and its intrinsic uncertainty. Our methodology depends on two main ingredients: an econometric model for company revenues and a set of firm-specific balance sheet relations that are estimated using historical data. We explore the effectiveness and scope of our methodology through a series of statistical exercises on publicly traded U.S. companies. At the firm level, we show that the fair value distribution derived with our methodology constitutes a reliable predictor of the company’s future abnormal returns. At the market level, we show that a long-short valuation (LSV) factor, built using buy-sell recommendations based on the fair value distribution, contains information not accessible through the traditional market factors. The LSV factor significantly increases the explanatory and the predictive power of factor models estimated on portfolios and individual stock returns.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Annals of Finance
Annals of Finance BUSINESS, FINANCE-
CiteScore
2.00
自引率
10.00%
发文量
15
期刊介绍: Annals of Finance provides an outlet for original research in all areas of finance and its applications to other disciplines having a clear and substantive link to the general theme of finance. In particular, innovative research papers of moderate length of the highest quality in all scientific areas that are motivated by the analysis of financial problems will be considered. Annals of Finance''s scope encompasses - but is not limited to - the following areas: accounting and finance, asset pricing, banking and finance, capital markets and finance, computational finance, corporate finance, derivatives, dynamical and chaotic systems in finance, economics and finance, empirical finance, experimental finance, finance and the theory of the firm, financial econometrics, financial institutions, mathematical finance, money and finance, portfolio analysis, regulation, stochastic analysis and finance, stock market analysis, systemic risk and financial stability. Annals of Finance also publishes special issues on any topic in finance and its applications of current interest. A small section, entitled finance notes, will be devoted solely to publishing short articles – up to ten pages in length, of substantial interest in finance. Officially cited as: Ann Finance
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信