A Full-Information Approach for Estimating Divisional Betas

Ehrhardt, Michael C.; Bhagwat, Yatin

doi:10.2307/3665730

Cited by 24 publications

(19 citation statements)

References 10 publications

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“…However, as there are more comparable business units than companies in their sample, there is no unique optimal solution. Ehrhardt and Bhagwat (1991) propose an approach known as full-information beta, which uses multivariate linear regression to solve the problem. A similar approach using WACC instead of betas was applied earlier by Harris et al (1989).…”

Section: Discussion Of the Techniquementioning

confidence: 99%

“…In this section, the general principle is discussed, and in the next section it is transferred to the question of how cost-of-capital and betas can be aggregated from a divisional level to the corporate level. The aggregation of cost-of-capital derived from the value additivity principle is a central premise in many important articles in the field of divisional cost-of-capital, for instance Fuller and Kerr (1981) and Ehrhardt and Bhagwat (1991). In particular, full-information beta approaches that use multiple regression analysis (Ehrhardt and Bhagwat 1991;Cummins and Phillips 2005;Chua et al 2006) are based on this premise.…”

Section: The Value Additivity Principle In Investment Theorymentioning

confidence: 99%

“…The aggregation of cost-of-capital derived from the value additivity principle is a central premise in many important articles in the field of divisional cost-of-capital, for instance Fuller and Kerr (1981) and Ehrhardt and Bhagwat (1991). In particular, full-information beta approaches that use multiple regression analysis (Ehrhardt and Bhagwat 1991;Cummins and Phillips 2005;Chua et al 2006) are based on this premise. This means that many of the empirical studies on divisional cost-of-capital also implicitly test the value additivity principle and its assumptions.…”

Section: The Value Additivity Principle In Investment Theorymentioning

confidence: 99%

“…There are numerous empirical studies that confirm this relationship, although not all studies find that industry is a significant factor (Pfister 2003). Also, some articles that deal with cost-of-capital of business units make the assumption that there is an optimal debt-to-equity ratio for an industry (Kaplan and Peterson 1998;Ehrhardt and Bhagwat 1991). However, there are certainly differences between the companies within one industry, so that some kind of average value has to be calculated.…”

Section: Capital Structure Of Business Unitsmentioning

confidence: 99%

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Background: Cost-of-Capital in the Finance Literature

Schlegel¹

2015

Contributions to Management Science

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The literature review in this thesis is distributed over two chapters. The aim of Chap. 2 is to discuss literature from the field of cost-of-capital. This is necessary as a foundation for the subsequent chapter, which is more application-oriented. In Chap. 3, previous empirical results on companies' cost-of-capital practices are discussed. Research gaps will be identified at the end of that chapter.This chapter is structured as follows: In Sect. 2.1, the broader field of company cost-of-capital is discussed. This includes a brief discussion of traditional seminal papers as a foundation for the rest of the literature review as well as a review of contemporary discussions about general issues of cost-of-capital, such as alternative determination models and the consideration of unsystematic risk. Section 2.2 shows how the field of cost-of-capital relates to the different sub-disciplines of Finance and for which fields of application of Managerial Finance it is relevant. In particular, the role of cost-of-capital in internal capital allocation, performance measurement and value-based management is discussed. In Sect. 2.3, a theoretical framework for the determination of cost-of-capital in a company group context that is derived from traditional Finance theory is presented as a foundation for the subsequent section. In Sect. 2.4, previous research on the determination techniques for the cost-of-capital of business units and projects is discussed thoroughly. This includes a detailed discussion of the techniques as well as the theoretical and empirical methods adopted by other researchers.

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Section: Discussion Of the Techniquementioning

confidence: 99%

Section: The Value Additivity Principle In Investment Theorymentioning

confidence: 99%

Section: The Value Additivity Principle In Investment Theorymentioning

confidence: 99%

Section: Capital Structure Of Business Unitsmentioning

confidence: 99%

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Background: Cost-of-Capital in the Finance Literature

Schlegel¹

2015

Contributions to Management Science

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“…Estimation of technology-specific beta factors from the actual fuel mix of the considered companies proceeds along the lines proposed by Boquist and Moore (1983), Ehrhardt and Bhagwat (1991), Kaplan and Peterson (1998) for deriving full-information industry betas. Thereby, estimation of technology betas is performed in two steps: First, firm-specific beta factors β i are estimated from an OLS time-series regression on historical returns 2005-2010 using Eqn.…”

mentioning

confidence: 99%

Fuel Mix Characteristics and Expected Stock Returns of European Power Companies

Sunderkötter

2011

SSRN Journal

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in AbstractThis article investigates the impact of the fuel mix structure in power generation portfolios on expected stock returns for major European power companies. The 22 biggest publicly listed European power producers are examined between January 2005 and December 2010. Based on the capital asset pricing model (CAPM) and multi-factor market models, the systematic risk of the power companies relative to the overall market performance and other typical energy and macroeconomic risk factors is analyzed. The full-information approach is used to determine technology-specific betas and risk factor sensitivities from the sample. Although most companies are not exclusively in the power producing business, it is shown that the generation fuel mix has a significant impact on the historical stock returns of the investigated companies. In particular, the sample companies exhibit significant differences in the systematic risk of gas and nuclear generation technologies compared with renewable technologies measured by technology-specific, delevered beta factors.This study extends existing literature and contributes new insights in two ways: Firstly, this is to our knowledge the first empirical analysis comparing the financial risk of different electricity generation technologies. Secondly, the results provide practical benefit to determine adequate riskadjusted capital costs for typical generation technologies. Therewith, this study is relevant for evaluating all kinds of power plant investments.

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Conclusion and Contribution to Knowledge

Schlegel¹

2015

Contributions to Management Science

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A Full-Information Approach for Estimating Divisional Betas

Cited by 24 publications

References 10 publications

Background: Cost-of-Capital in the Finance Literature

Background: Cost-of-Capital in the Finance Literature

Fuel Mix Characteristics and Expected Stock Returns of European Power Companies

Conclusion and Contribution to Knowledge

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