Unlevered Beta Research Articles

Predicting systematic risk: Implications from growth options

In accordance with the well-known financial leverage effect, decreases in stock prices cause an increase in the levered equity beta for a given unlevered beta. However, as growth options are more volatile and have higher risk than assets in place, a price decrease may decrease the unlevered equity beta via an operating leverage effect. This is because price decreases are associated with a proportionately higher loss in growth options than in assets in place. Most of the existing literature focuses on the financial leverage effect: This paper examines both effects. We show, with a simple option pricing model, the opposing effects at work when the firm is a portfolio of assets in place and growth options. Our empirical results show that, contrary to common belief, the operating leverage effect largely dominates the financial leverage effect, even for initially highly levered firms with presumably few growth options. We then link variations in betas to measurable firm characteristics that proxy for the fraction of the firm invested in growth options. We show that these proxies jointly predict a large fraction of future cross-sectional differences in betas. These results have important implications on the predictability of equity betas, hence on empirical asset pricing and on portfolio optimization that controls for systematic risk.

Systematic Risk & A-REIT Debt Characteristics

The study examines the relationship between systematic risk of Australian Real Estate Investment Trusts (A-REITs) and their debt characteristics over the period 1995 to 2008, controlling for firm size, organizational structure, property type, and time varying patterns in beta estimates. Both levered (normal beta) and unlevered fiscal year beta estimates of A-REITs are regressed against the A-REIT characteristics. Financial leverage variables do not show any statistically significant relationship with levered betas. In contrast two of the financial leverage variables, short-term debt and total debt are significant in the unlevered beta regression model. The study shows that size of A-REIT and property types owned by the A-REITs are important determinants of systematic risk. However, property type dummy variables are not significant after adjusting the fiscal year betas for thin trading. I find a significant time varying pattern in fiscal year beta estimates which is captured by the annual dummy variables in the regressions. I also find that the regression residuals display substantial heteroscedasticity and therefore needed to adjust for this by using Weighted Least Squares (WLS) method. The variance model I use to derive weights for WLS is also of independent interest because total financial leverage is statistically significant in explaining squared least squares residuals in all levered beta regression models. The results of the study will assist investors in A-REITs to make better risk return trade off decisions and A-REIT managers to evaluate their strategic decisions.

The Capital Structure Difference Across Australian Companies

This study investigate the relation between capital structure and firm characteristics in Australia. We use panel data regression to study an unbalanced panel of 367 firms over a 15-year period from 1992 to 2006. We find that debt-asset ratio is positively related to asset tangibility but inversely related to growth prospects and business risk measured by unlevered beta of equity. We also find that although levered firms are generally more profitable than unlevered, profitability decreases the debt ratio of levered firms. We do not find that firm size affects the capital structure of Australian firms. These results are consistent with the pecking order and the agency cost theories but contradict the tradeoff theory.

The Effects of Debt Equity Policy on Shareholder Return Requirements and Beta

This note outlines the link between shareholder-return requirements and a firm's use of debt. It explores the theoretical arguments concerning how the cost of equity changes with the use of debt and discusses the limitations of each view. It also provides conceptual and practical guidance on the use of levered and unlevered betas.

The Relevance of the Firm's Leverage as the only Factor in the Estimation of Systematic Risk: An Empirical Analysis using the Unlevered Betas for a Group of Firms in a Common Economic Sector

An extensive body of knowledge has been developed around the theoretical relationship between the assumption that support the theory of the cost of capital and those that support the Portfolio-Capital Asset Pricing Model. The main discussion concerning how these theories are related is focused in the use of beta as a measure of systematic risk for valuation purposes in corporate finance. The theory suggests that systematic risk is solely determined in function of the leverage (debt) used by a particular firm, under this premise various studies in corporate finance (especially those concerning firm's valuation methods) have suggested the use of proxy methods for the estimation of unlevered (debt-free) beta in order to calculate a more accurate estimate of the cost of capital of non-traded firms in an easy way. In this paper, we make an empirical test to see the validity of the theoretical assumptions concerning the premise that the unlevered betas of companies that are in the same economic sector, must be equal or at least they must have a similar variance around a grand mean throughout different periods in time. The dataset used for this analysis contains the quarterly financial information and daily closing stock prices of 1008 companies listed in the NYSE from 20 different economic sectors for the period comprehended between the 1st quarter of 1999 to the 4th quarter of 2004. By using ANOVA as our chosen statistical method, we found that in 15 of the 20 economic sectors under scrutiny, there is not sufficient empirical evidence to let us to confirm the premise about the equality and stability of the unlevered betas of a group of companies in the same economic sector. Therefore, this finding led us to conclude that by using a proxy method for estimating systematic debt-free risk, practitioners could be using an erroneous approach given the fact that there is not enough evidence that the unlevered betas for a group of firms in the same economic sector are equal.

Beta Levered and Beta Unlevered

We claim that in a world without leverage cost the relationship between the levered beta (BL) and the unlevered beta (Bu) of a company depends upon the financing strategy. For a company that maintains a fixed book-value leverage ratio, the relationship is Fernandez (2004): BL = Bu + (Bu - Bd) D (1 - T) / E. For a company that maintains a fixed market-value leverage ratio, the relationship is Miles and Ezzell (1980):BL = Bu + (D / E) (Bu - Bd) [1 - T Kd / (1 + Kd)]. For a company with a preset debt in every period, the relationship is Modigliani and Miller (1963):BL = Bu + [Bu - Bd] (D-VTS) / E, being the Value of Tax Shields (VTS) the present value of the future tax shields discounted at the cost of debt. We also analyze alternative valuation theories proposed in the literature to estimate the relationship between the levered beta and the unlevered beta (Harris and Pringle (1985), Damodaran (1994), Myers (1974), and practitioners) and prove that all provide inconsistent results.

New evidence on the impact of financial leverage on beta risk: A time-series approach

The traditional estimation of a project’s cost of capital often requires leverage adjustments to beta. Several researchers have empirically investigated the relationship between the debt/equity ratio ( D/ E) and beta implied by such leverage adjustments. Typically, this has involved cross-sectional analysis of a sample of U.S. firms in selected industry classifications. The major contribution of the current study is to extend this evidence by investigating the relationship between financial leverage and beta using a time-series approach. This has several advantages over the cross-sectional approach. Our results reveal that while the estimated unlevered beta produced by the time-series approach is quite close to the theoretically implied unlevered beta, the mean difference between the two measures across our sample of 348 U.S. stocks is highly significant. The analysis also reveals that 30–40% of our full sample rejects a theoretical D/ E restriction on the time-series model. Moreover, the results suggest that the restriction is much more likely to be rejected for stocks with high debt/equity ratios, which in general have low unlevered betas. Further, there is a considerable cross-sectional variation in the proportion of these rejections across industry groupings. Accordingly, these results suggest that due care needs to be applied when taking the traditional view of delevering beta risk.