Volume 14, Issue 1 -

A widely used methodology for estimating the beta of companies with the Capital Asset Pricing Model (CAPM) uses comparable firms based only on industry or sector classifications (Bancel, F., and U. R. Mittoo. 2014. “The Gap between the Theory and Practice of Corporate Valuation: Survey of European Experts.” Journal of Applied Corporate Finance 26, no. 4 (Fall): 106–17. doi:https://doi.org/10.1111/jacf.12095, 112; KPMG. 2017. “Cost of Capital Study 2017: Diverging Markets, Converging Business Models.” Accessed September 28, 2018. https://assets.kpmg.com/content/dam/kpmg/ch/pdf/cost-of-capital-study-2017-en.pdf, 37). We hypothesize that even within industries, there is a significant relationship between the cost of equity and the life cycle of a firm. We argue that these variables are correlated because different life-cycle stages exhibit different degrees of systematic risk. Therefore, as the firm moves along its life cycle, its unlevered beta decreases. We define the stages of the firm life cycle based on a modification of the theoretical typology of (Miller, D., and P. Friesen. 1984. “A Longitudinal Study of the Corporate Life-Cycle.” Management Sciences 30 (10): 1161–83. http://www.jstor.org/stable/2631384, 1162–3) and then classify a sample of listed companies into these stages using (Dickinson, V. 2011. “Cash Flow Patterns as a Proxy for Firm Life-Cycle.” The Accounting Review 86 (6): 1969–94. doi:https://doi.org/10.2308/accr-10130) cash flow statements methodology. We construct value-weighted portfolios that are formed based on our life-cycle stages classification, adapting the procedure of (Fama, E., and K. R. French. 1993. “Common Risk Factors in the Returns on Stocks and Bonds.” Journal of Financial Economics 33 (1): 3–56. doi:https://doi.org/10.1016/0304-405X(93)90023-5). Finally, we compare the betas (levered and unlevered) of these portfolios to determine whether there are statistically significant differences. Our results show clear evidence of a relationship between betas and the corporate life cycle and that this relationship is robust to both changes in the period of analysis and omitted variables bias (when controlling with the four-factor model of (Carhart, M. M. 1997. “On Persistence in Mutual Fund Performance.” The Journal of Finance 52 (1): 57–82. doi:https://doi.org/10.1111/j.1540-6261.1997.tb03808.x). We believe our results show an important shortcoming in a widely used methodology among practitioners for estimating the CAPM.

Our study’s objective is to develop and analyze a dynamic approach for estimating firms’ expected cost of equity capital. We contribute to the literature by enabling the usage of any required estimation date, resolving the major shortcoming of the existing models—their reliance on one fixed estimation date. This paper presents our model and discusses it from the perspective of the extant body of literature. We show that the current state of the art approach in dynamic estimation does not satisfy theoretical and practical demands, and offers scope for significant improvements. We conduct our analysis by specially considering capital market efficiency, the consistent appreciation of cash flows with respect to timing, and straightforward practical implementation for researchers and practitioners. Building on semi-strong capital market efficiency, the analysis reveals further insights into residual income valuation as we demonstrate that any realization of residual income in the course of the year is irrelevant to valuation in the absence of dividend realization. Consequently, assumptions regarding the shape of earnings in the course of the year are also irrelevant to valuation. Additionally, our theoretically founded model conveniently facilitates the undistorted incorporation of different fiscal year-ends in large samples and avoids stale measures of expected cost of equity capital.

Examining 416 transactions over the 1996 to 2013 time period, we find that size, stock price volatility, block size, price-to-revenue, and EBITDA margin are significantly related to restricted stock discounts. We do not find registration rights or the initial holding period to be statistically significantly related to discounts. Our results suggest that simple correlations or sorting of discounts by various criteria do not capture what factors are statistically significantly related to restricted stock discounts in the complex world of private placement deals.

This study focuses on answering whether EV/EBITDA multiple of public companies in the food industry can be useful to obtain the Terminal Value (TV) in the valuation of unlisted small and medium-sized food companies. A case study into Spanish unlisted agribusinesses is designed for several samples and accounting years from 2010 to 2013. By means of a discounted cash flow (DCF) model combined with bootstrap techniques, the TV/EBITDA empirical distribution of the unlisted multiples is obtained for two different scenarios of free cash flow (FCF) growth, and then compared with the EV/EBITDA of the listed companies in the same industry. The results show that the stock market EV/EBITDA multiple may be used to determine the TV in the valuation process of unlisted small and medium-sized food companies that consistently obtain positive cash flows.

It is widely accepted that financial markets tend to make assessments of value on expectations of post-tax cash flows, since that is what equity investors receive. There is however, from time to time, a need to ascertain and apply a pre-tax discount rate to discount pre-tax cashflows. Examples include (i) the assessment of regulatory returns and (ii) impairment testing of cash generating units. This paper highlights the implicit assumptions inherent in the most commonly applied shorthand method of determining pre-tax discount rates before considering modifications to create a more realistic assumption set. The paper concludes with the derivation of a shorthand formula for finite life project cashflows, which often require a pre-tax discount rate. The author agrees that while all the cash flows should be modelled on a post-tax basis and then back solved, using an iterative approach, to find the actual pre-tax rate, where a shorthand is required the formulae discussed in this paper can be applied, provided the limitations are understood.