The EDS Comp sheet helps investors identify the right peers using a combination of industry classification and multiple metrics, such as Profitability, Growth and Quality factors. A CFA Journal publication, entitled Stick to the Fundamentals and Discover Your Peers, written by Jens Overgaard Knudson, Simon Kold and Thomas Plenborg highlights the importance of using this combination approach to "discover" your peers. The end result is a more accurate valuation estimate, leading to higher conviction in price targets and risk/reward calculations, which leads directly to a higher quality portfolio and increased alpha. The study highlights:
Identifying comparable companies on the bases of profitability, growth and risk is an essential alternative to the industry classification method.
Most investors only use industry classification as a proxy for company comparability.
The most accurate results are obtained when both methods are used, as they each capture different fundamental aspects.
EDS takes this concept and puts it into practice in an efficient and scalable way for investors, across over 12,000 equities, in seconds - making our dynamic "Comp Sheet" an alpha generating tool for investors.
Excerpts from the Article
The "multiples approach" relies on the theory that perfect substitutes should sell at the same price. This theory implies that the selection of comparable companies is a crucial step.
Most analysts and investors use industry classification as a proxy for company comparability. The use of industry relies on the assumption that companies in the same industry share the same economic characteristics—that is, profitability, risk, and growth. However, this is rarely the case and thus, they should not necessarily trade at the same multiple.
Prior studies have demonstrated that identifying comparable companies on the basis of different proxies for profitability, growth, and risk may be a useful alternative to the industry classification method. In our study, we defined a target company’s peer group as the companies with the smallest sum of absolute rank differences across the target company’s variables of interest. The SARD approach is similar to the clustering algorithm known as the “Manhattan distance.” Results show that the SARD (sum of absolute rank differences) approach yields significantly more accurate valuation estimates than the industry approach.
In addition, a combination of the SARD approach and the industry classification approach results in even more accurate valuation estimates, suggesting that the two approaches capture different aspects of peers’ fundamentals. Our findings are robust across time, company size, and varying numbers of peers, which, coupled with the practical applicability of the approach, makes it a highly relevant tool in a financial analyst’s toolbox.
One of the core differentiators of the EDS platform is the ability to easily build the relevant list of comparable companies using a combination of the traditional industry classification approach and similar fundamental measures, such as Profitability, Growth and Quality.
Dynamic Regressions and a Warranted Multiple Bhojraj and Lee (2002) estimated a series of annual cross-sectional regressions of EV/sales (enterprise value divided by sales) and P/B on eight different proxies for profitability, growth, and . They referred to this prediction as a company’s “warranted multiple,” which is used to identify comparable companies. Bhojraj and Lee found that their warranted multiple provides more accurate valuation estimates than alternative selection methodologies, such as industry classification and size.
EDS's Valuation Regression allows fundamental investors to choose relevant fundamental measures to calculate the 'warranted multiple' based on comparable companies. See below for CMG