Discovering appropriate friends for monetary evaluation is a vexing job that requires cautious consideration of companies’ underlying economics, accounting decisions, and monetary assertion presentation. However with out comparable monetary assertion info, peer benchmarking might yield much less significant and even deceptive insights that negatively affect earnings forecasts.
In a current research revealed in The Accounting Evaluate, we developed a technique to determine comparable companies for benchmarking and analyzed its implications for analyst outcomes and valuation with multiples. On this submit, we’ll spotlight the salient particulars, a few of which can shock you.
There are alternative ways to outline peer companies, equivalent to {industry} membership, inventory index membership, closeness in market capitalization, and similarity in worth drivers (e.g., P/E ratio, return-on-invested capital, and progress).
As a substitute for conventional classifications, researchers have examined new methods to determine peer companies, equivalent to traders’ co-search, depth of companies’ filings with the SEC’s EDGAR, and inventory info on Yahoo! Finance.
These extensively utilized strategies fail to straight tackle a vital facet of agency benchmarking: the supply of key monetary assertion info for peer companies. When a number of monetary assertion line gadgets are lacking for a peer agency, analysts wrestle to derive significant inferences from the comparative to the focal agency’s monetary statements.
Our monetary assertion benchmarking (FSB) measure goals to fill this hole. The info and code are freely obtainable on our web site.
Capturing the Diploma of Overlap Between Monetary Assertion Gadgets
Constructed on the Jaccard similarity coefficient, pairwise FSB captures the diploma of overlap in monetary assertion gadgets reported by two companies, with scores starting from 0 (no overlap) to 1 (full overlap). The upper the FSB rating, the higher the benchmarking info obtainable to exterior customers.
As an example, if the focal agency has reported 270 gadgets, 200 of which overlap with 220 gadgets reported by the peer agency, the FSB rating is 0.69 (200 / (270 + 220 – 200). To place this into context, the common rating for analyst-chosen friends in our pattern is 0.68.
Assuming that FSB is a useful metric in capturing the similarity of two companies’ underlying economics and accounting decisions, we count on it to be positively correlated with analysts’ decisions of peer companies.
Our pattern of analyst-chosen friends comes from a Evaluate of Accounting Research article, “Analysts’ selection of peer corporations.” By manually screening greater than 2,500 sell-side fairness analysts’ studies, the authors extracted information on comparable peer companies chosen for the focal agency in every report.
In our research, for every analyst-chosen peer agency, we chosen an identical agency in the identical {industry} that was not chosen however which had the same measurement and valuation a number of. The outcomes present that analysts have a tendency to decide on peer companies which might be extra corresponding to a focal agency from a monetary assertion benchmarking perspective.
When FSB is larger by one-standard-deviation, the chance of being chosen as a peer agency by an analyst will increase by 13%.
Greater FSBs Enhance Accuracy of Earnings Forecasts
Does selecting friends with larger FSBs have constructive implications for analyst efficiency? We discover that when the common FSB of the set of analyst-chosen peer companies is one-standard-deviation larger, the accuracy of analysts’ earnings forecasts will increase by about 23%.
When choosing peer companies, search for companies which have extra related monetary statements to the focal agency, even when meaning looking out exterior the focal agency’s essential {industry}. In reality, solely 40% of the analyst-chosen peer companies function in the identical product market because the focal agency.
Which corporations do you suppose can be good peer companies to decide on when analyzing Colgate-Palmolive? Morningstar lists Procter & Gamble and Unilever as prime friends for the corporate. Regardless of being listed on a US inventory change, Unilever has a modest 0.69 FSB rating with Colgate-Palmolive.
That is seemingly as a result of the corporate makes use of Worldwide Monetary Reporting Requirements to organize its monetary statements. Utilizing totally different accounting requirements reduces comparability resulting from variations within the recognition and presentation guidelines. In distinction, P&G and Colgate-Palmolive have the next FSB rating of 0.77, suggesting a higher comparability than Unilever and Colgate-Palmolive.
In distinction to Morningstar’s method, Google Finance creates a listing of peer companies based mostly on traders’ co-search exercise. Notably, among the many peer companies Google Finance lists for Colgate-Palmolive is Coca-Cola. Though this remark could appear unintuitive at first blush, our methodology means that, from a monetary assertion benchmarking perspective, Coca-Cola can be a wonderful match on this case as a result of its FSB rating with Colgate-Palmolive is effectively above the common at 0.82. This will likely clarify why traders extensively co-search the monetary info of the 2 corporations.
Validation and Testing
After validating and testing the pairwise FSB metric, we aggregated information throughout all {industry} friends of the focal agency to grasp how straightforward it’s to benchmark a agency’s monetary statements general. This course of yielded a big panel of firm-level FSB information. Additionally, to counterpoint our methodology, we decomposed FSB on the monetary assertion stage, producing separate FSB scores for the revenue assertion, stability sheet, and assertion of money flows.
Whereas analysts’ consensus earnings and web debt forecasts are extra correct when firm-level FSB is excessive (i.e., it’s straightforward to benchmark and perceive a agency’s monetary statements), revenue assertion and stability sheet benchmarking play totally different roles in these outcomes.
We discover that the Earnings assertion FSB rating predicts the accuracy of earnings forecasts however not web debt forecasts. In distinction, stability sheet FSB rating predicts the accuracy of web debt forecasts, however not earnings forecasts. In financial phrases, a one-standard-deviation improve in revenue assertion (stability sheet) FSB is related to a 17.3% (12.1%) extra correct consensus earnings (web debt) forecasts. These findings spotlight that benchmarking advantages depend upon the context of the evaluation.
For the Investor: Trade, Trade-Dimension, or FSB Friends
Past constructive analyst outcomes, a key query for traders is whether or not selecting peer companies based mostly on FSB improves valuation with comparables. To this finish, we in contrast the predictive potential of the valuation multiples fashioned utilizing FSB-based friends to these of the fashions using conventional strategies for peer agency choice, equivalent to industry- and size-based friends. Particularly, we regressed the long run enterprise value-to-sales ratio (EVS) of the focal agency on the common EVS calculated for 3 units of friends: (1) {industry} friends, (2) industry-size friends, and (3) FSB friends.
When predicting one-year, two-year, and three-year-ahead EVS, the fashions utilizing the common valuation a number of of FSB-based friends constantly outperform these using solely industry- and industry-size friends. As an example, the R-squared of the mannequin predicting one-year-ahead EVS will increase from 24.8% to 31.8% when the common EVS of the 4 highest FSB friends is included within the mannequin.
In conclusion, we be aware that FSB is a straightforward, easy measure summarizing the overlap in peer companies’ underlying economics and accounting decisions, that are the important thing elements that form monetary statements. FSB is obtainable on the pairwise and agency ranges, permitting exterior customers to seek out appropriate peer companies for varied functions, together with relative efficiency, compensation, and valuation benchmarking.
