Thursday, November 28, 2024

For the analyst: Peer benchmarking methods to enhance earnings forecasts

Finding suitable colleagues for financial evaluation is a difficult task that requires careful consideration of the corporate’s underlying economic conditions, accounting decisions and financial reporting presentation. However, without comparable financial reporting information, peer benchmarking can provide less meaningful and even misleading insights that negatively impact earnings forecasts.

In one Recent study published in , we’ve developed a strategy for identifying comparable corporations for benchmarking and analyzing their impact on analyst results and valuation using multiples. In this post we are going to highlight the important thing details, a few of which can surprise you.

There are other ways to define peer firms, similar to: Industry affiliation, Membership within the stock index, Proximity to market capitalizationAnd Similarity of value drivers (e.g. P/E ratio, return on capital and growth).

As a substitute for traditional classifications, researchers have tested recent methods for identifying peer firms, similar to: B. the joint search of investors, the intensity of the SEC EDGAR filingsand storage information Yahoo! Finance.

These widely used methods do circuitously address an important aspect of corporate benchmarking: the provision of key financial reporting information for peer corporations. If several individual items are missing from the annual financial statements for a comparable company, it’s difficult for analysts to derive meaningful conclusions from the comparison with the annual financial statements of the focal company.

Our Financial Statement Benchmarking (FSB) goals to shut this gap. The data and code are freely available on our site website.

Capture the extent of overlap between balance sheet items

Based on the Jaccard similarity coefficient, the pairwise FSB captures the degree of overlap in balance sheet items reported by two corporations. Values ​​range from 0 (no overlap) to 1 (complete overlap). The higher the FSB rating, the more benchmarking information is obtainable to external users.

For example, if the focal company reported 270 items, 200 of which overlap with 220 items reported by the comparison company, the FSB rating is 0.69 (200 / (270 + 220 – 200). To put this into context: the typical Score for analyst-selected peers in our sample is 0.68.

Assuming that the FSB is a useful measure for capturing the similarity of two corporations’ underlying economic and accounting decisions, we expect it to be positively correlated with analysts’ decisions for peer corporations.

Our number of analyst-selected peers comes from an article: “Selection of peer companies by analysts.” By manually screening greater than 2,500 reports from sell-side equity analysts, the authors extracted data on comparable peer corporations that were chosen as focal corporations in each report.

In our study, for every analyst-selected peer company, we chosen an identical company in the identical industry that was not chosen but had an analogous size and valuation multiple. The results show that analysts are inclined to select peer corporations which might be more comparable to a focal company from a financial reporting benchmarking perspective.

If FSB is one standard deviation higher, the probability of being chosen as a peer company by an analyst increases by 13%.

Higher FSBs increase the accuracy of earnings forecasts

Does selecting competitors with higher FSBs have a positive impact on analyst performance? We find that the accuracy of analysts’ earnings forecasts increases by roughly 23% when the typical FSB of the set of analyst-selected peer firms is one standard deviation higher.

When choosing comparison corporations, search for corporations whose financial reports are more much like those of the focal company, even when this implies you could have to look outside the focal company’s primary industry. In fact, only 40% of the peer corporations chosen by analysts operate in the identical product market because the focal company.

Which corporations do you’re thinking that can be good comparators to investigate Colgate-Palmolive? Morningstar lists Procter & Gamble and Unilever as the corporate’s top competitors. Despite being listed on a US stock exchange, Unilever has a modest FSB rating of 0.69 on Colgate-Palmolive.

This is probably going because the corporate uses International Financial Reporting Standards when preparing its financial statements. The use of various accounting standards reduces comparability because of different recognition and presentation rules. In contrast, P&G and Colgate-Palmolive have the next FSB rating of 0.77, suggesting higher comparability than Unilever and Colgate-Palmolive.

Unlike Morningstar’s approach, Google Finance creates a listing of peer corporations based on investors’ collective search activity. Coca-Cola is certainly one of the comparable corporations that Google Finance lists for Colgate-Palmolive. Although this statement could seem counterintuitive at first glance, our methodology suggests that Coca-Cola can be an amazing fit from a financial reporting benchmarking perspective on this case, as its FSB rating is well above Colgate-Palmolive at 0.82 is the typical. This could explain why investors intensively search the 2 corporations’ financial information together.

Validation and testing

After validating and testing the pairwise FSB metric, we aggregated data from the entire focal company’s industry peers to know how easy it’s to check an organization’s financial statements overall. This process yielded a big set of company-level FSB data. To enrich our methodology, we also decomposed FSB on the financial plan level and created separate FSB scores for the income statement, balance sheet, and money flow statement.

Tile with current issue of the Financial Analysts Journal

While analyst consensus forecasts for earnings and net debt are more accurate when the company-level FSB is high (i.e., it is simple to check and understand an organization’s financial statements), the income statement and balance sheet comparisons play into these results a distinct role.

We find that the FSB income statement rating predicts the accuracy of earnings forecasts, but not net debt forecasts. In contrast, the balance sheet FSB rating predicts the accuracy of net debt forecasts, but not earnings forecasts. In economic terms, a one standard deviation increase within the FSB’s income statement (balance sheet) is related to a 17.3% (12.1%) more accurate consensus profit forecast (net debt). These results illustrate that the advantages of benchmarking rely on the context of the evaluation.

For the investor: industry, industry size or FSB peers

Beyond positive analyst results, a vital query for investors is whether or not choosing peer corporations based on the FSB improves valuation with peer corporations. To this end, we compared the predictive power of valuation multiples formed using FSB-based peers with those of models using traditional peer company selection methods, similar to: B. Industry and size based peers. Specifically, we regressed the longer term enterprise value to sales (EVS) ratio of the studied company on the typical EVS calculated for 3 groups of peers: (1) industry peers, (2) industry peers, and (3) FSB peers .

When predicting one-year, two-year, and three-year EVS, models that use the typical valuation multiple of FSB-based peers consistently outperform models that use only industry- and industry-sized peers. For example, the R-squared of the model predicting one-year EVS increases from 24.8% to 31.8% when the typical EVS of the highest 4 FSB peers is included within the model.

In summary, we discover that FSB is an easy, straightforward measure that summarizes the overlap within the underlying economic and accounting decisions of peer corporations, that are the important thing aspects in shaping financial reports. Available on the pair and company level, FSB allows external users to look for appropriate comparable corporations for various purposes, including relative performance, compensation and valuation benchmarking.

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