How do sell-side analysts actually set price targets for the stocks they follow? I know from my own experience teaching investments classes that target prices are theoretically set as a function of the present value of future expected cashflows.  But do the analysts adhere to the logic of traditional valuation or do they utilize other methods as short-cuts? Has anyone ever really checked?  I believe you will be surprised. I was.

Expected EPS ×Trailing P/E

  • Itzhak Ben-David† and Alex Chinco
  • Working Paper
  • A version of this paper can be found here
  • Want to read our summaries of academic finance papers? Check out our Academic Research Insight category.

What are the research questions?

  1. Do sell-side analysts use traditional present value methods to forecast stock prices?
  2. Is the use of trailing P/E ratios to set target prices widespread?
  3. What are the implications for the traditional approaches that are taught in academic finance courses (remember the Gordon model from your introductory investments course?)  and publicized as “best-in-class” for conventional security pricing models?

What are the Academic Insights?

  1. NO.  The dominant method to set price targets is to multiply short-term earnings forecasts by a trailing P/E ratio.  The authors analyzed 513 stock reports and determined that 94.5% of the analysts surveyed used one or another type of “multiples” approach, typically based on P/E ratios.
  2. YES. Ninety-one percent of the variability (R-sq) in price targets was explained by trailing P/E ratios rather than present value methods. The visuals included in Figure 3 demonstrate the relationship between price targets, earnings forecasts and backward-looking P/E ratios. For Home Depot (HD) and a single analyst, the price target is set by multiplying the analyst’s earnings forecast by 21x, which is a trailing P/E ratio. There is not a discounted cashflow for HD in sight.
  3. It seems that we have some explaining to do. Reconciling the “multiples” model with traditional present value approaches is not unheard of in courses concerned with valuation.  The two are in fact related on a fundamental level and could be equivalent under a number of strict conditions. The core principle of pricing equity securities assumes that market prices simply reflect the present value of expected cashflows. Central to that formulation is the use of discount rates aka ‘required rates of return’ that work to balance the payoff with the riskiness of the payoff. Backward-looking multiples like the P/E ratio are devoid of any notion of a tradeoff between the expected risk and expected payoff on an equity investment. Placed in the context of a target price provided by the sell-side to investors, the implications of this type of discontinuity are significant. Case in point: the recent and very painful sell-off associated with Nvidia, where the price reaction clearly failed to reflect how cashflows are likely to behave.

Why does it matter?

This study analyzes the methods analysts use to forecast prices and whether they adhere to present-value logic or rely on other techniques, such as trailing price-to-earnings (P/E) ratios. Given that analysts set security price targets by utilizing backward-looking P/E multiples instead of discounting future earnings or cashflows, it may be that investor reaction to negative and positive earnings surprises can be modulated. For instance, the authors argue investors should place more emphasis on multiples and short-term forecasts of earning and less on expected long term growth of earning and required rates of return. At the very least, investors should be better equipped to anticipate market reactions to earnings announcements, surprises and changes in analyst forecasts. The implication for academics is significant. If the academic research fails to recognize and account for the differential between financial market behavior in theory and the real world, then the ability to model markets will become more difficult.

The most important chart in the paper

The results are hypothetical results and are NOT an indicator of future results and do NOT represent returns that any investor actually attained.  Indexes are unmanaged and do not reflect management or trading fees, and one cannot invest directly in an index.

Abstract

All of asset-pricing theory currently stems from one key assumption: price equals expected discounted payoff. And much of what we think we know about discount rates comes from studying a particular kind of expected payoff: the earnings forecasts in analyst reports. Researchers typically access these numbers through an easy-to-use database and never read the underlying documents. This is unfortunate because the text of each report contains an explicit description of how the analyst priced their own earnings forecast. We study a sample of 513 reports and find that most analysts use a trailing P/E (price-to-earnings) ratio not a discount rate. Instead of computing the present value of a company’s future earnings, they ask: “How would a firm with similar earnings have been priced last year?” Even if other investors do things differently, it does not make sense to put discount rates at the center of every asset-pricing model if market participants do not always use one. There are other options. Trailing
twelve-month P/E ratios account for 91% of the variation in analysts’ price targets. We construct a new kind of asset-pricing model around this fact and show that it explains the market response to earnings surprises.

About the Author: Tommi Johnsen, PhD

Tommi Johnsen, PhD
Tommi Johnsen is the former Director of the Reiman School of Finance and an Emeritus Professor at the Daniels College of Business at the University of Denver. She has worked extensively as a research consultant and investment advisor for institutional investors and wealth managers in quantitative methods and portfolio construction. She taught at the graduate and undergraduate levels and published research in several areas including: capital markets, portfolio management and performance analysis, financial applications of econometrics and the analysis of equity securities. In 2019, Dr. Johnsen published “Smarter Investing” with Palgrave/Macmillan, a top 10 in business book sales for the publisher.  She received her Ph.D. from the University of Colorado at Boulder, with a major field of study in Investments and a minor in Econometrics.  Currently, Dr. Johnsen is a consultant to wealthy families/individuals, asset managers, and wealth managers.

Important Disclosures

For informational and educational purposes only and should not be construed as specific investment, accounting, legal, or tax advice. Certain information is deemed to be reliable, but its accuracy and completeness cannot be guaranteed. Third party information may become outdated or otherwise superseded without notice.  Neither the Securities and Exchange Commission (SEC) nor any other federal or state agency has approved, determined the accuracy, or confirmed the adequacy of this article.

The views and opinions expressed herein are those of the author and do not necessarily reflect the views of Alpha Architect, its affiliates or its employees. Our full disclosures are available here. Definitions of common statistics used in our analysis are available here (towards the bottom).

Join thousands of other readers and subscribe to our blog.