In equity valuation, stock market multiples have become one of the most exploited valuation tools used by both professionals and scholars. Multiples are used in research reports and stock recommendations of both buy-side and sell-side analysts, in fairness opinions of investment bankers, or at road shows of companies pursuing an Initial Public Offerings (IPO). Even in cases where the value of a firm is primarily determined using discounted cash flow, multiples play the important role of providing a second opinion. Despite their extensive usage among practitioners, studies on how to guide multiplesâ application in assessing relative valuation performance on equity markets or in building profitable investment strategies based on accuracy performances of those valuation metrics are sporadic.
The relative valuation topic has been widely discussed in specialized literature and hands-on textbooks on business valuation proliferate. It is a classical valuation theme, but basically all published works tend to be very descriptive explaining every technical aspect of an appropriate and effective implementation of this valuation approach and in some cases also considers a fundamental analysis approach.
The majority of available literature has rarely been focused on empirical efforts that try to explain how relative valuation effectively works on equity markets and what we can learn observing this piece of evidence. One explanation could be that it is a well-rooted and widespread conviction that valuation is very much an art more than a science, based mainly on analystsâ own expertise and know-how, since market participants and equity analysts select comparable firms in the multiples approach more carefully and take into account situation-specific factors that cannot be adequately considered by researchers or scholars where large datasets are used.
On the contrary we are convinced that only an empirical effort testing the informational content of the valuation technique can improve our knowledge on this subject. For these reasons we have observed that there are still very few analyses focused on the empirical evidence of how this valuation approach relates to stock market price movements. We have found some papers, which are published in top-rated academic finance or accounting journals, which are largely unknown to a larger practitionersâ audience. But even in this case the existing researches are quite limited to stock market multiples accuracy performance. Our research goes further trying to show how and if different levels of multiple valuation errors (or accuracy performances) can predict future price movements and be exploited in stock selection strategies.
An added original feature of our research consists in the database employed. Most existing researches are based on evidence and a dataset confined to the pre- financial crisis era (the years before 2007 subprime mortgages collapse). Our dataset instead covers all the more recent years of the global financial crisis until 2014. Accordingly, it captures all the discontinuities that were evident during recent severe and long lasting financial crisis. In our research we have come to some original conclusions that exceed those already available from the existing literature. These findings can provide meaningful insights that practitioners can expect when adopting relative valuation in their everyday work.
A second relevant contribution of our original dataset is its focus on the very liquid and highly traded segment of the equity market, which enables us to dispense with all small and micro-stocks which are not directly comparable with the large cap ones and which are often of less interest for the institutional investors. In fact this segment of the capital markets is not representative, for liquidity reasons, of the typical equity investment opportunities which they face.
The aim of our research is as follows: analyzing multiplesâ accuracy in the stock markets and subsequently investigating whether a stock selection strategy based on multiplesâ accuracy can generate, over time, sustainable returns.
In the first part, following the path principally traced by the seminal work of Liu et al. (2002), and focusing only on the US equity market, we examine the effectiveness of commonly used multiples to explain the stock prices of a large sample of liquid US corporations between 1990 and 2014. We perform our analyses by focusing on both forward looking and historical multiples. The dataset created and the results found therein are subsequently employed in the later part of the work, when we move to a more market oriented point of view.
More specifically, the aim of the second part is twofold. First, we try to analyze whether a link exists between large valuation errors and future price performance; second, we try to understand if the multiples previously introduced can be used as investment criteria to build successful investment strategies.
The structure of this book is as follows. We start with the topic of relative valuation, analyzing its assumptions, strengths and weaknesses. A review of the specific empirical literature follows, highlighting the results of previous studies and areas where a deep analysis is still lacking. The fourth chapter represents the core part of the work. It starts with a description of the dataset and the methodology adopted to assess the performance and the accuracy of multiples, and then continues presenting and discussing the main results that can have an impact on our current knowledge of how the multiplesâ approach to equity valuation really works. The fifth chapter moves to a more market oriented point of view, and investigates whether a stock selection strategy based on multiplesâ accuracy performance can provide sustainable returns. Here we introduce the methodology adopted, present the different investment strategies implemented and finally comment upon the results. Finally, all the conclusions are summarized in the Chap. 6
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Concluding these introductory remarks, multiples approach on equity valuation is not a new topic and many excellent books exist. Basically they tend to be typically normative, âhow to doâ, books tackling directly the many details and complexities in applying, from a practitionerâs point of view, the relative valuation metrics. They can give us a lot of useful insights on how to solve each technical problem that arises in practical equity valuation tasks. Choosing to adopt a different perspective this book is focused on testing directly the relative valuation approach on equity markets. In doing so we want to assess the proximity to actual stock prices of valuations generated by multiplying a value driver, such as earnings, by the corresponding multiple, where the multiple is obtained from the ratio of stock price to that value driver for a group of comparable firms. The findings produced from such an empirical approach could help and give basic guidance on how relative valuation to equity analysis should be handled by the financial community. From this viewpoint our objective of bridging practice and research can move a step further.
For all these reasons we would like to stress that our work cannot answer all questions encompassing the main topic. We do not want to discuss the âbest practicesâ on equity valuation, or give practical hints on how employ efficiently the relative valuation approach; we seek to enhance the current knowledge on this topic by asking what kind of performance we should expect from this equity valuation tool given its widespread and popular practice by equity analysts, investment bankers and portfolio managers.
With this in mind, we hope that practitioners can widen their comprehensive understanding of the âmarket performancesâ of the tools they are handling in their everyday work.
Reference
Liu, J., Nissim, D., & Thomas, J. (2002). Equity valuation using multiples. Journal of Accounting Research, 40(1), 135â172.CrossRef