3. Valuation Ratios

The P/E was actually not always the go-to option. In the 19th and into the 20th centuries, dividend yield (Section 3.4) was the preferred metric. “In the US, bond issues during the 1800s and early 1900s outweighed stock issues 3 to 1. The stock market consisted largely of railway stocks, with utilities and then industrials only becoming more important by 1900. In these circumstances it is hardly surprising that dividend yield was the favored method of deciding whether a stock was cheap or expensive because dividend yield could be directly compared to the yield on a bond.” The P/E came into fashion with the stock market boom of the 1920s, as growth and capital gains it began to supplement and then displace dividends as the predominant component of shareholder returns. See Nilesh Soman, “Retracing the History of the Price to Earnings Ratio,” January 7, 2014. Online at www.moneycontrol.com/news/business/personal-finance/retracinghistoryprice-to-earnings-ratio--1185979.html

This is true for almost all of the forms of the Multiple discussed in this chapter. Price is always the current price, not a forecast. Deviations from this principle are rare. An exception is the Cash-Adjusted P/E (Section 3.11).

GAAP of course refers to Generally Accepted Accounting Principles, which is the American accounting standard for the preparation of financial statements.

There are many nuances attached to the figure for the number of shares to be used in calculating EPS. We will review some of these in Chapter 6.

As of February 27, 2009, the S&P US Preferred Stock Index had 72 constituents (or about 14% of the S&P 500). The total market value of the Preferred was approx. $100 billion – about 1% of the value of the total equities market (Standard & Poor’s, Preferred Stock Primer, March 25, 2009). Following the financial crisis, Preferred Shares fell further out of favor. By 2018, this has declined to less than 1% (Janney Investment Group, Investable Themes: Preferred Securities, September 2018) – not quite negligible, but nearly so.

Tech companies that grant a lot of employee options might be expected to show a significant effect related to dilution calculations that would reflect unexercised options. But perhaps not. For example, the difference between Facebook’s “basic earnings per share” and “diluted earnings per share” is less than 1% (2018), despite the liberal use of employee options. Netflix also shows a less than 1% difference (2018).

There may be minor assumptions or estimates incorporated in the calculation of net earnings, such as reserves to account for bad debt (customers’ failure to pay), possible warranty expenses, or product returns.

“For valuation purposes, analyst consensus is the preferred method of determining future EPS. Analyst consensus represents the average (or ‘consensus’) of all the equity research analysts that cover a stock and submit their estimates to IBES on Bloomberg or another data set.” (a typical definition, from the Corporate Finance Institute, available at https://corporatefinanceinstitute.com/about-cfi/).

James Mackintosh, “Hope Springs but Profit Pitfalls Lurk,” The Wall Street Journal, January 6, 2017. Reproduced by permission from The Wall Street Journal.

Mark T. Bradshaw, Michael S. Drake, James N. Myers, and Linda A. Myers, “A re-examination of analysts’ superiority over time-series forecasts of annual earnings,” Review of Accounting Studies, Vol. 17 (2012), pp. 944–968. However, as with so many “findings” in the academic literature on the financial markets, other studies point in the opposite direction. Liu et al., in 2002, found that “forward earnings perform the best, and performance improves if the forecast horizon lengthens (1-year to 2-year to 3-year out EPS forecasts).” (Jing Liu, Doron Nissim, and Jacob Thomas, “Equity Valuation Using Multiples,” Journal of Accounting Research, Vol. 40, No. 1 (March 2002), pp. 135–172).

Jing Liu, Doron Nissim, and Jacob Thomas, “Equity Valuation Using Multiples,” Journal of Accounting Research, Vol. 40, No. 1 (March 2002), pp. 135–172. See also John Authers, “Number Crunchers Are Socially Desirable,” Financial Times, July 11, 2017. The FT piece cites also Jing Liu, Doron Nissim, and Jacob Thomas, “Is Cash Flow King in Valuations?” Financial Analysts Journal, Vol. 63, No. 2 (March/April 2007) pp. 56–68; but with respect to the comment on the superiority of Forward P/E to Trailing P/E, this piece appears to be based largely on the earlier 2002 article by Liu et al., cited first.

According to a Bank of America/Merrill Lynch study, the Forward PE is preferred by a more than 2 to 1 margin over the Trailing P/E among individual investors. Another recent study gives a 6 to 1 advantage to Forward P/E vs. Trailing P/E in use by professionals (Jerald Pinto, Thomas Robinson, and John Stowe, “Equity Valuation: A Survey of Professional Practice,” CFA Institute, September 7, 2015).

“Forward p/e ratios…are above their abysmal levels from the worst of the post-Lehman crisis, but beyond that they are as cheap as they have been in decades… Forecast profits…look rosy… Optimistic forecasts might make forward multiples artificially low.” (John Authers, “Optimists Say This is the Time to Buy Equities,” Financial Times, July 10, 2011). We may note that the aftermath of the post-Lehman crisis (late 2008 or early 2009) would have been the very best time to enter the market in decades, and even investors entering in July 2011 would have enjoyed a more-the-100% gain since that time. So the “abnormally low” Forward P/E does seem to have predicted well the boom in future returns.

See Chapter 4, Section 4.3.2.

It is used in 90% or more of professional analysts’ reports. See Footnote 1 in the Introduction. It is also reported that 80% of individual investors make use of the P/E multiple (Maggie Fitzgerald, “Everyone Still Relies on Stock’s P/E Ratio…” CNBC, June 2019, citing a BofA Merrill Lynch study).

“Operating Income” appears as a line in a GAAP-approved income statement. Some analysts use other definitions of “earnings” which are non-GAAP (although still permitted with the appropriate caveats and reconciliations). There is confusion over closely related terms, such as Earnings Before Interest and Taxes (EBIT), a standard though non-GAAP figure. Some have argued that Operating Income (GAAP) should be differentiated from Operating Earnings (non-GAAP), but this seems to me to be a misnomer. I believe that Operating Income, Operating Profit, and Operating Earnings are used synonymously for the GAAP category describing the residual after all operating expenses are subtracted from revenues and before interest, taxes, investment income, gains or losses from disposal of assets, and various “extraordinary,” “unusual,” or “irregular” items.

The terminology has been changing. The Financial Accounting Standards Board (FASB) has recently eliminated the term “extraordinary items” from the accounting vocabulary [FASB Accounting Standards Update No. 2015-01, “Income Statement – Extraordinary and Unusual Items (Subtopic 225-20) – Simplifying Income Statement Presentation by Eliminating the Concept of Extraordinary Items,” January 2015].

For example, in 2017, Valero – the largest American oil refining company – suffered a shutdown and loss of business due to the impact of Hurricane Harvey on its Gulf Coast refining operations. In its financial statements, it chose to separate some of those costs from Operating Income, as “other expenses.” These one-time charges were nevertheless subtracted to arrive at Net Earnings. This would have temporarily depressed Net Earnings and raised the Trailing P/E. The Price-to-Operating Earnings metric might have avoided this “spurious” volatility. Such charges include facility shutdowns – when Ford closes a factory permanently because it is ceasing production of a particular model, it has to write off the remaining value of that factory which it had been carrying on its balance sheet. If it exits a major line of business entirely, selling it at a book value loss or ceasing operations altogether, it may incur such a charge. Other examples might include damage suffered from unexpected natural or manmade disasters – floods, fires, strikes, wars – and perhaps large adverse financial judgments or settlements associated with lawsuits brought against the company. The general idea is that these events are “irregular” or “unusual” or “non-recurring” – and therefore should be set aside when evaluating the current ongoing business.

(The rules governing the determination of which expenses can be considered, or must be considered, as either non-recurring or extraordinary are elaborate. It is not within our scope here to parse the changing terminology of “extraordinary,” “unusual,” “irregular,” “non-recurring,” etc. applied to expenses (and gains) or to track which ones allow or require particular accounting treatments that may rule them either in or out of “Operating Income” calculations.)

Though not always – sometimes there is an extraordinary gain, as when an asset is sold for a much higher price than its book value.

Gretchen Morgenson, “What? They Never Heard of WorldCom?” The New York Times, March 21, 2005; and Mark Gongloff, “Investors, It Pays to Mind the GAAP Gaps,” The Wall Street Journal, September 18, 2009.

Mark Gongloff, “Investors, It Pays to Mind the GAAP Gaps,” The Wall Street Journal, September 18, 2009. Reproduced by permission from The Wall Street Journal.

A personal comment here: From my own experience in the tech industry, I am in general agreement that accounting for incentive stock options granted by tech companies (and others) to their employees as though it were the same as cash compensation is seriously misleading as to the nature of the “expense.”

Miriam Gottfried, “Blowing the Froth off of Big Tech Earnings,” The Wall Street Journal, May 20, 2015. Reproduced by permission from The Wall Street Journal.

Dirk Black, Ervin Black, Theodore Christensen, and William Heninger, “Has the Regulation of Pro Forma Reporting in the US Changed Investors’ Perceptions of Pro Forma Earnings Disclosures?” Journal of Business Finance & Accounting, Vol. 39, No. 7 (September/October 2012), pp. 876–904. Also Susan Albring, Maria Cabán-Garcia, and Jacqueline Reck, “The Value Relevance of a non-GAAP Performance Metric to the Capital Markets,” Review of Accounting and Finance, Vol. 9, No. 3 (2010) pp. 264–284.

Justin Lahart, “S&P 500 Earnings: Far Worse Than Advertised,” The Wall Street Journal, February 24, 2016. Reproduced by permission from The Wall Street Journal.

Dahlia Robinson, Mark Dawkins, Babajide Wintoki, and Michael Dugan, “Has S&P’s Core Earnings Lived Up to its Expectations? Assessing the Usefulness of Core Earnings Relative to GAAP Earnings,” University of Georgia Working Paper, September 5, 2008: http://media.terry.uga.edu/documents/accounting/dawkinspaper.pdf

Matthew M. Wieland, Mark C. Dawkins, and Michael T. Dugan, “The Value Relevance of S&P’s Core Earnings vs. GAAP Earnings,” Management Accounting Quarterly, Vol. 15, No. 4 (Summer 2014), pp. 18–26. See also Matthew M. Wieland, Mark C. Dawkins, and Michael T. Dugan, “The Differential Value Relevance of S&P’s Core Earnings Versus GAAP Earnings: The Role of Stock Option Expense,” Journal of Business Finance & Accounting, Vol. 40, No. 1/2 (January/February 2013), pp. 55–81.

Spencer Jakab, “Idea of a Dividend Bubble Has Some Pop,” The Wall Street Journal, June 8, 2012; also “Veni Divi Vici,” Financial Times, March 30, 2010.

Scott Cendrowski, “Dividends for the Long Run,” Fortune, November 23, 2009: “Since 1972, companies that increase or begin paying dividends have returned 9.5% a year, soundly beating the 6.8% return of the S&P 500.”

For example, the family of fundamentally weighted index funds offered by the firm Wisdom Tree (which emphasize dividends) outperformed the cap-weighted market average during an earlier phase of the recent bull market (although in other periods they have underperformed) (“Get Your Coupon,” Financial Times, January 14, 2012).

For example, the well-known “Dogs of the Dow” formula is based on Dividend Yield. The strategy involves buying the ten Dow Jones Industrial Average component companies with the highest dividend yields, using a high Dividend Yield to screen for an underpriced stock. Elizabeth O’Brien, “History Says These Dogs are Usually Barking Up the Right Tree,” The Wall Street Journal, August 13, 2012.

Chart source: Crestmont Research.

The lower credit rating does reflect “default risk” officials, according to S&P. But given AT&T’s history and business model, it is hard to credit this assessment. AT&T could easily restructure its balance sheet, which might reduce returns to shareholders, but it seems unlikely that it is at any true risk of default which it could not take measures to mitigate.

In some industries, there is the question of whether to book revenue when products are sold to an intermediary wholesaler or distributor or to wait until the product is “sold through” to the end user. (GAAP allows either approach.) For example, in 2006 it was reported that the semiconductor manufacturer Texas Instruments used “sell-in” revenue recognition, where sales were recorded when product was shipped to the distributor (not the end customer). Intel, a direct competitor, used “sell-through” revenue recognition where sales were not recorded until the intermediary distributors sold the Intel product to the final customers. A number of the examples of companies switching from one form of revenue recognition to the other are cited, which obviously means that P/S (and perhaps other multiples) is not readily comparable from before and after the switch (Herb Greenberg, “A Shift to ‘Sell-In’ Accounting Could Be a Clue to Brewing Trouble,” The Wall Street Journal, June 18, 2006).

Martin Peers, “Investors Should Focus on Apple’s Core,” The Wall Street Journal, September 24, 2009. Also Michael Rapoport, Yukare Iwatani Kane, and Ben Worthen, “U.S. Accounting to Aid Tech Firms,” The Wall Street Journal, September 24, 2009.

“Some companies expect the new rules to accelerate revenue, while others say the timing of when they can record revenue as earned will be delayed, even though their underlying business remains unchanged.” (Tatyana Shumsky, “Updated Accounting Rules Reverberate,” The Wall Street Journal, June 13, 2018).

Korea is rated in comparative studies near the bottom of the international scale in terms of Financial Reporting Quality – see Jennifer Martínez-Ferrero, “Consequences of financial reporting quality on corporate performance. Evidence at the international level,” Estudios de Economia, Vol. 41, No. 1 (June 2014), pp. 49–88. See also T. H. Choi and Jinhan Pae, “Business Ethics and Financial Reporting Quality: Evidence from Korea,” Journal of Business Ethics, Vol. 103 (2011), pp. 403–427. Acknowledging the deficits in Financial Reporting Quality in Korea and commenting on the adoption of IFRS, the international accounting standard, which in general allows even more flexibility than GAAP for the interpretation of “revenue recognition” principles, the authors state: “IFRS, which is a principles-based accounting system requiring the sound judgment and interpretation of accounting standards by managers, Financial Reporting Quality will depend on how Korean companies apply and interpret IFRS even more than before.”

Spencer Jakab, “Cleaning Up in Aisle Five with Kroger,” The Wall Street Journal, September 12, 2013. Of course, Whole Foods is now a subsidiary of Amazon.

Spencer Jakab, “Cleaning Up in Aisle Five with Kroger,” The Wall Street Journal, September 12, 2013. Reproduced by permission from The Wall Street Journal.

Spencer Jakab, “Amazon’s Growth Story Continues to Sell,” The Wall Street Journal, January 30, 2014. Reproduced by permission from The Wall Street Journal.

Amazon’s business model has evolved in very diverse fields, from retail to cloud computing to entertainment. This is a confounding factor in interpreting the P/S signal vs. a much more focused competitor such as Walmart.

EBITDA is a relatively recent and somewhat controversial innovation: “EBITDA came into vogue during the dot-com era of the 1990s. It was a period when many startup technology companies, telecoms, and other fragile startup companies could not generate a profit and needed an alternative metric besides GAAP earnings to convey a positive picture to investors.” (Stanley Block, “Methods of Valuation: Myths vs. Reality,” The Journal of Investing (Winter 2010), pp. 7–14).

There may be additional adjustments for preferred stock, pension liabilities, etc. EV is not a standardized metric (it is non-GAAP); it is not always constructed in the same way.

By analogy with a simple real estate transaction, EV would be equivalent conceptually to the purchase price on a leveraged property – buying a house and paying the seller his equity claim plus paying off the seller’s mortgage. (It has always puzzled me somewhat why if the numerator includes the value of the company’s debt, the denominator (EBITDA) excludes the payments to service that debt. The use of EV/EBITDA has become fairly common, but it seems in this and in other respects to be rather unexamined, another of the “received ideas” that have proliferated in the field of Finance.)

The cash cow gives her milk, but some of the proceeds from the sale of that milk today have to be spent on her feed and care, so that she will give more milk tomorrow.

There are various labels used, and differing definitions, for this sort of metric, e.g., “Free Cash Flow Excluding Certain Items” (Pepsico, 2017), “Net cash provided by operating activities reduced by capital expenditures” (Kellogg, 2017), “Management Operating Cash Flow” (many companies).

There is no standard formula. Companies often develop idiosyncratic metrics that they believe in good faith will better represent certain aspects of their performance. For example, United Rentals – in the business of renting heavy machinery to its customers – uses “Adjusted EBITDA,” which they define as follows: “Adjusted EBITDA represents EBITDA plus the sum of the merger related costs, restructuring charge, stock compensation expense, net, and the impact of the fair value mark-up of acquired fleet.”

Pacer ETFs – www.paceretfs.com

The Sears scenario – Gretchen Morgenson, Michael Barbaro, and Geraldine Fabrikant, “Saving Sears Doesn’t Look Easy Anymore,” The New York Times, January 27, 2008.

Note that the study also indicates high frequency of use for Price/Book and Price/Sales, both of which have been shown to be rather ineffective in recent years. This may be a sign of “box checking” by the survey participants, rather than an indication of actual pragmatic value.

Pacer ETFs – www.paceretfs.com – The Pacer Perspective, January 2017.

Adapted from Pacer ETFs – www.paceretfs.com – The Pacer Perspective, January 2017.

Asset values only change when a major event requires a “write-down” (never a “write-up”) – which is almost always late in coming.

Stock symbols: consumer sector – PEP, K, CFB, GIS; automotive sector – F, GM, TM; semiconductors – INTC, NVDA, QCOM; and tech giants – MSFT, AAPL, GOOG, FB, AMZN. Admittedly a nonscientific sample, but perhaps enough diversity to expose the relationships of interest.

In their 1934 classic security analysis, Benjamin Graham and David Dodd argued for adopting long-term horizons, both forward and backward, generally in analyzing a company’s earning power. They suggested that seven to ten years of earnings (historical or projected) should be the assumed timescale for valuation purposes.

Lately, the regularity of the “business cycle” has come into question. “There are real indications that the economy is less beholden to traditional cycles than it used to be… Business cycles are themselves contained within longer ones, which economists call ‘financial cycles.’ …. Economists have long struggled to separate the two types of cycles.” (Jon Sindreu, “Recession Worry is Overblown for Now,” The Wall Street Journal, June 8, 2019).

Laurence Siegel, “CAPE Crusaders: The Shiller-Siegel Shootout at the Q Group Corral,” Advisor Perspectives, February 18, 2014. Available at www.advisorperspectives.com/articles/2014/02/18/cape-crusaders-the-shiller-siegel-shootout-at-the-q-group-corral

Laurence Siegel, “CAPE Crusaders: The Shiller-Siegel Shootout at the Q Group Corral,” Advisor Perspectives, February 18, 2014. Available at www.advisorperspectives.com/articles/2014/02/18/cape-crusaders-the-shiller-siegel-shootout-at-the-q-group-corral

Alexandra Scaggs, “Nobelist’s Valuation Measure Draws Questions,” The Wall Street Journal, November 22, 2013. Reproduced by permission from The Wall Street Journal.

Laurence Siegel, “CAPE Crusaders: The Shiller-Siegel Shootout at the Q Group Corral,” Advisor Perspectives, February 18, 2014. Available at www.advisorperspectives.com/articles/2014/02/18/cape-crusaders-the-shiller-siegel-shootout-at-the-q-group-corral

Ibid.

Joseph Davis, Roger Aliaga-Díaz, and Charles Thomas, “Forecasting Stock Returns: What Signals Matter, and What Do They Say Now?” Vanguard Research, October 2012. Interestingly (given how infrequently these studies confirm one another), Ang and Zhang found exactly the same R2 of 38% for Earnings Growth as an explanatory variable for PEttm for the period from 1953 to 2009 (Andrew Ang and Xiaoyan Zhang, “Price-Earnings Ratios: Growth and Discount Rates,” The Research Foundation of the CFA Institute (2011), pp. 130–142).

Joseph Davis, Roger Aliaga-Díaz, and Charles Thomas, “Forecasting Stock Returns: What Signals Matter, and What Do They Say Now?” Vanguard Research, October 2012. Reproduced by permission from Vanguard Research.

Joseph Davis, Roger Aliaga-Díaz, and Charles Thomas, “Forecasting Stock Returns: What Signals Matter, and What Do They Say Now?” Vanguard Research, October 2012. Reproduced by permission from Vanguard Research.

Joseph Davis, Roger Aliaga-Díaz, and Charles Thomas, “Forecasting Stock Returns: What Signals Matter, and What Do They Say Now?” Vanguard Research, October 2012. Reproduced by permission from Vanguard Research.

Laurence Siegel, “CAPMing the CAPE” available at https://larrysiegeldotorg.files.wordpress.com/2016/09/siegel_capming-the-cape_2016_09_08.pdf

“Beware the CAPE Crusaders,” Renaissance Investment Management, December 2015. Available at www.reninv.com/large-cap-growth/

Liam Pleven, “Stocks: Are They Too High?” The Wall Street Journal, May 16, 2015. Reproduced by permission from The Wall Street Journal.

“Beware the CAPE Crusaders,” Renaissance Investment Management, December 2015. Available at www.reninv.com/large-cap-growth/

As long ago as 1947, T. J. Koopmans argued against the practice of averaging in the analysis of economic data: “Smoothing is found to be wasteful of information and to complicate mathematical treatment, because it mixes up the effects of successive disturbances as well as blurs the time-shape of exogenous variables.” [from “Measurement without Theory,” The Review of Economic Statistics, Vol. 29, No. 3 (August 1947), pp. 161–172].

Robert Shiller, “Price-Earnings Ratios as Forecasters of Returns: The Stock Market Outlook in 1996,” Yale, The Cowles Foundation, July 1996. In fact, ten years later, the market had roughly doubled, and the S&P 500 index has never dropped below the level it was at when Shiller offered this advice. Much later, in 2013, with CAPE still signaling an overpriced market, Prof. Shiller again suggested that investors should reduce their holdings. The market was up over 50% in the following five years – reported in Alexandra Scaggs, “Nobelist’s Valuation Measure Draws Questions,” The Wall Street Journal, November 22, 2013.

Koopmans extends this critique by arguing that the economic system itself (and subsystems such as individual business enterprises) is in effect averaging functions, smoothing out the impact of “shocks” and spreading the effects over longer time periods: “One of the reasons why business cycle analysis is a difficult undertaking is that the economic system itself is such an effective smoothing agent of the random shocks to which it is exposed. The analytical problem is one of de-smoothing rather than smoothing” [from “Measurement without Theory,” The Review of Economic Statistics, Vol. 29, No. 3 (August 1947), pp. 161–172].

Anderson and Brooks, op. cit., writing in 2006, comment on the shallowness of research in this area: “We have been unable to find any previous academic research into whether knowledge of earnings of previous years will improve the ability of the P/E ratio to predict future returns on individual shares. Graham and Dodd recommended the use of average earnings over a period of at least five years and preferably over seven to ten years, to give the analyst a more reliable view of the true value of a company. Yet their conjecture does not seem to have been tested by any academic research.”

Justin Lahart, “This Key Metric Rings a False Alarm,” The Wall Street Journal, October 6, 2016; also Justin Lahart, “Taking Stock Market at Face Value,” The Wall Street Journal, February 18, 2012.

Justin Lahart, “Taking Stock Market at Face Value,” The Wall Street Journal, February 18, 2012. Reproduced by permission from The Wall Street Journal.

E. S. Browning, “Is the Market Overvalued?” The Wall Street Journal, April 9, 2011. Reproduced by permission from The Wall Street Journal.

They show an R2 of 11% for the 5-year CAPE and an R2 of 25% for the 5-year CATY.

http://thewallstreetchallenger.com/Index/valuation.html; see also www.advisorperspectives.com/commentaries/2016/03/23/the-stock-market-as-monetary-policy-junkie-quantifying-the-fed-s-impact-on-the-s-p-500

Laurence Siegel struggles with this issue: “in order to be useful, the CAPE needs to be reconciled with the Capital Asset Pricing Model (CAPM). Specifically, CAPE-based estimates of the expected equity return need to be adjusted for fluctuations in interest rates, that is, for changes in the expected return on bonds….” – this is a line of reasoning which leads far afield, and on unsteady ground, as CAPM is by now rather thoroughly discredited (see Appendix A). From Laurence Siegel, “CAPMing the CAPE” available at https://larrysiegeldotorg.files.wordpress.com/2016/09/siegel_capming-the-cape_2016_09_08.pdf

Bunn et al. summarize the questions relating to the design of the average used in CAPE as follows: “The original definition of the cyclically adjusted price-earnings ratio in Campbell and Shiller [1988] divides the most recent price information by the arithmetic average of the logarithm of (inflation-adjusted) one-year earnings observations, thereby calculating a geometric ten-year earnings average. Campbell and Shiller later use a simplified definition and arithmetically average (inflation-adjusted) 1-year earnings observations, which is the conceptual version that we rely on here. Shiller [later] calculates the 10-year earnings average from monthly (inflation-adjusted) earnings observations, where each number captures income information for the past twelve months. This calculation, however, down-weights the most recent (as well as, less importantly, the most distant) earnings information, which we would not like to incorporate.” In short, even defining the Average is not a simple matter. From Oliver Bunn, Arne Staal, Ji Zhuang, Anthony Lazanas, Cenk Ural, and Robert Shiller, Escaping from Overvalued Sectors: Sector Selection Based on the Cyclically Adjusted Price-Earnings (CAPE) Ratio,” The Journal of Portfolio Management (Fall 2014), pp. 16–32.

Ben Casselman, “Cautious Companies Stockpile Cash,” The Wall Street Journal, December 7, 2012; Jonathan Cheng, “Firms Weigh Options for those Piles of Cash,” The Wall Street Journal, August 23, 2010.

A discussion of the reasons for this cash accumulation lie outside the scope of this work. But it is likely that they have to do with the business model shift previously alluded to – namely, the shift to reliance on intangible assets with inherently higher ROA and higher levels of profitability, with a reduction in the need for Capex, the traditional consumer of excess corporate cash.

Martin Peers, “Cash Returns: Where Apple Lags Rivals,” The Wall Street Journal, May 23, 2011. Apple’s cash later reached $200 Bn. Despite instituting a generous dividend and large cash buybacks, Apple still has $88 Bn in cash on hand as of this writing.

The cash could not be brought back to the United States for dividends or buybacks or domestic investment without paying a large penalty of up to 35%. This law has recently changed. But while it was in effect, it may have reduced the market’s perceived value of the cash so sequestered. At the very least, this sort of cash needs to be discounted for the likely eventual tax payment.

It would appear that the academic community has reached the conclusion that PEG is a nonstarter. There is very little published research on the PEG; what is available is mostly in the form of short journalistic “investment advice” pieces in the popular press.

Joseph Davis, Roger Aliaga-Díaz, and Charles Thomas, “Forecasting Stock Returns: What Signals Matter, and What Do They Say Now?” Vanguard Research, October 2012. In fact, the earnings growth rates have less “explanatory” power with respect to future real stock returns than the meaningless dummy variable (annual rainfall) introduced by the Vanguard authors to benchmark the threshold of obvious non-causality.

Block analyzes the PEG ratios of the 30 Dow component companies (December 2009) and concludes “As a guideline on Wall Street, stocks that trade at a P/E greater than their five-year growth rate (a PEG greater than 1) should be subject to special observation to make sure they are not overvalued. This would have to qualify as a myth; 27 of the DJIA stocks traded over 1 [in fact all of the Dow components with positive earnings, for which a PEG could be calculated], and few of the firms would have been considered to be overvalued based on other metrics.” (Stanley Block, “Methods of Valuation: Myths vs Reality,” The Journal of Investing (Winter 2010), pp. 7–14).

James Mackintosh, “Emerging Markets Are No Bargains,” The Wall Street Journal, September 4, 2018. Reproduced by permission from The Wall Street Journal.

“S&P 500 Sector Weightings: Tech Nears 26%,” Seeking Alpha, May 10, 2018; available online at https://seekingalpha.com/article/4172093-s-and-p-500-sector-weightings-tech-nears-26-percent

A “cap-weighted” index is one that assigns weighting to the individual stocks in the index based on their relative market capitalizations. Most indexes today are cap-weighted.

For example, extrapolating the CAPE from the starting year of 1871 (as its proponents routinely do) and constructing “normal” benchmarks or historical averages drawn over that entire period clearly presupposes that the market and the economy are essentially invariant over that very long period.