Reprinted with the permission of the American Association of Individual Investors

In the world of investing, no one piece of financial information tells all. But the price-earnings ratio comes close, containing a wealth of information about the market’s expectations for earnings growth.

However, if you look through any investment information resource commonly used by individual investors, you’ll find numerous definitions of the term.

Because the price-earnings ratio is a powerful summary of market opinion, financial analysts have frequently fiddled with it, producing what may appear to be endless variations on a theme.

Sorting out the different ways price-earnings ratios are quoted and how each different price-earnings ratio technique can be applied and interpreted should aid in your stock selection decisions.

What It Is

Price-earnings ratios (P/Es) are determined by taking a stock’s share price and dividing it by the firm’s earnings per share.

The ratio simply relates share price to earnings: the higher the price-earnings ratio, the more investors are paying for each dollar of earnings. If a stock has a price-earnings ratio of 15, it means that investors are paying $15 for each $1 of earnings.

Other terms for price-earnings ratios are: earnings multiple and price multiple.

The variations on price-earnings ratios occur with the decisions as to what share price to use (current, average, etc.) and which earnings figure to use (trailing 12 months, expected earnings, etc.).

How It Can Be Used

Price-earnings ratios are most commonly used to value future earnings.

In general, the higher the price-earnings ratio (relative to either its historical ratio, an industry ratio or the market ratio) the more the market is confident that earnings will grow in the future.

Low price-earnings ratios reflect expectations of lower growth and greater uncertainty.

All investors should be interested in finding firms that have a high, certain earnings growth rate and a relatively low price-earnings ratio. However, if the market agreed with your estimate of high growth, the price-earnings ratio would not be relatively low; rather, it would be either average, or perhaps even relatively high.

In order to form a judgment as to whether earnings are overvalued, undervalued or fairly valued using P/Es, you must judge whether you agree with the market’s opinion regarding the firm’s growth prospects.

How It Can Be Misused

A simple price-earnings ratio does not convey on its own all the information you need. Instead, it needs to be judged relative to other P/Es—by comparing a firm’s current price-earnings ratio, for instance, to its historical P/E, the industry average P/E or the market P/E.

Since earnings are in the denominator of the calculation, price-earnings ratios are not useful if the firm is not generating earnings (you cannot divide by 0), or if it has negative earnings (the resulting negative multiple is meaningless).

One-time events may also push price-earnings ratios up or down. Special charges or the sale of assets may lead to reported earnings that are below or above their normal levels. As long as the market interprets the earnings deviation as being only a temporary phenomenon, the abnormal P/E will be discounted by the market.

In addition, reported earnings themselves are subject to many assumptions and judgments, so if you are using price-earnings ratios, you must make sure that you understand the quality of the underlying earnings number.

P/E Variations

There are an endless variety of price-earnings ratio calculations. Here are the most common, along with how they can be applied and interpreted.

P/E Trailing Earnings

P/E trailing earnings is calculated using the most recent 12 months of reported earnings. This would give the most current actual earnings figure, but since earnings are reported quarterly, the trailing earnings could be over three months old.

P/E Current Earnings

P/E current earnings, used primarily by Value Line, steps into the future while straddling the past. The earnings used in the denominator are the most recent two quarters of earnings plus the estimated earnings per share for the next two quarters.

A common stock’s price today is based on expectations of future performance, a forward-looking valuation. Relating price to estimated earnings measures value today relative to expectations, and can serve as a guide as to whether a stock is relatively over- or undervalued.

P/E Forward (or Estimated) Earnings

P/E forward earnings uses estimates of annual earnings for the fiscal year in the denominator. An analyst’s forecast or a consensus of analysts is used.

At the beginning of the year, a price-earnings ratio using estimated earnings is completely forward looking, but as the year-end nears, more of the estimate is based on actual earnings and less is a forecast. Earnings estimates for the year are revised as new information is released and quarterly earnings become available.

P/E Average Price

P/E average price divides the average market price of the common stock for the fiscal year by the earnings per share for the fiscal year.

This approach attempts to smooth out the price-earnings ratio by reducing the day-to-day variation in ratios caused by stock price movements that may have been the result of general volatility in the stock market.

P/E Median

P/E median is the mid-value of a series of annual price-earnings ratios, ranked in ascending or descending order. The median is more useful than the average because the median, unlike the average, is not distorted by extreme values. The median of historical price-earnings ratios is valuable for gauging the current price-earnings ratio versus some historical norm.

P/E Normalized

P/E normalized is designed to derive a base, or normal, price-earnings ratio. It is similar in purpose to the forward price-earnings ratio, but with the further adjustment of using the following year’s actual earnings.

This approach is valuable because examining the history of price-earnings ratios using trailing or fiscal-year earnings does not capture the expectational component of the price-earnings ratio.

A normalized price-earnings ratio goes back in time and divides the previous year-end price, or the high or low (or both) for the year, by the following year’s actual earnings per share. These normalized price-earnings ratios can then be averaged.

Rather than looking at today’s price and earnings and determining whether the price-earnings ratio is relatively high or low, many analysts would suggest looking at today’s price and next year’s estimated earnings, so that the price-earnings ratio is based on estimated earnings.

The normalized price-earnings ratio makes the adjustment with actual, rather than estimated, earnings.

P/E Relative

P/E relative allows comparison of the price-earnings ratio of a firm to the price-earnings ratio of the overall market, currently and historically.

By dividing the firm’s price-earnings ratio by the market’s price-earnings ratio, P/E relative is determined. Often the Standard & Poor’s 500 is used as a proxy for the market. Prices and earnings for the firm and the market should reflect the same period.

Looking at these figures historically would generate median and average P/E relative figures for comparison to the current P/E relative. The P/E relative is much like relative strength measures, which relate the change in a stock’s price to the change in value of a market index.

A P/E relative can also be calculated using industry price-earnings ratio data instead of the S&P 500, if it is available.

Reprinted with the permission of:

American Association of Individual Investors (AAII)
625 N. Michigan Ave.
Chicago, IL 60611
(800) 428-2244
(312) 280-0170
(312) 280-9883 fax

www.aaii.com

The opinions and views expressed in this document do not necessarily reflect the views or opinions of InvestingMinds. InvestingMinds did not prepare and does not endorse such content. Please note that this document is intended for general circulation only and the recommendations contained herein do not take into account the specific investment objectives, financial situation or particular needs of any particular person. This document is for information purposes only and it should not be regarded as an offer to sell or as a solicitation of an offer to buy securities or other financial instruments. No part of this document may be reproduced in any manner without the written permission of InvestingMinds.

Reprinted with the permission of the American Association of Individual Investors

Why is it that bright, educated people who come across stocks that could make them wealthy for life, so frequently fail to capitalize on golden opportunities—not enough brains or education?

No, not even close.

Two things are responsible: Beating ourselves, and a lack of knowledge. Beating ourselves is mainly emotions, meaning too much fear or greed. Normally those things take control when investors lack knowledge—they do not know what they own and why they own them in enough depth.

Investing is actually common sense along with a focus on the key factors that drive the greatest stocks.

In fact, investors need focus on only four factors that seem to be common, identifying traits of the greatest companies and stocks, in my experience. I have termed these four factors BASM:

• Business Model: How the company plans to grow, be profitable and protect itself from competitors.
• Assumptions: The key assumptions the company makes about their markets upon which they then develop the business model.
• Strategy: This is simply the plan the company develops to implement the business model.
• Management: These are the actual people who create the great business models, assumptions, execution and all the rest. Great management is also needed, over time, to adjust business models for competitive situations.

One item not mentioned here is earnings. So, what about earnings, you ask?

Earnings are part of the metrics you use in evaluating a company—gross margin, net margin after taxes, and return on capital are just some examples of other metrics. These tell you a lot about the competitive position and how well the company is managed. But these are report-card issues. While you do learn something about management from them, the report card does not tell you about vision and fixing problems.

In short, earnings are the golden eggs that drive stock prices, but BASM is the golden goose that lays those golden eggs—it is the engine of earnings.

The Business Model

The business model is the core of how a successful company operates. But most investors cannot tell you much or anything about their best investments and the business models. So let’s start here—on the first big element in BASM.

A good company normally describes and discusses their business model in several places including what they file with the Securities and Exchange Commission when they go public or have successive stock offerings, and the annual reports, all of which are easy to access from the company and the Internet. Here are the three elements of a strong business model:

1) The company describes how they are going to make a lot of money (or why they already are). If they are young and embryonic, they describe the specific path to get to great profitability.

2) The company describes how they will grow for a long time in the future, and how they will retain great profit margins and overall profit growth.

3) The company describes how it will protect itself from the competitors that want to get a piece of their markets and profits. They must talk about competition and how they will compete, protect and win—in other words, how the first two things in the business model will stay that way and not fall prey to strong competitor companies that may come along.

That’s it, and as simple as this is, it is amazing how many companies overly complicate it or write a poor business model and show us that they may not be going great places.

Thus, if an investor does not see anything of a clear, straightforward business model in filings or the annual report, he or she will have spent five minutes wisely, but then can move on and not bother with anything else.

One of the best examples of a great business model is Home Depot. When Home Depot came public, many people said it was just another big discount retailer. Many others challenged Bernie Marcus’ (co-founder) plans to pay workers in his stores more and spend more than competitors on training. Bernie understood that discount retailing was going to be dog-eat-dog competitively, and yet there could be ways other than price to differentiate between companies.

The big thing for Home Depot was a business model that was designed to attract customers on the basis of customer service while being price competitive. Low prices often meant that people felt adrift and could not get enough help to purchase anywhere near what their potential might be.

Well, paying help more than the minimum wage and the extra spending on training as part of the do-it-yourself business model concept of Home Depot did bring them the customers, and that eventually was reflected in the stock price.

Assumptions

Any strategy that a company settles upon to achieve its business plan is built on a set of assumptions, or projections, about how big a market is for a company or a product. Assumptions also must be made concerning anticipated competition and demand over the next year or three years. The assumptions part of BASM is best illustrated with an example.

Bill Gates came into the software spreadsheet market facing skeptics who told him that, since Lotus Development had 70% of the spreadsheet market, he could do nothing, and it was already “game over.” (“Game over” is one of the great syndromes of ordinary investing that ignores the elements of BASM.) So Lotus ran the hot product race without any real worries about Microsoft.

But Gates made huge assumptions about the way people and companies would buy and use software.

His biggest assumption was that customers would have a critical need for standard software—in other words, consumers were looking for uniformity and continuity in software so they would not have to relearn everything from ground zero when new products came out.

Gates also assumed that consumers would stay with one company’s products cycle after cycle if those products met their needs and were competitive in new technologies.

Setting standards and achieving early domination flowed from those assumptions as the core company strategy was formulated.

Eventually, Lotus lost, and Microsoft (need I add?) won. Now it really is “game over.”

Strategy

Management may have a great business model, but it has to have a strategy to execute the details of its plans.

Operational differentiation and excellence are concepts that apply to many great companies.

For instance, Intel has excelled over the years by continually coming out with the best new microprocessor chips to serve as the brains for personal computers. But aside from great product research and development, Intel spends a fortune on research and development in production methods and systems.

To reach back a bit further, McDonald’s is one of the truly great companies. And it is clear the core secret to McDonald’s great management success was operations. In fact, the McDonald’s business model went into great detail about how consistency and quality would flow from great operations management, and those factors would bring in the customers and control costs—and it did work, just as the company said.

Management

The best management demonstrates that it can envision a great future for the company and articulate a cohesive and logical strategy for getting there. The strategy cannot be pie in the sky—it has to be based on resources—human, financial, technological—within the grasp of the company.

Management also has to show it can execute the details, so you must watch carefully.

Great managers make promises and projections to you, the stockholder, that they can deliver on. They are driven to stay ahead of the pack and understand how to lead. While they truly want to win, they are realists in terms of the goals they can execute.

Lastly, great managers admit mistakes early and move aggressively to fix them.

Investing for the Big Money

Most investors spend too much time chasing the wrong information.

Focus is the key, and the simplicity and focus of BASM really has worked to develop some of the greatest all-time investment records and wealth for many people. They do not always call it BASM, but they concentrate on what the golden goose is that creates the golden eggs of earnings.

Great Business Model Descriptions: eBay vs. Google

How does eBay differ from Google?

They are both the darlings of our time, very successful, and both household words.

But eBay has a great business model in which—instead of concentrating on the powerful technology that was making them the best—they concentrated on a way to build true community and bring in all the customers and retain them. That was all spelled out in the prospectus they printed when going public. Google, on the other hand, was fuzzy about their business model. We know it was a great buy on the technology lead and popularity. However, they are now experimenting with so many things at once, and yet still derive almost all of their revenues from search engines that will be further assaulted by competition.

These differences could be seen by investors who scrutinized the public offering documents. eBay had great business model descriptions when it went public; Google did not.

Here is how eBay described their strategy at the time of the initial public offering (IPO):

“The Company’s objective is to build upon its position as the world’s leading online person-to-person trading community. The key elements of eBay’s strategy are:

“GROW THE EBAY COMMUNITY AND THE EBAY BRAND. The Company believes that building greater awareness of the eBay brand within and beyond the eBay community is critical to expanding its user base and to maintaining the vitality of the eBay community.

“Although the Company’s historical growth has been largely attributable to word-of-mouth, the Company intends to build its user base and its brand name aggressively…

“BROADEN THE EBAY TRADING PLATFORM. The Company intends to pursue a multi-pronged strategy for growing the eBay platform within existing product categories, across new product categories and internationally. The Company will target key vertical markets in its user programs and marketing activities.”

There are many more details and components of the business plan, but the key thing was that they all held together logically. They described in straightforward terms how they would grow and make money, and they presented something of a roadmap for both the company and its investors. This is what you want to find.

Google, in contrast, seems to have a good model for generating advertising revenues on its search pages, and it is very profitable. Moreover, the marketing and mind share aspect of its ubiquity, such that people use “Google” both as a verb and a noun—“googling” is a part of the language these days––means that Google has some major assets as it strives to become a dominant leader.

So, Google does have the first part of a good business model, the profitability. But it lacks the second and third parts of a great business model—a plan for growing the profits into the future and protecting them from competition. On these parts there is a blank slate.

Interestingly enough, the filings from its 2004 public offering contain language that concedes that Microsoft will be a competitor to contend with. But also very important is that those filings—unlike eBay’s filings—have very little in them about competitive strategy and the details of the business plan.

Even in late 2005, Google was still adding to what their core service had been. This only makes it a bit tougher for management to define their ultimate strategy and business plan.

The stock has done well, but the jury is out—and based on the BASM yardsticks, the clarity of strategy when they went public is lacking.

Fred Kobrick managed mutual funds for Wellington Management and State Street Research & Management before founding his own firm in 1998. Under his management, the State Street Research Capital Fund was ranked by USA Today as one of the top five performing funds over a 15-year period. He currently provides investment advice to nonprofit institutions and lives in Sudbury, Massachusetts. His book, “The Big Money” (Simon & Schuster, 2006), provides case histories, written to teach the simple guiding principles from which his investment record was generated.

Reprinted with the permission of:

American Association of Individual Investors (AAII)
625 N. Michigan Ave.
Chicago, IL 60611
(800) 428-2244
(312) 280-0170
(312) 280-9883 fax

www.aaii.com

The opinions and views expressed in this document do not necessarily reflect the views or opinions of InvestingMinds. InvestingMinds did not prepare and does not endorse such content. Please note that this document is intended for general circulation only and the recommendations contained herein do not take into account the specific investment objectives, financial situation or particular needs of any particular person. This document is for information purposes only and it should not be regarded as an offer to sell or as a solicitation of an offer to buy securities or other financial instruments. No part of this document may be reproduced in any manner without the written permission of InvestingMinds.

Reprinted with the permission of the American Association of Individual Investors

What can you learn from three decades of monitoring investment newsletter performance?

Plenty.

It was nearly three decades ago that the Hulbert Financial Digest (HFD) began independently monitoring the performance of investment advisory newsletters. I’m devoting this column to a couple of the most important investment lessons that emerge from the list of newsletters that dominate the rankings of top performers.

The investment world today couldn’t be more different than the world that existed when the HFD set out to track newsletters, in mid-1980, at least on the surface. Back then, for example:

• The Dow Jones industrial average stood below 900—lower than where it had stood in 1966, 14 years earlier;
• Gold bullion, on the other hand, was just coming off a high of just under $900 per ounce—a record level that remains unbroken today, more than 27 years later (though gold is getting close);
• Inflation was in the double digits, as was the interest rate on long-term government bonds.

Given this stark contrast, it would seem that caution should be exercised in drawing any investment lessons based on which newsletters have performed the best since 1980. Why should anyone think that strategies appropriate to the investment world in 1980 would be appropriate today?

But I would argue that a closer look shows that, on average, the period encompassing the nearly 30 years since 1980 is not really all that different than what came before.

Down Memory Lane

Imagine, if you will, that you have traveled back in time to the early 1980s, and you are perusing the data in the 1980 Ibbotson Associates yearbook. This firm was created in 1977 by Professor Roger Ibbotson, and its yearbooks of historical data have become a must-have for financial planners and advisers. Those yearbooks, of course, contain the year-by-year performances back to 1926 of stocks, bonds and Treasury bills, and inflation rates.

What conclusions would you have reached? Here are two:

• Over the period of 1926 through 1979 (the period that would have been covered in the 1980 yearbook), stocks provided a handsome return, in both nominal and inflation-adjusted term;
• In addition, there was a healthy equity premium—that is, stocks outperformed bonds, compensating investors for the additional risk associated with investing in stocks.

But these same conclusions hold for the period since 1980, as is illustrated in Table 1.

To be sure, stocks in recent decades have produced higher returns (both in nominal and inflation-adjusted terms) than the returns they produced before 1980. But the real difference is not stock performance but rather bond performance—bonds did much better after 1980 than they did before. Because of this, the equity premium since 1980 has actually been less than the longer-term average, despite stocks themselves providing better overall returns.

This stock/bond relative performance difference between these two long-term time periods indicates, to me, that any “lessons learned” from the list of long-term top performers would have questionable relevance to the future if any of those top performers were highly ranked because they were heavily invested in bonds.

However, this is not the case—none of the newsletters at the top of the HFD’s rankings for performance since 1980 (see Table 2) derived a significant portion of their investment earnings from bonds.

All of which leads me to be fairly confident in drawing the following lessons.

Lesson 1: Long-term investors need not lose sleep over the markets’ short-term gyrations because the markets’ long-term patterns will eventually assert themselves.

To be sure, I am under no illusions that my drawing of this lesson will change many investors’ behaviors. For whatever psychological reasons, many are obsessed about the short-term and therefore can’t imagine not paying it the closest of attention.

What my data show, however, is that investors need not focus on the very short term to perform very well over the long term, thank you.

Consider The Prudent Speculator, the newsletter in first place on the HFD’s ranking for performance since mid-1980. Of any of the newsletters I monitor, this service has been the most buffeted by short-term market gyrations. And yet, none surpasses it in its willingness to either ignore or tolerate those gyrations.

Consider what happened to it in the crash of 1987, which just celebrated its 20th anniversary. On that day, according to the HFD’s calculations, the newsletter’s model portfolio lost 57%. And yet, far from panicking, Al Frank (the newsletter’s editor at the time) maintained his fully invested (and heavily margined) posture, patiently faithful that the stock market’s long-term uptrend would eventually win out. The newsletter’s long-term top ranking is a testament to that faith.

Lesson 2: Worrying about the short term can work against you.

Another lesson that emerges from my tracking of investment newsletters is related to the first: Constantly monitoring your investment performance can cause you to unnecessarily reduce the amount of risk you are willing to incur, causing your long-term performance to suffer.

According to behavioral finance researchers, constantly looking at how your portfolio is performing is not a benign act. It leads you to focus more of your attention on the short term than you would otherwise, leading you in turn to miss the veritable forest for the trees.

One researcher who has extensively studied this behavioral pattern, Richard Thaler of the University of Chicago, calls it “myopic risk aversion.” He hypothesizes that the more frequency with which an investor re-evaluates how he is doing, the more frequently he will experience loss, since any risky asset will not infrequently be exhibiting a short-term losing streak. No investor (except the occasional masochist) enjoys the experience of loss, and most investors prefer to avoid losses; therefore, this greater frequency of re-evaluation will tend to cause investors to own less risky assets and avoid stocks.

To test this hypothesis, Professor Thaler and fellow researchers several years ago constructed an elaborate simulation that imitated the many decisions that investors make over their lifetimes. One group was able to look at how they were doing every month, another group every year, and the third group got to take a look just once every five years. Just as Professor Thaler hypothesized, the investors who re-evaluated their portfolio every month had the lowest average equity exposure.

So, why does my own newsletter that reports investment newsletter performance come out monthly?

It’s a good question. The problem, of course, is that I wouldn’t be in business if I had a subscription product that came out infrequently. But the tension exists nonetheless.

One way I try to resolve this tension is by focusing my monthly newsletter on long-term performance. For example, none of the performance rankings in my monthly newsletter cover periods of less than five years. And most of my scoreboards cover much longer periods.

My hope is that, in the very act of responding to investors’ desire for constant re-evaluation, I can get them to focus on the long term. After all, a ranking covering performance over the last five years, or especially the last 10 or 20 years, doesn’t change that much from month to month.

Conclusion

If investors nevertheless want to obsess about the short term, they can be my guest.

But these short-term traders shouldn’t fool themselves into thinking that this obsession is necessary to build long-term health. On the contrary, it is probably standing in their way.

Mark Hulbert is editor of the Hulbert Financial Digest, a newsletter that ranks the performance of investment advisory newsletters. It is published monthly and is located at 5051B Backlick Rd., Annandale, Va. 22003; 703/750-9060; www.hulbertdigest.com. This column appears quarterly and is copyrighted by HFD and AAII.

Reprinted with the permission of:

American Association of Individual Investors (AAII)
625 N. Michigan Ave.
Chicago, IL 60611
(800) 428-2244
(312) 280-0170
(312) 280-9883 fax

www.aaii.com

The opinions and views expressed in this document do not necessarily reflect the views or opinions of InvestingMinds. InvestingMinds did not prepare and does not endorse such content. Please note that this document is intended for general circulation only and the recommendations contained herein do not take into account the specific investment objectives, financial situation or particular needs of any particular person. This document is for information purposes only and it should not be regarded as an offer to sell or as a solicitation of an offer to buy securities or other financial instruments. No part of this document may be reproduced in any manner without the written permission of InvestingMinds.

Why not just buy low and sell high? That’s easy enough, right? The classical answer is a resounding no and there are reams of analyses to prove that it’s not a good idea to try to do this. Most arguments against timing make the case that the market is extremely volatile and impossible to predict. It’s extremely easy to miss the best performing days and if you do you will have substantially worse performance than if you had stayed in the market the entire time. I’ve seen many variations of the following analysis [1] over the years:

The bottom line of this analysis is supposed to be that unless you have a crystal ball you are going to miss major upward market moves and you will seriously undermine your returns. In fact, in 1975 William Sharpe published a seminal article on this topic: “Likely Gains from Market Timing”. In this article Sharpe demonstrated statistically that in order to benefit from a market timing strategy you had to guess right 74% of the time. [2]

Historic performance data seems to confirm this conclusion. When Brinson, Hood, and Beebower conducted their analysis of the performance of 91 pension plans from 1974 to 1983 they determined that market timing had detracted from performance by .66% [3]

So maybe we should just end the article here. Why go on? Maybe because everyone believes that they are above average and people don’t like the idea of a passive strategy. More importantly, these analyses don’t tell the entire story.

First, every anti-timing analysis that I have seen, such as the first example given, focuses on the performance of binary strategies – you switch from being 100% in the market to being 100% out of the market. A more prudent strategy, and one that is actually practiced by portfolio managers, involves moderately adjusting your market exposure depending upon some appropriate signal. However, I have not seen this examined in the research.

Secondly, bubbles do occur and after the fact everyone clearly sees how overvalued the bubble assets were. There are historic patterns and there are limits to what is a reasonable price for any asset. If we can learn to leverage this knowledge then perhaps we can boost our returns.

I skimmed through parts of Graham (In case you didn’t know, Benjamin Graham was a young Warren Buffet’s mentor) and Dodd’s 1934 classic book, Security Analysis, in early 2002 and was awe struck by the timelessness of their writings. Considering the parallels between 2002 and 1934, I had to keep reminding myself that the book had been written almost 70 years prior. Let me share a montage of interesting quotes from the book (italics theirs): “…the prices of common stocks are not carefully thought out computations, but the resultants of a welter of human reactions. The stock market is a voting machine rather than a weighing machine. It responds to factual data not directly, but only as they affect the decisions of buyers and sellers…a conservative valuation of a stock issue must bear a reasonable relation to the average earnings. In addition, it must be justified by whatever indications are available as to the future. This approach shifts the original point of departure, or basis of computation, from the current earnings to the average earnings, which should cover a period of not less than five years, and preferably seven to ten years…But it is the essence of our viewpoint that some moderate upper limit must in every case be placed on the multiplier in order to stay with the bounds of conservative valuation. We would suggest that about sixteen times average earnings is as high a price as can be paid in an investment purchase of a common stock…it is difficult to see how average earnings of less than 6% upon the market price could ever be considered as vindicating that price. It would be acceptable only in the expectation that future earnings will be larger than in the past. In the original and most useful sense of the term such a basis of valuation is speculative.” [4]

Notice that Graham and Dodd heavily discounted expectations of future earnings. Maybe they were from Missouri and they never had to figure out what Google was worth but frankly I agree with their approach. It’s hard enough to know what a company really earned over the last 10 years, let alone project future earnings.

Fast Forward to February 2006 at The CFA Institute Risk Symposium and Yale professor Robert Shiller discusses the characteristics of bubbles and how they propagate. He also presents a few compelling market valuation indicators. [5] (Shiller is famous for his 2000 book, Irrational Exuberance, named after a term used by Alan Greenspan in a famous speech. Interestingly, Shiller had discussed the impact of market valuations on returns with Greenspan 2 days prior to the famous speech.) First, he examines the S&P P/E ratios from 1881 - 2005, calculated as Graham and Dodd would have them calculated. The graph below, from Shiller’s Web site, is the same one used in his presentation but is updated through February 2007.

As you might expect the graph shows massive fluctuations, with the most prominent peaks in 1929 and 2000. Of course there are two ways that a high P/E can come back down to earth – either the E can go up or the P can go down and you would have no way to know in advance which was going to occur. However, Shiller analyzed the relationship between the P/E and the subsequent 10 year return. Although the relationship would not make for a very good regression it clearly shows that a high P/E results in lower returns over the next 10 years. In particular, after the lows of 1919 the market averaged more than 15% per year and when the P/E was 20 – 25 the subsequent returns were near zero. So it would appear that Graham and Dodd were correct and that P/E is a valid indicator of fair value. By the way, as of February 2007 the P/E was at 30, which is not a positive indicator.

Shiller also presents his Valuation Confidence Index, which he has calculated since 1990 and which reflects the percentage of investors that believe the market is not overvalued.

Interestingly, the index bottomed out at around 30% right before the market peak in early 2000, which begs the question “if investors believed the market was overvalued then why didn’t they sell?” Maybe they didn’t believe in market timing. Unfortunately, his data only goes back to 1990 so we can’t be sure that this is a valid market indicator but it certainly bears watching. Note that by this measure the market is not currently at risk for a pullback.

In 2002 Pu Shen, an economist at the Federal Reserve Bank of Kansas City, took the P/E indicator a step further and empirically examined the performance of a signaling tool similar to the Fed Model. For the period from January 1962 to December 2000 he tested buy/sell decisions based upon what he calls the “short spread” between the S&P earnings yield and the yield on 3 month treasuries (E/P – 3 month treasury bill yield). (He also looked at the “long spread”, based upon the 10 year yield but that was not as powerful.) He used the tenth percentile of the spread as the signal – i.e. when the spread dropped below the tenth percentile it was time to get out of the market and into 3 month treasuries and when it rose above the tenth percentile it was time to get back into the market. (Note that this is one of those binary strategies.) The idea here is that when the earnings yield on stocks is too close to the yield on 3-month treasuries stocks are not a very good investment. Seems reasonable.

Here is a summary of the important findings from his 39-page paper:

• The buy and hold strategy returned 1.117% per month over the test period while the switching strategy returned 1.322% per month.
• On an annualized basis that amounts to 14.26% vs. 17.07%.
• Whether or not you consider this difference to be statistically significant depends upon how you frame the analysis. I did not find this part of the paper particularly enlightening.
• The switching strategy resulted in a less risky portfolio over time. The Sharpe ratio of the switching portfolio was 0.205 vs. 0.13 for the buy and hold strategy.

Seems like it would be hard to pooh pooh these results. However, Pu also tested switching strategies based upon just the earnings yield and just the 3-month yield and concluded that almost all the predictive power was in the 3-month yield. His interpretation of this result is that trading based upon the 3-month yield keeps you out of the market during inflationary periods, which are not good for the market. I think it’s just as valid to view this from the perspective of higher yields mean a higher discount rate on stocks, which gives lower stock valuations.

While I think this study raises some interesting possibilities, I do have one major concern. Given the amount of historical data available and the varied economic environments that the market has encountered I don’t think 39 years is a long enough time period for this kind of study. In fact, Robert Shiller pointed out that “Since 2000, [the Fed Model] has broken down, and also before 1970, there really was not a correlation. Thus, people seem to have been exaggerating the impact of interest rates on the stock market.” [7] Clearly he is of the mindset that we should focus on the P/E ratio alone and from my perspective there is good reason to believe him. Interest rates are going to go up, they are going to go down, they are going to oscillate around some “normal” level, and you can’t very effectively predict where or when they are going to move. So you might as well take a long-term perspective and focus on the P/E ratio alone. Unfortunately, Shiller did not do nearly as rigorous an analysis as Pu.

A similar analysis from Ned Davis Research shows that extreme values of the S&P P/E can be effective predictors of future stock returns. Analyzing the period from March 1926 to June 2006, using trailing 12 month earnings, they point out that the average P/E has been 15.9 and they have set buy/sell triggers at P/E ratios of 9.3 and 20.2. (I was unable to discover how they determined these thresholds.) 24 months after responding to these triggers the median return of the S&P has been 27.5% after a buy signal and 0.8% after a sell signal.

So where does all this leave us today? The current trailing P/E ratio of the S&P 500 doesn’t look so bad at 15.6. However, based upon Shiller’s 10 year trailing analysis above which shows the February P/E to be 30, it’s clearly north of 30 now, which is darn high. The reason for the big difference is that S&P earnings have been on a rocket since 2002. As long as you have confidence that earnings won’t retreat then maybe valuations aren’t so out of whack. However, consider the data over the past 135 years:

Using Shiller’s entire data set I have determined that the historic earnings growth rate has averaged 1.45% per year and earnings are currently well above the trend line. Picking different time periods than the last 135 years can give slightly different results for the average earnings growth rate but nothing dramatically different. For instance, in a 2002 Yale ICF working paper Ibbotson and Chen stated that earnings have grown at a 1.75% annual rate since 1926. [8]

Each time that earnings have shot well above the trend line in the past they have eventually regressed back to the trend line. There are several reasons to expect that to occur. First, as Ibbotson and Chen point out, earnings just can’t grow faster than the overall economy unless equities are becoming a larger factor in the economy. While the factor share of equities has grown it is not a huge effect. Therefore, one would expect earnings to grow at about the rate of productivity growth, which has been about 2% per year. [8]

Second, market forces also throttle earnings growth. Extraordinary profits invite additional competition, greater employment levels eventually cause labor rates to rise, and high production levels bid up energy and raw material costs. With unemployment at a 6 year low and rising commodity prices we’re already seeing evidence of this.

My belief is that we have been experiencing an earnings bubble – perhaps driven by huge liquidity injections and lax home mortgage originations. It would seem that profits are destined to go down. If that’s the case then Graham and Dodd are correct to be looking at the longer-term earnings average. We could very well be at a market peak right now and, while a complete withdrawal from the market might not be prudent, reducing one’s exposure to stocks might be wise.

[1] ING Special Report: Market Timing, July 2005
[2] William Sharpe, “Likely Gains from Market Timing”, Financial Analysts Journal, Vol. 31, No. 2, March-April, 1975, pp. 60 - 69
[3] Gary P. Brinson, L. Randolph Hood, and Gilbert L. Beebower, “Determinants of Portfolio Performance”, Financial Analysts Journal, Vol. 51, No. 1, January-February, 1995, p. 135
[4] Benjamin Graham and David Dodd, Security Analysis, 1934, pp. 452 – 453
[5] Robert J. Shiller, “Irrational Exuberance Revisited”, CFA Institute Conference Proceedings Quarterly, Volume 23, Number 3, September 2006, pp.16 – 21
[6] Pu Shen, “Market-Timing Strategies That Worked”, Research Division, Federal Reserve Bank of Kansas City, May 2002
[7] Robert J. Shiller, “Irrational Exuberance Revisited”, p. 19
[8] Roger G. Ibbotson and Peng Chen, “Stock Market Returns in the Long Run: Participating in the Real Economy”, March 2002

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