About Our Unique Investment Return Calculator

Question #1 on the new investment return calculator — What does the Return Predictor do?

The Return Predictor tells you what sort of long-term return you can realistically expect from an investment in the S&P index made at various valuation levels. For example, it reports that the most likely 20-year return for a purchase made today (this article was posted in February 2007) is an annualized real return of 2.6 percent. In contrast, the most likely return for a purchase made at moderate valuations is an annualized real return of 5.8 percent. The obvious strategic implication is that stocks offer a better value proposition at times of moderate prices than they do at times of high prices.

Question #2 on the new investment return calculator — What are the predictions based on?

The predictions are based on a regression analysis of the historical stock-return data (dating back to 1870). Valuations have always affected long-term returns in the past. The calculator assumes that this will continue to be the case in the future, and looks to the historical data to determine the probabilities of various outcomes. Precisely speaking, the calculator reports on the effect that valuations have had on long-term returns in the past.

Question #3 on the new investment return calculator — Is this calculator part of a market timing scheme?

It depends on how you define the word “timing.”

Investment Return Calculator

Many investors have heard numerous investing experts tell them that “timing doesn’t work.” There is indeed a good bit of evidence that short-term timing (trying to predict what stocks will do in one or two or three years) generally does not work. The new investment return calculator does not aim to help you engage in short-term timing.

The calculator attempts to predict long-term returns (returns achieved in time-periods of ten years or longer). What the calculator is really doing is assessing the long-term value proposition of stocks purchased at various price points. The price you pay for stocks obviously affects the long-term value proposition you obtain from owning them, just as the price you pay for any other asset affects the long-term value proposition you obtain from it.

Short-term timing does not work because it requires guesses about when stock prices are going to hit “bottoms” and “tops.” No such guesswork is required to practice long-term timing effectively. All that you need to do to practice long-term timing effectively is to assess long-term value propositions successfully and to make occasional changes in your stock allocation to reflect changes in the value proposition available to you.

Question #4 on the new investment return calculator — Do you sincerely believe that it is possible to predict future stock returns?

Yes, to a reasonable extent. If you have doubts about this, please do further research to either confirm your doubts or resolve them prior to making use of the new investment return calculator.

Question #5 on the new investment return calculator — If it is possible to predict long-term stock returns, why aren’t lots of other people doing it?

Lots of other people should be doing it. I think it is foolish for anyone to make a stock purchase (especially of an index fund) without first making use of some tool that assesses long-term value propositions.

The best explanation I can offer as to why most investors do not do this today is that easy access to the data and statistical tools needed to make effective predictions did not become generally available until recent decades, and, beginning in the early 1980s, the U.S. stock market entered a wild bull market that for many investors made it seemingly unappealing for a time to know how high prices affect the long-term value proposition of stocks. I expect to see calculators of this type become far more popular after we experience a big price drop.

Question #6 on the new investment return calculator — Are there experts who endorse this calculator?

Investment Calculators

There are a good number of experts who endorse the principles used to build the calculator. Yale University Professor Robert Shiller (author of Irrational Exuberance) is the leading figure in this field of investing research. John Bogle, founder of Vanguard, says in his book Common Sense on Mutual Funds that: “This analysis takes into account my conviction both that the performance of individual securities is unpredictable, and that the performance of portfolios of securities is unpredictable on any short-term basis. While the long-term performance of portfolios is also unpredictable, a careful examination of the past returns can establish some probabilities about the prospective parameters of return, offering intelligent investors a basis for rational expectations about future returns.” William Bernstein says in his book The Four Pillars of Investing, that: “The ability to estimate the long-term future returns of the major asset classes is perhaps the most important investment skill that an individual can possess.” There are a good number of others who have written about the difference between short-term timing and determining long-term value propositions.

No expert has directly endorsed this calculator, however. Most of the experts who understand the difference between short-term timing and assessing long-term value propositions evidence a reluctance to putting those insights to practical use by advising investors when and to what extent to change their stock allocations in response to price changes.

Question #7 on the new investment return calculator — Who developed the calculator?

The statistical work was done by John Walter Russell. There is a wealth of cutting-edge investment research that relates to the investment return calculator available at John’s web site .

Rob Bennett’s contribution was to make a pest of himself by asking lots of dumb questions about how long-term stock investing really works. The leading theory as to why John is so generous in helping fellow Financial Freedom Community members with their investing questions is that he is hoping that someday he will have provided enough answers to enough questions that he will satisfy Rob’s curiosity re these matters. He probably does not yet fully appreciate what he is up against.

Question #8 on the new investment return calculator — How did the calculator come to be?

It all started with a post that Rob put to a Motley Fool discussion board on the morning of May 13, 2002. The post asked whether valuations affect safe withdrawal rates. That question set off the most exciting and the most controversial series of investing discussions ever held on Planet Internet. The Stock-Return Predictor is one of the fruits generated by the insights developed during The Great Safe Withdrawal Rate Debate.

Question #9 on the new investment return calculator — Does this calculator only help people who invest in the S&P index?

In a direct sense, yes. Those who are not invested in the S&P index can use the calculator to gain a general sense of how their long-term investment returns may be affected by the valuations that apply at any given time. But other types of stock investments may of course provide returns significantly different from what the S&P index provides.

Question #10 on the new investment return calculator — How can the calculator know what sort of things are going to happen to the economy before they happen?

Free Investment Calculator

The calculator of course does not know what is going to happen. The assumption being used is that we will continue to see economic ups and economic downs somewhat similar to those that we have always seen in the past.

After the positive effect of the ups cancels out the negative effects of the downs, investors have in the past been left with a long-term annualized real return of about 6.5 percent. It has generally taken those who purchased at times of low or moderate valuations far less time to obtain that sort of return. The calculator seeks to inform you of the probabilities of obtaining various returns at various future time-periods, assuming that the economic realities remain more or less constant.

If you believe that U.S. companies will not be able to perform as well in the future as they have in the past, you should subtract something from the numbers generated by the investment return calculator to determine your own take on what is likely. If you believe that U.S. companies will be able to perform better in the future than they have in the past, you should add something to the numbers generated by the investment return calculator to determine your own take on what is likely.

Calculator Shows Effect of Stock Valuation in Predicting Stock Returns

The Stock-Return Predictor reveals the effect of the stock valuation level that applies at the time of a stock purchase on long-term returns.

The Stock-Return Predictor

This new calculator tells you what return you can reasonably expect at various time-periods from an investment in the S&P stock index, presuming that stocks perform in the future much as they have in the past. The results are expressed in terms of real, annualized total (that is, with dividends reinvested and without additions or subtractions to principal) returns.

The purpose of the calculator is to help you set your stock allocation strategy. Stocks generally offer a stronger value proposition at times of low or moderate valuation than they do at times of high valuation. By comparing the long-term returns likely to follow from stock purchases made at today’s stock valuation level with the long-term returns likely to follow from stock purchases made at a lower or higher valuation level, you can put together a stock purchase strategy likely to aid you in becoming a true Buy-and-Hold stock investor. Predicting stock returns by making reference to stock valuation levels prepares you for what is to come in the years ahead.

AUDIO: Rob’s Financial Freedom Insight #2 — Knowing Your Stock Return in Advance Takes the Risk and Emotion Out of Stock Investing


The Stock-Return Predictor results are based on John Walter Russell’s regression analysis of what the historical stock-return data shows regarding the effect of stock valuation on long-term stock returns, published at the www.Early-Retirement-Planning-Insights.com web site. Russell’s research grew out of The Great Safe Withdrawal Rate Debate, an ongoing exploration of the stock valuation question that has generated intense controversy at half a dozen Financial Freedom Community discussion boards for four years now, beginning with a post put to a Motley Fool board by Rob Bennett on May 13, 2002. Those discussions also led to development of the Valuation-Informed Indexing approach to investing, examined in articles posted by Bennett to the www.PassionSaving.com web site. The new calculator taps into the insights developed during those discussions in an effort at predicting stock returns. The default results set forth above show the returns you can expect for stocks purchased at the stock valuation levels that now apply (the default setting is adjusted monthly). To see how the value proposition of a stock purchase changes with upward or downward movements in stock valuation, please move the sliding control button (the “slider”) to higher or lower S&P price levels. For example, if you want to see what your expected returns over various time-periods would be if the price of the S&P 500 were to fall by 20 percent, move the slider to a price level 20 percent below the level that applies for the default results.

Stock Valuation

Moving the slider to a new S&P price level brings up the results that apply for stocks purchased at the P/E10 (P/E10 is the price of the index divided by the average of the past 10 years of earnings–Robert Shiller has long argued in favor of P/E10 as an effective means of assessing valuations, and Russell’s research offers support for Shiller’s position) level that applies at that S&P price level. An alternate way of viewing the results that apply for different stock valuation levels is to directly move the slider to different P/E10 levels.

The article “Valuation Ratios and the Long-Run Stock Market Outlook: An Update,” by John Y. Campbell and Robert J. Shiller, provides background on the P/E10 tool and its use in making reference to stock valuation levels in predicting stock returns.  P/E10 fell to between 5 and 6 in 1921 and 1932, and to between 6 and 7 in 1922 and 1982 (the starting-point of the huge bull market). The highest recorded P/E10 value is 44 (reached in early 2000, perhaps the ending point of the huge bull market). A moderate P/E10 value is 14. P/E10 exceeded 24 in 1928, 1929, 1930, 1966, and in all the years from 1995 through early 2006. The calculator shows that the stock valuation level that applies at the time a purchase is made is an important factor in predicting stock returns obtained in 10 years, 20 years or 30 years.

There is a 50 percent chance that the real-world return will be less and a 50 percent chance that the real-world return will be more than the returns identified by the calculator as “Most Likely,” according to Russell’s regression analysis of the historical stock-return data. There is only a 20 percent chance that the real-world return will be greater than returns identified as “Lucky” and only a 20 percent chance that the real-world returns will be less than returns identified as “Unlucky.” There is only a 5 percent chance that the real-world returns will equal or exceed the returns identified as “Best Possible” and only a 5 percent chance that the real-world returns will equal or fall short of the returns identified as “Worst Possible.”

Stock Valuations

Predicting stock returns is an inexact business. The Stock-Return Predictor results are the product of research resting on the assumption that stocks are likely to perform in the future much as they have in the past. It is of course not a certainty that this will prove to be the case. In any event, there are almost certain to be at least some ways in which stocks will perform in the future in ways different from how they have in the past. Moreover, it is important to understand that, while changes in stock valuation affect long-term returns as a matter of “mathematical certainty” (those are the words of William Bernstein, author of The Four Pillars of Investing ), predicting stock returns in the short-term (time-periods of less than 10 years) is extremely difficult, if not outright impossible.

The calculator is intended to serve as a guide to how changes in stock valuation may affect long-term stock returns. The authors of the calculator believe that it is a useful tool for predicting stock returns. But they also stress that the study of how changes in stock valuation affect long-term stock returns is very much an ongoing effort. The calculator’s authors (John Walter Russell and Rob Bennett) very much do not want any users of the calculator to read into the “predictions” offered any more certainty than is warranted by the nature of the research project that produced it.

The Famous Robert Shiller Stock-Market Prediction

Will Robert Shiller be proven wrong about the famous stock-market prediction he made in 1996? Or will be be proven right?

There was a recent thread at the FIRE discussion board (NoFeeBoards.com) in which a poster brought up the famous stock-market prediction made by Robert Shiller (Yale Professor and author of “”Irrational Exuberance”) in 1996. He said that, based on his review of the historical stock-return data available to him in January 1996, “it appears that long run investors should stay out of the market for the next decade.”

Robert Shiller's Bold Stock Prediction The poster suggested that Shiller’s views on the long-term predictability of stock prices have been discredited as a result of the failure of his prediction to come true (presuming that we do not see a big drop in stock prices by the end of this year). I maintain the opposite, that subsequent events back up Robert Shiller’s understanding of what the historical stock-return data tells us more than they discredit it.

The poster is making a fair enough observation in pointing out that the events that Robert Shiller said were coming to pass within 10 years are not likely to come to pass within that time-period. In that sense, Robert Shiller has indeed been proven “wrong” in his prediction.

The 10-year time-frame he put forward was a relatively insignificant aspect of the groundsbreaking message being delivered by Shiller at the time, however. Lots of evidence has accumulated in the past 10 years (including evidence gathered as part of our community’s Great Safe Withdrawal Rate Debate) that backs up the claims made by Robert Shiller far earlier.

Robert Shiller Was More Right Than Wrong

It probably will turn out that Shiller got the 10-year thing wrong. But look at what he got right! Robert Shiller was telling us nearly ten years ago important stuff about what the historical data says re long-term stock performance that the vast majority of investors still do not understand today. And the evidence backing up his arguments just keeps getting stronger and more compelling all the time. I don’t think Robert Shiller has anything to apologize for in guessing wrong just a wee bit as to when the things that the historical data says are going to happen actually do take place.

Robert Shiller’s mistake was in giving a precise date by which he expected to see stock prices fall. Giving short-term stock predictions is generally a fool’s game. Shiller is no fool, of course. My guess as to what happened is that he was trying to give a long-term stock prediction (where the odds of being proven right are good) and instead gave a short-term one (where the odds of looking like a fool are good).

Is 10 years a long time-period or a short time-period for purposes of measuring stock performance? It’s a twilight zone time-period, too long to be considered truly short and too short to be considered truly long. Stock valuations were very high in 1996. Looking at the historical data that existed at the time Shiller made his prediction, I can see why he was led to conclude that it was likely that we would see a big downturn in prices sometime within the next decade.

How Does Robert Shiller Predict the Future?

What caused Shiller’s prediction to go wrong is that we entered uncharted waters in recent years. There is no earlier time-period in the history of the U.S. stock market in which stock prices have remained this high for this long. Robert Shiller was fooled. But he was fooled for the best of reasons. He was fooled because he knows the true meaning of the historical data so well that he realized the great statistical unlikelihood of what has come to pass in the past 10 years.

What Matters and What Doesn’t

Robert Shiller really will be proven wrong on the small point (unless stock prices fall dramatically within the next few months). The important practical point for investors seeking financial freedom early in life, however, is that his groundsbreaking research has been vindicated on the big points. What difference does it really make if it takes 10 years for those who bet too heavily on stocks to regret doing so, or 11 years, or 12 years, or 13 years?

The true buy-and-hold investor is not concerned with whether something happens in Year 10, Year 11, Year 12, or Year 13. He is invested in stocks for the long run. In the long run, Shiller is going to be proven right, if stocks perform in the future anything at all in the way in which they always have performed in the past. That’s what matters.

Stock prices are going to head downward in years to come because they must. The speculative component of the return on stocks has grown too large to be sustainable for the long term. Stock prices are going to move to more moderate levels sometime in the not-too-distant future.

I’m not going to pull a Shiller. I’m not going to say when this is going to happen. But I am confident based on what I know of the message of the historical stock-return data that it is indeed going to happen. I am also confident that Robert Shiller will be recognized in days to come as a pioneer in development of the Valuation-Informed Indexing approach to stock investing (as will William Bernstein, Rob Arnott, Andrew Smithers, Peter Bernstein, Scott Burns, and John Walter Russell).

I doubt whether the investors who listened to Robert Shiller’s words of warning in 1996 are going to regret doing so because those words did not come true until 2007 or 2008 or 2009. My guess is that some of those who ignored Robert Shiller’s warnings may come to see that they are overlooking the forest for the trees in taking comfort that Robert Shiller may be proven wrong on the small point while being proven right on the aspects of the question that matter most.

 

Community Comments on Predicting Stock Returns

The thread on The Stock-Return Predictor at the Vanguard Diehards board is the second-longest (over 650 posts) in the history of that forum. Set forth below are snippets of some of the most helpful observations for the benefit of those who are not sure whether it is worth taking the time to read the entire thread. It is my hope that those who find value in the comments set forth below will be thereby persuaded to make time to read the entire thread.

hocus: “Until publication of the calculator, though, stock investors have not had a means of quantifying the valuation effect and of thereby putting advice to be wary of the effect of valuation changes to significant practical use.”

Probability Investing Russell: “Your calculator seems to show a dip at the 40 year mark …Is it just a peculiarity of the historical data?”

hocus: “Stocks have generally provided higher returns in the post-1921 era. So the predictions based on the larger data set (the 40-year, 50-year, and 60-year results) are slightly lower than what would be obtained from the more recent data only.”

statsguy: “Your calculator provides less pessimistic 10-year returns than the Weigand and Irons model from “Forecasting Stock Returns Using the Market P/E Ratio”, Journal of Portfolio Management (December 2005). The differences are small but significant if I did the calculations correctly.”

ccassell: “We can disagree on what to do with this information, but I don’t think we can debate the merits of this type of forecasting, unless we believe ‘this time it’s different.’ ”

Allan: “I’ve seen absolutely nothing from you [hocus] that I can use in a tangible fashion to formulate an investment plan. Your ideas are so mushy that it’s a complete waste of time to even consider them.”

ccbwc: “For real returns to be as high as your “Worst Possible” scenario over the next 30 years either: (a) Dividend growth will need to be about 50% higher over the next 30 years than it has been historically; or (b) Stocks will need to become more highly valued (as measured by dividend yield) than they are today.”

HockeyMike35: “It also uses data from all the way back to 1870. Does anyone really think earnings were reported in the same way then as they are now?”

JohnDCraig: “I prefer the Shiller general observations and the Gordon Equation to the JWR model. Among other things, the model builds in an historical 7 percent real return, which I don’t believe is supportable.”

cashNcarry: “Snake oil wrapped in a lot of babble and name dropping.”

hocus: “Think of these predictions as you think of weather predictions. When you hear that there is an 80 percent chance of rain tomorrow, do you jump to the conclusion that it is absolutely going to rain? No. But you don’t plan a picnic for a day when there is a prediction that there is an 80 percent chance of rain, right?”

statsguy: “I do not think I would trust the calculator until this research has passed rigorous refereed review.”

Predicting Stock Returns soaring: “No doubt to me that I come away with – valuation at time of retirement has a big impact on the long-term withdrawal rates so as not to run out of money. Now how I deal with that information is my challenge.”

hocus: ‘The difference is that I take this stuff seriously enough to directly state the implications of what we have learned in recent years about how to invest successfully for the long run. I think it is wrong to soften the blow. I think the story should be told straight.”

HockeyMike35: “Shiller with his PE10 data said there was a bubble in 1996. If you acted on that information and sold you would have missed out on ~8 the gains in the market over the last 10 years.”

Trebor: “Do you really think your simple tool is ‘wiser’ than the market? If it was that easy, everybody would be doing it.”

focus: “The expected return of stocks needs to be at least the Treasury Inflation-Protected Securities (TIPS) rate for stock investing to make sense.”

ccbwc: “I have used valuations to adjust my asset allocation for many years with very favorable results. My approach is different and more complex than Rob’s.”

Jim02: “I applaud his effort to inject another piece of objectivity into a very complex, highly subjective topic: making money in the market.”

stevec: “I don’t care if you do or don’t believe that the market will behave similarly as the past. Either way, this is an excellent way to understand what the US market has done in the past.”

hocus: “All of the calculations were done by John Walter Russell. My role in our partnership is to give people who don’t like what the historical stock-return data says about the effect of valuations on long-term returns somebody to yell at on internet discussion boards. (Yes, that’s a joke–sort of.)

Jim02: “I do have a problem with the idea that a dramatic shift in stocks will not be followed by a corresponding shift in bonds. The markets are not disconnected. Investors will continue to demand a risk premium.”

JWR1945: “William Bernstein got it wrong….You can’t have it both ways: a long-term return of 3.5% that lies between 6.5% and 7.0%.”

Know Your Stock Return in Advance

earnabuck: “It really is a shame and indefensible that so many feel the need to jump into it with no interest of posting on the topic but just to disrupt. Are you folks that insecure? I do know one thing, your character has shown loud and clear. Clearly some on the forum have an interest in this topic. If you don’t, stay out!”

JWR1945: “How often do you see confidence limits with financial predictions? Why don’t you see them with the Gordon Model? You should see them on a routine basis. Even if not perfect, they are a whole lot better than having a single number. This is a major shortcoming in today’s financial reporting. Would you really pay much attention to a Gordon Model debate, predicting ten years into the future, with a precision of 0.2% or 0.3%, if you knew the confidence limits? They are in the neighborhood of plus and minus 6%!”

JohnDCraig: “Irrational behavior in investing does follow certain patterns, and this has been well documented in many writings. Just how many experts in behavioral finance believe that such knowledge can be used to predict markets? Basically none, though they do believe such knowledge is generally helpful in investing. Similarly, you model is helpful, but IMO cannot attain the level of predictive value that you seem to claim.”

JWR1945: “I am comfortable using a simple, Gaussian (normal, bell shaped curve) approximation at the 90% (two-sided) confidence level. I believe that you can reasonably increase the precision to 95%, maybe even to 98%, with care, but not more. Higher precision takes you into the realm of what Nassim Taleb and Benoit Mandelbrot do.”

earnabuck: “Many take the SWR studies and consider them of value, though they are based on history. This goes above that to show, based upon that same past history, what the probabilities are for the future at various starting points. If the first has value, than surely this does too.”

JWR1945: “I have limited myself to using the most reliable statistical approximation that has meaning even though doing so limits my claims of statistical precision to 90% (two-sided, 95% one-sided). I have been careful to establish a theoretical basis to support my methodology. I have run a variety of out-of-sample type backtests…. My procedures cannot protect against a new, higher plateau. But it is easy to calculate an adjustment…. I have avoided excessive precision. This leaves open opportunities for others to calculate better numbers. They will need additional assumptions, but most will make sense.”

focus: “One point you made is that plugging in P/E10=20 gives a 10-year return of -3 to +9 . To me this shows that the range of results is so wide that you only get actionable information when the input is at the extremes.”

JWR1945: “I was careful to restrict myself to a single data source, Professor Robert Shiller’s database, because it should be a consistent set of numbers. I restricted the starting point to 1921 with the year 10, 20 and 30 returns specifically to keep us in the modern era. The P/E10 relationships are good at all times except for the single decade 1901-1910. (Gummy isolated this.) However, using more recent data is better than using the entire historical record (data starts in 1871, but P/E10 is not available until 1881). Working with real returns, the 1921-1950 data is reasonably consistent with the post-1950 data. Including 1921-1950 data adds data points without introducing serious errors. By the time that we extend the timeframe to 40, 50 and 60 years, we have to include the days with the Gold Standard and the days before the Federal Reserve…. Another point, highly important: I matched timeframes in my calculations. I used what happens in 10 years to estimate what will happen in 10 years. Similarly with 20 years and so forth. The market’s actual statistics are the standard. At least with the S&P500, failing to match timeframes causes serious errors.”

Robert Shiller's Research

hocus: “I find it revealing and disturbing that there are a number of people who generally describe themselves as “pro-stock” who have reached a point at which they feel that defending the Stocks-for-the-Long-Run Investing Paradigm requires that they argue that long-term stock returns are not predictable. The primary engine of the past bull market was the finding that long-term stock prices are predictable, and the claim that the predictability of long-term prices makes this asset class a good investment choice ‘for the long run’despite its frightening short-term volatility.”

JWR1945: “The most important application of the Stock-Return Predictor may be that it allows you to focus on what has changed, what is different from the past. It takes care of the numbers from the past. You can pay more attention to what is important, especially in terms of your own personal situation…. I agree with Rob Bennett that human (emotional) factors are far more important than numbers in isolation. How do you stick with stocks long enough to get to year 30 if you have lost money at year 10 and if you are barely above water at year 20? Should we really expect people to trust promises of financial success at year 30 if they have to live through that?”

hocus: “It’s not just the old SWR studies that got important numbers wrong, however. All sorts of investment analyses are proven wrong by this calculator.”

JWR1945: “The Gordon Model makes its best predictions 5, 10 and 15 years into the future. It does not do as well at 20 and 30 years. These are new findings. Previously, the Gordon Model had been associated only with the long-term.”

hocus: “It’s only in recent decades that we have gained the calculating tools we need to determine the message of the historical data accurately and effectively and conveniently and with a good bit of completeness. However, we also experienced the longest and strongest bull market in U.S. history during those same decades. So the early uses of these new tools have been efforts in investor self-deception. Most existing “studies” of the historical data are projects aimed not at learning what the data itself says, but projects aimed at rationalizing the absurdities of an extreme bull-market psychology.”

JWR1945: “This opinion is from pages 33 and 34 of “Common Sense on Mutual Funds” by John Bogle — ‘This analysis takes into account my conviction both that the performance of individual securities is unpredictable, and that the performance of portfolios of securities is unpredictable on any short-term basis. While the long-term performance of portfolios is also unpredictable, a careful examination of the past returns can establish some probabilities about the prospective parameters of return, offering intelligent investors a basis for rational expectations about future returns.’ ”

hocus: “There are hundreds of people who contributed to this. I think we all should be very proud of what we have done together. This calculator demonstrates in a compelling way the power of this new internet discussion-board communications medium.”

JWR1945: “You have described what I named “Idiot Switching.” It is about the worst kind of honest switching algorithm that I can imagine: jumping in and out, 100% or 0% stocks….I acknowledge that short-term timing is possible, with difficulty, with much greater sophistication than in the study, but with much lower returns than most studies indicate. Rob Bennett is not even willing to go that far. He questions whether short-term timing is ever feasible, at least for the investing public.”

hocus: “I noted above that the P/E10 that applies today–26–is an extremely high P/E10 level. But look at the most likely 30-year return predicted by the calculator — 5.4 percent real. Is that an “anti-stock” finding? It sure doesn’t seem so to me . It is critically important to show the differences between stocks held for 10-year time-periods and stocks held for 30-year time-periods. There are all sorts of strategic implications that follow from understanding that stocks provide different sorts of returns over different sorts of time-periods.”

JWR1945: “You can use TIPS to coast through an extended bad period even if you have to draw down principal. Your staying power is much better than you might imagine. Typically, you can coast through a decade while retaining 80% of your original buying power while making significant withdrawals.”

hocus: “Go to the calculator and plug in two P/E10 values right next to each other — say a P/E10 of 19 and a P/E10 of 20. The lower P/E10 will give results that are more appealing, but not all that much more appealing. Now take a look at the range of possible returns identified as possibilities by the calculator. The range over 10-year time-periods is large. The combination of these two realities tells you that putting two much stress on small changes in valuation is not likely to produce good results.”

Timing the Market Successfully JWR1945: “When you actually get close to the long-term, the Gordon Model routinely differs by plus and minus 3% to 5% from the historically accurate value, around 6.8% (real, annualized). Those are huge errors.”

hocus: “My understanding (I’d like to be corrected on this point if my current understanding is wrong because many of the strategies of the Valuation-Informed Indexing approach are rooted in this understanding) is that the long-term annualized return of 6.8 percent real does not contain anything speculative in it….If you purchase at moderate valuations, you stand a good chance of getting there within 10 years. If you purchase at today’s valuations, you will likely be getting into the neighborhood of 6.8 percent at the end of 30 years, but it might well take 60 years or longer to get all the way there. If you purchase at times of low valuation, you will likely have a return well in excess of 6.8 percent at the end of 10 years, but you will also likely see your return fall to something close to 6.8 percent by the end of 60 years.”

JohnDCraig: “I think it is very important for you to refine your understanding in this regard, since I am quite certain that neither Bernstein nor Swedroe would agree with your belief that the S&P index is sure to obtain annualized real returns of 6.8%. On the other hand, it seems quite clear that Taylor and Michael do agree with your conclusions on this point. I think what is needed is a full understanding and resolution of these differing views.”

hocus: “The stuff we are talking about here is fundamental stuff. It astounds me that there is so much uncertainty on such basic points. I can tell you what people like Bogle and Bernstein and Burns and Clements say in their books and articles and speeches. I can’t resolve the contradictions between the things they say at some places and times with the things they say at other places and times. The reality is that the big-name investing experts regularly contradict themselves on the most basic points of how stocks work.”

JWR1945: “As for other experts: what is missing are CONFIDENCE LIMITS. Those experts disagree about fine grain adjustments that are small fractions of the actual scatter observed throughout history. In reality, their disagreements involve ‘angels dancing on the head of a pin.'”

hocus: “Has Bernstein ever tried to make sense out of the jumble of contradictions he puts forward in the pages of his book? It is not my intent here to rag on Bernstein. He ain’t the only one doing this sort of thing. I’ve seen Bogle do it. I’ve seen Scott Burns do it. I’ve seen Jonathan Clements do it. The problem they all face is that the now-dominant investing paradigm is flawed to its core. The central premise — that stocks always offer a strong value proposition — is false and has been proven false.”

JWR1945: “With ideal inputs (dividend yield, real earnings growth and P/E10 change), the Gordon Model can cut the uncertainty range at year 10 to plus and minus 3% (at the extremes). This is one-half of the plus and minus 6% confidence limits of the Stock-Return Predictor. But the Stock-Return Predictor requires only the initial value of P/E10. With ideal inputs (dividend yield, real earnings growth and P/E10 change), the Gordon Model can match the uncertainty range of the Stock-Return Predictor at year 20 of plus and minus 2% (at the extremes). But the Stock-Return Predictor requires only the initial value of P/E10. The Stock-Return predictor is more accurate than the Gordon Model at years 30 and beyond.”

The Gordon Equation hocus: “Valuations don’t mean much in the short-term (time-periods of five years or less) because stock prices appear to be unpredictable in the short-term. Valuations don’t mean much in the very long-term (time-periods of over 30 years) because in the very long run there are so many ups and downs that they counter each other and the only thing that matters much is the real economic return (6.8 percent, presuming that stocks continue to perform in the future somewhat as they always have in the past). It is in the time-period from five years out to about 25 years out that valuations are a big deal.”

focus: “I would never invest in anything without having any idea what the expected return is. For instance, I would not walk into a bank and say “I’ll take one CD, please” without asking what rate they are offering.”

hocus: “People set the prices of stocks. So, yes, the P/E10 value is providing information bits about people. It’s a tool that tells you whether people at the moment are properly enthused about stocks, over-enthused about stocks, or under-enthused about stocks. The fact that people today are over-enthused about stocks does not reflect poorly on the asset class. Stocks are fine — at a reasonable price. The problem is that people have bid up the price of stocks so high that there are many circumstances in which buying stocks does not make sense. But that will change. People will come to their senses, and stock prices will return to moderate valuation levels. When they do, the P/E10 value will tell you so.”

JohnDCraig: “This model says that there is a 60% chance of a negative ERP in the next 10 years. Bogle and Bernstein both say that attempting to measure short-term returns (defined by Bernstein as less than a few decades) with any precision will likely do one more harm than good. Bogle describes in his book, Common Sense on Mutual Funds, how humbling an experience it was for him when he attempted to forecast 10 year returns in 1990.”

hocus: “Bogle’s mistake was being too precise. Please note that The Stock-Return Predictor avoids this trap by employing only the level of precision permitted when using a statistically valid examination of the historical stock-return data to generate the numbers.”

JWR1945: “For the first 15 years, you should dollar cost average either entirely into stocks or entirely into TIPS. At today’s valuations, you should dollar cost average entirely into TIPS. At year 15, continue to dollar cost average into your portfolio. You should vary allocations in accordance with P/E10 (i.e., what I call switching). Use the same switching algorithms as for retirement. The reason to begin switching at year 15 is that you have money. Only then does downside risk becomes meaningful.”

hocus: “I’ve seen things said on investing boards that I have never heard said in discussions of any non-investing topic. I think a case can be made that the question of whether valuations affect long-term stock returns is a topic that causes more people more emotional angst than does abortion or impeachment proceedings or the war in Iraq.”

focus: “Just using one factor to forecast returns is probably inadequate. For one thing, we need to know how well your current single factor model, i.e. P/E10, explains the future returns. Something like R-SQUARED needs to be made known. Somebody already linked to the Weigand and Irons paper that showed a six factor model that was superior to a single factor P/E model, so there is already academic work on that subject.”

hocus: “Extreme actions in either direction are a mistake, in my view. It is extreme to go with a 70 percent stock allocation with prices at today’s levels. It is also extreme (in most circumstances) to go with a zero percent stock allocation….The key is that you hold your stocks long enough to escape the 10-year numbers and the 20-year numbers and make it to the green fields of the 30-year numbers.”

The Stock-Return Predictor

JWR1945: “Earlier on this thread, someone pointed me to an academic study which claimed high levels of r-squared (and they were right), but which had much lower levels of r-squared than I routinely report. Let’s understand this number. R-squared simply tells us the strength of a correlation. It doesn’t tell us the size of the data spread. Even if r-squared were zero, the calculator would be right as long as I got the confidence limits right. Since r-squared is not zero, there is a shift in the most likely result. When we include the effect of the effective degrees of freedom, we find that the most likely result is known to about plus and minus 1% (which is just under 20% of [times] the confidence limits) for the Year 10 results. The most likely result varies much more than an adjustment of 1% (added to or subtracted from annualized total return percentage number). Whoever has been spouting off about bad r-squared numbers hasn’t done his homework.”

hocus: “I look forward to a day when there are scores of calculators on the internet that do what the Predictor does. The publication of more calculators will inspire more debate. More debate will teach us new things. Learning new things will help us develop enhancements for the Predictor. It’s a win-win-win.”

Andy71: “How long before you add a reference on your web site taking credit for starting yet another great debate in the investment community? Can it count as a great debate when 80% of the posts are by the thread’s 2 authors?”

hocus: “We are witnessing something phenomenal, Andy. I am totally convinced of that. I believe that we are seeing what Change looks like when we watch it play out in front of us up close and personal and in real time. There’s great stuff on this thread, from all sorts of people. It’s been a wonderful community effort and a wonderful Learning Experience for all who elected to take advantage of it.”

JWR1945: “The standard, normal, bell shaped, Gaussian statistics are best for the kind of thing that I am doing here. Specialized techniques are appropriate when buying and selling $100s of millions in derivatives.”

hocus: “The suggestion that I am expecting to see some pretty darn juicy long-term terms from the stock asset class is on the mark. I am a stock guy, and don’t let anyone tell you different. I think stocks offer the middle-class worker the best opportunity available to him to generate lasting wealth. The key is walking the buy-and-hold walk as well as talking the buy-and-hold talk. I believe that the historical stock-return data lays out a blueprint of what is required to pull that off (not to say that there won’t be any surprises) for the benefit of those willing to tune into its message.”

focus: “I like to think of the more traditional thinking that the stock market always has an expected return of about 7% real as a Zero-factor model. In other words, the expected return is a constant and not dependent on any factors. It is not a bad estimate taking no other information into account. Your model is a 1-factor model–it uses a single factor to explain future returns. I believe that taking that one additional bit of information into account greatly improves the forecasting model. Then you can add more variables like inflation, recent earnings growth rate, recent volatility, etc., like Wiegand and Irons did in their paper and get better forecasting models. Then the debate really becomes which variables should be considered and which excluded. So your model is a good step towards better and more accurate forecast models.”

modern portfolio theory hocus: “There are numerous ways in which the valuation factor is different from the others. One is that valuation is a huge factor. There are circumstances in which the valuation factor alone determines 50 percent of the total return. So ignoring valuations is simply not prudent. Also, we have lots of data on historical valuations, so we have a means of assessing its impact with more accuracy than can be achieved for the other factors. Also, we have control over the valuation level at which we make our stock purchases. So knowing the effect of this factor permits us to enhance our investment results in a way that we can not generally enhance them with knowledge of other factors.”

Sirschnitz: “Just as Investors are interested in the success of their portfolios, Professors are interested in the success of their theories. It’s part of the ‘human thing’.”

hocus: “I used to think that the reason why this assumption was employed was to make things look not so bad for the next 10-year period. It does do that, of course. I always thought that it was an unfortunate practice not to expect valuation changes because it understates the risks that investors face when going with high stock allocations at times of high valuations. I now see a second problem with assuming no valuation changes — it also understates the 30-year return.”

JWR1945: “If valuations were to remain constant, the mathematical requirements of the Gordon Model would be satisfied. The Gordon Model would have been correct throughout history. Examination of the Gordon Model’s 30-year historical performance shows that it has not been accurate. By the time that you reach 30 years, it routinely misses by 3% to 4%, with peak errors near 5%. The problem with the Gordon Model is that valuations change. Reinvested dividends yield something different from the initial yield. Those reinvested dividends earn more (after valuations have fallen) if valuations started out high. Those reinvested dividends earn less (after valuations have risen) if valuations started out at bargain levels.”

hocus: “Bogle and Bernstein have been talking about the effects of valuation changes for a long time. Bogle and Bernstein have failed in that time to translate the insights they have put forward into practical and actionable and reasonable and balanced investing advice. Both things are so.”

JWR1945: “The article looks at P/Ex. The Stock-Return Predictor actually uses 100/[P/E10]. The earnings yield and returns have a linear relationship (theoretically). Price to earnings does not.”

hocus: “Some stock advocates try to plant the suggestion that they are not basing their decisions on predictions of what may happen or expectations as to what may happen. They are either not talking straight or not thinking straight. It is an essential step in the asset allocation process to form some sort of view as to what sort of return it is reasonable to expect from the various investment classes. So the question is not — Should you form expectations re returns or not? It is — Should you look at the historical stock-return data in forming those expectations or not?”

Vanguard Diehards at Morningstar

JWR1945: “In terms of calculating 30-Year Safe Withdrawal Rates, P/E10 is a clear-cut winner. In terms of predicting Year 10 stock market returns, Tobin’s Q is best and 1/Tobin’s Q and 100E10/P are almost the same according to R-squared (with identical variances). However, Tobin’s Q and 1/Tobin’s Q have a problem with outliers. In terms of predicting Year 20 stock market returns, P/E10 is clearly superior.”

hocus: “It’s not possible for those who have come to believe that stocks are always best to accept that valuations always matter. The two beliefs are mutually exclusive. If valuations matter, there is obviously some valuation level at which stocks are not best. The two paradigms cannot be reconciled.”

The Experts Speak on the Effect of Valuations on Long-Term Returns

Investing Expert #1 — Jack Bogle (Vanguard Founder) on the Effect of Valuations on Long-Term Returns

Long-Term Returns

“This analysis takes into account my conviction both that the performance of individual securities is unpredictable, and that the performance of portfolios of securities is unpredictable on any short-term basis. While the long-term performance of portfolios is also unpredictable, a careful examination of the past returns can establish some probabilities about the prospective parameters of return, offering intelligent investors a basis for rational expectations about future returns.” — Page 33 of Common Sense on Mutual Funds

Investing Expert #2 — William Bernstein (author of The Four Pillars of Investing) on the Effect of Valuations on Long-Term Returns

“We’ve just acquired a much more valuable piece of information: the long-term expected return of the market. Think about it, which would you rather know: the market return for the next six months, or for the next 30 years? I don’t know about you, but I’d much rather know the latter. And, within a reasonable margin of error, you can. — Page 55, The Four Pillars of Investing

”The ability to estimate the long-term future returns of the major asset classes is perhaps the most important investment skill that an individual can possess.” — Page 73, The Four Pillars of Investing

Investing Expert #3 — Ed Easterling (author of Unexpected Returns) on the Effect of Valuations on Long-Term Returns

“Average returns and long-term probabilities of loss do not tell the whole story. The probability of loss while owning the market over a long enough period of time may indeed be minimal, but the probability of loss for periods of years, even decades, can vary dramatically depending on the market’s level of valuation. The probability of loss may be very high when valuations are high, very low when valuations are low, and modest when valuations are average.” — Page 185, Unexpected Returns

Investing Expert #4 — Andrew Smithers (co-author of Valuing Wall Street) on the Effect of Valuations on Long-Term Returns

“The stock market resembles roulette in several ways. In both cases the accuracy of sensible forecasts rises over time. The longer you play roulette the more certain you are of losing. Over time forecasts of stock market returns also become more reliable. If this were not in each case largely ignored, no one would play roulette and share prices today would be much lower….The evidence that stock market returns are not random seems to be little understood, or at least seldom used. This may reflect the training of those who make forecasts of equity returns, or simply the fact that it would render them extremely unpopular with their clients if they did so.” — Article entitled “A Case of Panic Now, Not Later”

Investing Expert #5 — Robert Arnott (editor of the Financial Analysts Journal) on the Effect of Valuations on Long-Term Returns

Investing for the Long Term

“Returns are for the most part a matter of simple arithmetic. For almost any investment, the total return consists of yield, growth and multiple expansion or yield change…. For stocks, based on very long-term history, growth tends to be around 1 percent above inflation. The 7 percent returns for the past 77 years, covered in the Ibbotson data, consist of roughly 4.5 percent from dividend yield, just over 1 percent from real dividend growth and 1.5 percent from multiple expansion (Ibbotson and Chen, and Chin, 2003). So why expect 7 percent in the future? The U.S. equity yield is currently well under 2 percent. And we probably should not count on resumed multiple expansion because the market is not cheap by any conventional definition. Much of our industry seems fearful of basic arithmetic of this sort.” — an Editor’s Corner column in the Financial Analysts Journal entitled “Is Our Industry Intellectually Lazy?”

Investing Expert #6 — Cliff Asness (author of the papers “Bubble Logic” and “Rubble Logic”) on the Effect of Valuations on Long-Term Returns

“Consider the hallowed property of equity returns — that stocks never lose if held for the long term. Well, if a decade is your idea of the long term, then this adage is true only if prices start out in the lower three valuation buckets. When prices start out more expensive, there are decades when stocks not only lose to inflation but lose big.” — a paper entitled “Rubble Logic: What Did We Learn from the Great Stock Market Bubble?”

Investing Expert #7 — Robert Shiller (author of Irrational Exuberance) on the Effect of Valuations on Long-Term Returns

“There is some popular confusion about..predictability in forecasting long-horizon returns….A related confusion concerns the apparent random-walk property of one-year returns. How, some will ask, can it be that one-year returns are so apparently random, and yet ten-year returns are mostly forecastable?..In looking at one-year returns, one sees a lot of noise, but over longer time intervals this noise effectively averages out, and is less important.” — A paper entitled “Price–Earnings Ratios as Forecasters of Returns: The Stock Market Outlook in 1996”

Investing Expert #8 — Michael Alexander (author of Stock Cycles) on the Effect of Valuations on Long-Term Returns

“No analyst can give precise answers to questions about the future of the stock market or the economy and be right all the time. This is the realm of prophecy and fortune-telling, not scientific analysis. On the other hand, it is not true that the future is completely unpredictable. As I write this sentence in January 2000 the temperature outside is well below freezing. If you were to ask me to predict whether it will be warmer or cooler next Tuesday, I would be unable to give a correct answer. However, if you asked me what sort of temperature to expect on April 9, I could predict “warmer than today” and almost certainly be right.” — Page 8 of Stock Cycles

Investing in Index Funds

”The effect of holding time on stock returns in overvalued markets is the opposite of what it is for all markets. Normally, holding stocks for longer periods of time increases the probability that they will beat other types of investments such as money markets. This observation led to the commonly held belief that for long-term investors, any time is a good time to invest since the long-term trend in Figure 2.1 dominates over time. In the case of overvalued markets (like today) holding for longer times, up to 20 years, does not increase your odds of success.” — Page 30, Stock Cycles

Investing Expert #9 — John Hussman (President of Hussman Econometrics Advisors) on the Effect of Valuations on Long-Term Returns

“The notion that rich valuations on record profit margins can be overlooked, and will not be followed by sub-par long-term returns, is a speculative idea that runs counter to all historical evidence. It is an iron law of finance that valuations drive long-term returns.” — Minding the Hinges on Pandora’s Box, January 7, 2008.

What’s Wrong (and Right) with Using Historical Stock Data to Predict Returns

Problem #1 with Using Historical Stock Data to Predict Returns — The Future Might Not Be Like the Past.

The Stock-Return Predictor does not really predict anything. It reports how stocks will perform from various valuation levels presuming that stocks continue to perform in the future much as they have in the past.

Historical Stock Data

That’s a reasonable assumption in a general sense. But it is almost certain that there will be surprises. To at least a small extent, it is certain that stocks will not perform in the future as they have in the past. It is possible, although far less likely, that stocks will perform in the future in wildly different ways from how we have ever seen them perform in the past.

The Predictor does not see into the future. To the extent that stocks perform in the future in ways in which they have not performed in the past, the results generated by the calculator will be off the mark.

Problem #2 with Using Historical Stock Data to Predict Returns — The Data Set on Which It is Based Is Limited.

We have available to us historical U.S. stock-return data dating back to 1870. That’s enough to generate meaningful return predictions using a regression analysis. The calculator would be more effective if we had more data available to us, however. More data is always better.

Problem #3 with Using Historical Stock Data to Predict Returns — P/E10 May Not Be the Best Valuation-Assessment Tool.

The Predictor uses the P/E10 valuation assessment tool to determine the effect of valuations on long-term returns. There are a good number of reasons for believing that P/E10 is the best valuation assessment tool available today. But it is possible that this is not the case.

Unfortunately, it is only a small number of investing analysts who trouble themselves to study the effect of valuations. The more people who worked this field, the more confidence we could have in our belief that P/E10 is the best valuation assessment tool. I can tell you that I believe that P/E10 does a good job. But I also urge you to research this question for yourself to come to a better understanding of the pros and cons of P/E10 and of the other valuation assessment tools available to us today.

Problem #4 with Using Historical Stock Data to Predict Returns — It Does Not Offer Short-Term Predictions.

The Return Predictor does not offer predictions for time-periods of less than 10 years. That’s because it is not possible with the tools we possess today to offer predictions that are statistically meaningful for shorter time-periods. It may never be possible.

My guess is that there would be a far greater number of investors who would be interested in making use of a calculator that offered one-year predictions or three-year predictions or five-year predictions. This tool does not pretend to be of value to any types of investors other than long-term investors.

Problem #5 with Using Historical Stock Data to Predict Returns — It Does Not Offer Much Precision in its Ten-Year Predictions.

Past Performance Is No Guaranty of Future Returns

At the time this article was written (March 2007), the 10-year annualized real-return prediction ranges from a negative 4.90 to a positive 7.10. That covers a lot of territory. Most investors would be horrified to obtain a 10-year annualized real return of a negative 4.90. Most would be quite pleased to obtain a 10-year annualized real return of 7.10.

That’s the best we can do with the tools we possess today. Knowing the range is valuable because it permits you to compare the value proposition of investing in stocks at today’s valuation level with the value proposition of investing in stocks at other valuation levels. Still, it would be nice if the 10-year predictions could be more precise. (The level of precision of the predictions improves at 20 years, and again at 30 years.)

Problem #6 with Using Historical Stock Data to Predict Returns — The Results Generated Always Cut In Two Directions.

The Return Predictor offers a dark view of the value proposition of investing in stocks today. The 20-year prediction is for a most-likely annualized real return of 2.6. You could do almost that well with risk-free Treasury Inflation-Protected Securities (TIPS).

The calculator is not telling you to stay out of stocks, however. It also reports that the 20-year annualized real return could be as high as 6.6, and that the most likely 30-year return is 5.3. Those numbers beat the socks off of what can be obtained from TIPS purchased today.

So the story is mixed. Stocks are generally not a good buy. But strong arguments can be made for investing a portion of your portfolio in stocks all the same.

The calculator is showing you how stock investing really works. The calculator is helping you to appreciate the long-term investing realities. Still, the sophisticated message being delivered by the calculator can be viewed as a negative in that it may confuse users who do not spend enough time with the calculator to appreciate fully what it does. This is a tool aimed at the investor who is serious enough to spend a bit of time coming to appreciate the complexities of real-life stock investing.

Problem #7 with Using Historical Stock Data to Predict Returns — It is Not Diplomatic.

Few of today’s investing experts are willing to tell it straight to their readers. Some of the best-informed will occasionally make note of the dangers of investing in stocks at today’s prices. Most engage in lots of happy talk, seemingly more concerned with remaining popular than with helping their readers avoid the portfolio-destroying losses that are characteristic of today’s high price levels.

History of Stock Investing

Many investors have become so accustomed to happy talk that they have come to view it as “rude” for someone to cite what the historical stock-return data says about the effect of valuations on long-term returns. The calculator reports numbers. When we are at the valuation levels that apply today, the numbers are not pretty. The calculator tells it like it is. The calculator is “rude” without intending to be. It reports numbers that a good number of investors would prefer not to hear.

Problem #8 with Using Historical Stock Data to Predict Returns — It Can Easily Be Misused.

Any tool can be misused. I can imagine a user of this calculator thinking that the return identified as “most likely” is certain to turn up. No! It doesn’t work that way. The most-likely return is bit more likely to turn up than any of the alternatives. But in all likelihood the real-world return is going to be a number at least somewhat higher or lower than the return identified as “most likely.”

Please spend some time thinking through how the calculator works and what it really is saying before putting it to use. Ask questions. Take the results you obtain and check with other sources as to whether they make sense or not. Use the calculator as a learning tool, not as a magic genie that sees into the future and tells you all that you need to know to invest without you also making use of both your common sense and all the rest of what you have learned about investing over the years.

Problem #9 with Using Historical Stock Data to Predict Returns — There Are Few Similar Calculators Available Today.

There is no other publicly available calculator that does precisely what the Stock-Return Predictor does. There are few web sites or books that offer information even similar to the information available through the Predictor.

It is my hope that that will change over time. As more such calculators are made available, we will discover enhancements that can be made to this one. Someone had to get the ball rolling by making such a tool available, and I am proud of the Stock-Return Predictor. I don’t view it as a perfected tool, however. We learn through trial and error. It’s not possible for the first version of anything to be the perfected version.

Problem #10 with Using Historical Stock Data to Predict Returns — Only Investors With Emotional Fortitude Will Be Able to Make Good Use of This Tool.

Stock Research

The information provided by the Return Predictor can make you a better investor. But guess what? The calculator provides only information. The most important factor determining how successful you will be is your emotional fortitude in sticking to a sound strategy when it’s not easy to do so. The calculator can serve to help build your confidence. It cannot do the job alone.

I am a firm believer that the most important aspect of the investing project is the emotional aspect. Please don’t ever come to believe that a tool like The Stock-Return Predictor can by itself transform you into a true long-term buy-and-hold investor. It’s a help. That’s all that it is intended to be.

Benefits of Using the Historical Return Data for Predicting Stock Returns

Benefit #1 of using historical return data for predicting stock returns — it permits you to know whether stocks are worth buying at the price they are being offered or not.

Historical Return Data

When purchased at a P/E10 valuation of 14 (a moderate valuation level), the most likely 10-year return on an investment in S&P stocks is 6.3 percent. When purchased at a P/E10 valuation of 27 (the valuation level that applied in March 2007, when this article was posted), the most likely 10-year return on an investment in S&P stocks is 1.1 percent. Those are greatly differing value propositions.

For most investors, there are some valuation levels at which it makes sense to buy more stocks and some valuation levels at which it does not make sense to buy more stocks. Predicting stock returns lets you know whether buying more stocks at the price level being offered to you at a particular time is a good idea or not.

Benefit #2 of using historical return data for predicting stock returns — it confirms the conventional wisdom of recent decades that stocks offer an outstanding value proposition when held for the long run.

Let’s make another effort at predicting stock returns for purchases made at a moderate stock valuation level (a P/E10 of 14) and at a high stock valuation level (a P/E10 of 27), this time looking at the most likely 30-year return rather than the most likely 10-year return. Go 30 years out, and there is not nearly as great a difference between the results obtained at the two very different valuation levels. The most likely 30-year return at the moderate valuation level is 6.7 percent. The most likely 30-year return at the high valuation level is 5.3 percent.

Both of those returns are darn juicy returns, no? You can probably beat the most likely 10-year return for the investment made at high valuation levels with an investment is something safe like Treasury Inflation-Protected Securities (TIPS). But it is not going to be easy to beat the most likely 30-year return of 5.4 percent.

The moral? Stocks really are an outstanding investment class for the truly long run. It’s just important that you understand how long the long run can go at times of high valuation. Holding stocks for 10 or 20 years often is not good enough at such times. Holding stocks for 30 years will in almost all circumstances offer you a likely return that is at least acceptable. Even the worst possible 30-year annualized real return (presuming that stocks perform in the future as they have in the past) for stocks purchased at a P/E10 of 27 is 3.3 percent.

Benefit #3 of using historical return data for predicting stock returns — it reveals the benefits that can be obtained by holding off on stock purchases when stocks are at high valuation levels.

Historical Stock Return Data

S&P stocks reached their highest valuation in the history of the U.S. market in January 2000, when the P/E10 level went to 44. By March 2007, the P/E10 level had fallen to 27. That’s still very high, but not quite as absurdly high. Did that drop in prices make a material difference in the return expectations of valuation-informed indexers who held off making stock purchases until recently? It sure did.

For purchases made at a P/E10 of 44, the most likely 20-year annualized real return is 1 percent. Not good. The most likely 20-year return for purchases made at a P/E10 of 27 is 2.6 percent. That’s nothing to write home about, but it’s a big improvement on the earlier number all the same. Those who were telling you that you would surely “miss out” if you did not immediately buy stocks when they were being sold at the absurdly high prices that applied at the top of the recent price super-bubble were offering guidance that leaves something to be desired. The sort of return provided by stocks purchased at a P/E10 level of 44 is something that most of us can afford to “miss out” on.

Benefit #4 of using historical return data for predicting stock returns — it reveals what factors influence stock returns at different sorts of holding periods.

At time-periods of less than 10 years, stock prices are unpredictable. There are so many factors affecting the result that no one factor—even the all-important stock valuation factor–controls.

Meaningful predictions are possible for holding periods of 10 years. But look at how much shorter the Color Bar of The Stock-Return Predictor is at 20-years than it is at 10 years. That shortening of the Color Bar represents an increase in the precision of the prediction being made. Stocks are only somewhat predictable at 10 years. The 20-year predictions possess more clarity.

At 30 years, the Color Bar grows shorter still. There’s a good degree of precision to stock predictions made for holding periods of 30 years. When a P/E10 of 14 applies, the range of predictions at 10 years goes from 0.34 percent to 12.34 percent. That range of 12 percentage points covers a lot of territory. At 30 years, the range is reduced to 4 percentage points (from 4.73 percent to 8.73 percent). A prediction extending over a range of only 4 percentage points is providing highly meaningful information.

The precision possible in predicting stock returns does not get much better, even when the holding period extends to 60 years. At 60 years, the range is down only another 1.5 percentage points, with possible returns ranging from 5.3 percent to 7.8 percent.

Benefit #5 of using historical return data for predicting stock returns — it identifies for you the time-periods in which the starting-point stock valuation level matters most.

The starting-point stock valuation level makes a big difference at 10 years. It is my view, though, that the predictions that can be made at 10 years are sufficiently imprecise that it is for 20-year holding periods that valuations matter most.

The range of possible outcomes for 10-year holding periods are sufficiently broad that it remains possible to obtain a good return for a stock purchase made at a high valuation level. Look again at the results obtained from The Stock-Return Predictor when the P/E10 value entered is 44, the level that applied in January 2000. The most-likely return is a negative number, as noted above. But the “Lucky” return (a return that has about a 1 in five chance of turning up) is 1.9. That’s not good. But it’s not so terrible for a 10-year time-period.

How Stocks Work

Now look at the “Lucky” return for a 20-year holding period. The number is higher — 3.0 percent. But is that a better result than the 1.9 percent “Lucky” return that applied at 10 years? In my eyes, it is not. Stocks are a volatile asset class, so volatile that the long-term returns provided by them are generally much higher than either of those numbers. I think that a good case can be made that it is worse to have to hold stocks 20 years to obtain a return of 3.0 percent than it is to hold them for 10 years to obtain a return of 1.9 percent. The 10-year return is better on its face. But the 20-year return is not enough of an improvement to justify holding a highly volatile asset class for an additional 10 years.

There are two competing forces coming into play in the move from a 10-year holding period to a 20-year holding period. The likelihood that the starting-point valuation will have had time to have had an effect is becoming stronger, asserting a negative effect on the 20-year number. And the likelihood that the effect of the starting-point valuation will have begun to diminish is also becoming stronger, asserting a positive effect on the 20-year number.

The timing of the price drop cannot be ascertained in advance. So we cannot know how far on the way to recovery we will be at 20 years. But the calculator tells us the most-likely scenario. It allows us to compare the most-likely scenario at Year 10 with the most-likely scenario at Year 20 and thereby to draw a conclusion as to which time-period is of greater significance.

My view is that the 20-year number is more troubling than the 10-year number. I don’t like the idea of earning only a 1.9 percent annualized real return from an investment for 10 years. I like even less the idea of earning only a 3.0 annualized real return for 20 years. Why? Because stocks purchased at fair prices can be realistically expected to earn a 10-year return of over 6 percent. There’s generally not much appeal in having your money tied up in a high-risk asset class for 20 years and obtaining a return of only 3 percent real for your trouble.

Benefit #6 of using historical return data for predicting stock returns — it permits you to develop informed assessments of alternate asset classes.

Treasury Inflation-Protected Securities (TIPS) were paying a real return of 4.0 percent at the top of the bubble. How attractive is that return? Compare it to the long-term return offered by stocks at times of normal valuations (which is what most investors do), and it does not appear that attractive. Stocks are of course riskier. But stock investors are compensated well for taking on the extra risk at times of moderate valuations. At a P/E10 of 14, the most likely 10-year return is 6.3. That’s more than 2 points of real return greater than what could be obtained from TIPS at the top of the bubble. My guess as to why many investors did not snap up TIPS at the time is that they were thinking that it was realistic to expect returns of 6.3 real even at those times of super-bubble-level prices.

What We Know About Stock Investing
The Stock-Return Predictor tells us that it is not so. The reality is that stocks purchased in January 2000 were not even likely to provide a positive return in 10 years. TIPS were by far the better choice. TIPS offered a far higher return at far less risk.

Benefit #7 of using historical return data for predicting stock returns — it disproves the Efficient Market Theory.

The Efficient Market Theory is the most dangerous of today’s investing myths. According to this “theory” (it is more properly termed an “assumption,” one very much at odds with both common sense and the historical record), stocks always must offer a better long-term return than a risk-free asset class like TIPS. Why? Because the theory assumes that investors are completely rational in their decisions as to what to do with their investing dollars. Rational investors would not be willing to take on the risks associated with stock investing without being compensated for it. So the theory assumes that there must always be a risk premium, that stocks must always offer a better return than risk-free investment choices.

Why, then, does a regression analysis of the historical data tell us that stocks were likely to provide a negative 10-year return at a time when risk-free TIPS were offering a return of 4 percent real? Because the root assumption of the Efficient Market Theory is nonsense. Investors do of course employ reason when selecting investments. Emotion is a more important influence, however. At times of high prices, most investors cannot stand the idea of passing up stocks because they have been providing good returns in the recent past. It is generally only when stock prices are low (and the value proposition for stocks is high) that investors are willing to give serious consideration to “boring” asset classes like TIPS. I doubt very much that TIPS will ever be providing returns of 4 percent real at times when stocks are low-priced (and, thus, unappealing to most investors).

The risk “premium” remains negative to this day. A better 10-year return is available today from TIPS than is available from stocks, according to the numbers generated by The Stock-Return Predictor.

Benefit #8 of using historical return data for predicting stock returns — it teaches you that small differences in valuations don’t matter much.

The difference in 10-year returns when we go from a P/E10 of 14 to a P/E10 of 16 is 1.3 percent. That’s not insignificant. But the precision of the 10-year numbers is not high. Given the lack of precision, the 1.3 percent difference really does come close to being insignificant, in my assessment. The calculator makes a case that it does not make sense to change stock allocations except when valuations change significantly.

Benefit #9 of using historical return data for predicting stock returns — it permits you to put temporary upward and downward price movements into context.

Past Performance Is No Guarantee of Future Results

Stocks prices were coming down in 2002 and 2003. Since then, they have headed upward. Many investors have thus come to believe that it was a mistake to lower one’s stock allocation in 2002 or 2003.

The Stock-Return Predictor argues otherwise. The lowest P/E10 value we saw during the downturn was a P/E10 of 21. That’s not low enough to justify a belief that stocks offer a strong long-term value proposition. Yes, we’ve gone upward since then — for a time. To the long-term investor, however, the value proposition of stocks has remained poor for 10 years now.

Using The Stock Return Predictor for predicting stock returns permits you to distinguish price drops that are worth taking advantage of from price drops that are traps for long-term stock investors. Just because the price of stocks has dropped significantly since 2000 does not mean that stocks are now a good buy. The price had gone so high in 2000 that it would take a huge price drop even from today’s levels to get to prices where the long-term value proposition would be strong.

Benefit #10 of using historical return data for predicting stock returns — it provides you the confidence needed to become a true long-term buy-and-hold investor.

There’s a song that argues that: “Everyone’s crying mercy, but they don’t know the meaning of the word.” I think that applies to stock investing, except that in that context the way that it needs to be said is that: “Everyone’s crying ‘buy-and-hold’ but they don’t know the meaning of the phrase.”

Buy-and-hold is good stuff. Buy-and-hold works. You want to practice buy-and-hold investing.

It’s hard, though. Real hard. Few are willing to tell you how hard.

Do you know what separates those who merely talk the buy-and-hold talk from those who truly walk the buy-and-hold walk? It’s confidence. To stick with your investing strategies when they are under fire, you need to believe in them in a deep way.

Dow Jones Industrial Average

Confidence follows from preparation. There are going to be times when your investing strategies are not going to be working out so well. Those times are going to be the test of whether you successfully pull off buy-and-hold or not. If you have properly used the The Stock-Return Predictor to inform your asset-allocation decisions, you will be prepared for what comes down the line, presuming that what comes down the line is no worse than what we have seen come down the line in the past (and the price crashes of the past have been bad enough that it is none too likely that we are going to see anything much worse).

Use the historical stock-return data to inform your investing strategies, and you probably will be fine in the long run. Allow yourself to get caught up in the euphoria of wild bull markets, and you stand a darn good chance of getting burned and needing to sell at the worst possible time for doing so.

The Stock-Return Predictor generates results that are hard medicine for some to swallow. That’s just what it is supposed to do. Those of us who are serious about wanting to succeed as long-term investors need to swallow some hard medicine from time to time. Today (we are now at price levels rarely before seen in the historical record) is very much such a time.