John Hussman has written a piece about market valuation and the Fed model that breaks some new ground. It is sufficiently different from his past work to deserve some special attention.
At "A Dash" we believe that thinking about valuation is important. Some idea of overall market valuation helps both individual investors and traders by providing context about risk and reward. Significant deviations in market prices from the "fair value" of one's model provide a signal of what we call long-term sentiment, be it euphoria or a "negativity bubble."
Dr. Hussman agrees about the importance of valuation, since he writes about it on a regular basis. He is an outspoken critic of the Fed model, preferring his own approach. He uses something he calls peak earnings, referring to the highest past level of GAAP earnings. While he writes with the objective of explaining hedging strategy to his own investors, his work is widely cited.
In another element of common ground, the Hussman articles frequently cite those using an approach like the Fed model, but not naming it explicitly. The many market commentators who view current stock prices as cheap, comparing forward earnings to interest rates, are doing something akin to the Fed model, but without citing it explicitly. Our guess is that many commentators wish to avoid the debate about this approach--the intellectual baggage associated with naming it.
We have not been bashful about analyzing and naming the Fed model. We get frequent questions, from readers and our own investors, asking why our approach differs so much in its conclusion.
The Key Issues
While the purpose of this article is the current Hussman argument, readers can understand the problem better by understanding the following key issues:
- Looking backward. Hussman (and other noted commentators) prefer to look at documented past earnings rather than the forward projections of analysts. We prefer prediction based upon the forward look. Our basic rationale is that a backward view misses turning points in the market and that analyst estimates are much better and more honest now than in times past. We like to take the work of hundreds of specialists, trying to do their jobs. Our daily reading of these reports suggest that there is plenty of skepticism built into their work.
- Using interest rates. Most of Hussman's work looks at interest rates OR earnings, not putting the two together. We believe this misses the major valuation point. When interest rates were at extreme levels, stocks deservedly had a low P/E (or high earnings return if one inverts the equation) to merit investor consideration. When interest rates are low, the opposite argument holds.
- Interest rate trend. Hussman feels that the trend in interest rates is an important element. We disagree. At any point in time, Mr. Market is offering the investor a choice between stocks and bonds. The investor can lock in a return via a bond purchase. The key element is NOT the direction of interest rates, but rather is investor skepticism about earnings estimates. One factor is known, the other is a matter of forecasting.
- Relevant time period. The Fed model uses data from 1980, because that is the time when forward earnings forecasts for the S&P 500 were available. Hussman believes that this period is atypical. Readers should read his work and consider his argument carefully. We believe that the time period includes a lot of interesting variation, and provides a lot of useful information. Like any researchers, we always wish we had more data, covering more time. Having said this, going back too far can also be a mistake. The investment world is much different in the time from the mid-70's to now. The use of computers by all participants and the availability of information, and the growth of options and futures are all important changes.
The Current Question
Dr. Hussman reports research that is innovative in two important respects. First, he combines interest rates and expected earnings. Second, he uses the known period of forward earnings to create an intriguing model. He uses information about past earnings and economic trends to create a model for forward earnings. He then takes the model and applies it to the past - the period before forward earnings were readily available -- to simulate what those forecasts would have shown had they been available.
He writes as follows:
Operating earnings are a “smooth” measure of earnings that, as it turns out, can be cleanly and accurately approximated using variables that are available historically - specifically, the highest level of S&P 500 (trailing net) earnings achieved to-date, the actual level of S&P 500 trailing net earnings, and the U.S. unemployment rate (which helps to capture business cycle fluctuations). The ISM Purchasing Managers Index provides slightly better accuracy than the unemployment rate, but has a shorter history. The results below are not very sensitive to the choice, so in the interest of data availability and to make it easy for others to replicate and verify these results, I've used the unemployment rate.
From this starting point, he derives the following regression equation:
forward operating earnings = k * record trailing net earnings to-date
k = 1.2721 + 0.3115 (current trailing net earnings / record trailing net earnings – 1)
- 0.5011 (unemployment rate / 16-month average of unemployment rate – 1)
- 0.5985 ( (record trailing net / record trailing net 5 years prior) ^ (1/5) – 1)
From this equation he develops a chart showing that in the pre-1980 era, going back to 1948, the Fed model did not have a good fit.
What the Equation Means
The essential problem is that very few readers have the methodological skills to interpret the Hussman equation (which is missing some parentheses, but we get the point). That means that people will focus uncritically on the conclusion.
At "A Dash" we believe in using experts whenever possible. Our own expertise is in choosing the right experts and in research methods. Let us try to interpret the Hussman findings.
The constant term of the model shows a "starting point" of 27% earnings growth. The next variable boosts that growth by a percentage calculated by looking at current trailing earnings versus record earnings. This is the hallmark Hussman variable.
The next variable considers the unemployment rate compared to the prior 16 months, giving earnings a reduction if the rate is higher. Fine.
The final variable looks at the "record trailing net" versus the record for the last five years and gives a major haircut to estimates if the record is higher. Hmm. We do not see the logic from this variable.
Before stating our analysis of this research, the differing perspective should be made clear to readers. Dr. Hussman is a developer of a valuation method which he has used to guide his fund management. He has skin in the game, and frequently writes to investors to justify his approach. If his messages were private, we would have nothing to say. The problem is that his work gets broad exposure, including our investors and many people we are trying to help with our work.
If we believed that the Hussman method to be superior, we would adopt it in a heartbeat. Regular readers know that we follow a disciplined approach that reacts to market conditions. We represent the consumers of valuation methods, open to any approach.
We have done thousands of regression models over the years, and taught the classes for grad students. What may make eyes glaze over for most is routine for us.
Here are some key thoughts, all of which come from old class notes:
- Think about the logic of the model. The key concept of the Fed model is that investors compare forward earnings to interest rates. In the pre-1980 days they did not have this information. More importantly, they did not have access to the Hussman model! The 1948 investors could not make the relevant comparison. They were not looking at past record earnings versus the prior five years or any of his other variables. We do not know what they were thinking. While we would love to have data about this era, we do not.
- Technique of model development. Let us suppose that we know about one period of time and wish to backtest a different period - the exact Hussman problem. We would divide the known period into two groups, developing the regression equation for one and testing it against the other. If the fit is not good, how can one make a forecast for the unknown period? Hussman did not do this, and we suspect that the correct method would generate a very different regression equation.
- The logic of each variable. Each variable should have an independent contribution, meaningful in theory as well as in improving the fit. In particular, we suspect the "record earnings" variables. If removing these variables creates wild swings -- even swings in the sign --of the other variables, then the model lacks intellectual integrity. We suspect that this is true, but cannot prove it without the data.
- Optimizing parameters. Whenever we see something like "16 months" we say "hmm." The question is why this value was chosen and whether the variable is "robust."
Dr. Hussman's work is not offered as a proprietary model. He is an advocate for his approach. Given this, he should be willing to share the data and invite alternative analysis.
Dr. Hussman's quest is a good one. He is an excellent business person and advocate for his method. If he is confident of his results, he should be willing to have peer review of his work, they way it is done in academic circles.
Meanwhile, we do not see the advantages of this approach.