Straight Talk From Ken Fisher

Explain some of the ideas driving your investment strategy. We have a theory at Fisher Investments that the human brain in its investing activities derives from Stone Age processes. The brain was set up to think about things a long time ago, and it was not set up to think about the financial markets. So it adapts what it is good at to investing. Investors act like hunter-gatherers, collecting. They look for categories they believe in and think they understand, such as growth and value. They like some categories and dislike others. It is exactly like collecting for a hobby. But what people collect tells you more about the collector than the collection. If I tell you I collect Beanie Babies and you collect antique steam engines, we just told each other a lot about ourselves. In investing, most category collectors believe their category is permanently better, which is why you have value investors saying value is better and growth investors saying growth is better. And they believe it. What they do not understand is that they are spiritually wed at the hip to Osama Bin Laden. Like Mr. Bin Laden they believe the thing they believe in is more powerful than the most holy “ism,” capitalism, the true religion of material wealth. Like Mr. Bin Laden, they follow a false faith.

Capitalism is holy? Embedded in capitalism is the capital market pricing mechanism. At its core and guts is that if you give it enough time, capitalism arbitrages all raw variances in capital costs by category to zero by adjustments in supply and demand for securities. The tech investor and energy investor have a hard time fathoming that the 20-year return on those two categories is identical. Similarly, the 30-year return on the markets of all major Western nations is almost identical. It’s the same thing with growth and value stocks, and big- and small-caps. If you don’t believe in the near-total power of the capital markets pricing mechanism to accomplish its goal, you don’t really believe in capitalism and will end up the same place Mr. Bin Laden will end up. In the long term, all major equity categories effectively perform nearly identically. Their differences are small and serendipitous. But people don’t think that way. The small-cap twits do a different stupid thing, by the way. They see the long-term excess return on small cap and miss that it comes from three two-year periods of 1933-34, 1943-44, and 1976-77, all emerging similarly from big bear markets. When you take away those three similar periods out of that long history, then big-caps do better. If removing three two-year periods ruins your long term trend, then you don’t have robust statistics and that completely undermines the statistical underpinning to the so called small-cap effect. The function of capitalism is to arbitrage differences in categories to zero. If you know that, then you know that categories are not important. The real issue is: What categories do well and badly next?

How do you do that? A core concept of finance theory that almost no one honors is that, to make long-term excess returns, you must know somehow, some way, something other people do not know. That is very, very difficult. Finance theory is quite clear that if you make investment decisions based on what you read in newspapers and see on TV, you will sometimes be right and lucky, more often wrong and unlucky, and overall do worse than if you had made no decisions at all. So the question is: How to you go about knowing something others do not know? It is a very basic question, but most investors do not ask it. Traditionally most investors and advisors have not even tried to answer it. Most advisors believe that if they get an adequate education, whatever that means, they are up to the task of making decisions, given a modicum of training in getting a designation or degree such as a CIMA, MBA, CFA, or CFP. Finance theory, however, says getting a designation or degree is insufficient. Educational curriculum is all known information. Therefore, it is discounted in securities pricing. Traditionally, the oldest way people would try to get information others do not have was to study companies and learn tidbits others did not know. But unless you’re talking about truly small companies, it is difficult to know what others don’t know about a company. If you think about a good-sized company, not only is all of Wall Street interested in it, but so are its customers, competitors and suppliers, all of whom would profit off the stock if they could. Plus, it is hard to know if the thing you know is information others really don’t know, because it is hard to know what they really do and don’t know.

You think differently from others on Wall Street. Pretty much all of Wall Street is screwed up. We don’t like investment advisors, we don’t like investment bankers, we don’t like brokers, and we don’t like financial planners. We think they’re pretty much all engaging in a catechism for which there is no basis in finance theory. We don’t like to hire people from the industry. We discriminate against MBAs, and have a particular bias against Stanford MBAs. We mostly hire bright kids and train from within. We think the industry is a long, continuous evolving succession of chaos, from a world that began and adapted through the evolution of concepts of modern finance. There is no Wall Street firm that is our role model. We look at Intel, when it started in 1968, and we see Bob Noyce and Gordon Moore, both already big-name semiconductor physicists, essentially saying that people don’t know much about how to make semiconductor chips compared to what they would know in 5, 10, 15, or 20 years. We believe finance theory and capitalism are near perfect and near holy. But we believe people don’t know much about how capital markets work today compared to what they’ll know five, 10 or 15 years from now. And every year, you can develop a little piece of capital markets science and, or, technology, to explain a little bit of how markets work in ways no one ever knew before.

Why? To know something others do not know, to be able to make some form of knowing bets, that’s our philosophy and goal: knowing what kind of stocks to own and whether to own stocks, or whether to own alternative asset classes. But even when you know more than you knew before, and know something no one else knows, there is still more you do not know than you do know.

What do you know that others do not? A standard phrase investment advisors use is “large-cap value.” That category is actually nonexistent. It is an oxymoron. And, if you believe it exists, you’re a regular moron. The way the market actually works, there is a size continuum from biggest to smallest, and if you take stocks a quarter as big as the average stock’s market capitalization, they would act more like the tiniest stocks than the stocks bigger than the market’s average capitalization. When you look at value, only a very few stocks are bigger than the market’s average capitalization, and they essentially are all energy-dependent such that you cannot build a diversified portfolio out of them. All value portfolios, unless synthetically created, have market caps smaller than the market’s average capitalization, unless they have zero industry diversification and very little single stock diversification. The impact is that what people call large-cap value is just a bet on less smallness than small cap-value. All value is a bet on a certain amount of smallness; the question is how much. So if you look at times when small-cap value is going great, big value is acting more like small-cap value than like large-growth and vice versa. When small-cap value is doing badly, what’s called big-value is again acting more like small-value than big growth.

Do you have any other examples of widely misunderstood concepts? Nobody, other than the tiniest percentage of investors in the world, really gets standard deviation. Let’s pretend that the standard deviation of the market is 20. What does that say? What it says is that if our return expectation for the time period ahead was 10%, we’d be pretty confident (but not completely) that our return would be between 30% and negative 10%. Nobody feels that way though. Everybody feels overconfident. Advisors may have studied standard deviation in statistics class, but they didn’t get it in their bones. They typically think returns cluster around the long-term average rather than fluctuate wildly around it. But we know that average returns are not normal. Normal returns are extreme and volatile and always have been. If you take your average advisor, he or she knows that the long-term history of stocks has averaged about 10%, which is true. In his bones, he will believe a return in any given year of 0% percent to 20% is more likely than a return above or below those levels. The history of Western markets, however, is exactly contrary to that. Returns are higher or negative 70% of years in America. They are between 0% and 20% only in the remaining 30% of the calendar years since 1926. In overseas Western developed markets, returns of zero to 20% happen in only 25% to 40% of years. Returns greater than that or negative happen 60% to 75% of years. Overwhelmingly, markets are more volatile than people think.

Give me another one. The pricing of securities is always, and this is a tough concept for the human brain, a function of shifts in supply and demand for securities. That is basic finance and economics. Yet it is safe to say that less than one-tenth of one percent of advisors–or anyone else–wakes up on any given day and says, “I want to think today about shifts in supply and demand for securities or a security.” They instead are thinking like hunter-gatherers would think about wind or rain, hordes or predators, lightning strikes, and roaming neighboring tribes. Investors want to think about interest rates, earnings growth rates, and all kind of other proxies for supply and demand of stocks. But they do not want to think about supply and demand. Our brain wants to think of interest rates the same hunters did wind, or about earnings growth rates the same way hunters saw rain. For hunting and gathering, thinking about the rain or wind worked. But for investing it does not. The capital market pricing mechanism is a different world. It is the world our brains don’t want to think in, a world dominated by supply and demand shifts, for instance, which we don’t think about. I seriously doubt that many of your readers have ever tried to build supply and demand schedules for any security and have no idea how they vary from the ones they were taught about in basic microeconomics. People pay attention to these proxies and not supply and demand directly. Forecasting supply and demand shifts five to ten years from now is beyond treacherous. If you remember your basic microeconomics, supply and demand shifts are all about the psychology and functions behind eagerness. How eager will people be for equities in a decade? And how eager will entities and bankers be to create them? If you think you can answer that with any precision, you are a fool. It is way beyond the current state of capital markets science.

You recently took a swipe at me in Forbes over something I quoted Harold Evensky saying about the equity risk premium. What Harold Evensky said was wonderful. Quoting from the interview you did with him, he said: “I don’t know anyone who has not accepted that returns will be lower in coming years, certainly not in professional circles.” To the extent that is true, it is the most bullish sentence anyone can make. If everyone believes returns will be low, that has already been priced into the market. The concept of the equity risk premium, which is very correct in finance theory, is almost totally and universally misapplied in real life. I can’t apply it because I don’t know how to do it correctly. It is just another way to guesstimate. The feature of the ERP that is troublesome is that if you have bearish assumptions, you will be bearish in your equity risk premium calculation. And if you have bullish assumption, you will be bullish in your ERP calculation. People making assumptions about the ERP are just trying to make 10-year predictions on the market. What Arnott, Ibbotson, and others are saying is whether they believe returns will be average, above average, below average, and they are usually talking about the next 10 years or so. With almost all academic calculations of the ERP, if you take their formulas and backtest them, you are likely to find their forecast for stock returns were vastly lower than the market’s actual returns. For example, Cliff Asness is one of the most widely cited ERP calculators. We put ourselves back in the early 1980s, took his formula, and applied the numbers to the economy then. It called for a negative equity risk premium for most of the last 20 years–not just a lower ERP, but a negative ERP in what turned out to be a very huge bull market. If the formula could be wrong for that long, what makes it right now?

But making long-term capital markets forecasts based on what’s known about the markets and economy would seem to be a pretty sensible, if not scientific, approach. No one could begin in the 1980s or early 1990s to see either good things that were not expected, like the fall of the Soviet Union, or the tremendous optimism that would come in the late 90s over things like the Internet. When you think about major events in history, few people could see them 10 years out. But the other issue is that it is actually the latter years in a 10-year period that matter most. History shows that. When you look at spreads of bonds versus stocks, or stocks versus cash, during rolling decades of calendar years since 1926, the highest spread is 18% in favor of stocks and the lowest is negative 4% or 5% depending whether you use cash or bonds to look at the spread. Those are huge swings. And it is the back-end optimism or pessimism in the 10-year periods that determines the returns, not the front-end of those periods. Ten years from now, will people again be wildly optimistic? I don’t know. But not only do I not know, no one else does either. And using an ERP that says equities should return 5% or 6% or 7% or 12% annually is simply a statement of not appreciating how wildly volatile equities are. Markets are far more volatile than investors think they are. The reality is we cannot tell how people will feel five or ten years from now. And because they tend toward extremes, they could be extremely optimistic or pessimistic, and we know the spread of stocks versus bonds or cash is positive 18 versus negative 4 or 5. If you think you can predict how people will feel five to ten years from now, you are what a behaviorist calls “overconfident” at the extreme. Three years ago, if you would have asked advisors a question about the equity risk premium, some would have had a low number and others a high number. Ironically, after a big bear market, most academic calculations brought their numbers down for the expected returns on stocks. And most people three years ago could not see three years into the future, and those who could may have been lucky. That’s three years ago, not ten. A 10-year forecast is much tougher. We believe it is wiser to take it one year at a time. Let’s worry about here and now and not worry about 2013 because there is not a lot we can do about 2013.

You are 100% in stocks now. Why? For years, we’ve done some forecasting looking one year out based on shifts in professional sentiment. We use that as a proxy for demand. The survey includes published forecasts by chief investment strategists for sell-side firms and buy-side firms both large and small, and it also includes hedge funds, and a sampling of brokers. The core center of what they agree on is priced into the market. It cannot occur. Something else must happen. This is not contrarian. Contrarians are silly. Contrarians believe that if folks are bullish, the market will fall, and if they’re bearish, the market will rise. History and the study of sentiment, correctly done, disproves this. People may be optimistic, but not enough. Or they may be pessimistic, but not enough. But whatever level of optimism or pessimism, what most folks can agree on is already priced into the market. Therefore it cannot occur and something else must happen. All through the second half of the 1990s folks were optimistic, but not optimistic enough. We run polls on professionals and have done this a long time. If you go back to say, 1996, as an example, you get a bell curve of their views. In the beginning of 1996, the middle of bell curve was calling for an 8% return for 1996. The forecasted return span of those polled ran from negative 8% to a 23% gain. Only one of the professionals we surveyed forecast a return above 17%. The market in 1996 came in with a 22% gain. We believed the market would come in above 17 or below -7. We just had to figure out which. In 1997, the range of the professionals we polled ran from predictions of a 16% positive return to a 29% loss. The market came in with a 33% gain, and this did not surprise us either. We look for the most likely case on the fringes of the bell curve. We throw out the middle of the curve. We look at the outliers because the markets are more volatile than people think and that which they agree upon has already been priced into the market. The market discounts all known information. That which we all talk about commonly does not have power because it has been priced by the market. When you look at collective forecasts, that’s just a way to quantify what is agreed on. Then you build a case for the outlier possibilities. You do that by throwing out scenarios that are not likely to come about. At the beginning of this year, for example, we said you have to have a monster up year or down year because everything else in between was discounted in the market already. Put that in the context of three monster bad years in a row and the likelihood of a fourth seemed remote. The three monster years were one data point we considered. To make a forecast, you do that over and over again and find other data points to make your case.