“Focused funds — portfolios with only a couple of dozen holdings — are getting attention in a market where stock selection is more important than ever,” Burton writes. He says that, according to Morningstar, the average mutual fund contains 172 stocks — and that kind of diversification has a downside. “It limits a fund’s chance to meaningfully outperform its index,” he says. “Moreover, an overly diversified portfolio can mimic an index fund, but at a much higher cost. And diversification doesn’t guarantee safety: When most every market sector crumbled last year, plenty of fully invested, diversified stock funds lost as much or more than their benchmarks.”

Of course, focused portfolios have their own challenges — a bad pick has a bigger impact on your portfolio than it would in a broader portfolio, and, as Burton notes, maintaining a focused portfolio can require more effort and patience than many investors possess.

That being said, we believe that investors can benefit greatly from a concentrated portfolio of stocks. In fact, one of the main “guru-inspired principles” Validea CEO John Reese discusses in his new book, The Guru Investor: How to Beat the Market Using History’s Best Investment Strategies, addresses that issue, and provides data to back it up. Here’s an excerpt about that key guru principle.

Diversify, but You Can’t Beat the Market by Owning It (Excerpted from The Guru Investor)

In general, diversification is a good thing. Putting all your eggs in one basket—that is, putting all your money in just a couple stocks—is far too risky for most investors. Even the best companies with the strongest fundamentals can run into trouble. Maybe their star CEO leaves and is replaced by a dunce; maybe a fire destroys their largest facility; maybe the company just plain makes a big mistake, like making oversized bets on risky loans.

Whatever the case, it’s clear that you need to spread your money over a reasonable number of investments. But many investors—especially professional fund managers—spread it too thin. Some mutual funds hold hundreds of stocks, spread over every industry. With that many stocks covering that broad a swath, you’re bound to end up approximating the overall market’s returns. And if market-approximate returns are what you’re looking for, you’re better off just buying an S&P 500 index fund or Vanguard Total Market Index Fund, which would have much lower fees than the average mutual fund.

So, what is a “reasonable” number of stocks to hold to limit risk without just mirroring the market? Well, in a 2003 study entitled “Stock Diversification in the U.S. Equity Market,” California State University-Chico Professor H. Christine Hsu and H. Jeffrey Wei found that “the benefit of risk diversification is somewhat limited when the number of stocks in the portfolio goes beyond 50.” (You should know that Hsu and Wei’s study was actually taking aim at investors who didn’t diversify enough, and that they said investors with a relatively high degree of risk-aversion should hold more than 50 stocks. Nonetheless, their finding about risk diversification being limited when you go over 50 stocks is quite relevant.)

Keep in mind, however, that while you don’t need to hold stocks in every sector or industry, you should maintain some diversification across those categories. You don’t want to have a portfolio that’s 80 or 90 percent retail stocks, for example, because you’ll really get hammered if the industry hits any prolonged struggles. It’s best to establish your own system—for example, making a rule that a particular sector won’t make up more than, say, 40 percent of your holdings—and then stick to it over the long haul.

As you’ve seen from the results of our model portfolios throughout this book, our own experience has found that when using a rigid fundamental-based system, portfolios of 10 or 20 stocks can be quite successful. The system isn’t going to beat the market with every pick, but we know that, historically, our models have been right more than they’ve been wrong. By holding 10 or 20 stocks, we put those odds in our favor. While these 10- or 20-stock portfolios are somewhat more volatile than the market, they’re large enough to eliminate a good deal of firm-specific risk, while small enough so that you don’t have to spend too much time managing your portfolio.

And the greater-than-market volatility has certainly been worth the price: Since their inceptions, most of which were four or five years ago, all of the 10-stock portfolios we track based on the strategies detailed in this book have beaten the market, and nine of the ten 20-stock portfolios have also beaten the market. In fact, in most cases these portfolios have doubled, tripled, or quadrupled the market’s gains over a fairly lengthy period, lending a lot of credence to the notion of not spreading investment dollars too thin.

As I’ve worked with my guru-inspired models over the years, I’ve learned a great deal about how to implement them in the context of a practical portfolio, and have been able to answer many of those questions. These lessons, I believe, can be just as important as the strategies themselves, which is why my new book includes what I call the “Six Guiding Guru Principles”.

In the latest Validea.com Hot List, I examine the first of these key principles, which details how to combine individual strategies used by the gurus to bolster your portfolio. Here’s a look at what that entails:

(Excerpted from The Guru Investor: How to Beat the Market Using History’s Best Investment Strategies.)

Principle 1: Combining Strategies to Minimize Risk and Maximize Returns

Over the long haul, there is no better or safer, when you consider inflation, investment class than stocks. But as we’ve seen, in the short term, Mr. Market (as the great Benjamin Graham called the stock market) can be extremely fickle. Sometimes he likes growth stocks; sometimes he likes value. Often he likes stocks with low price-sales ratios; other times, he thumbs his nose at them. There’s no single strategy that will please him all of the time and if you try to predict his whims by jumping from strategy to strategy, as we’ve seen, you’ll far more often than not end up buying high and selling low. The conundrum is thus how to even out those rough patches while sticking to your guns.

One of the best ways to do this, we’ve found, is to use a strategy that blends together different guru-based models that have a lower degree of correlation. What do we mean by “lower degree of correlation” It’s simple, really. It means combining strategies that perform differently in the same kind of market conditions. The simplest example would be growth stocks and value stocks. When growth stocks are in favor, value stocks tend to be out of favor; when growth stocks are out of favor, value stocks tend to be in favor. If you use a two-pronged approach that includes a growth-focused strategy and a value-focused strategy, you’ll see less volatility in your portfolio. Your highs might not be quite as high but, more importantly, your lows won’t be as low during down times.

Why is it particularly important to smooth out those down times? The biggest reason is that downside volatility isn’t just unpleasant it also costs you money. Let’s see why. Consider a $10,000 portfolio (you could use any amount) that gains 25 percent one year, loses 30 percent the next, and gains 14 percent in the third. On the surface, it would seem like your average annual gain was 3 percent, because that’s what you get when you average 25, 30, and 14 and divide by 3 years. But let’s look at what you actually would gain.

The first year, your 25 percent gain on that $10,000 investment grows your portfolio to $12,500. The second year, you lose 30 percent on that new amount, dropping the $12,500 down to $8,750. Then, you gain 14 percent on that $8,750 in the third year. That leaves you with $9,975 after three years, $25 less than what you started with.

What happened to the 3 percent per year gain we were expecting? In a sense, it got washed away in the 30 percent drop in that second year, which significantly knocked down your capital. The 30 percent decline was 30 percent of $12,500 ($3,750); by comparison, the 14 percent gain the next year was 14 percent of just $8,750 (what you were left with after that bad second year). Because of that lower starting point, your 14 percent gain in the third year didn’t get you back about half of the 30 percent you lost in year two, as you might expect; it instead recouped just $1,225 less than a third of what you lost in the second year.

The bottom line here is that in the stock market, your gains are compounded; that is, after your first year, you start earning money not on your initial investment, but on whatever you had at the end of the previous year, be it more or less than your initial investment. A bad down year thus doesn’t just mean you lose a bunch of money one year; it’s also limiting the potential money you can make next year, because any percentage gain will now be made on a lower base.

On the other hand, compound interest works for you if you’re gaining ground, since you are generating returns off your principal and your gains from the previous year(s). The more you can smooth out the valleys and keep your portfolio growing in a steady upward trend, the better, even if it means you’re smoothing out some of the peaks in big years.

There’s another less tangible reason to limit your downside volatility: You’ll feel less of an urge to ditch your approach when times get tough. Ideally, the data we’ve presented showing that sticking to a strategy is imperative has been so moving that you won’t need this reassurance. But when investment dollars start disappearing in chunks, emotions can get so intense that even the best investors can lose their cool and jump ship. Anything that helps keep you stay the course and stick to your long-term strategy is thus a help, and combining strategies to limit losses during down times does just that.

If this type of blending sounds familiar, it’s because you’ve seen it before. James O’Shaughnessy used such an approach in developing his United Cornerstone strategy, which we covered in Chapter 11. O’Shaughnessy’s United Cornerstone approach didn’t produce the best absolute returns in his study of more than four decades of stock market data; that distinction belonged to an approach in which he targeted stocks with price-sales ratios less than 1.0 and high relative strengths. But O’Shaughnessy settled on the United Cornerstone approach because it had the best risk-adjusted returns, as demonstrated by its Sharpe ratio, a risk-adjusted return measure developed by Nobel-laureate William Sharpe.

The Sharpe ratio takes into account not only returns, but also standard deviation. (If mathematical terms such as standard deviation make your head hurt, don’t worry; it’s basically just a measure of how volatile a strategy or a portfolio is). Notes O’Shaughnessy in What Works on Wall Street, “Generally, investors prefer a portfolio earning 15 percent a year with a standard deviation of 20 percent to one earning 16 percent a year with a standard deviation of 30 percent. A 1 percent absolute advantage doesn’t compensate for the terror of the wild ride.” The best combination of lower-risk, higher-return strategies, O’Shaughnessy found, was the blended United Cornerstone approach.

Our own findings support O’Shaughnessy’s research. A Total Blend portfolio of stocks that used all 10 of the strategies detailed in this book, weighting each one equally, would have produced a better Sharpe ratio than any of the individual strategies from July 2003 through April 2008. That is, it would have had a better combination of high returns and low risk than any of our individual models. Its annualized return of 19.89 percent was better than all but three of our individual models, and it posted those returns while having a lower standard deviation than all of the individual models except the Greenblatt approach (and it trailed that by only 0.08 percentage points).

Premium Blend

Using blended strategies in a single portfolio isn’t just a way to smooth out returns. Done properly, it can also improve returns over the long haul. While the “Total Blend” approach we examined in the previous section puts the top picks of different individual strategies into a single, large portfolio, another type of blending involves looking for stocks with the most combined interest from different strategies. Most of our models examine a series of different variables when analyzing a stock, which means that using just one of these strategies ensures you’re getting a stock that is financially strong on a number of different levels. But when you focus on stocks with multiguru approval, you’re getting stocks that have really been put through the ringer.

A good case in point is the Validea Hot List portfolio that we track on our website. The Hot List looks for stocks that get the most combined interest from our strategies. It also gives greater weight to the strategies with the most historical success, meaning that the stocks it picks are fundamentally strong on a number of levels and get interest from strategies that have been very successful over the long term.

The results show what a multiguru blending approach can do. After five years of tracking, the Hot List had a higher annualized return than all but two of our guru-based models (our Kenneth Fisher- and Benjamin Graham-based approaches). From its July 15, 2003 inception through July 15, 2008, the portfolio gained 123.4 percent, more than five times the S&P 500s 21.4 percent gain during that time. What’s more, the Hot List posted those impressive gains while having a standard deviation (remember, that’s a measure of volatility) not much greater than most of our individual strategies. On a risk-adjusted basis (i.e. based on its Sharpe ratio), the only strategy that beat the Hot List by any significant amount was our Fisher model.

While an individual guru model may outperform the Hot List in a given period (as the Fisher model has done in recent years), we believe that over the longer term a blended approach will achieve the best results, because it limits downside risk when an individual strategy is going through a down period.

How does using a blended approach keep volatility in check and still beat out so many individual strategies in terms of absolute returns? A big part of it has to do with the thoroughness of our diverse group of individual models. For example, you can usually find a handful of stocks in the market that pass both our Peter Lynch-based fast-grower approach and our James O’Shaughnessy-based value model. These stocks must be growing earnings at a clip of at least 20 percent over a five-year span and have manageable debt to pass the Lynch fast-grower test, but they also must have the size and strong dividend yield and cash flow that the O’Shaughnessy value method requires. That combination of factors makes for a very, very complete stock, one that is growing earnings quickly, is conservatively financed, and is even paying a nice dividend. Over the long haul, it’s hard to imagine many stocks with this kind of multiguru approval not improving.

To identify those types of companies, the approach uses four price-focused variables: Price-Earnings Ratio, Price-Cash Flow Ratio, Price-Book Ratio and Price-Dividend Ratio. For a stock to even be considered by my Dreman strategy, it needs to meet at least two of these valuation tests (in addition to a host of other criteria).

The follow two paragraphs are excerpted from my new book, The Guru Investor: How to Beat the Market Using History’s Best Investment Strategies, in which I talk about the Price-Dividend Ratio criteria:

The final way Dreman looked for stocks whose fundamentals were strong compared to their stock prices—i.e. those that were contrarian picks—was by looking at the price/dividend ratio. As with the other three contrarian indicators, our Dreman-based model looks for stocks in the bottom 20 percent of the market in terms of P/D ratio, since that’s what Dreman used in his book. (Looked at another way, the yield—the dollar amount of dividends for the last four quarters divided by the current share price—should be in the top 20 percent.)

Dreman conducted studies from 1970 to 1996 that showed stocks with P/D ratios in the bottom 20 percent of the market had an average annual return of 16.1 percent versus 14.9 percent for the market. Dreman was cautious about investing on the basis of this criterion, as it is mainly for income-seeking investors, who are better off investing in stocks that pass this criterion rather than investing in bonds. For investors with different objectives, this is a very useful criterion that should be used in conjunction with Dreman’s other criteria. We use it in our model in conjunction with the three other contrarian indicators.

Below, I have listed a few stocks that currently score highly using my overall Dreman approach and also have particularly low Price-Dividend Ratios.

*all of these stocks have a Price-Dividend ratio in the bottom 20% of the market (below 11.3) at the current time. 

David Dreman — The Great Contrarian

Dreman, whose company now manages more than $20 billion in assets [at the time the book was written], embraces his contrarian reputation. He uses the word “contrarian” in the title of several of his books on investing, and the jacket of Contrarian Investment Strategies refers to his yacht, named The Contrarian. While there may well be a naturally rebellious side to him, there are also some very concrete, intelligent, and observant reasons that Dreman adopted his swim-against-the-tide approach.

More so than perhaps any other guru we’ll examine, Dreman is a student of investor psychology. In fact, his first book, written in 1977, was titled Psychology and the Stock Market (unless otherwise noted, however, all quoted material for this chapter comes from Contrarian Investment Strategies, which also deals heavily with investor psychology). This makes Dreman particularly worth reading because he presented not only an implementable, proven strategy for investing; he also addressed the psychological reasons that many investors fail. Being aware of these dangers is useful, whether you are using Dreman’s strategy or a different one.

In Contrarian Investment Strategies, Dreman essentially states that he believes there are relatively simple, proven strategies you can use to beat the market—particularly contrarian approaches—yet most investors “cannot follow through” and stick to these strategies. Why can’t they?

According to Dreman, investors cannot follow simple strategies to beat the market because they are prone to overreaction, and, under certain well-defined circumstances, overreact predictably and systematically. For instance, if a stock is considered “good”—it’s one of the “hot” stocks you read about in the paper, hear about on cable TV, or get tips about from your friends and coworkers—investors consistently overprice it. If a stock is “bad”—its price has been dropping, the company is making negative headlines, there are concerns about its industry’s future—investors underprice it. What’s more, this overvaluing of the supposed “best” stocks and undervaluing of the supposed “worst” often goes to extremes.

Dreman thus found that the market is driven by how investors react (or, perhaps more to the point, overreact) to “surprises.” These frequent surprises include earnings reports that exceed or fall short of expectations, government actions that might affect a stock, or news about new products. What’s more, he believed that these surprises were often precipitated by analysts—mainly Wall Street analysts—who were more often than not wrong about their earnings forecasts. He writes:

There is only a 1 in 130 chance that the analysts’ consensus forecast will be within 5 percent for any four consecutive quarters. …To put this in perspective, your odds are ten times greater of being the big winner of the New York State Lottery than of pinpointing earnings five years ahead.” (Dreman’s emphasis)

When you put investors’ tendency to overreact together with the frequent surprises in the market, you get to the crux of why Dreman believed so much in a contrarian approach. Surprises occur a lot, he believed, and because the “best” stocks are often overvalued, good surprises can’t increase their values that much more. Bad surprises, however, can have a very negative impact on them. On the other hand, because they already tend to be undervalued, the “worst” stocks don’t have much further down to go when bad surprises occur. When good surprises occur, however, they have a lot of room to grow. And, Dreman found, the effect of an earnings surprise continues for an extended period of time.

His conclusion: Buy out-of-favor stocks because surprises (positive and negative ones) are commonplace. If you own favorites, you’ll get clobbered by negative surprises but won’t get much upside by positive surprises; whereas if you own out-of-favor stocks, you’ll hardly be penalized for negative surprises but will be rewarded handsomely by positive ones.

This sounds logical, but Dreman found that even people who had an idea of this concept often didn’t follow it. Part of the explanation for that, he found, was that people tend to be overly optimistic. They have unrealistic optimism about future events, thinking such events will come out better than they realistically are likely to be. In other words, they view themselves in an unrealistically positive light and they have unrealistic confidence in their ability to control a situation.

For example, they may believe that having lots of information will shield them from surprises in the market because they have studied everything worth studying and therefore know all that’s worth knowing. An example Dreman gives regarding how this overoptimism can play out is the securities analyst who knows that high-flying stocks will drop from the skies faster than a pelican diving for a fish if earnings come in below the Street’s expectations. Yet the same analyst will still recommend high flyers because he is confident he knows enough about the stocks he has recommended so there is no chance they will experience negative surprises. That might happen to other analysts, he thinks, but not to him. Of course, given the unpredictability of the market and events surrounding it, there’s a good chance it will happen to him.

The bottom line for Dreman is that investors should never underestimate the probability of a negative surprise occurring, because they occur quite often, and can send an overvalued stock tumbling.

——————-
The preceding was excerpted from John Reese’s new book, The Guru Investor: How to Beat the Market Using History’s Best Investment Strategies.

Says Zweig, “Nearly all of us try forecasting the market as if each of the past returns of every year in history had been written on a separate slip of paper and tossed into a hat. Before we reach into the hat, we imagine which return we are most likely to pluck out. Because the long-term average annual gain is about 10% we ‘anchor’ on that number, then adjust it up or down a bit for our own bullishness or bearishness.

“But,” he continues, “the future isn’t a hat full of little shredded pieces of the past. It is, instead, a whirlpool of uncertainty populated by what the trader and philosopher Nassim Nicholas Taleb calls ‘black swans’ — events that are hugely important, rare and unpredictable, and explicable only after the fact.”

What kind of impact do these black swan events have on investors who try to time the market? To get an idea, Zweig points to the research of Spanish finance professor Javier Estrada. Estrada has studied the daily returns of the Dow Jones Industrial Average from 1900 through 2008. His findings: Remove the market’s 10 best days, and two-thirds of the Dow’s cumulative gains for the 109-year period would disappear. Take away the market’s 10 worst days, and you would have tripled the Dow’s return in that period.

“The moments that made all the difference were just 0.03% of history: 10 days out of 29,694,” Zweig writes. Stock market history essentially involves lengthy periods of little activity interspersed with those type of huge up or down days, Zweig says — and no one can predict those black swan days.

That’s a big theme of my book. In The Guru Investor, I reference the research performed by professor and author Philip Tetlock, which found that so-called “experts” couldn’t predict more than 20 percent of outcomes when asked to make various political and economic predictions. Crude algorithms, on the other hand, yielded accurate predictions 25 to 30 percent of the time, while sophisticated algorithms were right almost half the time.

Zweig does say that there is a place for forecasting. Two professors performing a study for the National Bureau of Economic Research are estimating a 4.2% return in 2009, he notes, adding that you can do a “roll-your-own” version of their sophisticated study by adding the market’s dividend yield (3.4%) and the annual rate of earnings growth over the past 20 years (3.4%), and then adjusting for how speculative you think price/earnings ratios will become.

As for his own predictions, Zweig says he thinks stocks could average a 7% return over the next five years, though “along the way, the Dow might slump to 6000, or drop 10% or more in a day.”

“But just as huge losses often come out of a clear blue sky, gains can arrive when the world seems darkest,” Zweig concludes. “If you forecast the market with your gut feelings alone, you may never hit the target.”