Many value investors are following bad advice. Individuals wanting to profit from the stock market are consistently trying to become the next Warren Buffett (Trades,Portfolio).
They use careful analysis to find wonderful companies trading at fair prices. This investment strategy is bound to drag down long-term returns and minimize profits.
Value investors would be wise to stop thinking so hard about the stocks they buy. Evidence shows that the highest long-term results are achieved when applying highly simplified stock-selection strategies.
In 1934, Benjamin Graham and his colleague David Dodd wrote exhaustively on the merits of security analysis. Their book – amply named “Security Analysis” – has gone on to become one of the most influential financial publications ever written. Today, it’s considered the bible of value investing.
Security Analysis dives deep into the theory of common stock investments and details how to extensively examine financial statements. It’s essentially a textbook for elaborate techniques of finding superior value opportunities.
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Efficient market hypothesis
In 1976, Graham was asked the following question in an interview with “Financial Analysts Journal“:
“In selecting the common stock portfolio, do you advise careful study of and selectivity among different issues?”
Considering this question was asked to the man who wrote the definitive guide advising careful study of and selectivity among common stocks, you’d expect the answer would be obvious. But, 40 years after first publishing Security Analysis, the Father of Value Investing’s response was surprising:
“In general, no. I am no longer an advocate of elaborate techniques of security analysis in order to find superior value opportunities. This was a rewarding activity, say, 40 years ago, when our textbook ‘Graham and Dodd’ was first published; but the situation has changed a great deal since then. In the old days any well-trained security analyst could do a good professional job of selecting undervalued issues through detailed studies; but in the light of the enormous amount of research now being carried on, I doubt whether in most cases such extensive efforts will generate sufficiently superior selections to justify their cost. To that very limited extent I’m on the side of the “efficient market” school of thought now generally accepted by the professors.”
What are we to make of this statement? Benjamin Graham – the man who created Mr. Market and spent his career advocating that price and value often don’t match up – eventually came to agree with the Efficient Market Hypothesis?
Highly simplified approach
The key phrase in the last sentence of Graham’s statement is “To that very limited extent…“
What Graham eventually came to disregard were elaborate techniques and detailed studies of selecting individual stock investments.
When the interviewer followed up by asking which approach he does advocate, Graham clarified:
“Essentially, a highly simplified one that applies a single criteria or perhaps two criteria to the price to assure that full value is present and that relies for its results on the performance of the portfolio as a whole–i.e., on the group results–rather than on the expectations for individual issues.”
Just before his death – after 60 years of practicing, studying and teaching stock investing – the Dean of Wall Street no longer supported detailed security analysis. Instead, he encouraged investment strategies that select a diversified group of stocks with low price ratios.
It’s important to note Graham’s emphasis on “group results.” He is clear that “expectations for individual issues” are fruitless endeavors.
Towards the end of the interview, Graham provides specifics on two of his favorite stock-selection strategies.
The first is his NCAV approach. He says:
“I consider it a foolproof method of systematic investment – once again, not on the basis of individual results but in terms of the expectable group outcome.”
His second is a simple method of buying stocks with price-to-earnings ratios under 7. He says:
“I have every confidence in the threefold merit of this general method based on (a) sound logic, (b) simplicity of application, and (c) an excellent supporting record.”
What about Warren Buffett (Trades, Portfolio)?
At this point, many readers may be skeptical about the idea of blindly buying a group of stocks simply based on one or two key ratios. Buffett certainly doesn’t invest this way, and he was Benjamin Graham’s best student!
It’s true that Buffett’s investment portfolio is not comprised of individual stocks purchased through a systematic investment method.
But I bet he wishes it was.
Consider this quote by the Oracle ORCL +2.20% of Omaha:
“The highest rates of return I’ve ever achieved were in the 1950s. I killed the Dow. You ought to see the numbers. But I was investing peanuts then. It’s a huge structural advantage not to have a lot of money. I think I could make you 50% a year on $1 million. No, I know I could. I guarantee that.”
When Buffett says, “The highest rates of return I’ve ever achieved were in the 1950s,” he is referring to a decade in which he invested almost exclusively in Benjamin Graham-style NCAV stocks.
It wasn’t until his assets under management became so large, that Buffett’s investment approach turned from a highly simplified one to one consisting of elaborate techniques and detailed analysis.
Buffett didn’t buy wonderful companies at fair prices until he was forced to acquire entire businesses. He didn’t buy and hold until his size prevented him from being able to sell.
In a blog post on Base Hit Investing, Jon Huber encourages value investors to “think like Buffett in the 1950’s, not like Buffett in the 2000’s.”
If you’re investing less than eight-figures, there’s no reason to put yourself at a disadvantage. Rather than carefully analyzing specific investment opportunities, use a simple model which relies on the performance of the group outcome.
Less is more
In the 2007 #1 national best seller, “Blink: The Power of Thinking Without Thinking,” author Malcom Gladwell makes the case that complex decisions are more accurately made when less information is available. He uses the work of a cardiologist named Lee Goldman to show that “extra information is more than useless. It’s harmful.”
Goldman developed a simple equation that diagnosed heart attacks using only four basic risk factors. When put into practice the equation accurately predicted patients with heart attacks more than 95% of the time. When doctors disregarded Goldman’s system, their expert opinions were correct only 75% to 89% of the time.
Doctors who had too much information – such as a patient’s age, weight, gender, race, medical history, etc. – were far less accurate in their predictions.
How can this be?
Broken leg syndrome
Tobias Carlisle, in his book “Deep Value,” explains that simple models are more consistently accurate than expert opinions. He cites a well-accepted study that has come to be known as The Golden Rule of Predictive Modeling.
The observation discusses a hypothetical algorithm that predicts the weekly movie attendance of an individual. Logic would say that if the movie-goer has a broken leg which the model cannot see, an expert should override the model and predict that the subject will not go to the movies.
Here’s how Carlisle explained it in an interview with Tadas Viskanta:
“Statistical prediction rules get broken-leg problems incorrect because the particular case is so different from the base rate. If that is so, goes the argument, then surely these anomalous cases could benefit from an expert overriding the rule? The studies find that they do not. In fact, experts predict less reliably than they would have if they had just used the statistical prediction rule. The reason is that when experts are given statistical prediction rules along with permission to override them, the experts find more broken legs than there really are.”
When selecting a stock investment, investors feel that the more data they have regarding a particular company or the industry it’s in, the more accurate their analysis will be.
The problem is that qualitative information makes it nearly impossible to objectively assess an investment opportunity.
When looking to buy a wonderful company, investors attempt to use their expert opinions to find a business that will continually grow its earnings for decades to come. They may look at past operating results – including growth rates, and profitability ratios – as well as the long-term forecast of the company’s industry.
When looking to invest in an undervalued stock, qualitative information will always reveal why the stock is undervalued. Stocks are never cheap by pure chance. Whether it’s due to recently poor operating results, slow or no growth rates, or bleak economic outlooks, Mr. Market is pessimistic for a reason.
In either case, it’s impossible to predict the future. Through careful and detailed analysis, expert opinions will always find wonderful companies where they don’t exist and broken legs that will heal sooner than anticipated.
Hard to stomach
The facts surrounding the effectiveness of simple models over expert opinions are hard to digest. Everyone wants to feel important and to reinforce the idea that their opinions matter.
Later in “Blink,” Gladwell explains the reaction the medical community initially had towards Goldman’s system. When quoting Arthur Evans, he says:
“’Doctors think it’s mundane to follow guidelines,’ he says. ’It’s much more gratifying to come up with a decision on your own. Anyone can follow an algorithm. There is a tendency to say, ‘’Well, certainly I can do better. It can’t be this simple and efficient; otherwise, why are they paying me so much money?’’”
The same is true in the investment community. Behavioral finance and academic studies have demonstrated time and time again that companies with low price ratios and strong balance sheets vastly outperform the market. Yet, individual and institutional investors insist on using elaborate techniques to find wonderful companies trading at fair prices.
Don’t be an expert
As opposed to acting like experts and predicting which companies will exponentially increase profits, value investors are wise to let a highly simplified model select stocks for them.