3.2.1 Stock Pickers

Stock pickers are active investors who bet they can beat a market by picking stocks they believe will outperform an index. To be precise, the only proper comparison to their result is the portfolio they choose. All other portfolios will end up with different risk and return characteristics. Generally, stock pickers take on more risk than the index because they concentrate their bets on fewer stocks than those in the index. When they allocate their portfolio differently than the index, they are guaranteed to obtain a different return as well as a different risk level. Sometimes it is more and sometimes it is less, but we can always assume it will be different when looking at both risk and return. Since it takes at least 20 years of risk and return data to confirm skill over luck, stock pickers face a virtually impossible task in their ability to ensure continued success against the appropriate market index. However, indexes are a source of 20-year risk and return data, and consequently are the only logical choice for establishing efficient portfolios of various levels of expected risks and returns.

   3.2.2 Adjusted Performance

The performance of stock pickers must be examined on an adjusted basis. This means that all factors must be considered before we can determine if the stock picker has achieved a benefit over an appropriate index or benchmark. When comparing active management to an index, we must:

1. Make sure we are talking about the entire portfolios for the exact same period of time.

2. Confirm proper accounting of the returns, including the cash flows in and out of the account.

3. Consider the state and federal taxes paid on short and long-term capital gains and dividends.

4. Consider all fees when assessing net return. Most funds report gross performance before deduction of fees and commissions.

5. Adjust for the portfolios' exposure to market risk, size risk, and value risk factors.

6. Consider the level of diversification of the two portfolios.

7. Analyze the standard deviations or volatility measurements.

8. Consider if the over and underperformance is within the bounds of what would be expected randomly.

9. Be sure to compare results to an appropriate benchmark. Proper benchmark specification avoids inflated performance reports.

10. If looking at a group of stock pickers, be sure to include the returns of those pickers that did not survive the duration of the period, usually due to significant losses.

11. Look at all active managers in an asset class, both those who stayed in business and those who did not.

12. Check to make sure the stock-picking manager did not drift in its designated style during the period in question.

Making these comparisons requires a high degree of understanding of each of the concepts listed above. To simplify your analysis, you may consider that the only way to end up with a different performance than the index is to own investments different than the index. Since an index is the only source of long-term risk and return data, why would any investor choose something other than the index? The only question should be: What mix of indexes is appropriate for you?

Lets take a closer look at why stock pickers lose on average.

3.3

Problems

3.3.1 Why Stock Pickers Fail

The main reason that stock pickers fail is that stock prices are moved by news, and news is unpredictable and random in nature. Therefore, the movements of stock prices are unpredictable and random. This simple logic makes it impossible for any human being to consistently pick stocks that outperform the averages of a market.

Secondly, the news that moves stock prices is incorporated into the new price within minutes of its release. This adds a major hurdle for stock pickers. It means they must compete with thousands of highly intelligent and well-informed traders on a minute-by-minute basis.

John Stossel of ABC’s 20/20, reported a story on the perils of picking stocks. Stossel interviewed Professor Burton Malkiel of Princeton University, author of the book, "A Random Walk down Wall Street." In the interview, Professor Malkiel said that stock markets historically deliver a performance of 9.5% to 10% compounded per year over the long haul. Inquired Stossel: “To beat that average, should an investor listen to the Wall Street professionals?” “No,” replied Professor Malkiel. “All the information an analyst can learn about a company, from balance sheets to marketing material, is already built into the stock price, because all of the other thousands of analysts have the same information. What they don’t have is the knowledge that will move the stock, knowledge such as a news event, which is unpredictable and impossible to forecast.”

Indeed, an analyst can only guess about a future event, which is no different than throwing a dart at a newspaper while blindfolded to find a stock. Both events are unpredictable. The main purpose of the financial research industry is to try to predict the future course of events since that is the only thing that will drive future stock prices. If thousands of highly intelligent, sophisticated analysts with degrees from top universities and access to the best computing power available can’t predict the future, what use are they? How can one company or research analyst have more knowledge than another without it being inside information, which would be illegal?

3.3.2 The Stock Picker's Graveyard

“Survivorship bias” is one of the many reasons that stock pickers’ returns look better than they actually are. Survivorship bias is when mutual fund managers tout their fund’s performance based on comparisons with an “average” mutual fund. This average is calculated from a list of funds that have survived during a particular period. Funds that did not survive the period are not included in the calculation. According to the Center for Research on Securities Prices (CRSP) at the University of Chicago, if only data from surviving funds is considered, the growth of a dollar for the surviving funds appears to be 19% better since 1962. If only “live growth and income funds” are considered over this period, $100 appears to grow to about $2,500. However, the only way to properly account for all active managers is to include those mutual funds that did not survive. When taking these dead funds into account, CRSP found that the average stock picker’s $100 investment grew to only about $2,100.

	Rex Sinquefield Difficulties of Stock Picking Part 1
	Rex Sinquefield Difficulties of Stock Picking Part 2

The Center for Research on Securities Prices (CRSP) at the University of Chicago has the only complete database of both live and dead mutual funds.

Mark M. Carhart, currently Co-Head of Quantitative Research, Goldman Sachs Asset Management, New York, developed this unique database for his 1995 Ph.D. dissertation at the University of Chicago Graduate School of Business. In his dissertation, Survivor Bias and Persistence in Mutual Fund Performance, he noted that the explosion in new mutual funds has been "...accompanied by a steady disappearance of many other funds through merger, liquidation, and other means...this data is not reported by mutual fund data services or financial periodicals and in most cases is electronically purged from current databases. This imposes a selection bias on the mutual fund data available to researchers: only survivors are included.."

In estimating the performance of an equal-weight index of equity mutual funds, Dr. Carhart found that analyzing only surviving funds biases performance upward by about one percent per year.

The CRSP database includes 24,725 mutual funds from 1961 to 2004. In that time, 8,710 of the 24,725 mutual funds died. That means that more than 35% percent of mutual funds data is not included in the average returns of active managers. The active managers who run them happily bury most of the data about dead funds. Is it possible that the 8,710 dead mutual funds had high returns for their investors?

For advanced students, print out a more detailed fifty-one page analysis of Survivorship Bias, by Mark Carhart: Mutual Fund Survivorship. Also see this abstract by Elton, Gruber and Blake and this article by Horst, et al.

The financial press goes to great lengths to inform the public about active managers with good luck, e.g., "Last Year's Top Ten Mutual Funds." This kind of media reporting provides no data about those managers who lose money taking chances in the market, then shutting their doors and erasing their bad returns from the record. Well, we have bad news for those mutual fund managers: we are exhuming their results. We paid CRSP $1,000 (it is expensive to dig up old corpses) to prepare a list of the top 200 worst performing dead mutual funds going back to 1961. To our surprise, this had never been done before. Here are the top twenty of the worst performing dead mutual funds:

Table 3-1

3.3.3 Incubator Funds

	Rex Sinquefield Survivorship Bias 1
	Rex Sinquefield Survivorship Bias 2
	These two video clips are an explanation of survivorship bias by Rex Sinquefield, Co-Chairman of Dimensional Fund Advisors. Click on 1 then 2 to the left

In addition to funds that die, there is an indeterminable number of funds that are aborted. These funds are referred to as incubator funds, and are basically experiments within a fund firm that never develop into a publicly available mutual fund.

Upon their inception, the funds are not available to the public; therefore, they are safe from public scrutiny. After a time, the fund shop rolls out only the best performing funds. And some of the best performing funds have unusual reasons for performing so well, like limited access to IPOs, click here to see a SEC case on this issue.

Table 3-2

The stock picking managers of these incubator funds tried something new and ended up with a failure. This little known fact has yet to be quantified in the average returns of stock pickers.

Finally, there are the revolving doors of stockbrokers who are churning through clients and constantly rotating from one firm to another. Their records are quickly extinguished, never to be counted in the average of stock pickers.

In addition to dead mutual funds, there is a huge graveyard full of dead companies. Table 3-2 lists the largest bankruptcies from 1980 to 2006.

Two examples of bankruptcy filings help remind investors how easy it is to pick the wrong stock. The first example is Bethlehem Steel. Bethlehem Steel was founded by legendary steel tycoon Charles Schwab in 1904 in Bethlehem, Pennsylvania. The company produced some of the nation’s first steel railroad rails, revolutionized high-rise building construction with the introduction of structural I-beams in 1908, and built the country’s first aircraft carrier in 1925. Landmarks such as the Golden Gate Bridge, the Chicago Merchandise Mart, Rockefeller Center and the U.S. Supreme Court were constructed with Bethlehem steel. Peacetime employment reached a peak of 157,000 workers in 1957, and profits hit a record $426 million in 1988 and in 2001 the mammoth steel company filed for Chapter 11 bankruptcy.

Bethlehem was one of the stocks in the Dow Jones Industrial Average for nearly 70 years until its replacement by Johnson & Johnson in 1997. Its stock price reached a peak of nearly $60 in late 1959, and remained in a broad trading range over the next 40 years as the firm struggled to improve its competitive position through various acquisitions, divestitures, and cost cuts.

Indeed, only three members of the original 30-stock Dow Average established in October 1928 are still included in 2005: General Electric, General Motors, and Standard Oil of New Jersey, now ExxonMobil.

Another example is Polaroid Corp., which was founded in 1937 by 28-year old Harvard dropout Edwin Land. Land was a brilliant physicist and tireless inventor who accumulated 535 patents by the time of his death in 1991 (second only to Thomas Edison). An early quest to solve the problem of headlight glare led to a patented process for polarized glass, and a variety of optical products for military and commercial use. The self-developing Polaroid Land camera he ultimately developed was a marketing sensation when introduced for $89.50 in 1948. A steady stream of improvements including instant color film stoked consumer interest in the 1950s and 1960s.

Figure 3-1

Polaroid shares were a favorite among aggressive investors, soaring more than 40-fold from their initial public offering in 1957 to an all-time high of $149.50 in 1972 ($74.75 adjusted for a subsequent two-for-one split). The SX-70 camera, which ejected prints that developed externally, was introduced the same year. In addition, there was talk of a forthcoming instant movie system.

What’s more, in 1991, a successful patent infringement lawsuit against Eastman Kodak appeared to vanquish the sole competitive threat in instant photography. But Polaroid was unable to capitalize on the $925 million judgment, and struggled to broaden its product line amidst the proliferation of inexpensive 35mm cameras, one-hour photo kiosks and digital photography. Eventually Polaroid filed for bankruptcy in 2001.

The moral of these stories is that success today does not ensure survival tomorrow; therefore, investors need to diversify so that these kinds of events will not destroy their portfolio.

In the book Creative Destruction, McKinsey & Company consultants Richard Foster and Sarah Kaplan researched the original S&P 500, which was created in 1957. The survival of companies is similar to the survival of mutual fund managers. Figure 3-1 shows that in the 41 years from 1957 to 1998, only 74 of the original 500 companies were still in existence and only 12 of those outperformed the S&P 500 Index over the 1957 to 1998 period. The study found that the odds of picking a winning stock that beat the S&P 500 Index was one in 42.

3.3.3a Excellent Companies Don't Make Excellent Investments

Most investors operate under the misguided assumption that great companies are excellent investments. They believe that these companies can defy the poor odds of beating the market. In fact, almost the entire investment industry thrives on recommending a handful of “great stocks to buy now”.The firms represented in Figure 3-1a are widely considered to be industry leaders. They have been included at some point among the top ten "Most Admired Companies" in Fortune's annual survey.

The figure depicts the results of an IFA study which sets forth the total return comparisons for the S&P 500 index, IFA Index Portfolios and those of highly regarded companies. October 1, 2002 was chosen as a starting point because it was near the lowest point of the S&P 500 over the last 10 years. As you can see, not one of the admired companies came close to the total return of 104% for the S&P 500 Index in the 5-year time period from October 1, 2002 through September 30, 2007. The closest was Berkshire Hathaway, with a 59% return. The company's CEO, Warren Buffett, was named the World's Number One Billionaire for 2007, with a fortune valued at $62 Billion. The time proved to be even more profitable for the IFA Index Portfolios (IP). The small value heavily tilted all-equity IP 100 had a total return of 184%, while the all-equity IP 90 gained 172%. IP 80, with 10% fixed income to dampen volatility, gained 150%, while IP 70, with 20% fixed income gained 130%. IP 60 had 30% fixed income and still returned 112%. Even more interesting, the Emerging Market Value Index, that has had about the same risk (standard deviation) as Berkshire Hathaway over a recent twenty year period, had a total return of 586% (not shown in the chart below). Index investors enjoyed a wonderful increase in their portfolios, while investors of these admired stocks missed out on an enormous profit opportunity.

Figure 3-1a

In Figure 3-1b, you can see the risk and return of the 30 Dow Jones Industrial stocks, which include several of the stocks listed above, but over a 20 year period. Please note that for the risk taken, not one company exceeded the return that would be expected based on the diagonal line that estimates the appropriate return for the risk taken. This line is known as the Capital Markets Line.

Figure 3-1b

Further research demonstrating that good companies make bad investments is found in a 1987 study titled, “In Search of Excellence: The Investor’s Viewpoint,” investment analyst Michelle Clayman compared the returns of 29 “excellent companies” with 39 “unexcellent companies.” Clayman’s idea for this study originated from the 1982 best-seller In Search of Excellence by Tom Peters and Bob Waterman, which described 43 successful U.S. companies of which 36 were publicly traded. The book awarded companies an “excellent status” by virtue of their profitability, employee satisfaction and overall good working conditions, inspiring stock pickers nationwide to believe that they too could use winning companies to make winning investments. Clayman compared 29 of Peters and Waterman’s “innovative and excellent” companies with 39 “unexcellent” companies she selected. Her criteria for unexcellent companies included those with terrible profitability and “Dark Ages” management. Examples of her excellent companies included powerhouses such as Johnson and Johnson, Intel, Merck and Disney; unexcellent companies were made up of companies like U.S. Steel, American Motors, Westinghouse Electric and F.W. Woolworth.

Figure 3-1c shows that Clayman's excellent companies were stronger by every economic measure than her unexcellent ones for the five-year period between 1981 through 1985. “The excellent companies have qualities we would all love to see in our own companies, ”she observed.

Figure 3-1c

Clayman found, however, that the unexcellent companies showed significantly greater returns over the five years than their healthier counterparts. Figure 3-1d illustrates that between 1981 and 1985, the unexcellent companies earned investors a 298% total return while the excellent companies earned only a 182% total return. The two portfolios had almost identical standard deviations, so what made the unexcellent portfolio deliver such higher returns to its investors? The discrepancy arises because the higher cost of capital for unexcellent companies is paid to investors. Similar to individuals who approach banks for loans, borrowers with strong credit and payment histories will receive loans with lower interest rates (lower costs of capital) than that of a riskier borrower. Less stable companies end up paying higher costs of capital in exchange for their higher risk, which translates to a lower stock price relative to book value and a higher expected return for investors in those risky companies.

Figure 3-1d

3.3.4 Studies and Observations that Show the Daunting Odds of Stock Picking

The basic problem with stock picking is revealed when we examine how stock pickers are unable to beat a market over the long run. In a random and efficient stock market, active investors are just gambling or playing a game of chance. The money managers that run actively managed mutual funds are essentially gamblers, paid by the unsuspecting shareholders, with a high average annual fee of about 1.5%. 

Gambling may be fun when you go to Vegas, but it is not how investors should invest their hard earned money. Consider it this way: index funds investors invest like the owner of a casino, while the active investors behave like the gamblers in the casino. Attempting to predict the stocks, times, or managers that will perform the best is NOT a profitable expenditure of time or money. Assembling a portfolio of indexes is a very different story that has a guarantee of obtaining a low-cost, tax-efficient market rate of return, which is better than about 95% of stock pickers over 10 or 30 year periods.

A survey of both the popular and academic literature provides a crystal clear picture of the daunting odds of stock picking. Robert Jeffrey and Robert Arnott published a study titled “Is your Alpha Big Enough to cover its Taxes?” In the study, 71 large cap growth and growth and income active mutual fund managers were compared to the S&P 500 over a period of 10 years from 1982 to 1991. Most invested in styles that closely represented the S&P 500, but not one was exact. Only two of these 71 managers beat the index. That is a mere 3%! Had they all just invested in the S&P 500, they would have equaled its return. For those investors who were invested in either of the two funds that did beat the S&P 500, very few enjoyed the full returns of these funds. This is because huge cash inflows showed up in the last year of the time period, a typical sign indicative of manager or stock picking. See Figure 3-2.

Figure 3-2

The odds of throwing a two (snake eyes) at the craps table are the same as the results of this study, one in 36. The least likely rolls of a pair of dice are two and 12. The odds in roulette are one in 38 for picking a one-number winner. Gambling in Las Vegas may lead to more success th