Step 4 - Time Pickers

Definitions

The underlying assumption of all forms of stock market picking is that the picker knows news or information that is not known to the millions of other market participants. For continued success, the picker must have a never-ending source of information not available to all other traders. Let it go! No mortal can single-handedly possess such incredibly powerful and immensely valuable information.

Two concepts that support the concept that timers are unable to pick the right times to invest are the Random Walk Theory and the Efficient Market Hypothesis.

Random Walk Theory

The Random Walk Theory essentially states that there are no discernible patterns in stock market prices. The logic and reasoning goes like this. News moves the markets. News is both unpredictable and random by definition. At the moment of discovery, the new knowledge or information is no longer new and quickly becomes old news. Since free financial markets are free of constraints, this new information is continuously reflected in the prices of relevant financial instruments. Therefore, the world's markets move in a random and unpredictable manner. Over time the distribution of returns form a near bell shaped curve. See several probability machines that simulate monthly returns of the market here:

As an example of randomness, look at these Wall Street Journal market summaries:

July 24, 2002: The Dow Jones Industrial Average soared 488.95 points, or 6.4%, to 8191.29 Wednesday -- their second-highest point gain ever -- as bargain-hunting and short-covering provided a powerful antidote for the persistent sell off. The Nasdaq composite surged 60.96, or 5%, to 1290.01.

September 19, 2002: U.S. stocks slid Thursday as investors were bombarded by bad news from EDS, Morgan Stanley and Merrill Lynch. Few analysts saw the EDS news coming. The Dow Jones Industrial Average fell below 8000, dropping 230.06, or 2.8%, to 7942.39, while the Nasdaq Composite Index sank 35.70 or 2.9%, to 1216.43.

Sept. 25, 2002: U.S. stocks bounced back Wednesday from a four-week sell off as earnings news helped sway sentiment. The Nasdaq Composite Index surged 40.12, or 3.4%, to finish at 1222.29, while the Dow Jones Industrial Average gained 158.69, or 2.1%, to 7841.82.

Sept. 27, 2002: U.S. stocks moved lower Friday, weighed down by concerns about corporate profits and somber economic news. In late-afternoon trading, the Dow Jones Industrial Average fell 250 points, or 3.1%, to 7745, while the Nasdaq Composite Index slipped 13 to 1208.

Nov. 27, 2002: U.S. stocks rebounded Wednesday, with an abundance of upbeat economic data helping push the Dow Jones Industrial Average up 255.26, or nearly 3%, to end at 8931.68. The Nasdaq Composite Index jumped 43.51, or 3.1%, to
1487.94.

March 10, 2003: U.S. stocks sank as geopolitical tensions heightened, and investors steered clear of the market ahead of possible action in Iraq. The Dow Jones Industrial Average lost 171.85 points, or 2.2%, to 7568.18, the lowest since last October, while the Nasdaq Composite Index gave up 26.92, or 2.1%, to 1278.37.

March 13, 2003: Major U.S. stock indexes logged their biggest gains of the year on hopes for a delay in a possible war with Iraq. The Dow Jones Industrial Average surged 269.68, or 3.6%, to 7821.75 in heavy trading, while the Nasdaq Composite Index had jumped 61.54, or 4.8%, to 1340.78.

March 17, 2003: U.S. stocks surged Monday on signs the U.S. will go to war with Iraq, a move some say will remove a level of uncertainty in the market. The Dow Jones Industrial Average was up about 239 points in late-afternoon trading, while the Nasdaq Composite Index was ahead roughly 3.2%. The dollar rallied, while bond and oil prices sank.

March 24, 2003: The Dow Industrials tumbled 307.29 points, or 3.6%, to 8214.68 Monday as investors began to worry that the war in Iraq could drag out longer than anticipated. The Nasdaq composite lost 52.06, or 3.7%, to 1369.78.

July 7, 2003: U.S. stocks surged Monday, with the S&P 500-stock index rising above 1000 as investors pinned hopes on a strong second-quarter earnings season. By midmorning, the Dow Jones Industrial Average was up 179 points, or 2%, to 9251. The Nasdaq Composite Index jumped 45 points, or 2.7%, to 1708.20, and the S&P 500 rose 18.20, or 1.9%, to 1003.90.

May 25, 2004: Major stock indexes regained their footing Tuesday as oil prices fell. The Dow Jones Industrial Average finished up 159.19 points, or 1.6%, at 10117.62, while the Nasdaq Composite Index jumped 41.67, or 2.2%, to 1964.65. The S&P 500-stock index gained 17.67, or 1.6%, to 1113.08. Crude fell to $41.14 a barrel.

August 6, 2004: Stocks sank to their lowest level of 2004 as Wall Street expressed disappointment over weak payroll data. The Dow Jones Industrial Average fell 147.70, or 1.5%, to 9815.33, the Nasdaq Composite Index dropped 44.74, or 2.5% to 1776.89, and the Standard & Poor's 500 Index shed 16.73, or 1.6%, to 1063.97.

Aug. 10, 2004: Stocks climbed Tuesday after the Fed raised rates and said the economic soft patch was temporary, caused by high energy prices. The Dow industrials climbed 130.01, or 1.3%, to 9944.67, while the Nasdaq composite grew 34.06, or 1.9%, to 1808.70.

Of course there is a positive upward movement over 15 to 20-year periods in diversified portfolios due to the compensation that investors receive for subjecting their capital to risk. The higher levels of the right risk factors correlate to higher expected returns over long periods of time. But the positive upward movement is virtually invisible when looking at returns over smaller periods of minutes, hours, days, months, or even several years. This positive movement is so small that Nobel Laureate Paul Samuelson compares it to watching grass grow. Go out in a big field and take a look.

As a side note, the reason markets trend upward is that the sun shines on capitalism, as your cash provides the fuel to fund profitable ventures. Your cash can be injected into the market through the purchase of products, services, debts or equities. On average, this free market system works better than a central government controlled system. Communism still exists in only a few countries where there is a mentality similar to that of active investors. This mentality is based on the falsehood that free markets do not reflect all information. Market speculators and communists both think they know more than the collective opinion of millions of voting market participants. They assume that they possess information that has not yet been picked up by the radar of all traders throughout the world. On the other hand, indexers invest under the assumption that markets properly price assets and risk.

Rex Sinquefield is the co-founder and a director of Dimensional Fund Advisors. He is also one of the world's foremost experts on the stock market. In 1995, he was asked to represent index funds investing in a debate with an active manager at a Schwab conference. After an eloquent review of the history of capital markets from Adam Smith to Eugene Fama, he threw down the gauntlet to a room full of active managers, “So, who still believes that markets don't work? Apparently it is only the North Koreans, the Cubans, and the active managers.”

Efficient Market Hypothesis

The efficiency of communication has progressed as follows: horseback, slow boat, smoke signals, homing pigeons, flashing lights on navy ships, Morse code, telegraphs, telephones, radios, televisions, computer networks, and finally the Internet. With each step, information and news became cheaper, more accurate, and more rapidly disseminated.

The Efficient Market Hypothesis simply states that market prices accurately reflect all available information at all times. This leads to the conclusion that it is impossible to consistently beat the market averages. As Bachelier stated in 1900, the expected return of speculation is zero. The most recent studies by Richard Roll indicate that new information is reflected in market prices within five to sixty minutes. Within that sixty minutes there are hundreds or thousands of traders all competing to profit from the information. If you are in charge of one billion dollars, a 0.1% annual gain is worth one million dollars per year. Consequently, managers of those funds are applying considerable resources to squeeze out every little gain from new information. For this simple reason alone, there is an absence of opportunities for one trader to consistently profit from all other traders who have access to the same information at the same time! In short, all of us know more than any one of us and it is impossible for one person to consistently possess more knowledge than all the other traders combined.

From the DFA web site, on their FAQs page:

In layman's terms, what is the Efficient Market Hypothesis?

The Efficient Market Hypothesis says that market prices are fair: they fully reflect all available information. This does not mean that prices are perfect; some prices may be too high and some too low, but there is no reliable way to tell. In an efficient market, investors cannot expect to earn above-average profits without assuming above-average risks. Market efficiency does not suggest that investors can't "win." Over any period of time, some investors will beat the market, but the number of investors who do so will be no greater than expected by chance.

More from DFA on Efficient Markets

"The efficient markets hypothesis (EMH) is an organizing principle for understanding how markets work and what investors should care about. Professor Eugene F. Fama of the University of Chicago performed extensive research on stock price patterns. In 1966, he developed the efficient markets hypothesis, which asserts that:

• Securities prices reflect all available information and expectations.
• Current prices are the best approximation of intrinsic value.
• Price changes are due to unforeseen events.
• Stock prices follow a random walk and are not predictable.
• Although stocks may be mispriced at times, this condition is hard to recognize.

Viewing the markets as efficient has important implications. If current market prices offer the best available estimate of intrinsic value, stock mispricing should be regarded as a rare condition that cannot be systematically exploited through analysis and forecasting. Moreover, if new information is the main driver of prices, only unexpected events will trigger price changes. This may be one reason that stock prices seem to behave randomly over the short term.

The EMH implies that no investor will consistently outperform the stock market except by chance, and that all investors may be best served through passively structured portfolios. Rather than trying to out-research other market participants, a passive investor looks to asset class diversification to manage uncertainty and position for long-term growth in the capital markets.

Market efficiency argues that when securities become mispriced, market forces quickly push prices back toward fair value. This equilibrium does not depend on all investors having the same information or level of expertise. It only requires that many intelligent participants have information. No single investor will have all the information or know how to use it. In fact, no single investor can possibly have all the information, as it will be scattered among many participants who are all competing to maximize their potential profit as buyers and sellers. The market mechanism gathers the information, evaluates it, and builds it into prices.

It may be hard to conceive current stock prices as rational, especially when markets are extremely volatile. The EMH does not claim that markets are always rational or correctly factor information into prices. The only condition required is that a large number of market participants don't consistently exploit price differences to outperform the market average. Also, market efficiency does not rule out the possibility that some investors will earn above-normal returns. Over any period of time, some investors will beat the market, but the number of investors who do so will be no greater than expected by chance."

The job of the free market is to set prices so that investors are compensated for the risk they bear. Investors should be confident that every future period (day, month, year, 5, or 10 years), has approximately the same expected return (Er) for that period, given a certain investment (i). In other words, for each investment there is some probability distribution of future returns, where the average or mean of that distribution is the expected return. The expected return and standard deviation for diversified portfolios can be best estimated by looking at the last 50 years or using the Fama/French Five Factor Model for equities and fixed income, as explained here.

Market prices change so that buyers will be comfortable that they will earn the expected rate of return commensurate with the risk of their investment, based on the current estimated uncertainty of getting that expected return over the appropriate time horizon.

Investors should assume that the expected return is essentially constant based on the Five Factor Model or a long term (approximately 50 years) historical annualized return and standard deviation of a given investment, regardless of market conditions. The expected return changes very slightly as we add one data point at the end and drop one data point from the front of the historical data, to get the new average or annualized return and standard deviation.

Stated as a formula, the Current Price of an Investment (Pi) equals the current Expected Return (Eri) divided by the market's assessment of the current Uncertainty of that Expected Return (UEri), which we now call the Hebner Model:


Price (Pi) is expressed in currency ($), Er in % Return/Period of Time with an implied Standard Deviation based on your method of determination and UEri is a calculated index number with no units. Depending on your Price and Expected Return, you may want to multiply Uncertainty by 100 or some constant for charting purposes, see charts below.

Risk is actually represented twice in the model, with a certain level of risk embedded in the investment (such as Index Portfolio 50) and an additional layer of risk represented by current news or the Uncertainty of the Expected Return. In a really simplied version and a liberal interpretation of the terms, you could say that:

Price = Return/Risk
Risk = Return/Price and
Return = Price x Risk

To visualize how markets work, imagine an essentially constant Expected Return (Er) for a given investment portfolio set at the fulcrum of this teeter-totter. The Uncertainty of the Expected Return would be on the left side and the Price would be on the right side. The price is moving inversely proportional to the uncertainty of expected returns. When uncertainty (guided by unexpected and random new information about the systematic or market risk, i.e. news about capitalism) goes up 2%, prices (set by willing sellers agreeing with willing buyers in a free market) go down 2%. When uncertainty goes down 2%, the prices go up 2%, allowing expected return of the investment to remain essentially constant.

As illustrated in Figure 4 below, news (uncertainty), prices and returns are generated in a random series as time goes by, but within ranges (standard deviations) that are tied to the risk level of Index Portfolio 50.

IFA suggests that investors who score a 50 on the Risk Capacity Survey should invest in Index Portfolio 50 and that they should have an average holding period of about 7 years.

Figure 4 estimates 7 years (84 months) of news, prices and monthly returns. The 84 monthly returns are simulated by the dropping of beads from the center of the folcrum. The beads eventually form a bell shape curve, with a shape that resembles what was expected: an Average Return of near 0.9% /month and a Standard Deviation (2.5%). These characteristics are appropriate for Index Portfolio 50, based on 600 monthly returns. The 600 months of data are represented by the black outline of the distribution in the folcrum. This bell curve is our best estimate of the probability distribution of future returns or Eri.

Figure 4: As Time Goes By -

Enlarge

In Robert C. Higgins book, Analysis for Financial Management, he paints a vivid picture of how information is devoured by market participants: "Market efficiency is a description of how prices in competitive markets respond to new information. The arrival of new information to a competitive market can be likened to the arrival of a lamb chop to a school of flesh-eating piranha, where investors are--plausibly enough--the piranha.

The instant the lamb chop hits the water, there is turmoil as the fish devour the meat. Very soon the meat is gone, leaving only the worthless bone behind, and the water returns to normal. Similarly, when new information reaches a competitive market there is much turmoil as investors buy and sell securities in response to the news, causing prices to change. Once prices adjust, all that is left of the information is the worthless bone. No amount of gnawing on the bone will yield any more meat, and no further study of old information will yield any more valuable intelligence."

Benjamin Graham is the most famous of all stock pickers. Ultimately, even he agreed with the efficient market theory as seen in this video clip on the left. Eugene Fama's paper Market Efficiency, Long-Term Returns, and Behavioral Finance is the #1 downloaded academic paper on the web and explains the most recent challenges to this hypothesis.

Problems

Pickers are Fooled by Randomness

To save you some time, all you need to understand about time picking is the Random Walk Theory. This theory simply states that nobody can consistently see what tomorrow will bring. Just remember that markets are moved by news--news that is unpredictable and unknowable in advance (that is the very definition of "news"). Because news is random and unpredictable, the markets move in a random and unpredictable fashion. Period, end of story.

This simple and easy to understand concept about the markets was first published over one hundred years ago. Virtually all subsequent academic studies detailing actual stock market data conclude that time picking is not likely to be a successful investment strategy. Unless, of course, the Goddess Fortuna is directing your trades with whispers from above.

From 1901 to 1990, the stock market return was approximately 9.5% per year. The SEI Corporation completed a study in 1992 that determined that in order to just equal this average annual return over the ninety-year period, a time picker needed to correctly select about seventy percent of the ups and downs of the market.

They also determined that if a picker called one hundred percent of the declining markets and only fifty percent of the rising markets, they still would fail to exceed the return of the overall market during this period. To add a final blow, there was no consideration for the higher short-term capital gains taxes or transaction costs involved in this highly flawed strategy. No wonder ninety-five percent of market timing newsletters go out of business.

Missing the Best and Worst Days

Almost all big stock market gains and drops are concentrated in just a few trading days each year. Missing only a few days can have a dramatic impact on returns. Table 4-1a illustrates how an investor who hypothetically remained invested in the S&P 500 Index throughout the 20-year period from 1991 to 2010 (5,043 trading days) would have earned a sizable 9.14% annualized return, growing a $10,000 investment to $57,512. By missing only the five best-performing days in that time period, annualized return shrank to 6.93%, with $10,000 growing to $38,167. Even worse, if an investor missed just the one day a year (on average) with the largest gains, the returns were cut down to just 2.99% a year. If an average of just two of the biggest days a year were missed, an investment in the S&P 500 turned negative, with $10,000 eroding in value to just $8,243, a loss of $1,757!

Many market timers will tell you their aim is to miss the worst days, which is an even bigger issue than the problem of missing the best days. The predicament, however, is that the worst days are equally concentrated and just as difficult to identify in advance as the best days. If someone could have avoided the worst days, they would have obtained true guru status. Table 4-1b illustrates the value of missing the worst performing days in the 20-year period from 1991 to 2010. If the 40 worst-performing days of the S&P 500 Index were missed, an investor’s increased return would have been 769% more than investors who stayed in the market every day throughout the entire 20 years. The problem, however, is finding the crystal ball that can forecast the 40 worst performing days out of 5,043 days. This shows how market timing can be tempting and alluring.

University of Michigan Professor H. Nejat Seyhun analyzed 7,802 trading days for the 30 years from 1963 to 1993 and concluded that just 90 days generated 95% of all the years’ market gains—an average of just three days per year.

As MIT Professor Fisher Black says, "The market does just as well, on average, when the investor is out of the market as it does when he is in. So he loses money, relative to a simple buy-and-hold strategy, by being out of the market part of the time."

Table 4-1a

Table 4-1b

Big down days and big up days frequently come right next to each other. This is volatility—and it is why you have to stay in the markets to get the markets’ superior return.

The chart below shows the returns of the IFA Index Portfolios in the year that followed the bottoming of the market on March 9, 2009. One year later, to the day, we see that investors who pulled out of the market in early 2009 and remained terrified about getting back in, missed out on a 102.52 % gain on our IFA Index Portfolio 90, which is IFA’s full-equity portfolio.

Figure 4-1a

To better visualize just how hard it is to find those 20 days, here is an image of the whole period in the study.

Figure 4-2

Another study from cypen.com found that being fully invested in the S&P 500 for the five-year period ended December 31, 1995 yielded a 16.5% average annual total return. If a market timer missed the twenty best days, that return fell to 7.3%. And if the sixty best days were missed (that's only twelve days per year), the return plummeted to -3.4%.

In a January 24, 2009 article in the Wall Street Journal, titled " Why Market Forecasts Keep Missing the Mark," Jason Zweig recounted how difficult it is to predict the future direction of the market. In the article he states, "History shows that the vast majority of the time, the stock market does next to nothing. Then, when no one expects it, the market delivers a giant gain or loss -- and promptly lapses back into its usual stupor. Javier Estrada, a finance professor at IESE Business School in Barcelona, Spain, has studied the daily returns of the Dow Jones Industrial Average back to 1900. I asked him to extend his research through the end of 2008. Prof. Estrada found that if you took away the 10 best days, two-thirds of the cumulative gains produced by the Dow over the past 109 years would disappear. Conversely, had you sidestepped the market's 10 worst days, you would have tripled the actual return of the Dow. "Although we could make a bundle of money if we could accurately predict those good and bad days," says Prof. Estrada, "the sad truth is that we're very, very unlikely to do that." The moments that made all the difference were just 0.03% of history: 10 days out of 29,694."

The odds against success in picking the right times are overwhelming, and the odds become worse over time with the high taxes and costs associated with frequent trading.

Professor Hersh Shefrin took a look at some very interesting behavioral finance issues about investor's perceptions of how markets works. In surveys of both individual and professional investors, he discover that neither one understood that last year's return had no predictive value for the next year. Individuals tended to think there was a positive correlation, meaning that one bad year is followed by another bad year and one good year is followed by a good year. Professional investors tended toward the opposite point of view, thinking that one good year tends to be followed by a bad year and visa versa. The fact is that they are both wrong. As indicated by the very low R2 values in Figures 4a-4d below, no previous period was a predictor of the subsequent period. Shefrin also explores the investors lack of understanding of how risk has a positive correlation to returns, meaning more risk begets more return over the longer periods like 10 years. He stated, "...investors have a good sense of what makes up risk, but a poor sense of how to connect that to expected returns." (see his paper, Behavioral Finance, by Hersh Shefrin, CFA Institute, June 2007, pages 1-7)

Figure 4-2a

Figure 4-2b

Figure 4-2b1

Figure 4-2c

Figure 4-2d

Figure 4-2e

Figure 4-2f

Figure 4-2g

Figure 4-2h

Academic Studies Prove that Time Picking Doesn't Work

The literature is full of studies confirming the failure of market timing. All these peer- reviewed research papers share the same conclusion. Forget about trying to time the market.

In the paper entitled, "Selectivity and Market Timing Performance of Fidelity Sector Mutual Funds," Dellva, Demaskey and Smith concluded that there was negative timing ability among the Fidelity sector funds during the period from 1989 to 1998.

In 1994, Graham and Harvey, both distinguished professors at Duke University, studied 237 investment newsletters over the 1980-1992 period. As was stated in the introduction, they concluded that "there is no evidence that newsletters can time the market. Consistent with mutual fund studies, winners rarely win again and losers often lose again."

In 1998, Becker, Ferson, Myers, and Schill studied market timing in their paper entitled, "Conditional Market Timing with Benchmark Investors." They found no evidence supporting the claim that funds have significant market timing ability.

Wei Jiang presents his market timing studies in his 2001 paper, "A Nonparametric Test of Market Timing." After spending countless hours combing through the results of 1,557 retail mutual funds and 210 institutional funds, Jiang concluded that timing ability on average is negative. Just as a side note, this paper lists 41 other academic studies in the reference section, providing further corroboration that market timing doesn't work.

Super star academic William Goetzmann, along with Ingersoll and Ivkovich, put in their two cents with a paper entitled, "Monthly Measurement of Daily Timers." They performed four tests of timing skill on a sample of 558 mutual funds. They concluded that very few funds exhibit statistically significant timing skill.

In another paper written in 2002 by Johannes, Polson and Stroud, market timing was once again put to the test. Their simple yet powerful conclusion was that market timing strategies performed worse than the buy-and-hold strategy in all cases they examined.

To illustrate the extreme concentration of stock market returns, H. Nejat Seyhun carefully analyzed the 7,802 trading days for the 30 years from 1963 to 1993. Mr. Seyhum is the Chairman of Finance at the University of Michigan School of Business Administration, a position that is only achieved by highly dedicated and intelligent individuals who have spent many years learning how capital markets work. His conclusion provides a crushing blow to timers who think they can outsmart the market. A mere 90 days over 30 years contained 95% of all the market gains. That is an average of 3 days per year.

In "The Elements of Investing" by Burton Malkiel and Charles Ellis, the authors discuss a psychologist from Berkeley named Philip Tetlock, who studied over 82,000 varied predictions by 300 experts from different fields over 25 years, and concluded that expert predictions barely beat random guesses.  Ironically, the more famous the expert, the less accurate his or her prediction tended to be.

In summary, all of the above studies demonstrated that there is no evidence that time pickers can consistently know where the market is headed.

Time Picking Gurus

Even though financial academics widely accept the concept of market efficiency, Wall Street firms continue to pander their market timing predictions through their appointed gurus. Their strategy is to encourage their clients to trade more, even though academics conclude that trading is hazardous to the client's wealth. Their annual predictions of the Dow closing value have been far from accurate.

How often does a market-timing guru need to be right to beat an index? Nobel Laureate William Sharpe set out to answer that very question in his 1975 study titled, "Likely Gains from Market Timing.^{("(William Sharpe, "Likely Gains from Market Timing,") Financial Analysts Journal, vol. 31, no 2 (1975).}   Sharpe wanted to identify the percentage of time a market timer would need to be correct to break even relative to a benchmark portfolio. He concluded a market timer must be correct 74% of the time in order to outperform a passive portfolio at a comparable level of risk. In 1992, SEI Corporation updated Sharpe's study to include the average 9.4% stock market return from the period 1901 – 1990. This study determined that gurus must be right at least 69% and as high as 91% of the time, depending on the timing of the moves. ^{("Technical Note: Calculation of Forecasting Accuracy," SEI Corporation position paper, April 1992.)}

What percentage of times do market timing gurus get it right? CXO Advisory Group tracks public forecasts of self-proclaimed market-timing gurus and rates their accuracy by assigning grades as "correct," "incorrect" or "indecisive." The chart depicts CXO's percentage grades for 37 well-known market-timing gurus who made a collective 3,541 forecasts from as early as December 28, 1998 through August 15, 2011. The study shows that not one of the self-proclaimed gurus were able to meet Sharpe's requirement of 74% accuracy, or SEI's minimum 69%, thereby failing to deliver accuracy sufficient to beat a simple index portfolio. 

At first glance, the 11 gurus who had percentage accuracy of more than 50% might look appealing to a time picker – but beware, the opportunity costs associated with a time picker's proclivity toward holding cash in some up years creates a higher hurdle as they will have to make up those superior returns foregone by stocks. Transaction costs associated with market timing add another hurdle for market timers to break even. 

Also see Gurus.

The pied pipers of Wall Street do not have a good batting average. No Babe Ruths here. Smartmoney.com has been tracking the pundits dating back to 1997. The table below summarizes the batting averages of several of these market pundits. You can see that Ed Hyman has the best batting average with a 0.236 and Ed Hyman is considered one of the best economists. That is the equivalent of hitting an average double each time at bat. Or in the scoring system, a call that may win plaudits for accuracy but not for insight and strong feeling. Often a general statement that comes true. For example, the forecaster made a correct but obvious and wishy-washy call about the direction of interest rates. For those who scored lower, it generally means a true dud of a pick or a mostly inaccurate prediction that might have one redeeming feature but that likely fails the degree of difficulty and/or confidence tests. A batting average of 0.400 would indicate an accurate forecast that was difficult to make but still uttered with the utmost confidence.

Here are the averages as reported by Smartmoney, where the the average batting average for all 12 forecasters was somewhere between first and second base, 0.166. Since an accurate call would yield an average of 0.400, the most repected and well known market forecaster fall on the side of inaccuracy about 60% of the time and accuracy about 40% of the time.

Table 4-2

For further evidence of the heavy fog in crystal balls, let’s take a look at results from 2003 and predictions about them. In that year, stock prices rose in almost every global market. Returns for U.S. small company stocks were particularly strong; the total return for the Russell 2000 Index was 47.25%, the highest annual return since inception of the index in 1979, according to Russell Analytic Service; and the total return for the CRSP 9-10 Index was in excess of 70%, the highest annual return since 1967, according to the Center for Research in Security Prices, University of Chicago.

However, investors seeking to capture market rates of return in 2003 would have had to ignore a large body of opinion, a sample of which appears below, suggesting that stocks were unattractive. Most of the quotations listed appeared during the first quarter of 2003 when stock prices were slumping and the outlook most uncertain. Year-to-date returns for the S&P 500 and Russell 2000 Indices did not turn positive until mid-April.

One concept that investors need to remember is that the probability of getting a forecast correct maybe much higher than they expect it to be. For example, if an event has a 10% chance of occurrence and you make 10 forecasts about that event, there is a 65.13% chance that one of those guesses will be correct. See the chart below and test your own assumptions about forecasts.

Figure 4-2i

Since most investors only hear about the forecasts there were correct, here is an offset to that point of view. Most predictions are wrong, as seen in the many examples below.

“It’s going to be a difficult environment for stock investors. Don’t count on the market to move up. To make money, you’ve got to select the right names.” - Quotation attributed to David J. Winters. Source: Franklin Mutual Advisers LLC, “Brainwork from the Experts,” BusinessWeek (December 30, 2002): 102.  [From December 2002 to December 2006, the return of the S&P 500 was 62.46%, and for Index Portfolio (IP) 100 it was 145.54%.]

“I suspect that 2003 will end up being the fourth consecutive down year for the first time since 1932.” - Quotation attributed to Jeremy Grantham of Grantham, Mayo, Van Otterloo & Co. Source: “Is the Bear Market over?” Smart Money (January 2003): 71. [From January 2003 to December 2006, the return of the S&P 500 was 72.62%, and IP 100 was 153.66%.]

“Many investors have become skeptics, inclined to sell and take profits when stocks rise, rather than buy in hopes of more gains.” - Source: E.S. Browning, “Euphoric Burst, then it’s Back to Usual Blahs,” The Wall Street Journal, January 6, 2003, p. C1. [From January 2003 to December 2006, the return of the S&P 500 was 72.62%, and IP 100 was 121.91%.]

“War worries also are driving money back into Treasury bonds and even into the money market, despite the fact that both of those investments feature some of the lowest interest rates in years.” - Source: E.S. Browning, “Stocks Drop, Wiping out January’s Gains,” The Wall Street Journal, January 23, 2003, p. C1.  [From February 2003 to December 2006, the return of the S&P 500 was 77.30%, and IP 100 was 158.81%.]

“I do not believe a long-term investor will make money in this market because it is a secular bear market.” - Quotation attributed to Felix Zuelauf of Zuelauf Asset Management. Source: “On the Money — Roundtable Part II,” Barron’s (January 27, 2003). [From January 2003 to December 2006, the return of the S&P 500 was 77.30%, and IP 100 was 158.81%.]

“The fear is that it could be a long war and we could have a sustained sell-off because of it.” - Quotation attributed to Tim Heekin of Thomas Weisel Partners. Source: “Fears of War with Iraq Send Blue Chips below 8000,” The Wall Street Journal, January 28, 2003,pC1. [From January 2003 to December 2006, the return of the S&P was 77.30%, and IP 100 was 158.81%.]

“According to a monthly survey by Merrill Lynch, global money managers are more risk-averse than at any time since the days following the terrorist attacks of September 2001.” - Source: E. S. Browning, “Investment Pros Want No Part of Current Risk,” The Wall Street Journal, February 24, 2003, p. C1 [From February 2003 to December 2006, the return of the S&P 500 was 77.30%, and IP 100 was 158.81%.]

“Soaring energy costs, the threat of terrorism, and a stagnant job market have sent consumers’ spirits plunging to levels normally seen only in recessions. The Conference Board’s index of consumer confidence fell to 64 in February, the lowest since 1993.” - Source: Greg Ip, “Consumer Spirits Decline to Levels last Seen in ‘93,” The Wall Street Journal, February 26, 2003, p. A3. [From February 2003 to December 2006, the return of the S&P 500 was 77.30%, and IP 100 was 158.81%.]

“Mr. Grantham’s study of bubbles suggests that it takes them about as long to deflate as it did to inflate.... He says the Standard & Poor’s 500-stock index could fall more than an additional 20% from its current level.” - Quotation attributed to Jeremy Grantham of Grantham, Mayo, Van Otterloo & Co. Source: E.S. Browning, “A Party so Wild, the Cleanup Goes on,” The Wall Street Journal, March 3, 2003, p. C1. [From March 2003 to December 2006, the return on the S&P 500 was 80.02%, and IP 100 was 164.36%.]

“U.S. moves toward war against Iraq sent nervous Asian stock markets to lows not seen in years, even decades, threatening an already shaky regional economy.” - Source: Martin Fackler, “Nikkei Declines to Lowest Level in Two Decades,” The Wall Street Journal, March 10, 2003, p. C14. [From March 2003 to December 2006, the return on the S&P 500 was 80.02%, and IP 100 was 164.36%.]

“Investors continue to sour on stocks. So far this year, investors have made net withdrawals of $11.3 billion from their stock mutual funds — including a hefty $3.7 billion just last week — according to AMG Data Services." - Source: Gregory Zuckerman, “Investors Rush to Buy Bonds, Fleeing Stocks,” The Wall Street Journal, March 11, 2003, p. C1. [From March 2003 to December 2006, the return of the S&P 500 was 80.02%, and IP 100 was 164.36%.]

“No rally may be enough to entice some investors back. ‘I don’t trust it anymore,’ says Polly Sveda of the market, ‘I never should have trusted it.’ There is plenty of evidence that a growing number of individual investors are shunning stocks.” - Source: Tom Petruno, “After the Fall,” Los Angeles Times, March 16, 2003, p C1.  [From March 2003 to December 2006, the return of the S&P 500 was 80.02%, and IP 100 was 164.36%.]

“This quarter is shaping up to have the worst ratio of negative warnings to positive outlooks since the third quarter of 2001.” - Source: Jesse Eisinger, Ahead of the Tape, The Wall Street Journal, March 31, 2003, p. C1. [From March 2003 to December 2006, the return of the S&P 500 was 80.02%, and IP 100 was 164.36%.]

“If we see 8% this year, that will be good.” -Quotation attributed to Edgar Peters of PanAgora Asset Management. - Source: E.S. Browning, “Trading Ranges Keep the Bulls in.” The Wall Street Journal, April 21, 2003. [From April 2003 to December 2006, the return on the S&P 500 was 78.29%, and IP 100 was 164.76%.]

“These stocks still are way ahead of themselves. I am not at all sure we have seen the bottom; I think we could see new, lower lows.” - Quotation attributed to John Rutledge of Evergreen Investments. Source: E.S. Browning, “Experts Duel over Fate of Bellwether Rally,” The Wall Street Journal, June 16, 2003, p. C1. [From June 2003 to December 2006, the return on the S&P 500 was 56.47%, and IP 100 was 121.91%.]

“Several important signals suggest that prices at best have topped out for the time being, and at worst are primed to move back down. Such signals ‘are classic signs of a market top,’ says Charles Biderman, president of market-research firm Trimtabs.com.”- Source: Jeff Opdyke, “Four Signs Stocks May Be Near a Peak,” The Wall Street Journal, June 26, 2003, p. D1. [From June 2003 to December 2006, the return on the S&P 500 was 56.47%, and IP 100 was 63.50%.]

“In our view, the quality of earnings of the S&P 500 from an accounting standpoint is the worst it has been in more than a decade.” - Quotation attributed to David Bianco of UBS Financial Services. Source: Henny Sender, “At Earnings Halftime, Stocks Hear Mixed Messages,” The Wall Street Journal, July 28, 2003, p. C1. [From July 2003 to December 2006, the return on the S&P 500 was 54.57%, and IP 100 was 114.82%.]

“Even some bears now acknowledge that, when they warned people to stay away from stocks one year ago they were wrong. But they insist that now, after the market’s big gains, it is too late to buy.” - Source: E.S. Browning, “Stocks are Defying the Critics,” The Wall Street Journal, October 13, 2003, p. C1. [From the time this prediction was made until December 2006, the return of the S&P 500 was 50.62% and IP 100 was 94.93%.]

The year 2006 was another good year for investors around the globe as equity prices rose in 46 of the 50 countries whose equity market returns are reported by Morgan Stanley Capital International. Among these, only Israel, Jordan, Thailand, and Turkey saw their local stock market indexes slump for the year. Total return for United States stocks was 15.32% according to MSCI, placing it next-to-last among 23 developed markets (in dollar terms) and 42nd out of 50 countries in all. There were 36 markets with a total return greater than 20% (in dollar terms), and 19 had a total return greater than 40%. Nine of the top ten were emerging markets. (MSCI data, copyright MSCI 2006, all rights reserved.)

To capture the returns of equity markets, investors require a better understanding of market timing and capitalism than that of the so-called experts. A review of the many market guru predictions and other news events suggested that 2006 would be less profitable than what happened. Reading these should help you resist the temptation to alter your portfolio based on the coming market predictions for 2007. Investors are far better off to focus on the risk of their portfolios, and let the returns ebb and flow with the news about capitalism. Free markets were meant to be free... not managed.

"When US consumer-spending weakness is felt globally, export earnings and economic activity will nosedive and murder foreign stocks. Best advice: unload your foreign equities now on all those bullish latecomers."
A. Gary Shilling, "The Coming Bernanke Bust," Forbes, December 26, 2005. [From January 1, 2006 to December 2006, the return on the S&P 500 was 15.73%, and IP 100 was 22.33%.]

"The good news about last year's flat stock market? Stocks got cheaper. The bad news? They could get cheaper still . . . the market will stay flat as earnings rise—a situation akin to what happened through much of the 1970s into the early 1980s."
Justin Lahart, "Ahead of the Tape," Wall Street Journal, January 3, 2006. [From January 1, 2006 to December 2006, the return on the S&P 500 was 15.73%, and IP 100 was 22.33%.]

"Our five-year forecasts show that most asset classes are expected to earn very little over cash."
Quotation attributed to Gordon Fowler Jr. of Glenmede Trust Co. Source: Tom Petruno, "Whether or Not to Heed the Fed," Los Angeles Times, January 8, 2006. [From January 1, 2006 to December 2006, the return on the S&P 500 was 15.73%, and IP 100 was 22.33%.]

"Mr. Greenspan's departure could well mark a high point for America's economy, with a period of sluggish growth ahead. This is not so much because he is leaving, but because of what he is leaving behind: the biggest economic imbalances in American history."
Economist, "Danger Time for America," January 14, 2006. [From January 1, 2006 to December 2006, the return on the S&P 500 was 15.73%, and IP 100 was 22.33%.]

"Wall Street's most optimistic strategist on US stocks, Ed Keon of Prudential Group in New York, just became one of the most pessimistic."
Economist, Bloomberg News, "Strategist Turns More Bearish, Advises Clients to Cut Stocks," Los Angeles Times, February 7, 2006. [From February 1, 2006 to December 2006, the return on the S&P 500 was 12.74%, and IP 100 was 14.0%.]

"The January [trade] gap was 'little short of disaster' that could trim economic growth in the first quarter if it remains as large in the coming months, said Paul Ashworth, senior international economist at Capital Economics."
Reuters, "Trade Gap Soars 5.3% to New High," Los Angeles Times, March 10, 2006. [From March 1, 2006 to December 2006, the return on the S&P 500 was 12.44%, and IP 100 was 13.91%.]

"Safe bonds, risky bonds, equities, gold, property, and commodities are all expensive by historical standards."
Martin Wolf, "Why a Long-Term Bet on the Stock Market May Disappoint," Financial Times, March 22, 2006. [From March 1, 2006 to December 2006, the return on the S&P 500 was 12.44%, and IP 100 was 13.91%.]

"On Wall Street, the Dow slid 214.28 points, or 1.9%, to 11205.61—its biggest decline since March 2003. 'It's finally dawning on people that the Fed is going to have to raise rates until the economy slows."
Quotation attributed to Edgar Peters, PanAgora Asset Management. Source: Los Angeles Times, "Dow Has Biggest Drop in Three Years," May 18, 2006. [From May 1, 2006 to December 2006, the return on the S&P 500 was 9.6%, and IP 100 was 7.43%.]

"If either the inflation scare or the dollar scare prove correct, shares could have a long way further to fall."
Financial Times, "The Return of Fear to World Stock Markets," May 20, 2006. [From May 1, 2006 to December 2006, the return on the S&P 500 was 9.6%, and IP 100 was 7.43%.]

"Foreign stock markets suffered a wrenching sell-off Monday on deepening worries about the global economy . . . the selling wave, which slammed shares on every continent, also weighed on the US market."
Tom Petruno, "Global Cooling in the Markets," Los Angeles Times, May 23, 2006. [From May 1, 2006 to December 2006, the return on the S&P 500 was 9.6%, and IP 100 was 7.43%.]

"The economy could be facing a bout with stagflation. My feeling is we're headed for a tragedy here."
Quotation attributed to Prof. Peter Morici, University of Maryland. Source: Lisa Girion, "Stagflation Worries Are Mounting," Los Angeles Times, June 15, 2006. (Returns to be updated as length of time span increases).

"Too many bubbles, too many potential busts—that's what's confusing the global financial markets these days. . . . If we learned anything in the boom and bust in the last decade, it's that the bottom can be further down than anyone expects."
Michael Mandel, "Bubble, Bubble, Who's in Trouble?" Business Week, June 26, 2006. (Returns to be updated as length of time span increases).

"Corporate America is about to witness a sharp rise in bankruptcies caused by the recent boom in debt-funded acquisitions and hedge funds' growing appetite for takeovers, according to Wilbur Ross, the veteran investor in distressed businesses."
Francesco Guerrera, "More US Defaults 'Inevitable' Warns Ross," Financial Times, June 30, 2006. (Returns to be updated as length of time span increases).

"Israel's escalating incursion into Lebanon—with bombing attacks on Beirut's airport and a naval blockade—could turn its border fight with militant Islamists into a regional war that Israel is openly warning might lead to Syria, and beyond that to Iran."
Karby Leggett, "Threat of Wider Mideast War Grows," Wall Street Journal, July 14, 2006.

"Since the mid-1970s, every time the Fed has pushed rates higher, it has created a recession, a bear market, or both."
E.S. Browning, "Not Too Fast, Not Too Slow," Wall Street Journal, August 21, 2006.

"It's very difficult for me to tell our clients that all is clear for them to get into the market when we have the historically tough months of September and October ahead of us." [September and October, 2006 were the best-performing months for the Dow Jones Industrial Average in 2006.]
Quotation attributed to Linda Duessel, Federated Investors. Source: E.S. Browning, "Taking Stock: What's Ahead for Investors," Wall Street Journal, September 5, 2006.

"The chief executives of America's top companies have an increasingly pessimistic outlook on the US economy, according to a report published yesterday."
Daniel Pimlott, "Business Chiefs Grow Gloomier," Financial Times, October 6, 2006.

"International condemnation poured down on North Korea Monday for its announced nuclear test, as scientists tried to determine whether the underground blast was a successful nuclear explosion and diplomats conferred on how to contain the rogue regime."
Maggie Farley, "World Condemns North Korea," Los Angeles Times, October 10, 2006.

	August 13, 1979 Issue of BusinessWeek Dow Jones Industrial Average: 875.25 “The U.S. economy probably has to regard the death of equities as a near-permanent condition.” What happened in Index Portfolio 100 for the 5 years after this article?
	How accurate are predictions about recessions?

See more predictions from 2007.- The Press and Its Poor Market Timing

What the Pros said in Dec 2007: Buy Lehman Brothers, Bear Stearns, and Merrill Lynch and financial giant American International Group. :-)

If the highly paid experts can't get it right, then who can predict the near term direction of markets? Answer: Nobody.

Interesting Historical Data:

		August 13, 1979 Issue of BusinessWeek “The U.S. economy probably has to regard the death of equities as a near-permanent condition.”
	Note: Recorded May 2008
In Oct 1974, near the end of the 1973-1974 market decline, a Gallup Poll indicated that 51% of Americans agreed with economists that felt we were headed for another 1930's style depression. Look at the 29.56% per year return for the next 5 years after the prediction (click here, then scroll down to see the chart). Expected returns on bonds and stocks are higher when conditions are weak and lower when economic conditions are strong. - Fama and French, "Business Conditions and Expected Returns on Stocks and Bonds," (November 1989), Journal of Financial Economics

One example of an interesting period would be a view of the 1929 stock market crash period in an Index Portfolio 100. Or take a look at a more recent 6 year period (1969-1974) where Index Portfolio 100 was still down 34% after 6 long years, but that is why this level of risk is designed for 12 years or more time horizons. Or 6 years from 1975-1980, where it went up 363% total return.

Problems

Many measurements seem random, such as the heights of humans, the length of leaves, the roll of 5 dice, and the change of stock market prices. But when academics, statisticians and mathematicians view the world, they see patterns that others do not notice.

The device shown below on the left was first created by Francis Galton in about 1890 and today has many names; Probability Pinball, Galton Board, Quincunx Board, and Bean Machine. The Galton Board simulates random events and how the distribution of a large number of events tend to form a bell shaped curve. The beads falling through the pins are not predictable as to which course they will take, but the average outcome of a large number of dropping beads, just like 780 monthly returns of Index Portfolio 60, form a relatively predictable pattern. In 1794, Johann Carl Friedrich Gauss described the pattern as a normal distribution, referring the the fact that it is normal for random events to form such distributions. The more often an event occurs, the more a pattern emerges such as seen in the histogram of monthly returns for Index Portfolio 60. The beads randomly falling into different channels and the random monthly index price changes that are created due to investor's reactions to random news about capitalism, show essentially the same normal distribution.

Over the last 65 years, Index Portfolio 60 has an average return of 1.00% per month and a standard deviation of 3.13% and the pattern of the pins the beads flow through generate a distribution that looks quite similar. If the laws that provide for and regulate capitalism remain relatively constant, the risks will remain relatively constant and therefore the future monthly returns over a large sample of 20 years or more should emerge with similar distributions.

CLICK ON THE GALTON BOARD IMAGE BELOW TO VIEW ANIMATION

Gains and Losses are Impossible to Identify in Advance

Figures 4-3 through 4-15 shows the distribution of daily and monthly returns of the S&P 500 over several different time periods. The red bars indicate losses and the gold areas indicate gains. Note that the histograms is fairly evenly distributed (normal distribution) (or here), which is to be expected from a random distribution (see the Galton board.) Watch this video from the Khan Academy on the concept of the Normal Distribution.

The display of a central distribution around the average (Central Limit Theorem) is indicative of the randomness of the news that generates the random and unpredictable movements of the S&P 500 or any other index. Watch this video from the Khan Academy on the concept of Central Limit Theorem.

Based on the following histograms, investors can see how difficult it is to find the randomly distributed days with gains or to avoid the days with losses. For each period, the large gains or losses for the entire period are highly concentrated at the right and left tails, making them impossible to consistently identify them in advance. In other words, it is impossible for time pickers to consistently outperform the market.

Figure 4-3 (2010)

Figure 4-3 (2009)

Figure 4-4 (2008)

Figure 4-5

Figure 4-6

Figure 4-7

Figure 4-8

Figure 4-9

Figure 4-10

Figure 4-11

Figure 4-12

Figure 4-13

Figure 4-14

Figure 4-15

See the similarity of the distributions above to the 5 dice roll distribution on the right side of Figure 4-16 below. The characteristics of the average and standard deviation are not the same as the 964 monthly returns of the S&P 500 index, but the concept of a central distribution around the mean is very similar, as you see when they are compared. Also note the sampling error in the 5 year (60 month) periods as compared to the 964 months, which are very similar to the sampling error of only 60 roles of the dice, versus 1,000 rolls. The randomness of the news generates the random and unpredictable movements of the S&P 500. In a random distribution, successful market timing over the long term is impossible.

Figure 4-16

"A chance event is uninfluenced by the events which have gone before.  If a true die has not shown 6 for 30 throws, the probability of a 6 is still 1/6 on the 31st throw.  One wonders if this simple idea offends some human instinct, because it is not difficult to find gambling experts who... advocate ... the principle of 'stepping in when a corrective is due'." This is no different than stock market forecasters looking for the next "correction." Watch this video from the Khan Academy on the concept of the Law of Large Numbers vs Averages.

Time Pickers Lose

There seems to be universal agreement among investment experts that time picking is futile. Even so, it is not unusual for these same experts to actively tout its merits. Wall Street brokerage firms publish stock picking, time picking, money manager picking, and style picking studies to encourage existing and potential clients to change their investment strategies in midstream, which dumps more sales commissions into the pockets of these firms.

Time Pickers Pay More Taxes

Time pickers usually charge clients an annual fee of two to three percent of the value of their investment portfolios. These timers are nothing more than highly paid gamblers who bet with your money. Some investors who time markets invest in market timing mutual funds, which often produce high trading costs. The funds also generate short-term taxable capital gains due to the liquidation of fund stock positions to pay off departing shareholders. Investors can avoid cost-generating, tax-creating moves made by managers and shareholders of active mutual funds by remaining fully invested in index funds at all times. Especially mutual fund companies that restrict their shareholders to those who understand how the market works. Dimensional Fund Advisors is a firm that restricts access to their funds. Only large institutional investors and clients of pre-approved investment advisors are allowed to invest in the funds. You might call it a group of really smart investors.

In addition, when an investor moves in and out of investments, they create the possibility of paying a huge portion of their gains in taxes. For short-term gains, federal and state taxes can exceed 40% in some states. Even when time pickers are lucky enough to win, the taxes significantly reduce their return.

Solutions

The bottom line is this: the right time to be in the market is when an investor has money, and the right time to get out of the market is when an investor needs the money. The longer an investor can stay invested, the better. The investor who stays fully invested throughout the market swings experiences gains about two-thirds of the time. There is no reason to believe that professional market timers can correctly guess every two out of three favorable market periods over the long run.

Even though a buy-and-hold investor most likely experiences losses about one out of every three years over the long run, the losses of these fewer down years are far outweighed by the gains of the more numerous up years. Since 1926, the S&P 500 has averaged an excellent annual compound return of 10.7 percent with a range of plus or minus 20% two thirds of the time.

An investor who remains fully invested in down markets enjoys other advantages. The investor who remains in the market avoids exiting a down market, thus avoiding locking in losses on stock mutual fund shares. Hefty trading commissions or taxes on any realized capital gains are also deflected. An investor can also benefit by never again paying high market timing advisory fees.

Investors build real wealth only by maintaining a constant presence in the asset classes in which they are invested during the good times and the bad times. This not only gives long-term investors an immediate advantage each time the market goes back up after it has declined, it also allows them to participate in the market's climb in value over the long run. This makes them better stock pickers than the professionals who dart in and out of markets in unattainable attempts to anticipate where they will be heading in the future.

Summary

The goal of a time picker (also referred to as a market timer) is to obtain the upswings of the market and avoid the downswings. In other words, the goal is to get return without risk. Risk is the source of returns; therefore, investors must subject their capital to risk. It is only a question of how much risk is right for each investor.

Time picking is beneficial only to financial firms who make money trading shares and selling advice. The firms who charge top dollar for the best advice available in the world ironically end up with sub-market returns. Market strategists, even those considered successful have fallen away from the limelight. History has shown that market strategists, or any financial analysts for that matter, are right unless they are proven to be wrong. The industry has created a world in which complicated ratios and mathematical formulas are paraded in front of the public in hopes of impressing investors with superior knowledge and skills. This elevates the analysts in the public’s eye and ultimately influences investors’ decisions on which firm to choose to handle their investments.

The stock market has experienced a healthy upward climb in value over the long run, which is precisely what makes time picking so unnecessary. The best way for an investor to maximize advantage of these returns is to remain fully invested at all times, holding a globally diversified portfolio of index funds.

In Burton Malkiel's book, A Random Walk Down Wall Street, John C. Bogle is quoted as saying, "In 30 years in this business, I do not know anybody who has done it successfully and consistently, nor anybody who knows anybody who has done it successfully and consistently. Indeed, my impression is that trying to do market timing is likely not only not to add value to your investment program, but to be counterproductive."

In the end, time pickers have two critical decisions to make: when to get in the market and when to get out. The data is now conclusive that there is no reliable timing method to help with either decision. It is time, not timing, that determines an investor's return.

Review Questions

Please answer the following questions before moving on to the next Step:

1. What percentage of accuracy must a time picker maintain in order to be successful?

a) 60 percent
b) 40 percent
c) 70 percent
d) 30 percent

2. Who was the only successful time picker ever recorded?

a) John C. Bogle
b) William F. Sharpe
c) There are hundreds of successful time pickers
d) There are no successful time pickers

3. The S&P 500 produced an annualized return of 17.5% in the 1980’s. A $10,000 investment that stayed fully invested throughout the entire decade grew to $50,162.00. What would the end value be if an investor had missed the best 40 trading days?

a) 12.6% return or $32,763
b) 9.3% return or $24,333
c) 6.5% return or $18,771
d) 3.9% return or $14,661

4. The best lesson to learn from market timing pundits is:

a) Time pickers have no way of predicting the market, and are therefore valueless
b) Be choosy when selecting time pickers, and research their records thoroughly
c) Companies do not report their earnings on a timely basis

We hope that after careful analysis of the data presented in this step, you are getting the message that trying to pick which time is the best time to be in the stock market is an absolute waste of your precious time. Instead of worrying about the market, do something you can control. Hug someone you love, pick some daisies, watch a sunset, and enjoy your life. It's a wonderful world, but it's often hard to see the forest through the trees.

Step 1: Active Investors

Step 2: Nobel Laureates

Step 3: Stock Pickers

Step 4: Time Pickers

Step 5: Manager Pickers

Step 6: Style Drifters

Step 7: Silent Partners

Step 8: Riskese

Step 9: History

Step 10: Risk Capacity

Step 11: Risk Exposure

Step 12: Invest and Relax