Step 1: Active Investor
Active investing is a strategy that investors use when trying to beat a market or appropriate benchmark. Active investors commonly engage in picking stocks, times, managers, or styles. As later steps demonstrate, active investors who claim to outperform a market also claim the power to predict the future. When accurately measured, this is simply not possible. Surprisingly, the analytical techniques that active investors use can best be described as qualitative or speculative. They include predictions of future sales and earnings growth, and are often based on gut feelings and intuition. On the other hand, the passive index investing approach is best described as quantitative or scientific. Indexing techniques include statistical analysis of risk and return data of 20 years or more, in addition to extensive measurements of numerous performance criteria. Many indexes are now based on more than 85 years of risk, return, and correlation data.
As opposed to active managers, investment managers of index funds are far less active
in the buying and selling of stocks, because they do not pick stocks or managers,
time markets, pick styles, or make attempts to forecast the future. As previously
mentioned, the analytical techniques that index funds managers use are best described
as quantitative or scientific.
Approximately 25% of all individual assets and 40% of all institutional assets are currently invested in different index funds. Many institutional funds are one hundred percent indexed. Even Charles Schwab and Company recommends that investors put 80% of their large cap assets into index funds. Mr. Schwab himself has 75% of his mutual funds in index funds. Other indexing proponents include Barclay's Global Investors, Dimensional Fund Advisors, The Vanguard Group, Warren Buffet, Peter Lynch, numerous academic institutions, Economic Nobel Laureates, and Index Funds Advisors (IFA). Insurance companies use a similar approach to indexing when setting premiums for the risks taken by insuring against thousands of different random events. Most of those premiums are also invested in index funds while held in reserves for the inevitable claim payment.
Most investors believe that index funds investing means investing in familiar market indexes, such as the Standard and Poor's 500. S&P 500 funds are structured with the aim to provide the same investment performance as the S&P. By holding all the stocks in the same proportionate amounts as the S&P index, the fund index represents about 80% of the market value of all U.S. companies, mostly large blue chip stocks. The problem is that market indexes, such as the S&P 500, were not originally designed as investment vehicles.
Since the late 1980s, index funds have expanded and are based on more discrete customized indexes. Originally designed for very large pension funds, institutional-style index funds are meant to capture various financial risk factors or dimensions of the market. Exposure to a risk factor such as company size or value constitutes a risk dimension of the market. Investors have been compensated with higher returns for risk exposure to these risk factors since 1929. These dimensions of the market can also be referred to as indexes. Indexes are groups of stocks that have common risk and return characteristics and comply to specific and clearly defined sets of rules of ownership. These groups of stocks include companies from the United States, foreign companies, and even emerging markets. There are additional indexes within these markets, such as value, large value, small growth, large growth, real estate securities, and many fixed-income investments, such as short-term and long-term treasury bonds, municipal bonds, and corporate bonds. Companies are purchased and held within the index when they meet the index parameters. Stocks are sold when they move outside of these parameters and no longer meet the index rules.
An example of an index fund is Dimensional Fund Advisors' (DFA) Micro-Cap index fund, which invests in securities of U.S. companies whose size (market capitalization) falls within the smallest 4% of the total market universe. This includes all stocks traded on the New York Stock Exchange and the American Stock Exchange, as well as those listed in the National Association of Securities Dealers Automated Quotation Over-the-counter (NASDAQ OTC) market. Another example would be DFAs Small Cap Value Fund, which invests in companies ranked in the lowest eight percent by size, as well as the highest 25th percentile by book-to-market ratio (value).
DFA funds are now available to individual investors through a small qualified group of registered investment advisors who have demonstrated their understanding and commitment to the concepts described in this 12-Step Program.
The overwhelming majority of investors are active investors. Extensive research by many academics and investment professionals has shown that investors cannot beat a market in the long run with stock, time, manager, or style picking. It is disconcerting that about 60% of all institutional money invested in U.S. stocks is still actively managed.
The table below summarizes the differences between the two approaches to investing.
We reference the phrase beating a market throughout this 12-step Program.
This is defined as the attempt to obtain a higher net return on investments from
a portfolio of stocks, bonds, or mutual funds than from a relevant and investable
index or benchmark. The net return includes adjustments for all commissions, loads,
fees, expenses, risks, and federal and state taxes. It is calculated over a reasonable
period of at least five years, but preferably over 20 years. The net return of an
active investors stock portfolio can then be paralleled to the index fund
of a comparable index. The index may consist of the entire stock market or a more
specific index, such as small capitalization value stocks. No investor over or underperforms
an index. They simply invest in something other than the index. Since the index
is the only source of long-term risk and return data, why would an investor subject
hard earned savings to anything other than the index?
The most basic tenet of all investing is that exposure of your money to a higher level of risk should be rewarded with a higher expected return. In contrast, lower levels of risk should correlate to a lower expected return. One of the problems with measuring the performance of stock market investing is the lack of a standardized system of benchmarks from which to measure performance. This lack of benchmarking is the black hole of investing. If there is no definitive benchmark, it is impossible to determine if exposure to risk has been properly rewarded. In other words, has the active investor really beaten a market with repeatable skill, or can it just be attributed to luck?
There are many terms used by investment professionals and academics in their quest to define risk. These include markets, benchmarks, asset classes, styles, style boxes, investment objectives, risk factors, market dimensions, market segments, categories, market averages, buckets of stocks, rules of ownership, slices of the market, industry classifications, and indexes such as Dow Jones Indexes, Standard and Poor's Indexes, Russell Indexes, Wilshire Indexes, Morgan Stanley Capital Indexes, Wired Index, and many more. Diversification and measures of volatility, such as standard deviation, are also used to describe risk. Every one of these is an attempt to identify common risk and return characteristics among groups of stocks included in that classification. To reduce confusion, market or index will often be substituted for these terms.
An appropriate challenge to the investment industry is a call to action to develop an SEC-approved standard to measure the risk of various investments. The three-factor model proposed by Eugene Fama and Kenneth French in 1992 would be an excellent starting point. This model is discussed later in Step 8: Riskese™.
Active investors believe they are in control. They delude themselves that they have
a special understanding of the market, a superior edge over less knowledgeable investors,
making them immune to disaster. The truth is that all investors can access the same
information as professional money managers through the Internet and many other sources.
Still, many investors believe they are smarter and more sophisticated than the average
investor. Those under this illusion fail to realize how much investment performance
depends on luck. Most of them eventually pay dearly for this mistake.
Active investing in the stock market is a lot like casino gambling. Take a look at the numerous comparisons in the various news articles below. (Note the references to addiction.)
|Fidelity Outlook, Summer 1999; Cover Story, The New Psychology of Investing; Obsessive, Compulsive, and so far Successful||Forbes, September 13, 1999: Addicted to the Click, How my on-line trading frenzy ended in a lingerie department in Paris||San Francisco Examiner; Wrapped up in risk; Compulsion to gamble can blind even the best investors to bets gone bad|
Paul Samuelson, Nobel Laureate, MIT Economist
The title speaks for itself. by James Cramer, 2002, Cramer in Stockaholic Recovery Mode
New studies in the field of neuroeconomics confirm the release of dopamine when presented with the opportunity of a surging stock. This validates and confirms the addictive nature of Stockaholics™. The powerful allure of monetary reward leads to the overwhelming urge to trade stocks or funds. It has now been shown through brain imaging studies that the circuits that switch on at the prospect of big profits are the same as the ones that lead to the addictive nature of cocaine, casino gambling, alcohol, chocolate, and sex, just to name a few. The brain images below tell the story.
Figure 1-A (Chart Link)
In the October 2002 issue of Money Magazine, the highly respected journalist Jason Zweig writes a ground-breaking article about the new evidence of the release of addiction related dopamine in our brains. He declares, "the dopamine rush we get from long shots is why we play lotto, invest in IPOs, keep too much money in too few stocks and invest with active portfolio managers instead of index funds." He goes on to say that, "our brains are wired to force us into forecasting; it is a biological imperative. In fact, humans are born with what I've come to call "the prediction addiction." Zweig reports that there are several researchers working on nueroeconomics at this time. At Harvard, Hans Breiter is leading a project and has stated that they have discovered a "striking" similarity between the brain's reaction to cocaine, morphine, and the prediction of financial rewards. Please take the time to read Jason's new book on this subject, Your Money & Your Brain. Also see Center for Neuroeconomic Studies Duke University.
Follow up on above video: Tim Sykes, 25, ran a top-ranked, short-bias fund called Cilantro Fund Partners, which he founded in 2003 in his senior year at Tulane University in New Orleans. After suffering a roughly 35% loss over two years, on October 1, 2007, Timothy closed his hedge fund.
Meir Statman talked about his new book, What Investors Really Want: Know What Drives Investor Behavior and Make Smarter Financial Decisions, on Morningstar.com. When asked about index funds, he stated, "Well, index funds are fabulous. Now you say well can I do better than average? Can I perhaps exploit other people's cognitive errors? And the answer to that is probably yes. But the question really is how much does it cost you to exploit the cognitive errors of the others. Think about somebody who says there are $100 bills some place in the streets, so this is the equivalent of a cognitive error of other people, because they have left it lying down. Well, but it will probably take you three days to find that one $100 bill, if that. And so you're going to waste too much money looking to exploit other people's cognitive errors, and in the process you're going to really shortchange yourself by getting lower returns." Watch the full interview below.
In this new report from Barclays, The Role of Control in Financial Decision Making, the emotional mistakes investors make have been discussed and analyzed.
Table 1-2 illustrates some of the details of this unique study. The large gap between the funds' and shareholders' returns was a shock to even the researchers. The reason for this gap is attributed to active investors who followed the destructive behavioral patterns that Dalbar Research had been describing since 1994. These patterns include waiting for funds to have a good year or two followed by pouring in a flood of cash just before the fund reaches its peak. Then they ride the fund to near bottom and sell.
One encouraging exception was the Dimensional Fund Advisors (DFA) institutional index funds. DFA investors are limited to either large institutional investors or individuals who have been educated by specially trained investment advisors. Because the shareholders of these funds buy and hold diversified portfolios at all times, they ride out the market gyrations and end up obtaining market rates of returns. The table below shows the worst big funds ranked by how investors performed relative to the funds and five DFA funds listed in the article.
As an example of a fund that earned high returns yet managed to destroy wealth, the CGM Focus Fund (CGMFX) racked up an impressive annualized return of 13.00% from 1999 to 2012. However, the investor return over this period was a devastating annualized 5.09% loss. In total it was estimated that investors lost over $1 billion in this fund over this period, while the fund reported time-weighted returns of 13.00%. CGM Focus Fund earned fantastic returns for a relative handful of early investors. But fund's late, giant losses were shared by many more. A careful analysis of the chart below will reveal the tragedy of active investors behavior.
An annual study called the Quantitative Analysis of Investor Behavior (QAIB), which has been conducted by Dalbar since 1994, measures the impact of investor decisions to buy, sell, and switch in and out of mutual funds. Each year, the study has shown the average mutual fund investor earns significantly less than the mutual funds over the same time period. In fact, the report issued in March 2011 carried this headline: "Investor Behaviors Continue to Fall Prey to Market Forces." The study further concluded, "As this report has shown for the 17th time in as many years, mutual fund investors consistently underperform the relevant index. The report also shows that most of this loss in performance is due to psychological factors that translate into poor timing of their buys and sells (investor behavior)."
Figure 1-2 illustrates the results of the most recent 20-year Dalbar study that was published in March 2013, which shows a comparison of the returns of an average equity fund investor to the returns of the market from 1993 to 2012. Permitting their decisions to be driven by short-term volatility, the average equity fund investor earned returns of only 4.25%, while the S&P 500 returned 8.22%. An investment of $100,000 made in 1993 grew to an inflation adjusted amount of $142,226 over the 20-year period for an average equity fund investor, while the same amount invested in the S&P 500 grew to an inflation adjusted amount of $300,171. Even better, an investor who owned an all-equity, small-value tilted, globally diversified index portfolio such as IFA's Index Portfolio 100 would have grown a $100,000 investment to an inflation adjusted amount of $416,967. Clearly, investor behavior can have a far more negative impact on investment performance than investors realize.
Dalbar has conducted previous similar studies. (See these Dalbar QAIB Charts created by IFA).
Figure 1-2A shows the annualized returns of the average equity investor compared to the S&P 500 over various time periods ranging from 12 months to 20 years. See that the S&P 500 delivered higher returns in every time period.
Annualized Investor Return vs. Benchmark
Delving further into the 2012 Dalbar study, Figure 1-2B shows the average mutual fund retention rate vs. the recommended holding period for an investor. The average investor holds onto a mutual fund for 3.29 years, whereas IFA recommends holding onto an all-equity portfolio (Index Portfolio 100) for 15 years. See also the difference between an average holding period of 4.42 years for an asset allocation investor vs. a recommended holding period of 8 years for Index Portfolio 50 (60% equities, 40% fixed income).
Figure 1-2C shows the average asset allocation investor vs.comparative indices.
Figure 1-2D shows the average asset allocation investor vs. IFA Index Portfolios, showing that the Index Portfolios outperformed the average assets allocation investor over the 20 year period from 1992 – 2011.
In John C. Bogle's classic book, Common Sense on Mutual Funds, Fully Updated 10th Anniversary Edition,
Mr. Bogle provides color highlighted sections with all the updates to the original
1999 edition. On page 331, he comments that back in 1999 he did not reference the
fact that both individuals and most advisors tend to show up late for mutual fund
returns and just-in-time for losses. In other words, they were more heavily invested
before periods that declined than periods that had increased in value. He states
that the average time-weighted return for 200 large mutual funds for the 10 years
from January 1, 1994 to December 31, 2003 was 9.8%, but the average investors in
those funds only earned a dollar-weighted return of 6.5%.
This means that the bad behavior of investors and most advisors resulted in only capturing 66.3% of the fund's returns over the 10-year period. Compounded over this period, the average of the 200 funds earned a total of 152% or turned $100,000 into $254,697, while the returns-chasing whipsawed average investor only earned 88% or turned $100,000 into just $187,714. A whopping $66,983 difference.
Over this same period, a full equity IFA Index Portfolio 90 grew $100,000 to $264,163, net of IFA and DFA fees, and a S&P 500 Index Fund (DFA US Large Company, Symbol: DFLCX), net of fund expenses and an advisor's fee of 0.9%, grew to $256,609. As you will see in the discussion that follows, do-it-yourself indexers were shown to only capture about 82% of the index fund return due to the same, but somewhat reduced, behavioral finance problems. So without a purely passive advisor, the S&P 500 index fund return for the average do-it-yourself indexer would have hypothetically grown to $235,005 at a rate of 8.92% annualized, which is 82% of the 10.88% return for the S&P 500 from 1994 to 2003.
In John Bogle's Little Book of Common Sense Investing, Chapter 5 is titled
the Grand Illusion: Surprise! The Returns Reported by Mutual Funds Aren't Actually
Earned by Mutual Fund Investors. In this chapter he refers to two studies on this
subject. Also on page 50, a 25-year period is referenced when the average fund investor
earned a dollar weighted return of 7.3%, while the fund had time-weighted returns
of 10.0%. So the average investor only earned 73% of the funds returns over this
25 year period. Also, an S&P 500 Index Fund earned a 12.3% return in this period,
while the investors in that fund only earned 10.8%, only capturing 88% if the index
On page 56, an analysis of 5 Aggressive Growth Funds revealed that the average investor did not capture any of the 7.8% annualized returns over the 10 years from 1995-2005. Instead, they actually lost 0.5% annualized for the 10 years. The average investor in the Vanguard Index 500 only capture 78% of that fund's return over this period, earning 7.1% of the 9.1% annualized return.
Investors can benefit from hiring a purely passive investment advisor, who provides
quality education and mentoring, focused on changing their investing behavior, encouraging
long-term investing, and discouraging the speculation and gambling practices of
trying to beat a market.
Morningstar, a fund tracking service, started disclosing these "investor returns" in 2006. On the Data Definition page of their web site, they state that "Morningstar investor returns (also known as dollar-weighted returns) measure how the typical investor in that fund fared over time, incorporating the impact of cash inflows and outflows from purchases and sales. In contrast to total returns, investor returns account for all cash flows into and out of the fund to measure how the average investor performed over time. Investor return is calculated in a similar manner as internal rate of return. Investor return measures the compound growth rate in the value of all dollars invested in the fund over the evaluation period. Investor return is the growth rate that will link the beginning total net assets plus all intermediate cash flows to the ending total net assets."
Now that Morningstar is tracking such data, investors' bad behavior is finally quantified, as well the advantages of using a passive advisor who helps reduce investor error. In the Morningstar Indexes Yearbook: 2005, they analyzed how the average index investor did on their own versus those that are guided by an advisor using asset class index-type funds from Dimensional Fund Advisors. Here is what they had to say:
"Consider the success Dimensional Fund Advisors (DFA) has had in selling its funds through advisors who undergo training on the merits of passive investing and in portfolio construction theory. Consider that over the past decade the dollar-weighted return of all index funds was just 82% of the time-weighted return investors could have gotten with those funds. Yet, the figures for DFA are much better. In fact, the dollar-weighted returns of DFA funds over the past 10 years are actually higher than their time-weighted returns [see Table 1-3], suggesting advisors who use DFA encourage very smart behavior among their clients, even buying more out-of-favor segments of the market and riding them up, rather than buying at the peak and riding the trend down, which is usually the case with fund investors."
Note: This represents the 10 years ending 12/31/2009 Source: Morningstar
To compare this data with the IFA Index Portfolios, see below and HERE, and for a sample client over most of this period see HERE.
The emotions of investors tend to match the wild gyrations of the market itself. Investors might feel euphoric when the market hits a new high and panic-stricken when the market has dropped like a rock. Who can blame these investors? The stock market can be a scary place when gut instinct overrides knowledge of the specific market dynamics at play, including fair prices, randomness, efficiency, and the benefits of diversification.
Behavioral Finance is a field that studies the connection between investors' emotions and their financial decisions. In The Little Book of Behavioral Investing: How Not to be Your Own Worst Enemy,1 author James Montier talks about the importance of planning ahead to protect us from the "behavioral biases that drag down investment returns." He highlights the need for investors to pre-commit to an investment strategy in order to avoid the pitfalls of emotional decisions.
In Your Money & Your Brain,2 financial writer Jason Zweig details evidence of the release of addiction related dopamine in our brains when we anticipate big wins. "The dopamine rush we get from long shots is why we play lotto, invest in IPOs, keep too much money in too few stocks, and invest with active portfolio managers instead of index funds," Zweig states. "Our brains are wired to force us into forecasting; it is a biological imperative. In fact, humans are born with what I've come to call ‘the prediction addiction.'" Several researchers working in neuroeconomics, including Harvard's Hans Breiter have identified a striking similarity between the brain's reaction to cocaine, morphine and the prediction of financial rewards.
Even wealthy individuals struggle with emotions management and investing discipline. A 2011 Barclay's study3 found that 41% of high net worth investors wished they had more self-control over their investing decisions. The study concluded that emotional trading can cost an investor about 20% in returns over a 10-year period. Investors who prevent themselves from over-trading through specific strategies are on average 12% wealthier than those who don't use self-control mechanisms. These self-control strategies include minimizing time spent checking on a portfolio or talking to someone prior to making a buy or sell decision.
Several behavioral biases that tend to affect investor decisions include the following:
1. Overconfidence: People mistakenly believe they can outperform the market.
2. Hindsight bias: Investors think past events were predictable and obvious and believe they should have known better. The truth is that news moves the markets, and past events could not have been predicted in advance.
3. Familiarity bias: Investors invest only in stocks they know, which provides a false sense of security. An example may be a "legacy" stock that's been passed down in a family through many generations. Regional or geographical bias also comes into play when investors choose stocks of companies headquartered in their state or region of residence, which can lead to undiversified investments.
4. Regret avoidance: Investors vow to never repeat the same decision if it resulted in a previous loss or missed gain, not understanding that the future cannot be predicted.
5. Self attribution bias: Investors tend to take full credit for investment gains and blame outside factors for losses, wrongly attributing success to personal skill or ability.
6. Extrapolation: Investors base decisions on recent events, assuming past market trends will repeat themselves.
These behavioral biases cause investors to believe they have control in areas where they actually have none. A disciplined investing approach involves the understanding of the factors we can and cannot control, planning ahead and not giving into emotions when making investment decisions.
Figure 1-4 depicts the roller coaster of emotions active investors experience. In the emotional cycle, they wait until they feel confident their selected investments are on a perceived upward trend; then they place their orders. But once prices fall, doubt sets in. When that turns to fear, they often sell the investment, resulting in a loss.
In contrast, Figure 1-4a shows the constant relaxed emotions that indexers enjoy by accepting market randomness and relying on investing science instead of making decisions based on emotions. Passive investors invest regardless of market conditions, because they understand short-term volatility is unpredictable. They know succumbing to gut instincts and emotions undermines long-term wealth accumulation. They also know that news about capitalism is positive on average—but involves some stomach-churning volatility, as many experienced in the downturn of 2008 through March 2009, and again in 2011.
Passive investors also engage in periodic rebalancing and are rewarded in the long term for their discipline. Figure 1-4a1 depicts the disciplined emotions and approach of "Rebalancers" who sell a portion of their indexes that have grown beyond their target allocation and buy more of other indexes to restore their target allocation. This is actually the opposite behavior of active investors, because rebalancers will sell a portion of their portfolio after it has gone up and buy more of those investments that have declined in order to maintain a specific asset allocation. This strategy seems counterintuitive and can be emotionally difficult to implement. Annual rebalancing requires discipline and ensures that a portfolio will remain diversified in volatile markets. This discipline also enables passive investors to better fulfill the age-old investing axiom: "buy low, sell high."
We have created this chart to summarize the above studies.
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