High yields yield high returns Why? The reason is that they revert to lower yields, which results in a boost from the rerating component of returns. The link between the entry yield and subsequent returns is one of the strongest relationships in stock (and bond) markets, providing a golden longer-term rule and a Great Investment Picture. The graph below shows entry yields and returns from 1960 for the All Share Index (ALSI). Returns are calculated over five years. The strongest relationship is over a five-year horizon -- it becomes weaker over shorter periods. Note that an absolute change in yield of two percentage points results in a 100% change if it is from, say, 2% to 4% but only a 20% change if it is from 10% to 12% so a log scale is appropriate for the yield. Graph showing entry yield and subsequent five-year returns The message is quite clear and simple. Buying equities on high yields results in high returns, and vice versa. The strength of the relationship is impressive. We can use the graph to estimate future returns. For example, the market’s current earnings yield is 5.9% (equivalent to a PE of 17x). We can see that historically this has resulted in returns over the next five years that averaged around 9% p.a., with the lowest being 3% p.a. and the highest 15% p.a. The market is therefore not particularly cheap at present and we should expect returns well below the levels of the past. (From the picture we can see this average was around 20% p.a.) However, the picture also provides some comfort – over no 5-year period has the return from the market ever fallen below zero.
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In the long term, its only earnings Over the long term, the single most fundamental driver of price is earnings, and only earnings. Over very long periods, the contribution to total return from changes in PE is negligible and the contribution from dividend yield is relatively small. Therefore, long-term returns will be roughly equal to earnings growth. This results in the most fundamental picture of the behaviour of markets. This graph shows the long-term price performance of the United States market, represented by the Standard & Poor’s S&P 500 index, since 1871. Great Investment Pictures: Price follows earnings The United States market – price and earnings (S&P 500 index) Data source: Robert Shiller, Yale Price has tracked earnings closely over the long term. Phases of poor performance and bear markets have tended to result from price running too far ahead of earnings and vice versa. The price movements around long-term earnings are secondary effects, attributable to shorter-term changes in rating. The picture shows that the United States market’s price lagged earnings from 1974, and then began to accelerate from 1982, producing an almost two-decade long bull run, overshooting earnings from 1996 until its peak in 2000. The market price then followed the decline and subsequent recovery in earnings, with the gap almost closing, although earnings have since fallen. Incidentally, over the long term, the United States market has exhibited two distinct phases. In the first phase, from 1871 to 1941, its average price appreciation was quite uninspiring at slightly less than 1.0% p.a., with the market rising by only 100% over these 70 years. In the next 66 years to the end of 2008, the market rose by a dramatically higher 7.1% p.a., appreciating by 10 000% over this period. The fact that price follows earnings over the long term is universally true for all markets, including the South African market, as shown in the next graph of the ALSI and its earnings since 1960. The South African market – price and earnings (ALSI index) Again, price has tracked earnings closely and phases of strong bull and bear markets have tended to result from price deviating too strongly from the trend in earnings. In the words of Warren Buffett, “It is an inescapable fact that the value of an asset, whatever its character, cannot over the long term grow faster than its earnings do.” Obviously, the longer this growth persists, the better. Very high growth rates, however, are difficult to sustain, so there is often a trade-off between the level of growth and its duration. It is also an inescapable fact that most long-term earnings forecasts breach this principle. The first principle of long-term investing is therefore to select shares that will show good earnings growth over your investment horizon. And you can also find other Great Investment Pictures from The Effective Investor on Tickertalk at Great Investment Picture #2 Cheers, Franco
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In the long term, its only earnings Over the long term, the single most fundamental driver of price is earnings, and only earnings. Over very long periods, the contribution to total return from changes in PE is negligible and the contribution from dividend yield is relatively small. Therefore, long-term returns will be roughly equal to earnings growth. This results in the most fundamental picture of the behaviour of markets. This graph shows the long-term price performance of the United States market, represented by the Standard & Poor’s S&P 500 index, since 1871. Great Investment Pictures: Price follows earnings The United States market – price and earnings (S&P 500 index) Data source: Robert Shiller, Yale Price has tracked earnings closely over the long term. Phases of poor performance and bear markets have tended to result from price running too far ahead of earnings and vice versa. The price movements around long-term earnings are secondary effects, attributable to shorter-term changes in rating. The picture shows that the United States market’s price lagged earnings from 1974, and then began to accelerate from 1982, producing an almost two-decade long bull run, overshooting earnings from 1996 until its peak in 2000. The market price then followed the decline and subsequent recovery in earnings, with the gap almost closing, although earnings have since fallen. Incidentally, over the long term, the United States market has exhibited two distinct phases. In the first phase, from 1871 to 1941, its average price appreciation was quite uninspiring at slightly less than 1.0% p.a., with the market rising by only 100% over these 70 years. In the next 66 years to the end of 2008, the market rose by a dramatically higher 7.1% p.a., appreciating by 10 000% over this period. The fact that price follows earnings over the long term is universally true for all markets, including the South African market, as shown in the next graph of the ALSI and its earnings since 1960. The South African market – price and earnings (ALSI index) Again, price has tracked earnings closely and phases of strong bull and bear markets have tended to result from price deviating too strongly from the trend in earnings. In the words of Warren Buffett, “It is an inescapable fact that the value of an asset, whatever its character, cannot over the long term grow faster than its earnings do.” Obviously, the longer this growth persists, the better. Very high growth rates, however, are difficult to sustain, so there is often a trade-off between the level of growth and its duration. It is also an inescapable fact that most long-term earnings forecasts breach this principle. The first principle of long-term investing is therefore to select shares that will show good earnings growth over your investment horizon. And you can also find other Great Investment Pictures from The Effective Investor on Tickertalk at Great Investment Picture #2 Cheers, Franco
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Irrational volatility You may believe that: · The price of an asset is equal to the discounted value of expected future cash flows. · Risky assets are rated lower than less risky assets. · Markets are reasonably efficient most of the time. Unfortunately, you would be wrong. While the theory is rational, the world isn’t. The following seminal picture by Robert Shiller (first published in 1981 and subsequently updated) highlights this strikingly. Graph showing S&P500 price versus ex-post rational value - real detrended 
Source: Robert Shiller, Yale In the graph, the real price of the S&P 500 is compared with the ex-post rational real price. Ex-post simply means that we calculate the price afterwards so that we can pretend that we possessed perfect foresight and discount the actual future dividends. A constant discount rate equal to the average annual return from the S&P 500 over the period shown was used. Rational means the price was calculated as the discounted value of the actual future dividends. The actual and rational prices have been detrended to highlight the difference between them. The graph has three major messages. First, actual prices are dramatically more volatile than the rational price. Movements in the ex-post rational price are remarkably small and smooth. There are two reasons for this: first, the present value is equivalent to a weighted moving average of dividends (with weights corresponding to their compounded discount factors) and therefore changes only slowly, and second, real dividends simply do not vary much over the long term. For example, during the Great Depression, real dividends were substantially below their long-run growth path in only four of the ten depression years from 1929 to 1939, so the market’s major decline in 1929 was not rational in terms of subsequent dividends. The volatility of stock prices is much higher than can be attributed to new information about future real dividends, even with uncertainty (as measured by their actual historical variability). Movements in price are much larger than justified by actual subsequent events and too large to be in accord with efficient markets. The market overreacts spectacularly to both actual and anticipated events. Second, the graph implies that factors other than dividends (and their economic determinants) must be playing a major role in price determination. Notionally, this gives rise to the discipline of behavioural finance. Third, perfect foresight wouldn’t help us. This is perhaps the most unnerving implication for us as investors. Even if we know the precise path of future dividend streams, our valuations will be wrong most of the time, missing the large swings and roundabouts that generate the returns we would like to capture. This picture therefore resoundingly undermines the dividend discount model theory and the efficient market hypothesis and highlights the depressingly large magnitude of the “non-rational” (perhaps “irrational” is too harsh) component of the market. We must therefore conclude that we cannot be exclusively rational investors and must acknowledge market sentiment, even over long periods. In the words of behavioural finance expert Werner de Bondt, “... despite its many insights, modern finance offers only a set of asset-pricing theories for which no empirical support exists and a set of empirical facts (such as seasonality effects) for which no theory exists.”
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Time diversification After compounding, time diversification of risk is your second-best friend in the market. While the risk attached to being invested in equities in any one year is higher than that for the other major asset classes because of the higher variability of returns, the longer the investment period, the lower this variability becomes. The next graph shows the range of returns from equities over various time horizons. The importance of this message makes it one of the eleven Great Investment Pictures. Great Investment Pictures: Time diversification Range of returns (ALSI, 1960 – 2008) 
The range of returns over a relatively short period such as five years is very large, ranging from 5.8% p.a. to 40.7% p.a. However, even though in any single year losses as high as -8% have occurred, the above graph highlights the fact that over five years the worst outcome has never been negative. (In fact returns have never been negative for any period of four-years or longer.) The graph shows that the average return for very different investment periods ranging from five to forty years have been quite similar, and although the range of returns can be wide, this range narrows rapidly and steadily – after twenty five years it has become almost one-sixth of its five-year range. While returns are not negative over periods longer than four years, the lowest returns were still unacceptably low relative to the returns from the other major asset classes. Lengthening the investment period results in a commensurate increase in the lowest returns or downside risk. Investment periods greater than 15 years result in very acceptable risk compared with other investments. Time diversification also works in a portfolio context –the optimal weights of stocks in an efficient portfolio are significantly larger for long investment horizons than, say, a one-year horizon. Time dissipates the higher risk of equities.
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This week we’ll take a break from our travels through the Great Investment Pictures to take a lighter look at one of the classical psychological aberrations of investors. Unfortunately, like visual illusions, learning about these does not necessarily make them go away. But this knowledge can help you identify and, hopefully, avoid many pitfalls. Overconfidence People believe that their estimates are far more accurate than they actually are. The result is nasty surprises. For example, the next graph examines accuracy over a range of confidence levels for meteorologists’ predictions of rain and for physicians’ diagnoses of pneumonia. Overconfidence in weather forecasters and doctors. Sources: Allan Murphy and Robert Winkler (1984), Jay Christensen-Szalanski and James Bushyhead (1981). The meteorologists’ predictions are surprisingly good while the physicians’ confidence strongly exceeds their abilities, which is rather scary. Meteorologists and race handicappers are the least prone to overconfidence because they face the same problem every day, they make explicitly probabilistic forecasts and feedback on their judgements is both quantified and fast. These conditions exist for some market participants, but seldom for individual investors, who therefore err towards overconfidence. An interesting tweak: theoretical models predict that overconfident investors should trade excessively. Psychological research demonstrates that, in areas such as finance, men are more overconfident than women are. Therefore theory predicts that men will trade more than women. A study by behavioural researchers Brad Barber and Terrance Odean found that men trade 45% more than women (which reduced the men’s net returns by 2.7% a year compared with 1.7% for women!). Women are less overconfident, trade less and produce higher returns than men. The most overconfident investors also turn out to be the worst performers. Also, while we believe that the more information we have the better, this is not true. Numerous studies have shown that an increase in information does not lead to an increase in performance, but, insidiously, leads only to a large increase in confidence. Analysts’ preoccupation with small incremental snippets of information on their companies is useful and necessary for marketing to their clients, but does not necessarily lead to better forecasts or judgements. OK - so how overconfident you? Try the following test. For each of the following ten items, provide a low and high guess so that you are 90% sure the correct answer will fall between the two. Your challenge is to be neither too narrow (i.e. overconfident) nor too wide (i.e. underconfident). You needn't get the absolute correct answer, you need only be 90% sure that the correct answer lies within your high/low span. A self-test for overconfidence 1. Martin Luther King’s age at death. 2. Length of the Nile River (km). 3. Number of countries that are members of OPEC. 4. Number of books in the Old Testament. 5. Diameter of the moon (km). 6. Weight of an empty Boeing 747 (kg). 7. Year in which Wolfgang Amadeus Mozart was born. 8. Gestation period (in days) of an Asian elephant. 9. Air distance from London to Tokyo (km). 10. Depth of deepest known point in the oceans (m). From Russo, E.J. and Schoemaker, P.J.H., The Ten Barriers To Brilliant Decision-Making And How To Overcome Them, Simon & Schuster, 1990. The answers are below**. If you successfully met this challenge you should have 10% misses – that is, exactly one miss. Did you have more than one? The authors found that less than 1% of the 1000 managers they surveyed had zero or one miss. Most missed between four and seven out of the ten questions. Overconfidence is rife. ** Answers: 1. 39 years; 2. 6 737 km; 3. 13 countries; 4. 39 books; 5. 3 475 km; 6. 176 900 kg; 7. 1756; 8. 645 days; 9. 9 588 km; 10. 11 033 m.
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The Frailties of Forecasts Our largest investing mistakes often come not from wrong decisions but from right decisions based on wrong forecasts. Consensus forecasts are appalling. First, the term consensus is wrong – there is not necessarily any agreement between economists or analysts. The “consensus” forecast is actually the average of their forecasts. Probably the single most important macroeconomic variable is the R/$ rate. Ironically, this is arguably also the most difficult to forecast. Nevertheless, economists’ efforts here are a lesson in how not to do it. The next graph shows the R/$ exchange rate together with the Reuters Econometer consensus forecasts. The thick line shows the actual path of the R/$ exchange rate and the thin lines show the consensus forecast’s expected path for the rand at different times. Great Investment Pictures: The frailties of forecasts R/$ forecasts – the Reuters Econometer consensus Data source: Reuters Econometer The period shown encompassed very strong depreciation of the rand, from R/$6 to R/$12 (on quarterly data), followed by equally strong appreciation back to below its starting point. The picture has many amusing aspects. Rand forecasts are always for depreciation. When the rand is depreciating, the consensus forecasts further depreciation; when the rand is appreciating, it forecasts a change to depreciation. Only the last five of the 126 forecasts shown here were for appreciation. Effectively, over a third of the forecasts shown (those from 2002 through 2004) were therefore forecasting a turning point in the currency (usually a very brave thing to do) and they were all wrong. One would expect forecasts to change their direction depending on whether you are close to a possible peak or trough. After all, while the rand is difficult to forecast, the times when you have the most certainty is when it is at the extremes of its historical range (particularly relative to purchasing power parity). That forecasts don’t change direction is therefore extraordinary behaviour. It means that there is not the faintest pretence at any fundamental view or acknowledgement of the possibility of mean reversion. The actual long-term depreciation from 1979, when the exchange rate was floated, up to the end of 1999, where the picture above begins, was 6.9% p.a. The average depreciation of all the forecasts shown was 8.6% p.a. To use behavioural finance terminology, this is anchoring in its grandest sense, with the forecasts being anchored close to the historical long-term nominal depreciation of the currency. It becomes worse. As the rand approached its 2001 peak, forecasts began looking for increasing depreciation, but when the rand strengthened to lower levels, expectations for depreciation declined. Again, a positive feedback loop like this is irrational, since it simply ignores the fact that rand movements have been strongly cyclical around the long-term trend. Similar deficiencies accompany the consensus forecasts for all the other macroeconomic variables such as interest rates and inflation. Be sceptical of macro forecasts. They seldom forecast turning points, economists are particularly prone to herding and the economic consensus is frequently wrong. Remember the Harvard Economic Society’s Weekly Letter of 16 Nov 1929: “A severe depression like that of 1920-21 is outside the range of possibility.” The scary thing is, although we cannot forecast more than three years out, at best, in order to justify the high prices of some shares their forecasts need to show above-average earnings growth for 10 years or more. First, this is not likely, and second, even if it were we wouldn’t be able to forecast it. So why do we continue to do it? First, there is a feeling that one has to have forecasts, no matter how bad, in order to do valuations. Second, wrong forecasts are always subsequently justified, leading to the perennial hope that they should do better in future. Classic excuses along the lines of “It would have been correct except for … (some factor) which happened and was unpredictable”, “It was almost right, except for...” or “It's still going to happen!” There are two solutions: 1. Do not use forecasts. Base valuations and views purely on historical data. This has worked remarkably well in some situations such as buying value stocks based on low trailing PEs. Dividend discount models using historical values as forecasts can be more accurate than those using even perfectly accurate forecasts. Momentum methods, which can work well in the short term, are also backward looking rather than forward looking. 2. Use forecasts, but put error bounds around them. Then only acknowledge any resulting decision as meaningful if its conclusion remains intact for the forecast’s outcome being at the least favourable bound. In other words, make liberal use of a factor of safety, as advocated by Benjamin Graham. Forecasting is intrinsically very difficult and the results are therefore usually poor. Consensus forecasts tend to anchor, use blind extrapolation, ignore fundamentals and mean reversion and are frequently irrational. The time we spend trying to make very accurate earnings and dividend forecasts is disproportionally large relative to their influence on valuations. We should spend more time analysing instead of attempting to forecast. And you can also find other Great Investment Pictures from The Effective Investor on Tickertalk at Great Investment Picture #2 Great Investment Picture #3 Great Investment Picture #4
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Weighing expectations In evaluating investments, investors usually calculate future returns but seldom attempt to quantify the downside risk. They also tend to focus on how often they are correct – the hit rate of their investment method. But while a 90% hit rate may sound good, if we are right nine times out of ten, each time making a gain of 5%, and are wrong only once but this incurs a loss of 70%, our portfolio will be significantly down. You need to incorporate the size of gains and losses as well is their probability. We usually use “future”, “forecast” or “expected” returns interchangeably. However, the term “expected return” can have a very specific meaning. The expected outcome of an investment is given by a very simple formula that should be committed to memory and used until it becomes second nature. Although not strictly a picture, it warrants inclusion as one of our Great Investment Pictures. Great Investment Pictures: The expected return formula 
Imagine a stock that is vulnerable to a specific event (for example, an interest-rate hike, the weather or a political act). If this event doesn't happen, which is 80% likely, it will continue to perform reasonably well, possibly appreciating by about 10% p.a. However, if the event does occur, which has only a 20% probability, its share price could easily halve over the year, i.e. decline by 50% p.a. The expected outcome is therefore (80% × 10% p.a.) + (20% × –50% p.a.) = –2% p.a. It would be irrational to make this investment – the size of the probable loss outweighs the size of the probable gain. For example, after calculating expected returns from earnings growth and PE we can then examine the downside risk by looking at the lowest end of the error range for our earnings forecast and the lowest PE that occurred historically for this scenario. You can calculate the best, most probable and worst returns and then assign probabilities to these, or, to be really conservative, use only the most probable and worst scenarios All too often we don’t think along these lines of “if it loses, how much could it lose?”, and every investment we make should be tested against this criterion. Always incorporate the risk of loss in your return calculations. Your expected return is the weighted probability of gains and losses. And you can also find other Great Investment Pictures from The Effective Investor on Tickertalk at Great Investment Picture #2 Great Investment Picture #3 Great Investment Picture #4 Great Investment Picture #5
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The Wealth of Patience The stock market is designed to transfer money from the active to the patient. – Warren Buffett Compounding is one of the few factors you have influence over, and that is also a dependable, safe and predictable way of maximising your wealth over the long term. All you need is time and patience. The next picture provides an illustration of compounding at work, using actual returns from the JSE. Assume that two investors contribute equal nominal amounts over time. One investor begins to invest early, at age 20 (i.e. in 1962), contributing R1 000 in the first year, escalating in line with inflation for the next 11 years, and investing this in the ALSI. He then makes no further payments. The second investor begins investing 11 years after the first, at age 31 (i.e. after the first investor has stopped his contributions), contributing an amount equivalent to the early investor’s R1 000 escalated by the inflation of the intervening years. She continues to invest amounts escalated by inflation, for 34 years until an assumed retirement age of 65. On retirement, the first investor is actually worth more. His total investment of just over R14 600 has grown to R13.9m compared with R12.8m for the second investor, who invested a total of R641 000 – over forty times more. Even taking the time value of money into account, which results in the two investors having invested approximately R8 000 and R27 500 respectively, the second investor has contributed over five times more but accumulated a lesser amount. (In this discounting, an interest rate of 9.7% was used, the actual average for cash from 1960.) This is illustrated in the seventh of our Great Investment Pictures. Note that the vertical axis has a log scale. 
One cannot overemphasise the importance of beginning an investment plan as early as possible. Because the human mind tends to think linearly, compounding (i.e. exponential growth) is unintuitive and difficult to visualise. A traditional example is the lily pond parable, where a pond begins with one lily, doubling every day until it is fully covered after 30 days. Halfway through the month, at day 15, progress is invisible, with only 0.003% of the pond covered. Even on day 25 only 3% is covered. On day 28, three-quarters of the pond still remains open. On day 29, just one day before the end of the month, the pond is only half-covered. And one day after month-end there would be enough lilies to cover two ponds. Initial progress is imperceptible; final performance is dazzling. Compound interest calculations are not new. In 1606 Galileo produced a calculation device of his own design called a geometric and military compass. Among the many uses of the device was the calculation of compound interest and currency conversions. Source: Singer, C., (ed). Studies in the History and Method of Science, Vol II, Clarendon Press: Oxford, 1921. There is a quick way to estimate the effects of compounding, commonly known as the Rule of 72. To find the number of years required to double your money at any interest rate, just divide 72 by the interest rate. For example, if you want to know how long it will take to double your money at 10% p.a. interest, divide 72 by 10, giving an answer of just over 7 years. Conversely, if you want to double your money in, say, 5 years, divide 72 by 5, giving a required interest rate of about 14% p.a. (This is an approximation for annually compounded interest, designed to be exactly correct at an interest rate of 10%. For continuously compounding interest it becomes the Rule of 69 and is exact, although the mental arithmetic is harder.) Compounding is one of the most powerful factors driving long-term returns. Time just happens, but emotional fortitude is required to provide the patience. For other Great Investment Pictures see The Effective Investor by Franco Busetti, Pan Macmillan, 2009, available at Exclusive Books branches or online at Effective Investor at Exclusives as well as Kalahari The Effective Investor at Kalahari.net And you can also find other Great Investment Pictures from The Effective Investor on Tickertalk at Great Investment Picture #2 Great Investment Picture #3 Great Investment Picture #4 Great Investment Picture #5
Great Investment Picture #6
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Is your manager skilful or lucky? Imagine you are a portfolio manager. You’ve just outperformed the market by a healthy 1% this quarter. On top of this, your portfolio is relatively low-risk, with only half the volatility of the market. And it’s the fourth successive quarter you’ve done this. People are starting to tell you you’re a star. You’re beginning to believe you’re a star. But are you? Or do you have a nagging doubt that you may only have been lucky? The short answer is that you still have a long way to go before your stellar qualities are established beyond reasonable doubt. Based on the above quarterly data, this degree of outperformance must persist for 37 successive quarters or nine years to establish, with a 90% degree of confidence, that this is the result of skill rather than luck! The attribution of performance is essentially the comparison of two fuzzy processes — that of the portfolio and that of the benchmark against which it is compared. In the short term, noise swamps any signs of outperformance skill, but in the longer term the signal emerges from the noise and the degree of skill becomes apparent. The question is how long this takes. Some of these elements are captured neatly in the following picture, which shows, for any given degree of outperformance, how long a track record is required to establish the presence of investment skill with various degrees of confidence. This relationship is important enough to make this another Great Investment Picture. Great Investment Pictures: Time required to distinguish between luck and skill The picture illustrates that the larger the degree of outperformance, the less time is required to conclude that this is not due to chance, and generally, the greater the volatility or noisiness of the portfolio and the benchmark, the longer it will take. Also, the greater the degree of confidence required and the lower the correlation between the portfolio and the benchmark, the more time is necessary. Note that while the above picture uses annualised data, you can use it for any period. For example, if you are using monthly data, simply annualise the excess return and the standard deviation of the portfolio (multiply the monthly standard deviation by √12). The required number of periods read off from the graph will be in years, which you can then convert back to months. Some parameters have been fixed in the picture. We assume the benchmark is the ALSI – its annualised volatility over the long term has been roughly 20%. Many fund managers are also keenly aware of tracking error and do not deviate too strongly from the ALSI’s weightings. We therefore assume the portfolio’s correlation relative to the ALSI is 0.90. We would also like our results to have a confidence level of at least 80%. Typical portfolio standard deviations over three years have a median around 16% p.a. and the median excess return above benchmark was 1.13% p.a. From the graph we can see that it would take almost 16 years to establish, with 80% certainty, that this level of outperformance was attributable to skill. If the average fund had a standard deviation of only 4% p.a., this would increase to 21 years. But if the excess return were much larger, say 3% p.a., these two periods would fall dramatically from 16 years to four years and from 21 years to eight years respectively, so for funds that show strong outperformance or underperformance, distinguishing between luck and skill can be done within a reasonably short time. However, histories this long generally do not exist for the industry. Only approximately half our funds have a history as long as five years. Less than 10% of unit trusts have been around for 15 years. The time required to distinguish between skill and luck in a manager is measured in years if not decades, so most funds and fund managers do not have sufficiently long histories. There are implications for both investors and fund managers: § The time required to confirm the presence of skill is much longer than you think. A large number of managers do not manage portfolios for as long as the required evaluation period. § The horizon over which fund performance is measured is usually much shorter than this period. The scrutiny applied to short series of quarterly or monthly results and the huge emphasis on rankings over these too-short periods is totally misplaced, since it does not actually reveal manager skill. § The consequent flow of money from bottom-ranked funds to top-ranked funds after just a few quarters of noticeable (but probably temporary) underperformance leads to unnecessary turnover and the resultant erosion of investors’ returns by transaction costs. § The underestimation of the period required to establish skill has clear implications for institutional asset managers’ evaluations of their portfolio managers (e.g. how long it takes to decide that a portfolio manager is unlikely ever to be successful), and consequently industry turnover, as well as the structure of performance-linked rewards. When unsuccessful fund managers’ performance hits a bad patch they tend to be sidelined and thus lose the opportunity to continue building a performance history (which could establish that they do indeed have skill that will win through in longer-term returns). The industry is thus locked into a short-term momentum game. But momentum doesn’t work over the long term. As a potential investor you should worry less about the style of a manager and more about whether they have sufficient skill to generate consistent returns. However, you can only measure this for managers who have long records. Even then, you need to be careful. In 2005, Bill Miller, manager of the Legg Mason Value fund, had produced an unprecedented 15-year winning streak against the S&P 500. I remember him pointing out that if any year-end other than 31December had been used, this would not be true. The message is that all numbers on performance need to be treated with caution. (Inevitably, his streak came to an end, with his fund subsequently underperforming the market severely.) For other Great Investment Pictures see The Effective Investor by Franco Busetti, Pan Macmillan, 2009, available at Exclusive Books branches or online at Effective Investor at Exclusives as well as Kalahari The Effective Investor at Kalahari.net And you can also find other Great Investment Pictures from The Effective Investor on Tickertalk at Great Investment Picture #2 Great Investment Picture #3 Great Investment Picture #4 Great Investment Picture #5
Great Investment Picture #6 Great Investment Picture #7
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