Schwager takes aim at the most perniciously pervasive academic precepts, money management canards, market myths, and investor errors. Like so many ducks in a shooting gallery, Schwager picks them off, one at a time, revealing the truth about many of the fallacious assumptions, theories, and beliefs at the core of investment theory and practice.
- A compilation of the most insidious, fundamental investment errors the author has observed over his long and distinguished career in the markets.
- Brings to light the fallacies underlying many widely held academic precepts, professional money management methodologies, and investment behaviors.
- A sobering dose of real-world insight for investment professionals and a highly readable source of information and guidance for general readers interested in investment, trading, and finance.
- Spans both traditional and alternative investment classes, covering both basic and advanced topics.
The following are a sampling of observations about how markets really work:
- The market is not always right. The best opportunities arise when the market is most wrong.
- Big price moves begin on fundamentals, but end on emotion.
- Past returns are not future returns. Past returns can be very misleading, if there are reasons to believe that future market conditions are likely to be significantly different from those that shaped past returns.
- The best-performing past investments often do worse than the worst-performing past investments in the future—and the future, after all, is where we all have to make our investment decisions.
- The best time to initiate long-term investments in equities is after extended periods of underperformance.
- Faulty risk measurement is worse than no risk measurement at all because it will lull investors into unwarranted complacency.
- Volatility is frequently a poor proxy for risk. Many low volatility investments have high risk, while some high volatility investments have well-controlled risk.
- The real risks are often invisible in the track record.
- High past returns sometimes reflect excessive risk-taking in a favorable market environment, rather than manager skill.
- Return alone is a meaningless statistic because return can always be increased by increasing risk. Return/risk should be the primary performance metric.
- Leverage alone tells you nothing about risk. Risk is a function of both the underlying portfolio and leverage. Leveraged portfolios can often be lower risk than unleveraged portfolios—it depends on the assets in the portfolio.
Every few years, one or more global markets experience a price move that many portfolio managers insist should occur only “once in a thousand years”. Where do these probabilities come from? They are the probabilities of such magnitude price moves occurring, assuming prices adhere to the normal distribution.
One might think that the repeated occurrence of events, that should be a rarity, would lead to the obvious conclusion that the price model being used does not fit the real world of markets. But for a large part of the academic and financial establishment, it has not led to this conclusion. Convenience trumps reality.
Chapter 1 – Expert Advice
Picking the best past performers doesn’t seem to provide any edge over the S&P 500, but avoiding the worst past performers appears to be a good idea.
Investment Misconception 1: Advice from financial experts is helpful.
Reality: The amazing thing about expert advice is how consistently it fails to do better than a coin toss. They actually do worse than random. The chimpanzee will bet them.
Chapter 2 – The Deficient Market Hypothesis
The efficient market hypothesis (EMH) says markets cannot be beat. If that were true, then Technical Analysis would be a waste of time, and so would Fundamental Analysis. Even the enforcement of insider trading rules would be a waste of time because insider trading would not beat the market either.
There is no shortage of evidence that clearly seems to contradict the EMH:
1) Prices that are demonstrably imperfect.
2) Large price changes unaccompanied by significant changes in fundamentals.
3) Price moves that lag the fundamentals.
4) Track records that are too good to be explained by luck, if the EMH were true.
Another basic flaw of the EMH is that it doesn’t allow for the actions of the ignorant masses to outweigh the actions of the well-informed—at least for a while—and this is exactly what happened in many cases.
Sometimes, emotions will cause investors to behave irrationally, resulting in prices that are far removed from fundamentally justifiable levels (eg., Palm Spin-off from 3Com, where the market assigned a huge negative price to all of 3Com remaining assets).
The improbability of the October 1987 is 10 -160 which is roughly equivalent to randomly picking a specific atom in the universe, and then randomly picking the same atom in a second trial. But it still happened. Randomness in action!
There are two ways of looking at the 1987 crash in the context of the EMH:
1) Wow, that was really unlucky!
2) If the EMH were correct, the probability of the 1987 crash is clearly in the realm of impossibility. Therefore, if the model implies the impossible, the model must be wrong.
The market action determines the interpretation of the news, not the other way around.
To achieve the Renaissance Medallion Fund’s track record by chance, you would need to have a number of traders in the market closer to the number of estimated atoms in the earth than to the number of people on the planet.
Market actions by hedgers and governments can cause price disequilibrium and implied profit opportunities, which are not supposed to exist according to the EMH.
Virtually, all the contradictions to the EMH can be traced back to the potential for human emotions and irrational behavior to distort prices. Markets do not accurately discount all known fundamentals, but rather they over-discount or under-discount this information, depending on the market’s emotional environment and indeed this is one of the sources of investing or trading opportunities.
The 5 main EMH-arguments:
1) The markets incorporate all known information. Assume TRUE
2) Therefore, prices are always correct. FALSE
Markets are traded by people, not robots, and people often react on emotion more than information. The influence of emotion can cause irrational behavior, resulting in prices being much too high or low vis-à-vis an objective assessment of the fundamentals.
3) The arrival of new information is random. Assume TRUE
4) Changes in prices depend on new information. FALSE
Price moves often lag the information and often occur in the absence of new information.
Everyone having the same information does not imply that everyone will use information with equal efficiency.
5) Therefore, you can’t beat the market. FALSE
Prices can be significantly out of line with reasonable valuations.
Prices don’t move in tandem with information.
Some people are more skilled in interpreting information.
Investment misconception 3: Markets can’t be beat.
Reality: Markets are difficult, but not impossible to beat—a critical distinction that implies that some winners are winners because they are skilled, not because they are lucky (although some winners will merely be lucky).
Although markets are often efficiently priced, there are many exceptions and it is the exceptions that provide skilled market participants the opportunity to outperform. Not only can human emotions exert an important price impact, but the distortive impact of emotions often creates the best investment opportunities.
Chapter 3 – The Tyranny of Past Returns
It is clearly evident that there is a consistent superior performance of years following low-quartile return periods, versus years following high-quartile return periods. Investors would be better off diversifying to achieve average returns than to concentrate their investment in the past best-performing sector. It follows that selecting the highest-return mutual funds of the past would also lead to subpar return/risk performance because those funds are likely to have an investment focus on the past best-performing sectors.
Investment misconception 6: Invest in equities when the market is performing well.
Reality: The best time to start a long-term investment in equities is after an extended period of low returns.
Chapter 4 – The Mismeasurement of Risk
More money has been lost through the mismeasurement of risk than by the failure to measure risk.
Volatility, as measured by the standard deviation, is the ubiquitous measure of risk. The standard deviation is a measure of dispersion.
Volatility is useful in defining approximate downside risk, only if historical returns are representative of the entries that can be expected in the future.
Beta and correlation are mathematically related and provide two different ways of examining similar information. Correlation indicates the degree of the relationship between a return series and a benchmark, while beta indicates the estimated changes in the series for each 1% change in the benchmark.
Absence of evidence of high risk is not evidence of low risk.
Investment Misconception 9: Risk measurement is always beneficial.
Reality: Faulty risk measurement is worse than no risk measurement at all, because it may give investors an unwarranted sense of security.
Chapter 5 – Why Volatility is not just about Risk, and the Case of Leveraged ETFs
Most investors don’t realize that higher volatility also reduces return as well. The greater the volatility, the lower the cumulative return that will result from any given average monthly return.
The longer the holding period, the greater the intrinsic negative returns has in leveraged ETFs. => Investors and longer-term traders should simply avoid buying leveraged ETFs.
Chapter 6 – Track record Pitfalls
Never make investment decisions based on past track records, without first asking whether there is reason to assume that past returns offer some guideline for the future.
The investment trap is that sometimes past outperformance reflects the negative characteristic of greater risk, rather than the positive quality of manager skill.
Longer track records could be less relevant for any of the following reasons: Changes in strategy and portfolio, change in portfolio manager, declining efficacy, and strategy
Chapter 7 – Sense and Nonsense about Pro Forma Statistics
Chapter 8 – How to Evaluate Past Performance of Funds
The NAV (Net Asset Value) Chart can offer a good intuitive sense of past performance in terms of both return and risk. In fact, if an investor were to examine only a single performance gauge, the NAV chart would probably be the most informative. The log scale is always the correct way to represent an NAV chart and is especially critical when there is a wide NAV range.
Both 12-month and 24-month rolling window return charts are helpful.
Investment Misconception 23: The average annual return is probably the single most important performance statistic.
Reality: Return alone is a meaningless statistic because return can always be increased by increasing risk. The return/ risk ratio should be the primary performance metric.
The Sharpe Ratio is the most widely used return/risk measure, but because it does not distinguish between upside and downside volatility, many of the alternative return/risk measures are more consistent with the way most investors perceive risk.
Investment Misconception 28: The maximum drawdown is one of the most important risk measures.
Reality: The maximum drawback of the maximum drawdown is that it is based on only a single event. A retracement measure based on all data points, such as the average maximum retracement (AMR), would be far more meaningful than the maximum drawdown.
Chapter 9 – Correlation: Facts and Fallacies
Chapters 10 to 16 – Hedge Funds
The conventional wisdom about hedge funds has it exactly backwards. The common perception is that hedge funds provide the potential for high returns for those willing to take high risk. The reality, however, is that hedge funds (using a fund of funds approach) offer only moderate returns, but with much lower risk than conventional equity investment. The question should not be “Would you put your grandmother in hedge funds?” but rather “Would you put her in mutual funds?”
Hedge funds are better-performing asset in return/risk terms.
Hedge funds provide a diversification benefit.
Chapter 17 – Diversification: Why 10 is Not Enough
- Randomness Risk: The diversification effect beyond 10 is highly substantial. The probability of getting three-quarters or more losing funds falls under 4%, when the number of holdings increases to 16 uncorrelated funds.
- Idiosyncratic Risk: This is the implied portfolio loss due to a single investment experiencing a highly unrepresentative loss far in excess of worst-case expectations for that investment. More than 10 funds is essential to lower that risk substantially.
Always assuming that added investments are as attractive as existing investments. If, however, diversification requires extending the portfolio to include less desirable investments, the net benefit of diversification can no longer be assumed.
The critical point is that for diversification to work, the investments added to the portfolio must have a low average correlation to the existing investments and to each other.
Chapter 21 – Portfolio Construction Principles
Eight Principles (see pages 305 ff).
Epilogue lists 32 Investment Observations (pages 315 ff)