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April 1 - July 8, 2024
Technical analysts, however, would look for some tangible evidence before they could be convinced that the investment idea was, in fact, catching on. This tangible evidence is, of course, the beginning of an uptrend or a technical signal that predicts an uptrend.
They build their strategies upon dreams of castles in the air and expect their tools to tell them which castle is being built and how to get in on the ground floor.
I have since made it a rule never to eat with a chartist. It’s bad for digestion.
Technical analysis is anathema to much of the academic world. We love to pick on it. We have two main reasons: (1) after paying transactions costs and taxes, the method does not do better than a buy-and-hold strategy; and (2) it’s easy to pick on.
Just as fast as he (or she) creates charts to show where the market is going, the academic gets busy constructing charts showing where the technician has been.
Chartists believe momentum exists in the market.
The results reveal that past movements in stock prices cannot be used reliably to foretell future movements.
The stock market has little, if any, memory.
Although momentum exists in the stock market, described more fully in chapter 11, any investor who pays transactions costs and taxes is unlikely to employ a trading strategy to benefit from it.
Sometimes one gets positive price changes (rising prices) for several days in a row; but sometimes when you are flipping a fair coin you also get a long string of “heads” in a row, and you get sequences of positive (or negative) price changes no more frequently than you can expect random sequences of heads or tails in a row. What are often called “persistent patterns” in the stock market occur no more frequently than the runs of luck in the fortunes of any gambler. This is what economists mean when they say that stock prices behave very much like a random walk.
Mathematicians call a sequence of numbers produced by a random process (such as those on our simulated stock chart) a random walk. The next move on the chart is completely unpredictable on the basis of what has happened before.
There is some momentum in stock prices. When good news arises, investors often only partially adjust their estimates of the appropriate price of the stock. Slow adjustment and crowd psychology can make stock prices rise steadily for a period, imparting a degree of momentum.
Investment funds managed in accordance with momentum strategies often have subpar results.
The history of stock price movements contains no useful information that will enable an investor consistently to outperform a buy-and-hold strategy in managing a portfolio.
If the weak form of the random-walk hypothesis is valid, then, as my colleague Richard Quandt says, “Technical analysis is akin to astrology and every bit as scientific.”
In the stock-market experiments, the placebo with which the technical strategies are compared is the buy-and-hold strategy. Technical schemes often do make profits, but so does a buy-and-hold strategy. Indeed, a simple buy-and-hold strategy using a portfolio consisting of all the stocks in a broad stock-market index has provided investors with an average annual rate of return of about 10 percent over the past one hundred years. Only if technical schemes produce better returns than the market can they be judged effective. To date, none has consistently passed the test.
Under the popular “filter” system, a stock that has reached a low and has moved up, say 5 percent (or any other percent you wish to name), is said to be in an uptrend. A stock that has moved down 5 percent from a peak is in a downtrend. You’re supposed to buy any stock that has moved up 5 percent from its low and hold it until the price moves down 5 percent from a subsequent high, at which time you sell and even sell short. The short position is maintained until the price rises at least 5 percent from a subsequent low.
When the higher transactions charges incurred under the filter rules are taken into consideration, these techniques cannot consistently beat a policy of simply buying the individual stock (or the stock index) and holding it over the period during which the test is performed. The individual investor would do well to avoid using any filter rule and, I might add, any broker who recommends it.
The basic Dow principle implies a strategy of buying when the market goes higher than the last peak and selling when it sinks through the preceding valley.
Unhappily, the signals generated by the Dow mechanism have no significance for predicting future price movements.
In the relative-strength system, an investor buys and holds those stocks that are acting well, that is, outperforming the general market indexes. Conversely, the stocks that are acting poorly relative to the market should be avoided or, perhaps, even sold short.
a computer test of relative-strength rules over a twenty-five-year period suggests that such rules, after accounting for costs and taxes, are not useful for investors.
Price-volume systems suggest that when a stock (or the general market) rises on large or increasing volume, there is an unsatisfied excess of buying interest and the stock will continue its rise. Conversely, when a stock drops on large volume, selling pressure is indicated and a sell signal is given.
If you bought those stocks with buy signals, and sold on sell signals, your performance would have been no better than that achieved with a buy-and-hold strategy.
The psychologists conjecture that the persistent belief in the hot hand could be due to memory bias. If long sequences of hits or misses are more memorable than alternating sequences, observers are likely to overestimate the correlation between successive shots.
The following chart suggests a loose tendency for bull markets to be associated with bare knees and depressed markets to be associated with bear markets for girl watchers.
David Leinweber found that the indicator most closely correlated with the S&P 500 Index is the volume of butter production in Bangladesh.
With large numbers of technicians predicting the market, there will always be some who have called the last turn or even the last few turns, but none will be consistently accurate.
The random-walk theory says only that stock prices cannot be predicted on the basis of past stock prices.
The problem is that once such a regularity is known to market participants, people will act in a way that prevents it from happening in the future.
Any regularity in the stock market that can be discovered and acted upon profitably is bound to destroy itself.
The past history of stock prices cannot be used to predict the future in any meaningful way.
The point is that market timers risk missing the infrequent large sprints that are the big contributors to performance.
At heart, the Wall Street pros are fundamentalists.
Wall Streeters feel that fundamental analysis is becoming more powerful all the time. The individual investor has scarcely a chance against the professional portfolio manager and a team of fundamental analysts.
They have argued that fund managers and their analysts can do no better at picking stocks than a rank amateur.
To predict future directions, analysts generally start by looking at past wanderings. “A proven score of past performance in earnings growth is,” one analyst told me, “a most reliable indicator of future earnings growth.”
Such thinking flunks in the academic world. Calculations of past earnings growth are no help in predicting future growth.
“Higgledy Piggledy Growth.”
Many in Wall Street refuse to accept the fact that no reliable pattern can be discerned from past records to aid the analyst in predicting future growth.
Analysts can’t predict consistent long-run growth, because it does not exist.
Unfortunately, the careful estimates of security analysts (based on industry studies, plant visits, etc.) do little better than those that would be obtained by simple extrapolation of past trends, which we have already seen are no help at all.
Security analysts have enormous difficulty in performing their basic function of forecasting company earnings prospects.
It is always somewhat disturbing to learn that highly trained and well-paid professionals may not be terribly skillful at their calling.
Another experiment proved that professional staffs in psychiatric hospitals could not tell the sane from the insane.
The point is that we should not take for granted the reliability and accuracy of any judge, no matter how expert.
There are, I believe, five factors that help explain why security analysts have such difficulty in predicting the future. These are (1) the influence of random events, (2) the production of dubious reported earnings through “creative” accounting procedures, (3) errors made by the analysts themselves, (4) the loss of the best analysts to the sales desk or to portfolio management, and (5) the conflicts of interest facing security analysts at firms with large investment banking operations.
He hopes for a total flop, so that no one will ask questions about where the money went.
But accounting abuses appear to have become even more frequent during the twenty-first century. Failing dot.coms, high-tech leaders, and even old-economy blue chips all tried to hype earnings and mislead the investment community.
the tendency of companies to report so-called pro forma or adjusted earnings as opposed to actual earnings computed in accordance with generally accepted accounting principles.
