Objective decision-making processes based on data, math and a quantifiable logic result in superior results over the long term
Traders work on the floor of the New York Stock Exchange. Photo by Brendan McDermid/Reuters Cycles are inevitable. They have persisted since markets have existed and will endure for as long as humans engage in the pursuit of profit.
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In prolonged up cycles, people are euphoric, bid prices up to unsustainable levels and sow the seeds for subsequent misery. Similarly, severe price declines result in unsustainably pessimistic sentiment, pushing prices down to bargain levels, thereby sowing the seeds of the next up cycle.
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Neither bull nor bear markets continue indefinitely. Despite this incontrovertible truth, every time an up or down cycle persists for an extended period and/or to a great extreme, the “this time it’s different” crowd becomes increasingly pervasive, citing changes in geopolitics, institutions, technology and behaviour that render the old rules obsolete. But then it turns out the old rules do apply, and the cycle resumes.
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The persistence of cycles is in large part the result of the inability of investors to remember the past.
“Extreme brevity of financial memory … When the same or closely similar circumstances occur again, sometimes in only a few years, they are hailed by a new, often youthful, and always supremely self-confident generation as a brilliantly innovative discovery in the financial and larger economic world,” legendary economist John Kenneth Galbraith said.
“There can be few fields of human endeavour in which history counts for so little as in the world of finance. Past experience, to the extent that it is part of memory at all, is dismissed as the primitive refuge of those who do not have the insight to appreciate the incredible wonders of the present.”
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Without a doubt, macroeconomic factors, such as interest rates, inflation, fiscal policy, gross domestic product growth, unemployment, etc., exert a significant influence on the ebb and flow of markets. In my view, however, fluctuations in psychology have the greatest impact on cycles. More than any other factor, changes in sentiment are what cause shifts between hospitable and treacherous markets and, therefore, between gains and losses.
In market cycles, most excesses on the upside and the inevitable reactions to the downside (which also tend to overshoot) are the result of exaggerated swings by the pendulum of psychology. Even Benjamin Graham, the father of value investing and Warren Buffett’s mentor, acknowledged the tremendous influence of psychology in his allegory about Mr. Market. Depending on his volatile mood swings, Mr. Market will buy assets at unrealistically high levels or sell them at bargain basement prices.
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In bear markets, investors demand generous risk premiums to compensate them for taking risk. In these environments, valuations are undemanding and chances are good you will be rewarded for taking that risk.
As the cycle progresses and markets begin to rise, investors are neither overly pessimistic nor blindly optimistic. People require adequate compensation for taking risk, valuations are neither depressed nor excessive, and you can expect returns that approximate the long-term historical average.
During the latter stages of bull markets when prices have significantly risen over a period of several years, investors become euphoric and adopt a lopsided desire for return with little regard for risk. People require scant compensation for bearing risk, valuations become unrealistic and losses become more likely than gains.
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In essence, the pendulum of investor psychology is heavily influenced by the recency bias of what has happened over the past several years, swinging between collecting $100 bills in front of a tricycle during the bad times and picking up pennies in front of a steamroller at market tops.
In the real world, things generally fluctuate between “pretty good” and “not so hot.” But in the market, investor psychology seems to spend much more time at the extremes than it does at a happy medium. At any given point, markets are more likely driven by greed or fear rather than greed and fear.
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Article content In the 51 years from 1970 through 2020, the S&P 500 fell within two per cent of its long-term “normal” return of approximately 10 per cent (that is, between eight and 12 per cent) only three times. During the same period, its return was at least 10 per cent lower or higher than average (lower than zero or higher than 20 per cent) more than half the time. And calendar-year returns were either 20 per cent lower or higher than average (worse than -10 per cent or greater than 30 per cent) more than a quarter of the time. Clearly, the average isn’t the norm.
Macroeconomic analysis and predictions are of limited use in their ability to achieve superior investment results. I am not saying that macro developments are not influential, but rather that they simply aren’t knowable. There is no shortage of evidence demonstrating that expert predictions have on average demonstrated no more accuracy than throwing darts blindfolded.
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Article content In each December since 2000, the median Wall Street forecast has never called for a stock market decline in the following year, and yet the market fell in six of those years. Moreover, since these forecasts never materially stray from the market’s long-term historical average return, they tend to be the least accurate when accuracy would have been most profitable. It’s hard to argue that agnosticism isn’t better than self-delusion when it comes to investing based on forecasting.
“All these people see the same data, read the same material, and spend their time trying to guess what each other is going to say,” Galbraith said. “(Their forecasts) will always be moderately right — and almost never of much use. We have two classes of forecasters: those who don’t know and those who don’t know they don’t know.”
We must learn to be humble in situations where intuition and forecasting are simply not as good as rules-based processes based on statistical analysis.
Objective decision-making processes based on data, math and a quantifiable logic result in superior results over the long term.
Noah Solomon is chief investment officer at Outcome Metric Asset Management LP.