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February 6 - February 21, 2022
The odds of financial ruin in a free, global-market economy have been grossly underestimated.
What a company does today—a merger, a spin-off, a critical product launch—shapes what the company will look like a decade hence; in the same way, its stock-price movements today will influence movements tomorrow.
Warren E. Buffett, the famously successful investor and industrialist, jested that he would like to fund university chairs in the Efficient Market Hypothesis, so that the professors would train even more misguided financiers whose money he could win.
They know that a wild Tuesday may well be followed by a wilder Wednesday. And they also know that it is in those wildest moments—the rare but recurring crises of the financial world—that the biggest fortunes of Wall Street are made and lost.
Patterns are the fool’s gold of financial markets. The power of chance suffices to create spurious patterns and pseudo-cycles that, for all the world, appear predictable and bankable. But a financial market is especially prone to such statistical mirages. My mathematical models can generate charts that—purely by the operation of random processes—appear to trend and cycle. They would fool any professional “chartist.” Likewise, bubbles and crashes are inherent to markets. They are the inevitable consequence of the human need to find patterns in the patternless.
This trading time speeds up the clock in periods of high volatility, and slows it down in periods of stability.
Research in this field has far to go. It took more than sixty years after Bachelier’s thesis for economists to formulate properly the Efficient Market Hypothesis, and another decade beyond that for their work to find valuable applications in the real world of zero-coupons and call options.
Seeing nature through the lens of probability theory is what mathematicians call the stochastic view.
In short, the normal curve is indestructible. It is mathematical alchemy. It is what you inevitably get if you combine lots of little variations, each one independent from the last, and each one negligible when compared to the total. No one individual matters much to the total IQ curve; no one coin toss matters much to Harry and Tom’s game. But cumulatively, over time or across a population, the way the results vary forms a regular and predictable pattern. The data points are grains of sand on a shoreline, blades of grass in a lawn, electrons moving along a copper wire.
The Exchange reacts to itself, and the current trading is a function, not only of prior trading, but also of its relationship to the rest of the market.
one cannot help but marvel that the movement of security prices, the motion of molecules, and the diffusion of heat could all be of the same mathematical species. As will be seen, it is one of many such strange liaisons in nature.
Cheaper and safer to ride with the market. Buy a stock index fund. Relax. Be passive. Or as Samuelson at MIT put it: “They also serve who only sit and hold.”
A respect for evidence compels me to incline toward the hypothesis that most portfolio decision makers should go out of business—take up plumbing, teach Greek, or help produce the annual GNP by serving as corporate executives. Even if this advice to drop dead is good advice, it obviously is not counsel that will be eagerly followed. Few people will commit suicide without a push. From The Journal of Portfolio Management, 1974.
As an industry, finance buys more computers than almost any other. It hires a huge proportion of the world’s newly minted math and economics graduates. It is a vast calculating machine, a robot to hang an electronic price tag on every product, service, company, and country that deals in global commerce.
None of this would exist if the original Black-Scholes formula were accurate. Of course, the formula remains important; it is the benchmark to which everyone in the market refers, much the way, say, people talk about the temperature in winter even though whether they actually feel cold also depends on the wind, the snow, the clouds, their clothing, and their health.
As James notes, there is a big difference between spotting veins of gold in old price charts and minting real gold in live markets.
Brokers often quote prices in round numbers, skipping intermediate values. Thus in the currency market, professional traders observe, about 80 percent of quotes end in a 0 or a 5, skipping the intermediate digits. The usual odds would suggest those values, being just two of the ten possible final digits in a number, should occur only about 20 percent of the time.
the sharper the move in the first month, the more likely it is that the price trend will continue into the next month, although at a slower rate.
When a statistician finds a result he had been expecting, he tends not to put his tests under as critical a microscope as he should— especially when he is also assuming a Gaussian world.
The problem lies at the roots of the standard model, in its assumption that the best way to think about stock markets is as a grand game of coin-tossing.
“Clouds are not spheres, mountains are not cones, coastlines are not circles, and bark is not smooth, nor does lightning travel in a straight line.”
Such is the power of fractals and chance working together: Simple rules build complex structures, and complex structures deconstruct into simple rules.
“The variation of certain speculative prices,”
why people often specialize in one profession, rather than hop from trade to trade. The reason is common sense, but the mathematics support it. If they invest in their own profession—for instance, get a graduate degree—they will probably rise higher and faster up their own industry’s income curve. If they change fields or dabble in many, they will probably make less. That helps explain why, when a new multidisciplinary industry like e-business appears, salaries can shoot up: The new companies have to offer absurdly high compensation to induce people to take the risk and leave their own,
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Let us mull the promises that science makes to society to win its support. The grand promise is to endeavor solving the great mysteries— to the list of which I have added one. But there is also a more practical promise. It consists in helping society to improve, to prevent it from acting on the basis of theories that sound nice but are not true to the facts, and to help it act on the basis of facts—even if those facts have yet to find a theory that fully explains them.
anyone who claimed to find a common thread from tree rings to sun spots to mud layers must have taken “a sensational step towards finding the single universal law of nature.”
“When we fade from this business, something will be lost. That is the memory of 1929.”
The brain highlights what it imagines as patterns; it disregards contradictory information. Human nature yearns to see order and hierarchy in the world. It will invent it where it cannot find it.
A value of H smaller than one half, shown on the top panel, has strong “anti-persistence”: Successive changes tend to cancel each other out.
abrupt change, and almost-trends. These are the two basic facts of a financial market, the facts that any model must accommodate.
Suppose, for instance, that you have an “almost-trend” emerging in a stock price: a few weeks, say, in which a stock price rises seven days out of ten. The pattern must eventually break up, of course; otherwise, it would be a real trend that you could bet on continuing for another few weeks, and hope to make some real money. But when the “almost-trend” finally does break, it can do so rapidly. A sudden lurch downward, perhaps. A discontinuity. Or, in the terms of the Biblical metaphor, a Noah Effect produced by Joseph-style dependence.
Scaling enters the system from the fundamentals of weather patterns, resource distributions, and industrial organization. Scaling finishes—and feeds back through the system again— in the marketplace.
You cannot beat the market, says the standard market doctrine. Granted. But you can sidestep its worst punches.
To be sure, I do not argue there is no such thing as intrinsic value. It remains a popular notion, and one that I myself have used in some of my economic models. But the turbulent markets of the past few decades should have taught us, at the least, that value is a slippery concept, and one whose usefulness is vastly over-rated.
Finance must abandon its bad habits, and adopt a scientific method.
“The world is just fractal, and if you try to view fractal markets from a Euclidean perspective you just get it wrong from A to Z,”
Using his models, his computers look for moments when the short-term traders are moving opposite to the long-term investors—and then he bets that the imbalance will correct itself.
“In no field of empirical enquiry has so massive and sophisticated a statistical machinery been used with such indifferent results.”
