Since the beginning of the financial Tulip Mania of 1637, when a bulb was priced more than a house, other bubbles followed: The Mississippi Bubble, The South-sea Bubble and so on., boom and bust have happened. From the Dutch
We could go on for an entire page, list all the bubbles happened in the last centuries. You may think that at this point we learned many lessons from them. Did we? Of course, we did not. In fact, one typical pattern of all those bubbles is “this time is different.”
Yet it wasn’t. In their brilliant paper entitled “This time is different,” Carmen M. Reinhart Kenneth S. Rogoff show us how defaults and crises are happening throughout the centuries taught us some valuable lessons, which very few seem to have grasped.
The catch is that those defaults often happened with some years or decades apart, with the consequence of inducing market players and policymakers that “this time was different” but when the next crisis struck they eventually turned out to be as severe if not more than the previous ones.
But if that is the case what did we get wrong?
We Got It All Wrong
The primary assumption made by many economists and investors is that financial normal distribution, also called Gaussian curve. In short, this kind of tells you that that move too far from the average are rare.follow what is called a
A tool to know how far values are spread out from the average is the standard deviation, also expressed in the Greek letter, sigma (σ). In other words, value, which has a Sigma of five, is way rarer than an amount that has a sigma of one.
The Gaussian curve though tells you thatof 5/10 sigma are so rare that you shouldn’t expect them to happen in millions of years. But how is this possible if only in the last decades we saw financial crashes – which were considered by most economists, in the magnitude of 10/20 sigma – happening time and time again?
The problem is that we got it all wrong. In fact, those Cauchy distribution. To understand this kind of analogy, we will use an unusual analogy: that of a drunken squad shooting into a wall., which are deemed to be so improbable according to the Gaussian distribution, are not such if we make a different assumption: financial follow a modified form of , called
Financial Markets Are Like a Drunken Firing Squad
in the book “The Physics of Wall Street: A Brief History of Predicting the Unpredictable” James Owen Weatherall describes the Cauchy Distribution with the following analogy. Imagine a drunken squad about to shoot on the wall in front of them:
“If you make a notice of where each bullet hits the wall you can use this information to come up with a probability that any given bullet will hit any given part of the wall…The firing’s drunken squad bullets hit the middle part of the wall most of the time – more often, in fact that the normal , would have predicted. But the bullets also hit very distant parts of the wall surprisingly often – much, much more often than the normal would have predicted.”that corresponds to the
In other words, this kind of probability of certain “rare ” to happen. In fact, according to David Hand, in his book “The Improbability Principle” a 5-sigma that according to the Gaussian distribution has a 1 in 3.5 million years to happen, in the Cauchy distribution, it has a 1 in 16 probabilities to happen!changes the
This means that not only market crashes are not rare, but we should expect them to happen way more often than we usually have thought in the past!
Keeping this in mind, you may want to be sure your retirement fund get not blindly exposed to financial.
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