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Financial markets are often compared to casinos. This parallel was first made by John Maynard Keynes and is still repeated in the media today. It is, in our view, from a historical point of view that the comparison is with financial risk management – at least until 1952. A shared history so far links financial risk management and gambling.

Probabilities, a very recent invention »

The notion of quantifiable risk, now at the heart of finance, dates back to the mid – 20th century-long after financial markets began to flourish. It is based on the concepts of probability, which curiously did not emerge until the 16th century, thanks to the study of games of chance.

However, gambling existed long before our era. The ossicles, precursors of the dice, are painted on Greek vases and the walls of Egyptian tombs dating from 3,500 BC. Since the ossicles do not have the same size faces, it would have been difficult to calculate probabilities from this instrument.

The Greeks, however, would have used dice, both for divination and for playful purposes. Despite their advanced mathematical knowledge, they have never been interested in probabilities, which today form the basis of risk management. Bernstein attributes this to the fact that the future was at the time the reserved domain of the gods. To know, we went to see an oracle and not a philosopher or a mathematician (often the same person).

Similarly, the Greeks maintained a love for purity and mathematical demonstration. The probabilities hardly correspond to this characterization. Today’s mathematicians have always tended to view chance as an unenforceable field of study.

It was not until the 16th century that this branch of mathematics appeared, and the research of the Milanese physician Girolamo Cardano. It is in the context of his addiction to gambling that he develops an analysis based on probabilities. It is funny to see that he specifies in his book, ” if the dice are not stacked.”

Later, probabilistic research is often carried out as a more or less playful “sidebar” by scientists of the time in response to requests from hard-core players. Galileo thus worked on the subject of probabilities at the request of his employer The Grand Duke of Tuscany, Cosimo II-according to some historians without much pleasure. In France, the Chevalier de Méré will get in touch with the famous Blaise Pascal and Pierre De Fermat to find out how to divide the winnings when a game of chance is stopped during the game.

It is from Daniel Bernoulli that the notion of risk appears. Again, it is due to a hypothetical Game of Chance, called the St. Petersburg Paradox. Let’s imagine the next coin toss. You bet an initial bet, which we cash in. We throw a coin. If the face appears, we’ll pay you $ 1, and we’ll stop playing. If not, we’ll raise the currency. If the face looks, we pay€ 2, and we end the game. If not, we’ll build the coin. If the face appears, we pay you 4€, and so on.

So your expectation of gain is infinite. How much would you be willing to pay to play this game?

Daniel Bernoulli postulated that a reasonable man would not be willing to put more than 20€ in this game (in the first paradox, the amounts were in ducats). His idea is: between receiving 1€ or 2€, there is a big difference – much more significant than between 1 000 and one 001€. Following the same reasoning, most people will, therefore, prefer to keep their 20€ than to flip a coin for a potentially infinite win.

Sort of ” better one yours than two you’ll get.” The idea of quantifiable risk was born – humans do not like variability.

Funnily enough, this age-old probabilistic enlightenment research using gambling has left its mark today. Probabilities are always taught in the form of games of chance.

Even more impressive, “games of Chance” are still used today in research, to understand the attitude of individuals towards risks. They are always a preferred method of studying risk.

A lottery to test “temperance,” a feature of risk aversion (Nousair et al., 2014). The left option is less risky. Noussair et al. Two thousand fourteen

Risk management in finance today

The history of financial risk management and gambling is very clearly separated in practice in the second half of the 20th century – after the death of Keynes in 1946. One may, therefore, wonder what Keynes would think today of the profound mathematization that revolutionized finance after his death.

Before the second half of the 20th century, decisions in market finance were made without the use of generally accepted mathematical models. It is, therefore, generally intuition, “the gut,” or heuristics of choice, more or less arbitrary, that prevails.

The French Louis Bachelier made the first attempt at mathematization in 1900. His thesis received a very mixed reception by the famous Poincaré. It is the fact that this young mathematician attacks a field far removed from traditional mathematics which condemns him to a weak recognition. Paul Samuelson returns to this line of research in the 1960s and shows that stock prices follow a random pattern, implying that the distribution of returns is (almost) normal. The recognition of Louis Bachelier– who also died in 1946-was thus posthumous.

But it was in 1952 that a real revolution in financial risk management took place. Based on the idea that variability is a thing to be avoided and the expectation of gain a something to be maximized, Harry Markowitz defines the problem of Management in his thesis as a simple problem of optimization. Modern finance was born. Funnily, Milton Friedman, who was on Harry Markowitz’s Jury and who would later win the Nobel Prize in Economics, told him in his defense :

“Harry, this is not an economics thesis, and we can’t give you a Ph.D. in economics for something that isn’t economics. This is not math, and this is not the economy; it is not even the management “.

“Harry” did get his Ph. D. and the Nobel Prize in economics for his work. These are now part of the economic and financial fundamentals.

The following decades saw the rise of mathematical models in risk management, together with the development of computer science. Risk perception, measurement, and control are incredibly dynamic areas of research today. Increasingly multidisciplinary research-sometimes involving mathematicians, managers, psychologists, and neuroscientists – could lead to new leaps forward in understanding the risk for both what it is and what it means to investors.

Perhaps a final word is needed on the difference between market finance and casino. First, there is an economic interest in investing – this money is useful to the economy, which is not the case with a casino bet. Indeed, it should not be forgotten that the issue of securities by companies, financial statements, and other economic agents allows them to finance themselves. The gain on this investment is linked to the first prediction of the state of the economy in general and of one or more companies in particular in the future, and thus rewards a generation of information useful to society. Finally, statistically, a diversified portfolio of several securities will have positive long-term earnings expectation. A casino offering the same services would go bankrupt.