The new Black Swan III – The Remarkable Story of Uncertainty!

Stock markets are said to be barometers for economic measurements. Stock markets existed since long, yet there was never a single number that would quantify the true risks associated with them. All those were set to change.

It would be worthwhile to take a step back. The dawn of the twentieth century witnessed some incredible progressions in science and technology, the beginning of which were traced back to the great Industrial Revolution as chronicled by me in the preceding article. Along with that, arrived some pioneering work in the field of mathematics and social sciences like economics.

The arrival of John Maynard Keynes revolutionised the classical economics we were accustomed with. The doctrines and postulations preached and practiced (pre-Keynes) those days heavily relied on two (fundamentally flawed) concepts: 1. Human decisions are rational, and, 2) There are no uncertainties in the market. Everything is known to us and we take decisions based on those ‘known information’ that brings a perfectly competitive market into the play. We all know now, how erroneous those concepts are, isn’t it?

Keynes published a work, A Treatise on Probability, wherein he rejected the term ”events” as was known to the classical school thus far. As ”events” are based on forecasts that imply mathematical frequencies of past occurrences, Keynes preferred the term ”proposition” that has semblance about the probability of future events. Does this mean that Keynes considered probability a subjective concept (more futuristic than past events)? In his own words, “” Once the facts are given which determine our knowledge, what is probable or improbable in these circumstances has been fixed objectively and is independent of our opinion.”

There were severe criticism to this somewhat ‘unrealistic’ view of probability by Keynes. Yielding, he began to focus fully on the aspects of uncertainties influencing decisions. If you look at the modern world today, with the surging virus and socio-political uncertainties affecting economies, you will realize how important Keynes’ work is!

Keynes’ work on economics ultimately revolves around uncertainty. Uncertainty as to the income of a family, uncertainty around how much to spend or save, or, what percentage to spend or save; uncertainties around the companies operating and decisions that determine the profitability, all weighed in in his works. Another great aspect of uncertainty to consider, that you all are/will be engaged with in your corporate life – the uncertainty over capital allocation, how to fund projects and expansions in future. Please note, I was asking this question in my earlier article as well. This was a definitive groundwork on the modern Risk Management. Since all these capital investment decisions are irreversible, they have consequences on the probabilistic assumptions made at the point of ‘entry’! No doubt, your risk assessment have to be prudent and scientific!

Keynes rejected postulations that ignored uncertainties. He proposed a course of action that stood diametrically opposite to the doctrine of ”laissez-faire”; a more active role of the government in creating demand in the economies and reducing uncertainties in the broader economy and internationally so that the business environments stay stable and less volatile. We have seen later than Keynes’ theories has had negative implications in the international context, there were doubtful governmental actions that created more distortions than good; but no one can deny that these were significant steps to identify and effectively manage risks. I believe, for all practical purposes, a systematic study of risk can never ignore the Keynesian doctrines and postulations.

Something more were already on its way. Welcome to the world of the Game Theory.

Read on in the next instalment!

Published by Subhamay Bhattacharya

I am a Finance executive with more than two decades of global experience. I specialise in quantitative analyses on finance, risk and associated data. I am an active data scientist with focus on machine learning and deep learning tools. I am passionate about team building and knowledge asset creation and transition.

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