As I stated in my previous article, John Maynard Keynes, the exceptionally gifted intellectual and one of the first proponents of the concept of ‘’probabilistic’’ way of viewing economic activities (or choices) based on uncertainties prevailing, can be considered as the modern architect of a systematic measurement of Risk.
This brings me to the forefront of a critical concept, that I want to share with you, in details. It’s intelligent and thought provoking!
The greatest human faculty, in favourable or adverse circumstances alike, is its ability to take decisions. We take numerous decisions, every day since the dawn of civilisation. When we say ‘decision’ it is but understood, in its simplest essence, that we have ‘choices’ to make. Without choices, there is no decision. Of course, there can be a decision without a choice. When we face an extreme situation or a point of no return, we take a decision considering its ‘inevitability’. In other words, extreme decisions are not not rational but (perhaps) driven by extreme conditions. Let us set that aside from this discussion. Let us consider a bunch of available choices or options. Each choice has an economic value add to it. We can weigh the pros and cons, and responsibly understand the consequences of the choice(s) made. Our understanding of a particular choice may have limited implications from the ’long run’ perspective (in the long run everything is uncertain. Keynes famously said ‘in the long run, we are all dead!’), but it must have been considered ‘best’ at the point of the decision. Such preferential decision making amid host of available choices attaches a semi mathematical angle to it. When we are bound by limitations, we make an ‘informed’ decision by choosing (say) X over Y, as statistically analyzed, X offers, at that point, better opportunities over Y. Please note this is not accidental but probabilistic! We have a simple probability model here; we have taken a decision based on our ‘’estimated’’ (not entirely random) understanding of the associated benefits such decision or choice will bring forth. If I may sum up the longish paragraph in one sentence, it looks like follows:
Decision Making = function (Available Best Choice + Uncertainty Attached to Each Choice)
The next interesting aspect is the associated evaluation of the uncertainty attached to a choice. Or a preferred uncertainty if I may say so!
As rational beings, we usually choose something on which the perceived uncertainty is the least, even though selection of the choice seems attractive. Some of us are hooked to buying ‘penny stocks’ as the returns ‘may be’ handsome. This is based on certain historical observations and events. But we know jolly well that the associated risks are enormous, and that we may end us losing the entire investment. Does going for penny stocks still make you a wise investor? Perhaps not! Still the act of foregoing is a difficult one here. The highly liquid stocks that are your next best available option (to maximise portfolio returns) may give you staid returns. Here the risk is there but less compared to the first choice (penny stocks). Going further, we may look at buying ‘’risk free’’ (there is nothing called risk free in real world!) treasury securities that yields a very poor return. What should be our ideal decision making matrix then? Based on the simple equation I wrote above, we have these three scenarios here:
Scenario 1: Penny Stocks with very high Risk (may be highest return)
Scenario 2: Liquid Stocks with medium Risk (decent return)
Scenario 3: Treasury securities with low risk (certainly low return) but certainly not risk free
Please also note that in scenarios 1 & 2 the returns may be zero as well, with maximum probability in scenario 1.
Still what decision one makes is based on one’s risk appetite. I brought this concept in my earlier articles. Now I am developing this very critical parameter of Risk, or even better, a systematic measurement of Risk. Given a host of choices, humans will take rational decisions that seems ‘’rational’’ to them at the point of making it. These choices and the applicability of mathematical acumen are not linear. Decision making is a complex, layered process where economic and behavioural considerations play a pivotal role, and are often juxtaposed.
It is not wise to consider that decision making is an isolationist process. The old school of thought believed that way. We could safely state that a decision making is mathematically inevitable, if the available choices and the attached rationality do not entangle to form a complex matrix. Such entanglement is at the root of the modern Risk Management.
Welcome to the world of the Game Theory!!
This powerful theory was first proposed by Von Neumann (pronounced as Noyman), whose contribution to the development of the Quantum Mechanics is significant. Game Theory is considered extremely powerful from the perspective of the decisions— each decision we make is a result of ‘a series of negotiations’ in which we try our best to reduce, if not eliminate, uncertainty by trading off what other people want in return for what we want ourselves.
Take a re-look at my ‘investment’ choices now. The decision to be made under these circumstances is governed by multiple factors including what other people would have done. The old economic premise of ‘ceteris paribus’ does not hold here. Game Theory thus brought a whole new meaning to the concept of uncertainty. It was indeed a game changer, and, other than the Theory of Probability, a definitive step in the modern understanding of Risk. All the reason more because in this particular ‘game’ there is no clear winner like, say, Chess. The ‘’winning’’ here is highly relational or relative. Someone else’ ‘good’ choice may be bad for someone. One may take a very risky decision based on choosing an alternative that is ‘’judged’’ the best; and the associated pay-off may provoke strongest of reservations against the ‘contrarians’ – people who are on the other side of the decision making process. You buy a share hoping to gain maximum only because the seller thinks otherwise!! This is a wonderful conundrum that defines the tenet of the Game Theory and systematic study of Risk Management.
The mathematical delimitation is also a fascinating aspect of this very powerful concept. As I said earlier, a decision making process is not linear but multi layered and laced with additional decision making. At every aspect in life, we search for meanings that define the boundaries of our existence. Man’s search for meaning (read the book by Viktor Frankl, it’s amazing!!) leads to choices that define future. Risk management assumes the role of art here. While we assign, to the best of our abilities, specific values to variables to systematically ascertain the total outcome (think of your MBA from College A plus a career in data sciences plus decision to settle in the USA = a successful and wealthy life!), such outcomes, neither the factors that build them up in entirety, under no circumstances, are a mathematical certainty. At best it’s quasi mathematical. There are many judgemental elements to it.
To all students and professionals of risk, remember this for life. Never ever consider risk ‘’certain’’ and fully measurable. Your models are going to produce erroneous results. We, as risk mitigation, give a best shot in understanding the hidden pattern. To me Black Swans are more of hidden patterns or tendencies that an actual, unfortunate event that decimates markets. As Risk Managers, one has to identify this pattern, to the best of his abilities using available mathematical techniques; then use plain common sense to arrive at a decision point. That decision may or may not be accurate and incur costs that have negative repercussions. Like a decision to Hedge. Hedging has a cost while it gives no profit. It merely protects if the market turns against the favourably predicted decision making point.
One does a large trade to gain, while he hedges it to protect. Either of the positions will lose money. Look at the application of the Game Theory here. Very interesting, isn’t it?
Lastly, Game Theory leads to settlement for compromise alternatives!!!!
We are familiar with the terms ‘maximin’, ‘minimax’….
We only settle for the ‘’best’’ of the bad bargain!
Finance & Risk Demystified 