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Recession: Machines can put a price on everything but a value on nothing!

Updated: Apr 7, 2021

Last month I took part in a Goldman Sachs Housing and Consumer Finance conference, where every speaker on the stage was asked the same question: When and how will the next global recession start? The answers, given both by CEOs and by some of the leading analysts of the world’s financial markets, tell us a little bit about what is likely to happen with fintech industry in the coming years.

From a banker’s perspective, investing in credit looks better than betting on equities, as credit markets are at an all-time high of 40 percent, compared with stocks, which are priced higher than ever. Real estate prices in the US are rising between 3 and 5 percent per year, as are salaries and other expenses. There are no clear indications of deflation in the foreseeable future, so it looks like smooth sailing ahead from debt investors.

Historically, recessions are caused by the private sector spending more than it earns. A situation that — according to macroeconomic analysts — rarely happens when, as now, corporations are enjoying record-breaking profits. In a few sectors, however, the signs are not so positive — US car loan defaults are abnormally high, for example. But this is most probably an isolated case, related more to weak scoring than to a systemic problem.

Goldman’s analysts have revised the reasons for last century’s crisis and grouped them under headings such as oil, industrial, monetary, financial, and fiscal. According to currently available data and analyzed trends, in the unlikely event of a crisis happening in the coming years, it will do so for absolutely different reasons.

So, what could possibly go wrong?

When Oscar Wilde’s character Lord Darlington describes a cynic as someone who “knows the price of everything and the value of nothing”, he could easily be talking about the computers that do most of the financial trading in our modern world. In current market practice, this means that machine-provided liquidity goes away faster than human trader regulated fungibility. In regular markets, computers are much more efficient than humans, but in non-standard market situations, crashes can happen very fast and for no apparent reason.

The best example of something like this was Black Monday in 1987 when markets crashed and — to this day — nobody really understands why.


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