What the Trading World Teaches in Risk Management in Blockchain

Recently the crypto world was rocked by several high-profile bankruptcies like Terra Luna, Celsius and more recently FTX. Though FTX is a slightly different case because of fraud allegations, the point is that these failures have been blamed on a lack of proper risk management. In plain English, the CEOs of these companies were blindsided by what they didn’t know, notwithstanding some possible intentional fraud in some cases. As a venture capitalist and real estate investor, I see important lessons in cases like these that can ultimately help blockchain as it continues to gain a foothold.

These recent examples join older ones such as Long Term Capital Management (LTCM), a hedge fund started by Salomon Brothers head of trading John Meriwether and Nobel Prize laureate in Economics Myron Scholes, Lehman Brothers and AIG. All of these examples seemed to theoretically have good ideas, but were destroyed by reality risk miscalculations. It turned out that all their risk models were wrong. The 2008 mortgage crisis for example happened because the experts all thought that no one would skip paying their house mortgage payments. We now know how wrong they were. Only a few hedge funds run by Michael Burry and others actually went through the thousands of mortgages to find out that these were mostly insolvent. The others, even major Wall Street investment banks like Lehman, never bothered to.

It is perhaps human nature that we tend to worship people who come from the Ivy league, and have the proper work experience like from prominent Wall Street banks or trading firms. But it is not an excuse to let our guard down, and not to trust our gut. Sam Bankman Fried for example managed to fool financiers like Kevin O’Leary, Anthony Scaramucci, Sequoia Capital, Softbank, Tiger Global, the Singapore sovereign wealth fund Temasek and a host of others because of his MIT and Jane Street trading pedigree.

Noted risk statistician Nassim Nicholas Taleb, however, gives more weight to people who stand to lose from their management decisions because they have “skin in the game.” Taleb, the author of The Black Swan, talks about a type of hubris that infects academicians who don’t risk their own money and play around with other people’s money using fancy mathematical formulas. Taleb feels that we tend to worship experts too much based on their credentials, often skipping due diligence. Due diligence that could have saved investors money in all of the examples above.

It doesn’t help when these celebrated “experts” are celebrated on television interviews or magazine covers. Media needs to regain its skeptical cynicism, smelling when something is fishy. Both Elizabeth Holmes and Sam Bankman Fried were media darlings and on business magazine covers before allegations caught up with them.

We are at the cusp of revolutions to be created by blockchain in traditional sectors such as banking and finance, communications, entertainment, agriculture, energy, and even real estate. For example, tokenized real estate offers the promise of liquid real estate investments, easily traded on the blockchain, thus freeing up idle unproductive lands and properties anywhere around the world.

But the promise of blockchain will be derailed if the bad actors are not removed from the scene. Ideally, smart contracts and “code is law” are supposed to minimize the need for human intervention. But since we are at an early stage, having humans lead the effort cannot be avoided. It is thus imperative that we are able to quickly spot the shysters, thieves, incompetents, and others who can do harm to blockchain’s progress.

The best course of action is perhaps to strike a balance between giving some importance to academic degrees, but equally also experience and skin in the game. Some people may not have the right pedigree, but they’ve lived through important events in history. The most important learning of all, is that all prospective deals need to undergo due diligence, no matter how impressive the proponents’ credentials are.