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May 2021

This is the first in a 3 part series of commentaries focusing on Risk Management.

We all know the cliché.  Markets are driven by greed and fear.  Too much greed is really too little fear and can lead to catastrophic results.   On the other hand, a preponderance of fear can suppress greed and lead to anaemic results.

                                                        FEAR IS GOOD


We all know the cliché.  Markets are driven by greed and fear.  Too much greed is really too little fear and can lead to catastrophic results.   On the other hand, a preponderance of fear can suppress greed and lead to anaemic results.

Measurement of risk is as much art as it is science.  I know this will strike many in my industry as heresy.  They believe that risk can be measured scientifically. They are wrong.  Risk is about what might happen in the future.  The future is unknowable and therefore it cannot be measured.

I have broken this commentary into three parts.  In Part I – Skin in the Game, I pose the question – why do major investment banks and hedge funds miscalculate risk?  It is an important question for any serious investor to ask.  I believe that risk assessors in Lehman Brothers, Bear Stearns and Long-Term Capital Management et al were lacking in fear. This lack of fear is a common thread that contributed to their downfall.

In Part II – Fear, A Dispatch from the Frontline, I tell a story.  It is a story of survival from my previous company JK Brokers Ltd (“JKB”), a floor(pit) brokerage/execution firm.  The nature of the business meant that JKB habitually sailed close to the abyss.  I believe that my ‘fear experience’ is a very useful input into risk management at The Great O’Neill.

In Part III – The Great O’Neill and Risk, I demonstrate how my experience of risk colours my thinking on assessing the risks pertaining to The Great O’Neill. I show some of the internal risk management tools that we use and show some real samples of our estimated risk exposures. Furthermore, I explain how our behaviour has evolved to tone down the fear input and increase the greed factor.




We will always have major investment industry bankruptcies and collapses. They often generate headlines and have knock on effects throughout the system.  Putting aside collapses associated with malfeasance it is worth taking the time to consider why risk is so often under calculated by the best and brightest in the industry.  It is commonly accepted that leverage and liquidity play a primary role.  Added to this there can be a degree of hubris. However, there is another factor which might be worth considering – skin in the game. But first we need to understand that measuring risk is as much art as it is science.

Calculating the what ifs on a portfolio of investments or trades is impossible. After all, there are an infinite number of what ifs.  The degree of difficulty is illustrated by the caliber of people involved in some of  the better-known busts.  In 1998, one of the worlds most celebrated and sophisticated hedge funds, Long-Term Capital Management (“LTCM”),collapsed.  LTCM had 11 partners, 7 of whom had doctorates in finance, and 2 of which are Nobel prize winners.  Clearly there was no shortage of brains.  But even they got it wrong.  The US federal reserve led a team of 14 financial institutions to bail them out. The fund was obliterated and shut down.

Aside from major hedge funds, the list of investment bank failures grows every decade. The best and brightest brains in Bear Stearns, Lehman Brothers et al also miscalculated risk.  Most recently, Credit Suisse has suffered a $5.4Bn loss from its relationship with hedge fund Archegos.  According to the Financial Times, the loss is 300 times their annual revenue earned from Archegos.  Clearly, it is genuinely hard to calculate risk.  What follows is a simple step-by-step approach to calculating risk to a portfolio of positions.

1.      Identify all the events that can impact each position, including the unknown unknowns.

2.      Assign a probability to the likelihood of each event.

3.      Calculate knock on events that may happen from each previously identified event (1.).

4.      Calculate the impact each event could have on each position and the overall book.

Nobody can identify an unknown unknown.  Assigning probabilities to known unknowns is just guesswork.  Added to all of this we need to consider feedback loops or reflexivity as George Soros likes to call it. Like I have already said – measuring risk is hard.  However, it can be made even harder when a risk manager has no skin in the game.


Dinghies and Ocean Liners

My background in this business stems from running my own floor brokerage firm (JK Brokers - “JKB”) on the New York Board of Trade (now ICE U.S.).  The NYBOT had a small trading floor in Dublin.  Virtually all of the brokerage firms in both Dublin and New York were little ‘mom and pop shops’ employing no more than a handful of people.  If world markets could be described as vast oceans, then the NYBOT pit execution firms could be described as little dinghies.  If a market became turbulent or stormy, these little dinghies would often go bust and sink to the bottom of the ocean never to be seen or heard of again. This happened all the time. The pits were Darwinian.

JKB only dealt with large hedge funds and institutional clients – the Ocean Liners. The individuals I met at these firms were Ocean Liner passengers – they had very little skin in the game.  I had to submit 100% personal guarantees to be in the business.  On a bad day I could be rendered bust, career-less, and houseless.  The worst that could possibly happen the employees that I met would be that they would be in the market for a new job.  I have seen small firms and individuals go bust on the NYBOT.  I cannot recall any of the ocean liner employees losing their jobs because they had a bad day.  Ocean liners like Lehman do sink, but the employees don’t go bankrupt.  I think this is an important distinction.

Forget talent. Risk assessors at large institutions are generally shielded personally from risk.  This dulls their fear senses and allows complacency to creep in. Greed is not constrained by fear.  The upside spoils from a winning (levered) investment are not off set by a downside fear of loss.  If the bank wins, I win.  If the bank loses I still win.  There is nothing immoral or stupid about this attitude.  It is just the nature of the job.  

Bankers do take risk seriously and they do go to great lengths to measure and assess potential risks.  However, my contention is that they are inclined to take too much comfort from mathematical risk models.  Each model can be nothing more than an accounting of what has happened in the past. Risk is about the future.  It is about the unknown.

People with skin in the game are likely to be more fearful and less complacent. Otherwise, they would be out of business.  I believe that the sailors of tiny dinghies that have proven themselves to be survivors have a greater respect and fear of the unknown.  A good analogy might be an example of two soldiers.  The one that fights at the frontline has better fear reflexes than the one that works in logistics far away from the frontline. In the context of assessing risk - Fear is Good.

In Part II – A DISPATCH FROM THE FRONTLINE, I tell a story of one of the storms that helped to form my respect (and fear) of the unknown.

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