The irrational nature of liquidity and its role in financial crises
A short while ago, I was sent a copy of a paper written by an American lawyer by the name of A. Edward Gottesman, which is titled “Credit Crisis 1.0.1.” and which opens with the words “In the end, subprime mortgage loans were only the catalyst for the crisis. The main culprits were the computers. Or, more accurately, the computer models”. The footer on the page reads “WORLD ECONOMICS – Vol. 9 – No. 3 – July – September 2008. Yes, Gottesman’s article was published the very month in which Lehman Brothers went under and when the global financial system came as close as it ever has to falling to pieces.
The piece is a wonderfully direct critique of credit markets as they coughed and spluttered their way into the Global Financial Crisis. The author is not a banker but a lawyer and as such had no axe to grind in terms of self-justification. As we approach the 15th anniversary of Lehman Brothers, that great pirate ship, foundering, it might be useful to many of those who were too young to have experienced the full force of the hurricane that swept down Wall Street and across the City to take the time to see what Gottesman had to say.
He goes on: “Confidence in valuations is the bedrock of financial markets. In economics, it is a fundamental axiom that the market value of a product or service is what a willing buyer and a willing seller agree at a given time. A myriad of factors, including monopolies, the cost of money, war, government controls and temporary disruptions of supply or demand, go into determining the price at any moment. Major problems arise only when buyers or sellers go on strike.”
Yes, in 2008, the author kicked the hornets’ nest which is still sitting right in front of us and upon which markets seem increasingly reluctant to focus. Actually, there are two hornets’ nests. The first, a subject which I am currently struggling to get across, is that price and value are not one and the same thing and that after over two decades of artificially cheap and plentiful money, there is an entire generation of producers, purveyors and consumers of investment assets who were never confronted with the challenge of bringing the two into equilibrium. Judging by what I hear and read, they are either ignorant or in denial of the huge matter in hand. The second which Gottesman correctly identifies as “ a willing buyer and a willing seller” looks like nothing to worry about although in my mind it is the most difficult one to understand. And it is this one upon which I would like to dwell.
The willing buyer and the willing seller are supposedly the platform upon which price formation in markets is based. That, of course, assumes that the willing buyer and willing seller are both willing at the same time and in the same place. That is where first market squares and then exchange floors came into play. When neither were accessible market makers, essentially banks’ trading floors, had their role in stepping in and helping to bridge the time and space between willing sellers wanting to trade and willing buyers deciding to step up to the plate too. Market making traders, as opposed to proprietary ones, needed to judge the risk inherent not only in markets moving during the time in which they hold a position but also how long it might take and how easy it will be for them to be able to unload or cover it again, be it long or short. The ease with which positions can be traded logically depends on the frequency with which a given security trades which in turn is a function of how many investors are happy to hold it. And that is what creates what is known as liquidity.
Market makers are not supposed to make a living from directional bets. That’s for the prop desk. Market makers’ income is, in theory at least, generated from the bid/ask spread, the price they pay for stock and the price at which they offer it out again. By being there for their clients, be they buyers or sellers, when the other side of the trade is not forthcoming on the part of another end user they are creators of liquidity. They provide a service for which they rightfully deserve to be paid and their price, articulated in the bid/ask spread, depends on the amount of risk they have to take when it comes to ease with which the trade they have just done with one client can be reversed with another. To facilitate matters, there are the brokers who communicate with the market makers and bring banks with buyers and no sellers together with banks with sellers but no buyers. It’s not a quiz.
The harder it is expected to be to re-trade a security, the more the dealer will want to be compensated. This, apart from credit risk and directional market risk is known as liquidity risk. If the dealer can, based on experience, see absolutely no exit, then there will be no bid and the willing seller is left hanging. If for whatever reason the seller is a forced seller, in other words, must unload the securities at any price, then “any price” can in certain circumstances be a fraction of what the seller had had in mind and what the position had been marked at in their portfolio. At this point, a market price has been established and all other holders of the same security find themselves obliged to mark down the price of their own holdings. The principle of mark to market, the prevailing policy for valuing portfolios, blithely assumes that the market is always right even if as a result of emerging liquidity risk it blatantly isn’t.
Liquidity risk, the inability to sell securities at the assumed mark-to-market price, is the highest and most difficult to assess of all risks that investors are exposed to. The old cynics’ definition of liquidity is that it is something that is only there when it is not needed. But liquidity risk is no joke. It is very serious but, to come back to Gottesman, it is not something that can be modelled by computers. It depends on nothing other than at-the-minute sentiment. Market liquidity can appear and disappear at the blink of an eye. It is not rational; it is not enforceable and access to liquidity in difficult markets needs to be earned through trust developed between investors and their banks.
Old bond dogs like myself – and I suppose equally old equity, real estate, currency, and commodity dogs – have an instinctive understanding of liquidity risk and know that liquidity is unpredictable and that it can therefore not be expressed through some standard pricing model. The failure of computer models in the 2007/2008 financial crisis is currently in peril of not only being forgotten but of being replicated in spades, doubled and re-doubled. Artificial intelligence, as good as it might be in creating deep fake videos of world leaders spouting rubbish – do we really need AI to see that? – will fail when it comes to coping with liquidity risk. And as we experienced during the GFC, the more we believe that computer modelling provides the answers, the more we expose ourselves to the vagaries of what happens when they fail to deliver.
Liquidity risk can’t really be quantified and yet it is it’s not being priced which makes it so risky. Generations of coders, until not so long ago referred to as programmers, have tried to create models which permit a definitive comparison of two or more diverse assets, and which generate acceptable comparative pricing. Option pricing depends on it, the all-singing and all-dancing solution of which lies in the measure of volatility. A month today, on September 23rd, we will be marking the 25th anniversary of the collapse and bailing out of Long Term Capital Management, LTCM, the epitome of disregard of liquidity risk. Amongst the lead partners of LTCM were Myron Scholes and Robert Merton, both Nobel laureates, who had helped to create the myth that computer models could assess risk better than people and that markets are always right and for modelling purposes even perfect. Had over a dozen banks which were exposed to LTCM not created a liquidity lifeboat- of the cash-in-hand kind – and financed a bridge in time until positions could be unwound in an orderly fashion, the consequences could have been catastrophic. In the event – and this is not often mentioned – the banks that did step up to the plate ended up making out like bandits while LTCM, its partners and its investors got wiped out.
US Supreme Court Justice Potter Stewart – do I really have to call it SCOTUS? – nailed it in his legendary judgement in the 1964 obscenity trial Jacobellis vs Ohio. In it, he wrote with respect to the charge that a film was pornographic and in contravention to Ohio state law “I shall not today attempt further to define the kinds of material I understand to be embraced within that shorthand description [“hard-core pornography”], and perhaps I could never succeed in intelligibly doing so. But I know it when I see it, and the motion picture involved in this case is not that”. The immortal part of is “…I know it when I see it…”
I also know liquidity risk when I see it and it would be hypocritical not to admit that a large part of my retirement fund was generated when I was broking corporate bonds for my own account through the darkest days of the GFC. Market liquidity had all but dried up. Panic sellers were horrified when they found market makers refusing to bid on paper, more often due to their banks’ risk and compliance animals behaving like rabbits in the headlights than to the traders themselves who would have loved to cash in on the opportunities, so it was we freelancers who were left to ring the till. Unfair and unethical profiteering? Maybe, but what’s the correct price for a bottle of chilled Evian water in the middle of the Sahara?
Some of my younger readers – that’s anyone under the age of 69 – might see in me a superannuated technophobe Luddite. They are free to do so. The definitive book on the implosion of LTCM is Roger Lowenstein’s “When Genius Failed”. One of the best volumes on the GFC might be Andrew Ross Sorkin’s “Too Big to Fail”. Both books have “fail” in their titles and both books describe how what could not go wrong went wrong. Both crises escaped control when liquidity dried up and when any meaningful relationship between price and value was lost. This could happen again any day. It might be triggered by nothing more than the equivalent of a butterfly flapping its wings in the Amazon and when chaos theory morphs into chaos practice. That is when artificial intelligence will prove to be exactly what it is which is artificial. That is when real human intelligence will be most needed. We cannot but hope that the lawyers and accountants in risk control and compliance will remember that and that institutional and individual investors will acknowledge and that markets sometimes behave as though it were real life.
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