PsyFi Search

Wednesday, 11 May 2011

Black Swan Down

Uncertainty Up

The world is suddenly full of uncertainty: tsunamis, nuclear threats, civil wars, regime changes and sovereign debt default are all high on the agenda. Yet, despite this plethora of potential pitfalls, markets have remained remarkably sanguine, for the most part.

We should expect, surely, that sudden and frightening events such as these, some of which at least are genuine Taleb style Black Swans, should send investors and markets into a dramatic tail-spin. Yet it ain’t so, and there’s a lesson here, which is that markets aren’t moved by events in quite the way we think they are.


Black Swans, as we saw in Black Swans, Tsunamis and Cardiac Arrests, are defined as outlier events; rare but catastrophic and scientifically unpredictable. Such happenings, supposedly, can cause massive losses in financial markets, especially where quantitative models of risk are used, because such models depend on regularity and predictability and can’t cope with catastrophic breaks.

The Japanese tsunami seems to meet the requirements of a Black Swan. Sure, it was inevitable that an earthquake on the Ring of Fire would eventually happen and damage Japan’s industrial complex. However, the magnitude and timing of the disaster wasn’t anything anyone could have anticipated: still less the one metre drop in the coastline that contributed to weakening the flood defences.

OK, admittedly, building a nuclear power station on a flood plane in an earthquake zone shows a startling lack of imagination which, as we saw in Trading on the Titanic Effect, is a common if worrisome quality in risk planners. Even so, surely the knock-on consequences of the tsunami were unforeseeable and predictable?

From Riyadh to Dublin

Perhaps the uprisings in the Middle East were less surprising, although again the timing and nature of these could never have been precisely calculated. The combination of ineradicable information flow from the Internet and socio-economic problems exacerbated by rises in food prices seem to have been the triggers, but it could have been anything. The ultimate resolution of the situation is uncertain, and anything that threatens the oil supply chain is something we’d expect to cause markets to start gyrating wildly, oil traders being notable sufferers from attention deficit disorder (see Peak Oil: The Revenge of Planet Earth).

Meanwhile the travails of the Euro go on, as demonstrated by beleaguered Ireland, whose government is caught on the horns of a painful dilemma: accept a bailout from Europe that condemns their economy to a long and excruciating squeeze or leave the Euro, default on their debt and suffer the consequences of being an international pariah.

Understandably the Irish would like a compromise between the two paths, but any debt default is anathema to Germany, whose banks would suffer further losses and whose fiscal credibility would take a further knock. With Portugal, Greece and possibly even Spain waiting in the wings this isn’t a scenario they can afford to accept. Although the Euro is defined by compromise, so watch this space.

White Swans

Perhaps, though, these events are closer to White Swans, a term coined by James Montier to explain the housing market crash of a few years ago:
“It is wholly wrong to characterize what happened to the US economy and markets as a black swan. To do so is, in fact, an abdication of responsibility. If these extraordinary events were totally unpredictable, then there would have been nothing we could have done to prevent them.

The events of 2003–2008 were not black swans at all. They were “predictable surprises.” The term was first coined by Michael Watkins and Max Bazerman. A predictable surprise also has three characteristics: (1) At least some people are aware of the problem; (2) The problem intensifies over time, and (3) Eventually the problem explodes into a crisis, much to the “shock” of decision-makers. As Bazerman says: “The nature of predictable surprises [is that] while uncertainty surrounds the details of the impending disaster, there is little uncertainty that a large disaster awaits.”
On this basis the troubles of Japan, the Middle East and the Euro seem more like White Swans than Black. Yet as we saw in the wake of the housing crisis, the colour of the plumage made little difference to the effect on the markets: they dropped, rapidly and vertiginously.

The Crash of ‘87

If we cast our minds back even further we can find the Crash of ’87. On Monday October 19th, the Dow dropped 22%, the largest one-day percentage fall in history. Markets across the world also fell sharply. Yet there was no single event that caused these falls and, even to this day, experts disagree over what caused it.

The picture that emerges here is nuanced, and complicated. Black Swans can cause markets to fall suddenly – 9/11 is a prime example – yet a major unpredictable tsunami on a major industrial country has had a negligible effect. The reason for this is probably simple: what 9/11 introduced was a new and unpredictable type of risk whereas the tsunami has simply crystallised a set of economic losses.

Montier Moments

Meanwhile White Swans, in Montier’s nomenology, can cause dramatic shifts in markets while nothing at all, apparently, can send them spinning out of control. So it’s clear, even if nothing else is, that we can’t rely on Black Swans to create massive market movements. Something else is going on.

Montier suggests that the timeline of a White Swan goes through the classic problems of bubble formation and deflation espoused by Kindleberger and Minsky (see Panic!) . Something triggers the formation of a bubble, too much credit gets created out of thin air, eventually people realise that the bubble is based on nothing more than hope and the whole thing implodes. As liquidity dwindles, loans get called in the situation snowballs unpleasantly.

In the Kindleberger-Minsky model the thing that makes the difference is not the uncertainty of the Black Swan but the liquidity, or otherwise, of the White. Markets feed on the availability of money and if you stoke them with it they’ll soar. Deny them their fuel and they’ll flame out. This may, in fact, be the explanation for the Crash of ’87.

Portfolio Management

The eighties saw the creation of some of the first quantitative risk management strategies based on the use of computers and a demented belief that the future was as predictable as the past. The first proponents of this developed a concept known as portfolio insurance, which allowed funds to insure their portfolios using a system of derivatives. This worked beautifully right up to the point that it didn’t, as Eric Bouyé describes:
“After 1987, portfolio insurance products were pointed out by the Brady Commission as being partly responsible for the amplification of the volatility of the market during the crisis. Indeed, with such strategies, the fund manager sells the risky asset if it has a negative performance. And conversely she buys the risky asset if it increases. This type of strategies are also sometimes called trend-chasing.”
The problem, in October ’87, was that suddenly markets all went one way at the same time. What caused this isn’t understood but we do know that occasionally entirely random sequences of events can look like a pattern to our brains and can trigger further positive feedback: ever been in a room full of people chatting away which suddenly goes quiet for no reason?

Murky Turkeys

Well, a theory is that this is what happened in ’87. Normally, people would have eventually realised this was purely a random effect and started talking again. Unfortunately the automated portfolio management systems weren’t much good at small talk and simply kept on trying to follow the pattern – and sell.

The designers of these systems had made one tiny mistake: they assumed there'd always be a willing buyer. When liquidity dried up there was no one willing to buy and stock prices fell rapidly. In fact, as Mark Carlson relates, this was posited even as a potential problem at the time:
"There were concerns that the use of portfolio insurance could lead many investors to sell stocks and futures simultaneously; there was an article in the Wall Street Journal on October 12 citing concerns that during a declining stock market, the use of portfolio insurance “could snowball into a stunning rout for stocks” (Garcia 1987)"
With hindsight this was all perfectly predictable – a White Swan. At the time it seemed inexplicable – a Black Swan. In truth it’s probably more of a Murky Turkey, and this is likely to be the situation for most market falls.

Liquidity Rules

Returning to the present, if liquidity is generally the key for investors and if Central Banks start raising interest rates, or even just removing the life-support of quantitative easing, to squeeze inflation out of the system, it’ll be hard for markets to make progress. If this does happen, then good companies that are able to grow their earnings will see their prices stagnate, their price-earnings ratios drop and their yields rise. This will occur even as markets, at best, go nowhere and experts tell us that equities are a poor investment.

Yet cycles move on and, when liquidity returns, history suggests that those investors who’ve filled their boots with quality stocks during the down times will see their faith rewarded. According to Buffett markets go in seventeen year cycles, up and down. Apparently we’re currently in year twelve of a down cycle that started in 1999. Perhaps it’s time to place your bets on the Murky Turkey for 2018.

Related articles: Black Swans, Tsunamis and Cardiac Arrests, Panic!, Springing the Liquidity Trap

1 comment:

  1. I appreciated your post, and think that it is correct. I wrote a related post a while ago, and leave it for your consideration.