I am not in the habit of reading classic horror stories but this weekend I picked up John Kenneth Galbraith’s 1955 book, The Great Crash: 1929. Unfortunately it is non-fiction. And even more unfortunately it is selling well in the university bookstore. Galbraith is gone but his book lives on. In a new Foreword written in the 1990s he noted that it has never gone out of print since its publication more than 50 years ago, mainly because every decade or two we have a new stock market crisis to renew interest. Since 1929 these crises have all been harbingers of recession, not depression. It isn’t clear if this one will be different or another 1929 disaster. Reading the book, however, is frightening because the parallels are eerily similar, from the incessant incantations of convenient wisdom (the fundamentals are sound, the big players are stabilizing things, the market is poised for rebound after being oversold, etc., etc.) to the actual behavior of the market.
The free fall of Black Thursday (October 24, 1929) was presaged by a number of other sell-offs and in fact the market rebounded and finished off only a bit below its start. The panic was over by noon that day as the “organized support” of a cabal of Wall Street bankers moved in to support prices. They held steady on the Friday after Black Thursday and were off only a little on Saturday (a normal but shorter trading day at that time). Then on Monday the real disaster started to unfold. Free fall and no closing rally. On Tuesday, the worst day in Wall Street history (until now). Then a brief respite on Wednesday, with a gain. But for the next two and half years, the direction was generally and inexorably down as the country and the world went over the cliff into the abyss.
Will this be averted this time around? Possibly. Possibly not. Those at the helm don’t seem to have a firm grasp of the situation, which is not surprising since people are still arguing over what caused the 1929 crash. Those with their hands on the wheel in the US seem more than usually clueless. They’ve wasted three weeks in to staunch the bleeding that many predicted wouldn’t work. The obvious approach — essentially to nationalize the banks — was not taken for ideological reasons. Europe, led by the UK, has now taken the lead. If we are lucky, the US will be a tardy follower.
There’s no doubt there are a lot of smart people involved in trying to figure this out. But the system is extremely complex. We have a hard time predicting the weather and the arguments over climate modeling are well known. But it turns out that scientists are in agreement that we have better models for climate than we have financial models:
With Wall Street’s vaunted financial models looking shaky, could other models of complex systems — say, the climate models that underpin our understanding of global warming — have similar faults?
In two words, say scientists and financial engineers: not really. It turns out that it’s much harder to model human sentiment, the basis of value, than particle interaction.
“It’s the physics. The issue is that economic models aren’t based on any underlying physically observed facts. They’re based on people’s feelings,” said Gavin Schmidt, a climate modeler at Goddard Institute for Space Studies. “We’re not having a climate crisis because there’s a lack of confidence in water vapor.” (Wired)
These are the models that the technicians use to price the derivatives and other complicated financial instruments that are part of this unholy global mess. But we are much farther ahead with climate models which have a sound scientific basis:
“Climate models are very complex but you more or less understand the basic physics or chemistry,” said [Emanuel Derman, a physicist turned financial engineer, who teaches at Columbia University]. “[Finance papers] look like physics but a lot of the similarity is syntactic more than semantic.”
For example, stock options are priced with the Black-Scholes model, which says that stock price movement can be seen to move like the random movements of particles suspended in a liquid, i.e. Brownian motion. But stock price models differ from particle models because they describe the aggregate actions of people.
“When you put out a weather forecast, the weather doesn’t read your forecast and get affected by it,” Derman said.
In other words, Derman argues, in a soon-to-be released essay, the primary difference between physical and financial models is that the accuracy of financial models could be fundamentally unknowable. No test can really validate how they works.
“The gap between a successful financial model and the correct value is nearly indefinable,” he writes.
Functionally, the ability to generate returns determines how useful a financial model is.
“What then is the test of the [Black-Scholes] model?” asked Jeremy Bernstein in a prescient 2004 Commentary article. “Presumably, it is that if one uses it as a guide to buy these options and, as a result, goes broke, one will be inclined to re-examine the assumptions. Presumably.” (Wired)
I guess we aren’t presuming this any longer. Or shouldn’t be. But who knows? The same people who are climate change deniers because they don’t believe the science-based models are often the same people who were willing to put financial policy in the back seat while much worse models were running the autopilot.
Now we can have the best of both worlds: climate change and global depression. Lucky us.