This is priceless. Being an objectivist means never having to take responsibility for your actions. Greenspan has now decided to pin the financial market crisis on models.
Gee, it was your Fed, Mr. Greenspan, that endorsed letting regulated entities decide how to mark and manage their derivative and structured product risks without anyone at the Fed developing the skills to evaluate how good those techniques were. That’s fine if you are willing to let anyone and everyone fail; Darwinian forces and a heighten concern for survival with no safety net might have done the trick. But the LTCM debacle, when the very top minds in the industry, and ones operating without any expectation of a rescue, blew themselves up spectacularly, illustrated how incorrect that assumption was.
I could go on about other self-serving lapses, such as the utter failure to acknowledge that negative real interest rates, which are a sure fire was to encourage speculation, might have had something to do with the current sorry state of affairs. But hopefully readers will have some choice observations of their own.
I’ve omitted the first part of the piece, in which Greenspan goes through the inventory overhang in the housing market and concludes that we won’t know where the bottom for the housing market is until excess inventories are liquidated, and it isn’t clear how long that will take. How insightful.
From the Financial Times:
The crisis will leave many casualties. Particularly hard hit will be much of today’s financial risk-valuation system, significant parts of which failed under stress. Those of us who look to the self-interest of lending institutions to protect shareholder equity have to be in a state of shocked disbelief. But I hope that one of the casualties will not be reliance on counterparty surveillance, and more generally financial self-regulation, as the fundamental balance mechanism for global finance.
The problems, at least in the early stages of this crisis, were most pronounced among banks whose regulatory oversight has been elaborate for years. To be sure, the systems of setting bank capital requirements, both economic and regulatory, which have developed over the past two decades will be overhauled substantially in light of recent experience. Indeed, private investors are already demanding larger capital buffers and collateral, and the mavens convened under the auspices of the Bank for International Settlements will surely amend the newly minted Basel II international regulatory accord. Also being questioned, tangentially, are the mathematically elegant economic forecasting models that once again have been unable to anticipate a financial crisis or the onset of recession.
Credit market systems and their degree of leverage and liquidity are rooted in trust in the solvency of counterparties. That trust was badly shaken on August 9 2007 when BNP Paribas revealed large unanticipated losses on US subprime securities. Risk management systems – and the models at their core – were supposed to guard against outsized losses. How did we go so wrong?
The essential problem is that our models – both risk models and econometric models – as complex as they have become, are still too simple to capture the full array of governing variables that drive global economic reality. A model, of necessity, is an abstraction from the full detail of the real world. In line with the time-honoured observation that diversification lowers risk, computers crunched reams of historical data in quest of negative correlations between prices of tradeable assets; correlations that could help insulate investment portfolios from the broad swings in an economy. When such asset prices, rather than offsetting each other’s movements, fell in unison on and following August 9 last year, huge losses across virtually all risk-asset classes ensued.
The most credible explanation of why risk management based on state-of-the-art statistical models can perform so poorly is that the underlying data used to estimate a model’s structure are drawn generally from both periods of euphoria and periods of fear, that is, from regimes with importantly different dynamics.
The contraction phase of credit and business cycles, driven by fear, have historically been far shorter and far more abrupt than the expansion phase, which is driven by a slow but cumulative build-up of euphoria. Over the past half-century, the American economy was in contraction only one-seventh of the time. But it is the onset of that one-seventh for which risk management must be most prepared. Negative correlations among asset classes, so evident during an expansion, can collapse as all asset prices fall together, undermining the strategy of improving risk/reward trade-offs through diversification.
If we could adequately model each phase of the cycle separately and divine the signals that tell us when the shift in regimes is about to occur, risk management systems would be improved significantly. One difficult problem is that much of the dubious financial-market behaviour that chronically emerges during the expansion phase is the result not of ignorance of badly underpriced risk, but of the concern that unless firms participate in a current euphoria, they will irretrievably lose market share.
Risk management seeks to maximise risk-adjusted rates of return on equity; often, in the process, underused capital is considered “waste”. Gone are the days when banks prided themselves on triple-A ratings and sometimes hinted at hidden balance-sheet reserves (often true) that conveyed an aura of invulnerability. Today, or at least prior to August 9 2007, the assets and capital that define triple-A status, or seemed to, entailed too high a competitive cost.
I do not say that the current systems of risk management or econometric forecasting are not in large measure soundly rooted in the real world. The exploration of the benefits of diversification in risk-management models is unquestionably sound and the use of an elaborate macroeconometric model does enforce forecasting discipline. It requires, for example, that saving equal investment, that the marginal propensity to consume be positive, and that inventories be non-negative. These restraints, among others, eliminated most of the distressing inconsistencies of the unsophisticated forecasting world of a half century ago.
But these models do not fully capture what I believe has been, to date, only a peripheral addendum to business-cycle and financial modelling – the innate human responses that result in swings between euphoria and fear that repeat themselves generation after generation with little evidence of a learning curve. Asset-price bubbles build and burst today as they have since the early 18th century, when modern competitive markets evolved. To be sure, we tend to label such behavioural responses as non-rational. But forecasters’ concerns should be not whether human response is rational or irrational, only that it is observable and systematic.
This, to me, is the large missing “explanatory variable” in both risk-management and macroeconometric models. Current practice is to introduce notions of “animal spirits”, as John Maynard Keynes put it, through “add factors”. That is, we arbitrarily change the outcome of our model’s equations. Add-factoring, however, is an implicit recognition that models, as we currently employ them, are structurally deficient; it does not sufficiently address the problem of the missing variable.
We will never be able to anticipate all discontinuities in financial markets. Discontinuities are, of necessity, a surprise. Anticipated events are arbitraged away. But if, as I strongly suspect, periods of euphoria are very difficult to suppress as they build, they will not collapse until the speculative fever breaks on its own. Paradoxically, to the extent risk management succeeds in identifying such episodes, it can prolong and enlarge the period of euphoria. But risk management can never reach perfection. It will eventually fail and a disturbing reality will be laid bare, prompting an unexpected and sharp discontinuous response.
In the current crisis, as in past crises, we can learn much, and policy in the future will be informed by these lessons. But we cannot hope to anticipate the specifics of future crises with any degree of confidence. Thus it is important, indeed crucial, that any reforms in, and adjustments to, the structure of markets and regulation not inhibit our most reliable and effective safeguards against cumulative economic failure: market flexibility and open competition.
17 comments
Comments are closed.
That guy is going to live just long enough to see his reputation move through the same cycle as George Bush’s approval rating. From stratospheric, down to the point that people can hardly comprehend it was ever anyhing but a joke. He retired at the anti-perfect moment.
Alan Greenspan’s Wikipedia entry in 2020:
“Former US Federal Reserve chairman chiefly known for implementing the disastrous policies leading up to the 2008-?? recession that proved to be the death knell of neo-liberalism.”
Blind trust in risk models have disconnected him and many others from reality. If intellectually honest, he could apologize and recognize he has been fooled by randomness.
Particularly hard hit will be much of today’s financial risk-valuation system, significant parts of which failed under stress.
They failed a long time before that.
Letting speculative fevers break on their own is simply too devastating to too many innocent bystanders to be allowed to continue. If this is the best that economists can come up with, then they have utterly discredited themselves as a discipline.
Greenspan’s legacy, like that of the last president he served, will be written in the ashes of the unprecedented destruction that’s been brought about by his policy failures.
I just wonder if Greenspan did it on purpose. What better way to bring back the gold standard than to allow the fiat money system run amuck?
he is lucky he is old. not hard to imagine people calling for his incarceration.
Yves, I share your incredulity.
Mr. Greenspan is so blinded by his faith in unregulated markets that he thinks the answer to inadequate models is to make the models even more complex, even after admitting that current models were too complex for people to understand.
But there is another way: make the financial world simpler. Well thought out regulation can make the financial world easier to model by specifying and regulating the way that different markets interact with each other, and the ground rules that every player follows.
Take the American stock market vs. the Chinese, for example. I would argue that the American stock market is much simpler to model because you don’t have to figure in companies cooking their books, opaque reporting, unscrupulous brokers trading against you, etc. etc. (Yes, these things happen on Wall St. too, but not nearly to the extent as they do in China). An American retail investor can reasonably assume that these things are regulated by the SEC and so can focus his/her models on profit expectations, market growth, etc. etc. Thus, the U.S. govt, through regulation and enforcement, has removed some variables from the models, thus making them simpler.
I’ve argued before that what we need are financial systems that are “boring” in the sense that they are predictable, reliable, stable, and relatively static even at the cost of higher prices. After all, the purpose of a financial system is to facilitate transactions between holders of capital and the people that need it. It’s not for financial transactions to become an exercise unto themselves. Such a system becomes drastically easier to model. Only a tight and comprehensive regulatory scheme can provide that.
It’s extremely annoying to see people like Greenspan start with the (sometimes hidden but always present) assumption that the “free” market is a natural reality that can’t be changed, and we must resign ourselves to conforming to its whims. The fact is, the “free” market has been created by a series of rules, treaties, and organizations, all created and run by people, not God. We can change the underlying rules if/when we decide that’s the best course of action. We’re not powerless.
Secondly, Greenspan forgets the fact that the models worked very well for the people that created them. After all, they’re walking away with 100’s of billions of dollars in bonuses for the past few years. Or does he actually think the models were meant to improve the financial system rather than ultimately pad their own profits? I’d expect that if you correct the severe agency issues present in financial firms, their models will become much more reliable…
Oh no yah dont…models are the future! As I recall all the pension “stuff” is now to be based on modeling, all the models that are linked to the models at The fed and rating agencies……it’s all factored in and the models all work…….yah!
Here is a fashionable model post from a few months back:
The aging tuning parameter is designed to speed up or slow down the aging effect in the model. The aging effect controls when the model forecasts loan/pools to reach their full amount of turnover and refi SMM’s. Increasing the aging parameter will make the model reach the full amount of turnover and refi SMM sooner, and decreasing it towards 0 will push the aging peak out further. Values for aging can be any number greater than 0, and the default value is 1.0.
The lag weighting on the mortgage coupon used when determining refinance incentive. The model uses a blended mortgage interest rate from the previous 3 months to determine the relative refinance rate for a given loan/pool. Adjusting the lag parameter above 1.0 puts more weight on the interest rate from 3 months ago, and decreasing towards 0 places more weight on the rate from last month. Values for lag can be any number greater than 0, and the default value is 1.0.
Burnout tuning allows the user to adjust the rate at which the model’s burnout occurs. There are two types of burnout tuning, “model” and “sensitivity.” Choosing “model” will change the historical burnout rate (if you are running an analysis where the loan/pool has already aged) from pool/loan origination, and going forward into forecast. Choosing “sensitivity” will only change the burnout rate going forward from today, i.e. in the forecast only. This tuning parameter is useful for situations where the user feels that the model does not slow down enough when the loan/pool becomes seasoned, or where too much prepayment occurs too soon and the speeds being forecast for the older ages are too low. Increasing this parameter above 1.0 will make more prepayments occur sooner, and decreasing towards 0 will make seasoned collateral prepay at a higher rate. Values for burnout can be any number greater than 0, and the default value is 1.1.
Bashing the FED seems to be a favorite of many here. The points made by Greenspan seem entirely reasonable to me, namely that the dynamic of breakdown is not currently captured in models. I believe that these breakdowns, driven by “negative feedback loops”, lead to dynamically unstable models. These models are well understood in the context of solid state physics for example where they explain phase transitions. They are also used in weather forecasting. Non-linear dynamics can be utterly puzzling to predict yet a lot can be learned. I find Greenspan’s comment actually pretty insightful, for a non-techie, when he offers the historical evidence that recessions, driven by fear are short while expansion can run linearly for a long time. It may not be a case of “missing variables” rather than a case of missing dynamics. An excercise in risk-management, like weather prediction, can say “under these and these conditions expect showers with 80% probability” or “under this amount of leverage, the risk of a systemic breakdown with a “seed” (subprime) is bla bla”.
13 paragraphs to say computers cannot model the extent to which greed and fear can corrupt.
That says a lot about where we are at today.
Marcf,
Greenspan’s comments are entirely reasonable if you believe that markets are some sort of natural phenomena that we must do our best to predict and model rather than try to change. The weather can’t be changed by people (in the short term, at least, global warming aside…), so the best we can do is predict it as accurately as possible, continuing to tinker with our models as our knowledge increases.
But the markets are our own creation. Rather than accept negative feedback loops and other phenomena that lead to instability, why not regulate the markets better and force a more linear (or at least more predictable) behavior?
For example, after the 1987 crash, the feedback loop nature of program trading was recognized. What did we do? We didn’t just exhort traders to update their models. We changed the rules and instituted circuit breakers to suspend trading when there are extreme swings in a stock.
Again, I think Greenspan’s fundamental mistake isn’t his analysis of models. It’s his inability to entertain any alterations to his beloved “free” markets as part of the solution.
Lune,
If I ever get around to writing a book, I am sorely tempted to have a go at this incoherent, internally inconsistent, yet somehow-part-of the-orthodoxy concept of “free markets.” Free markets is interpreted as meaning “unregulated” but if anyone understood what that meant, no one would want to operate in a system like that (well maybe Harry Lyme types, acting as profiteers in an lawless regime).
The problem is that others have written books in this general subject area and the orthodoxy remains intact (and I’m not sure the books did all that well either).
Stocks are an inappropriate instrument to exchange on an anonymous basis; unlike bonds, which make very specific promises regarding their payments and the owners’ right if there is a default, equities are extraordinarily ambiguous” “gee we’ll pay a dividend if we make enough money and we feel like it. Oh, and you can vote, but hey, don’t be surprised if you are diluted.” Historically, equity owners were more like venture capitalists: they knew the company and the management and were often actively involved in promoting the enterprise.
Lots of regulation made it possible to trade stocks on a mass basis. Yet most people thinks of the stock exchange as an idealized example of a market. Bizarre.
Yves and Lune
Frankly, regulation scares me, blame it on some long delayed bout of adolescent instinct to rebel. Regulation keeps most people oin line but tends to encourage the channelling of creativity towards finding loopholes and exploiting them, think for instance SIVs. Give guidelines, encourage compliance, let investors, lawyers and the market in general “punish” those who don’t want to play nice, so to speak, moral hazard really is about how people won’t learn not to stick their hand into the fire until they feel the scorch. That’s not not dismissing the fact that some people like pain, hey, it takes all kinds to make the world.
As for models and regulation, sure the Chinese have more incidents of irregularities and opacity, but no model can ever include fraud as a variable or even opacity, some things cannot be quantified, that is a major failing of a system that is so reliant on stats and quantification. As said in a previous post on my own site (no, this is not pr or advertising; just stating that this is not a new thought), the wider the number of variables, the less accurate the resultant model. Aggregation of models might produce conflicts in terms of predictions as well as reasonableness (did that make sense?).
What is sad in the present crisis is not the widespread failure (amongst some of the best minds in the business) to see crisis looming but that reaction and the race for solution has been pushed aside by a desire to pass the buck. The best model cannot rival reality and foreseeing disaster is useless if you don’t have a solution.
foesskewered,
With all due respect (and I know you are sincere in your distaste for regulation), you can’t have “compliance” without regulation.
You would get no, or very unreliable financial statements if there were no regulation. Brokers could tell you anything, not be held to fiduciary standards, misexecute your trades, and you’d have no recourse if there were no regulation (I’ll be the first to admit the arbitration process ain’t great, but it’s better than nothing). You wouldn’t have standardized settlement if there were no regulation. Brokers are now required to execute market orders within a very tight time frame (I think 3 seconds of electronic receipt of the order) AND they have to be able to prove they executed it within that time. No more playing with the order book to benefit the house to the disadvantage of the customer.
I worked in the securities industry when it was more heavily regulated as a whole than today. Aside from the fact that the SEC now requires disclosure documents to be written in a more user friendly fashion, the industry then delivered much better results for the economy as a whole than it does now. And despite your concerns, there was far less off balance sheet and whatnot creativity than we see today.
Yes, fees and spreads are lower than they were then. But does the world benefit from the hair trigger trading that lower costs facilitate? The average time that an NYSE stock is held is now 7 months. No wonder no one manages for the long term. They pretty much don’t have long term shareholders. And that trend has been hugely destructive to the real economy. (One of my buddies nearly 15 years ago proposed a transaction tax because he recognized that near-fricitionless trading would foster speculation).
Similarly, as I’ve noted before, the Fed sat by while derivatives markets exploded, Now I have worked for derivatives firms; derivatives can be highly useful tools. But you can blow yourself up very quickly with them.
And the biggest derivative market, credit default swaps, isn’t a classic derivative but more like a massive unregulated insurance market. There have been so many firms whose balance sheets are not subject to outside inspection (hedge funds) writing CDS that it is scary. Oh, they will assure you they are hedged. Right. Dynamically hedged using correlation models with maybe 5 years of data, never tested in a bad market, and oh BTW many of those models are blowing up right now. I assure you we will have a CDS train wreck; the only question is whether it can be contained or whether it spirals into something worse.
Regulation does not stop bad behavior, but when designed properly, it makes it sufficiently difficult and costly so as to limit its scope and therefore hopefully its impact. The S&L crisis was the direct result of poorly thought out deregulation. When you have a financial system that is effectively underwritten by the public at large, it is imperative to have some controls.
Richard Bookstaber has compared the modern financial system to a nuclear reactor. You wouldn’t dream of letting a private unregulated operator set up a nuclear reactor within 20 miles of your home. This is fundamentally no different.
I believe the problem with regulation is a) the difficulty of tweaking rules when they are discovered to work badly and b) the fact that regulators are subject to “regulatory capture” meaning being co-opted by their charges. The SEC and the FDA are prime exhibits of the latter. But that is also due to the cultural drift over the last 25 years successfully fomented by the Chicago School against regulation. As this credit debacle rolls on, regulation will come to look very attractive because we will get repeated illustrations of the costs of insufficient regulation.
Poor Greenie – he is on a mission to try to save his legacy. He’s been talking like no one has ever criticized him, but the critics have been prolific for many years. I guess he thought he could retire near the peak of the housing lunacy he sparked and go out at the “top of his game.”
“Greenspan has now decided to pin the financial market crisis on models.”
Just as an fyi, this is not something Greenspan has just recently decided to pin the problem on.
Infact, as early as 2002 (http://www.federalreserve.gov/boarddocs/speeches/2002/20020830/), the fed has been referring to this, as well as myriad other inadequacies in the financial market.
E.g. Risk management within financial bubbles.