Category Markets

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What criticism with knowledge looks like

Jul 12, ’09 8:59 PM

I complained last week that Duncan Watts’ editorial was an argument without much substance, effectively an argument based on deep knowledge of networks but shallow knowledge of markets.

At the end of last week, James K. Galbraith testified for the Subcommittee on Domestic Monetary Policy and Technology. And it was pretty awesome. First, it was a takedown of the Fed’s potential role as the main regulatory body in charge of system risk (which he thinks would be a bad idea because it should be the main, not secondary goal of the regulatory body; and because the Fed kind of historically sucks badly at identifying systemic risk). Second, he went on to talk about ‘too big to fail’:

Would the country be worse off with a smaller, simpler financial system, largely operating out of institutions called banks and thrifts, themselves reorganized, downsized, broken up, more competitive and less profitable than the financial sector has been in recent years? I can see no reason to permit the continued existence, let alone to foster the market dominance, of financial institutions so large as to be unmanageable by their own top leadership, let alone efficiently regulated by public authority. Edward Liddy, CEO of AIG, has written that he realized quite early on that the firm was “too complex, too unwieldy and too opaque” to manage as a going concern. In general, “too big to fail” is a synonym for “too big to manage” and “too big to regulate.” Such institutions exist, in part, to help with international tax evasion, to evade regulations, to project political power, to facilitate the kind of “financial innovation” that is the essence of systemic risk. They are intrinsically unsafe. An appropriate goal of public policy would be to shrink them, permitting other institutions of more reasonable size, more conservative practice and greater alignment with public purpose to grow into their market space.

I agree so much with this perspective in general and this statement in particular. It’s worth a longer, more sustained argument to suggest that financial services organizations are not entitled to their business model just because it’s ‘working’ for them. But for now, compare Galbraith to the statement by Robert C. Merton looking for a way to mush-mouth an apology for financial innovation:

You’ll hear in this case as in the past, “Look at all this financial innovation or financial engineering–it’s caused too much complexity, and now the system has run off the tracks.” To that I would say, structurally, one would expect that in the case of a successful innovation, the infrastructure to support it properly will lag behind. Why is that? It’s because if you have 100 innovations, maybe 2 of them will be successful. So it is not practical to build a full infrastructure–regulatory, educational, et cetera–for all 100 innovations. Innovations are going to run ahead of the infrastructure. That, we have to recognize, is structural. It’s not about bad people, it’s not about incompetent people, it’s not about greedy people. It’s not about having a market system or a nonmarket system. Whether the problems are addressed by external regulation or a combination of that along with internal regulation–whatever set of ways, we have to be prepared when innovations come in to have some degree of oversight modulation. If you do too much of that and you stifle innovation, that’s not good. If you do none at all, that’s not good either. So there’s something in between. Sometimes we don’t do enough of it, or the growth of innovation is too quick, but the point is that there is a reason why you will typically find that financial crises are often connected with what are perceived as new things, big changes–innovations.

For Merton, the problem is just that we have so much great innovation and we can’t tell which ones are going to be successful, that we couldn’t possibly have infrastructure and regulation to support them all.

It’s just that Galbraith’s argument is just so much more convincing.

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When you have a hammer, all the world's a nail – network edition

Jul 10, ’09 10:43 AM

I’ve read a few times the editorial by my former colleague Duncan Watts, and despite some interesting discussion, I can’t help thinking that this is a guy who knows a lot about networks and not so much about financial markets.

The article is about the problem of size and complexity in financial services organizations. Watts argues that we ought to pay attention to:

a general trend toward building ever larger and more complex networks. In recent years, hundreds of millions of people have rushed to join online social networks, while billions more rely on e-mail and cellphones to stay connected to friends and coworkers all day, every day. Technologists wax lyrical about “Metcalfe’s Law,” which posits that a network’s “value” increases in proportion to the square of the number of people or devices in it. And system designers revel in the ability of networks to improve a system’s overall efficiency by dynamically distributing computer-processing load, power generation, or financial risk, as the case may be.

And the answer is that we should prevent firms from becoming big and complex enough to be deemed “too big to fail.” For Watts, too big to fail is too complex to exist. Fair enough. But this is suggested in a complete absence of any content of what financial services firms, hedge funds, or other trading organizations actually do. For instance, are we speaking about proprietary trading positions in various markets that tie them together, like multi-strategy hedge funds (.pdf)? Or are we speaking about a firm that acts as a clearing member for a bunch of other firms, as it was the case in 2007 when the top 10 investment banks were counterparties to 90% of all credit market trades? Or are we speaking of firms that are/were wildly leveraged, like Bear Sterns (or its subsidiary, the magical Everquest Financial and its CDO-squared monster Parapet)?

In other words, Watts’ version of systemic risk only makes sense if we just put brackets around a disparate set of practices, encompassed in varied institutions, and call them all “a series of complex, interlocking contingencies.” Well, sure, a complex system of interlocking contingencies does indeed sound like it might create systemic risk. But it doesn’t say much else. And let me be clear that I’m on board with the problem of systemic risk. I just don’t know why it makes sense to think of financial markets as the same as email, and electric grid, or an epidemiological event.

So what instead? First, I think we need people with substantive knowledge of what financial services organizations do. This is not a way of saying that only finance people and economists should be figuring out what to do (these are the people, after all, who made this disaster), but it is a way of saying that abstract knowledge of risk or organizations or networks is insufficient. Securitization is not just an interlocking contingency – or rather, it is, but that’s saying almost nothing. The roots of that contingency, including the measurements of risk in the creation of new assets (as Yuval Millo would suggest) and the institutional and legal conventions of creating a limited liability trust incorporated in the Caribbean to launder asset-backed securities into invest-able shares (as I would suggest) are where the action is.

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Valuation of Warrants

Jun 30, ’09 7:47 AM

From the CBO’s June update on TARP funds (that’s a .pdf):

The market value of outstanding warrants held by the Treasury is around $6 billion, CBO estimates.14 Of the total, about $1 billion is from warrants issued by the 10 banks that recently repaid their TARP funds. However, those calculations are sensitive to the assumptions used in CBO’s models—particularly for treating the volatility of future stock prices (that is, how widely stock prices fluctuate over a given period).

14. CBO uses a Black-Scholes options-pricing model to price TARP warrants that relies on observed stock prices, estimated dividend yields, and historical data on volatility compiled from weekly securities returns for a period of 10 years.

Because what other methods are you gonna use?

Interestingly, the current estimate of the amount of ‘subsidy’ from $700+ billion TARP (that is, the part we’re not going to get back) is $159 Billion. Cost is weird here, since there are three main sources of governmental assistance: 1) asset guarantees; 2) very cheap loans; and 3) payments not going to get paid back.

And in particular (ahem, Goldman Sachs), $35 Billion to AIG in loans and stock purchases, lots of which went directly to pay off GS and others’ credit default swaps. Another $40B lost to the auto industry, and $50B to the as-yet-established mortgage relief plan.

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Cap and Trade irony

Jun 26, ’09 10:56 AM

I love that when Cap & Trade was introduced in the 1990s, Democrats and environmentalists derided it as putting a price on the environment and capitulating to business. Republicans pushed it as a market-based solution to a social problem.

Now, Democrats and environmentalists embrace C&T as the greenest thing around (well, other than structurally-similar carbon taxes), and Republicans deride it as a massive tax increase.

It (still) is what it is: an incremental improvement on environmental pollution, mobilized by a (probably flawed) market mechanism, that will increase costs (but not as much as if the EPA began regulating carbon by itself).

It (still) is not economic Armageddon or a serious solution to environmental degradation.

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Banks, TARP, Treasuries

Jun 10, ’09 9:58 PM

This week, we find out that 10 banks are returning TARP money. Or more specifically, 10 banks are repaying $68.3 billion in federal bailout money. This does not mean that these banks are freeing themselves from the yoke of government (only, says the snark in me, it allows them to pay themselves obscene amounts of money to retain the best and the brightest. Best and the brightest. Just keep clapping!).

On the contrary, their ability to bring in profits over the past quarter are almost certainly the result of near-zero federal funds rates and an alphabet soup of government support programs.

The FDIC has been providing a Temporary Liquidity Guarantee Program (.pdf) since November 2008 (guaranteeing unsecured senior debt of eligible banks); the Federal Reserve’s Commercial Paper Funding Facility (CPFF) purchases three-month unsecured and asset-backed commercial paper from banking institutions; the Fed’s Asset Backed Commercial Paper (ABCP) Money Market Mutual Fund (MMMF) Liquidity Facility and the Money Market Investor Funding Facility (MMIFF) buy asset-backed debt to support money market funds; the Fed’s Term Asset-Backed Securities Loan Facility (TALF) supports “the issuance of asset-backed securities (ABS) collateralized by student loans, auto loans, credit card loans, and loans guaranteed by the Small Business Administration (SBA).”

There are two effects here, one practical and one theoretical. The practical effect is to make money cheap and relatively risk-free, or at least to transfer the risk to the federal government and the profits to the private sector. So think about what this means, not for the 10 banks whose free money is putting them above the ‘stress test’ line, but the rest of the banks (Citi!!!) whose free money isn’t.

The second effect, which is more interesting from the point of view of economic sociology, is that the federal guarantee of almost any risky asset held by a private financial institution effectively alters the information contained in the market price of these institutions and assets. I would almost but not quite suggest that the state has effectively transformed the toxic assets held by banks into US Treasury bonds, but it’s not not doing that.

More specifically, you might ask: what the price of an asset is that is guaranteed by the federal government? How valuable is it? How much risk does it embody? These questions are unanswerable, and in this sense, the alphabet soup of programs and supports have significantly reduced the signal-to-noise ratio of credit market prices. This is a momentous shift in the financial system.

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The rise of futures trading, part who knows what

May 29, ’09 11:24 AM

The financial crisis has made it appear as though futures markets have been humming along famously and unproblematically until the past few years, when credit default swaps and esoteric derivatives made the otherwise functional system toxic. And this may be. But let’s not pretend that futures markets were always just hedging mechanisms with an added speculative benefit for entrepreneurial risk-takers. They’ve been primarily about speculation for some time.

A couple of interesting data points here. The first is a chart from EHnet (in a well-cited article:

What happened between 1970 and 2002?

What happened between 1970 and 2002?

As you can see, the total amount of produced grain trends upwards, but the amount of speculation trends exponentially. More data points would help, of course. But I can provide an educated guess that in the mid-1970s the modal speculator in futures was a rich, risk-taking individual; by the 1990s it was corporate and financial institutions; and in the 2000s it’s been financial firms big and small.

And why might rich folks have taken note of futures trading through the 1970s and into the 1980s? Taxes, baby.

There are numerous ways that uses of futures markets for tax avoidance purposes are practiced by people who have income from “unrelated sources,” such as real estate, stock transactions, etc. Brokerage houses and advisory services have promoted these tax avoidance ideas among high income persons. And such uses have been growing.

A common method is the “tax straddle” and its many variants. Essentially, these are spread positions in pairs of futures delivery contracts that fluctuate closely together – most commonly in pairs of delivery months for the same commodity – handled in such a way as to create paper losses in the current tax year, with offsetting gains deferred until the next tax year (and repeatable in the following tax year). Also, it enables short-term capital gains to be converted to long-term capital gains.

The precious metals futures markets have become rife with such transactions, as well as other types of tax avoidance maneuvers, but so have interest-rate futures markets and perhaps some agricultural commodity markets, like soybeans. All futures markets are subject to tax avoidance transactions and many have been used for that purpose by traders in such markets.

The Treasury estimates that in 1981, about $1.3 billion will have been lost by taxpayers’ use of futures markets to defer taxes and to convert tax obligations from ordinary income and short-term capital gains rates to long-term capital gains rates. The IRS has been challenging such taxpayer claims in the courts and believes it will win most cases but wants to plug the loopholes now through legislation (see “Statement of the Honorable John E. Chapoton, Assistant Secretary for Tax Policy Before the Committee on Ways and Means, House of Representatives,” U.S. Congress, House, 97 Cong. 1 sess., given 30 April 1981, unpublished transcript).

There seems to be general agreement that futures markets should not exist for tax avoidance purposes but there is apprehension in agricultural circles that the liquidity of agricultural commodity markets would suffer if the successful speculator in futures could no longer count on sheltering income from speculating in futures from high tax rates. They argue for exclusion from any modifications in the tax laws.

- pg. 301, fn 8 in Paul, Allen B. 1982. “The Past and Future of the Commodities Exchanges.” Agricultural History 56(1): 287-305.

Interesting, no?

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Socially acceptable markets

May 28, ’09 9:29 PM

Cedric Cowing, in his wonder book Populists, Plungers, and Progressives, writes about the distinctions between futures and options in the 19th century and the tenuous myth of deliverability:

Probably the greatest difficulty the exchange forces faced was the task of differentiating between a simple option and a futures contract. Options permitting fulfillment by settlement of differences alone were regarded by the courts as gambling contracts and hence unenforceable, so it was vital that the brokers draw a careful distinction between futures contracts, their principal form of business, and these illegal options. In theory the difference was that a simple option could always be settled by cash, whereas the purchaser of a futures contract could demand delivery of the actual product. In practice, however, the distinction was meaningless, because futures contracts were settled just as simple options – by the payment of differences. In only 3 per cent of the futures trades was there actual delivery; in fact, to demand delivery was to brand oneself a miscreant and led to ostracism by the brokers.

This distinction might have seemed tenuous to the layman, but it was fundamental according to prevailing legal thought. The right to require delivery, contained in the futures contract, made it possible to say that the seller at the time of the sale intended to make delivery and therefore, his intent being legitimate, the contract was legal and binding. The simple option, on the other hand, was inescapably a wagering contract because the purchaser could offer no intent other than a desire to profit by a price change. The intent to profit, where no goods were exchanged, was held to be socially unjustifiable. Thus it was only the delivery provision in the futures contract that enabled traders to refer to themselves as brokers and speculators rather than gamblers, and decided whether – at least in the legal mind – they were assets or liabilities to society.

Two things are important here. The first is that it was necessary to create a fiction that allowed early exchanges to distinguish speculation from gambling. Because the public found ‘risk transfer’ (or rank market speculation) unconvincing. And second, a failure of economics as a discipline was (here at least) its imposition of ‘market efficiency’ as a socially desirable end in and of itself. By late 20th century, speculation as a form of risk transfer was promoted as a way to make markets more efficient. And market efficiency obviated the need for some kind of ‘real economy’ justification.

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Asshole corporate doublespeak

May 18, ’09 10:06 PM

from their website: AMERICAN EXPRESS ANNOUNCES REENGINEERING PLAN TO GENERATE $800 MILLION COST BENEFIT

from the New York Times: American Express to Cut 4,000 Jobs, Saving $175 Million

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more aggrevaluation

Apr 24, ’09 9:18 AM

[this is a comment on Brayden's post, which got long enough that I'm reposting the comment here. Go read that thread though, it's quite interesting.]

Ha, I step out for an evening and realize I’m being called out by name, even praised, after I was so unkind to the orgtheory. Brayden you’re trying to make me reconsider…

A few things. First, I’m lumping together into ‘aggregation’ and ‘wisdom of crowds’ a number of different types of activities. Recommendation engines and the Hollywood Stock Exchange (where I’m currently ranked 47943th, with a lifetime ROI of +1,164.95%) are very different, and rather than go with the it’s complicated routine, I lumped a bunch together. I’d go a step further than Lena and say it’s a categorical error to suggest either expert opinion or crowd-sourced outcomes are generated with same logics. I’d like to hear more about the relative value of expert-vs-the crowd across these differences.

Second, design-wise, I might be wrong about exploitation v. exploration. I had in mind that if you put a movie on HSX and try to value it, you will be way off on movies that don’t already conform to existing kinds of movies. Or, if you base your decisions on what kinds of things people like/want, you end up with Playstation 3 and Xbox 360, and miss the Wii – because people didn’t ‘want’ it before it existed. Ugh, I’m getting muddy.

But I might be wrong – I mean, Paul DePodesta (of Moneyball, soon a movie with Brad Pitt and ironically undervalued at $31.75 on HSX) explicitly noted that he used data and no assumptions about existing scouting experts to come up with a new way to assess player value. Clearly exploration through data mining.

(and a propos Mike’s comment above, why 538 and Netflix does well, it seems as though it is something about the difference between regression analysis and Singular Value Decomposition/factor analysis; but that requires more explanation)

But my problems are theoretical, and here I enlist Hahn and Tetlock’s definitive Information Markets: A New Way of Making Decisions. Which for a theoretical basis starts with (on p2) “Why do information markets work as well as they do?” And then references….The Wisdom of Crowds. And then moves on to design. And Surowiecki’s theoretical answer?

“At heart, the answer rests on a mathematical truism. If you ask a large enough group of diverse, independent people to make a prediction or estimate a probability, and then average those estimates, the errors each of them makes in coming up with an answer will cancel themselves out. Each person’s guess, you might say, has two components: information and error. Subtract the error, and you’re left with information…With most things the average is mediocrity. With decision making, it’s often excellence. You could say it’s as if we’ve been programmed to be collectively smart” (p10-11).

Not really obvious at all. There is no answer why a market metaphor would result in something better than experts. But we have the technology to do it, and it seems experimentally to work, and in web 2.0 we can get users to do this all for free! And so screw it – off with the design team and on with the user testing.

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Aggregation aggravation

Apr 22, ’09 9:56 AM

It seems to me that one of the fundamental advances and problems with web 2.0 is that it poses expertise against aggregation. The ‘old’ system (and here I would say that these are overlapping, not coterminous ways of doing things) is one of expert reviews, or critics. You want to know what movie to see, so you ask Roger Ebert (though his recent review and ongoing defense of Nicolas Cage’s Knowing strikes me as bizarre). If you want to know what music to listen to, you turn to Sasha Frere-Jones. For consumer goods, Consumer’s Guide. For electronics, David Pogue. And so on.

The point is fractal, incidentally. In this ‘old’ system, for policy advice you would call on sociological experts (naturally, though maybe other lesser social scientific experts if you’re interested in worse advice). In organizations, you would look for marketing advice from your marketing division, operations from operations, finance from finance. Obviously the more general the point I make the more fault you can find with it. And you would be right. But bear with me for a moment.

The ‘new’ system rests on a Wisdom of Crowds knowledge. That is, if you take a bunch of people and ask them their opinions, you can get a better fix on uncertain knowledge than you can with a small number of experts. Now, Surowiecki himself is not this simple: at minimum one must overcome problems of cognition, coordination, and cooperation. But this said, proponents of this kind of system point to rather stark indicators of success. Google’s PageRank (though I find the idea that they use 500 million variables and 2 billion terms absurd); Yelp; the Iowa Electronic Markets; Metacritic. And in the more general point, we see a substitution of ‘market’/crowdsourcing/datamining as a substitution for design, marketing, strategy. Here I mean the A/B testing ad absurdium as a substitute for design. Data-mining as a substitute for marketing. Quantitative finance as a substitute for market forecasting.

This whole edifice actually rests on a kind of efficient markets hypothesis, or more specifically a Friedrich Hayek-type consolidation of ‘adverse’ knowledge (meaning, in this context, private knowledge) via a market mechanism. While Hayek wanted to argue that market-based societies are better than centrally-planned societies, his work has become the intellectual touchstone of all things information market. And really that’s what it comes down to. Crowd-sourcing: a replacement of expertise with market.

However, there are some things to think about here that make this ‘new’ system quite problematic. And I ain’t sayin’ so just because I’m an expert (after all, the policy people really don’t come talking to sociologists, despite my preferences). There are one specific and one theoretical.

The first specific is that some people are just crazy, and aside from creating a tail-end of a distribution curve, it’s not at all clear what these folks contribute to the crowd. Old but still hilarious is Andy Baio’s Amazon Knee-jerk Contrarian Game. Personally, I like the ratings game at Yelp, an often-loved but massively crowd-sourced guide. Take, for instance, the Museum of Modern Art in NYC (i.e., the, or one of the, best modern art museum in the US and the world):

Why 1 star? Its just a horrible place to visit never ever again, screw this contemporary art thing, the exhibits they had going on were……… yeah no way to describe the sheer disappointment in the place. The place is designed to shock and awe you, all it did was bore me.
and
Most of the exhibits at MoMA are just random objects or B.S. paintings–hardly classifiable as art.
I could just go down to my garage or get a toddler to paint on a canvas to receive the MoMA experience. No crowds or superinflated entrance fees there, either.
and
I was so jazzed to go there. Many people I know raved about it.
All I came away with from this place was one word: Overrated.
Quality Modern Art is subjective. In my mind, for the hype this place gets is unwarranted. So sad…

So how do these reviews contribute to overall ratings systems? More broadly, what if the feedback/view/idea/opinion from your customers is just wrong? In 2.0 way of thinking about things, this is like saying that a market price is incorrect – it is axiomatically impossible, barring something wrong with the system (an information problem being the first culprit). And there is no ‘expert’ to say otherwise.

More theoretically, it has never really be adequately explained why a ‘market-like’ information crowd-sourcing should work. I understand why markets might produce a price that incorporates most public and private information about a commodity. But the widespread substitution of expertise with data mining and crowd-sourcing is a market metaphor more than a market. Why should a metaphor work? This is at the heart of someone like Daniel Davies’ criticism. And I get that sometimes aggregation does work. But there’s no good reason why.

My own feeling is that, using March’s metaphor of ‘exploitation’ and ‘exploration’ (where the first is the plumbing of existing knowledge/arenas, and the second is the seeking out of new opportunities), aggregation mechanisms are better at exploitation than exploration. They do better with existing standards of knowledge, of tastes, of commodities, than they do with something that is new. You know, Blue Ocean and such. I think there are better solutions for a 2.0 world that combine expertise and aggregation (for instance, Five Thirty-Eight‘s work on the 2008 elections that combined data mongering with theoretically-driven and field-visit-driven analysis). But this post is already too long.

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