Comment of the day comes from Chris:

The person most willing to take on risk is the one unaware he is doing so. He charges no risk premium…

The resulting market equilibrium is that the guy who is unaware of the risk ends up loaded with it. Then the music stops.

This is possibly a very beautiful and elegant explanation for the extreme profitability of investment banks. They charge their clients a lot of money to take risk off their hands, and then they transformed that risk, using sophisticated financial engineering, into instruments which didn’t, on their face, look risky at all, and which could easily be sold to risk-averse investors. Bingo, massive profits.

Financial complexity and innovation, on this view, are essentially tools of obfuscation. And it’s easy to hide risks when risk-averse investors want debt-like products which retain their face value: such instruments tend to have very low volatility, and so look and feel as though they’re low-risk, even if they’re full to bursting with enormous amounts of tail risk. The answer, as I’ve said many times in the past, is for risk-averse investors to be willing to take a small amount of explicit market risk, and to move towards safe equities (utilities and the like) and away from debt. Because if they go to an investment bank asking for safety, they’re likely to just get hidden risk in return.

Eleanor Laise has the encouraging news this morning that Deutsche Bank is planning to launch a money-market fund whose shares fluctuate in value, rather than being artificially pegged at $1.

On the face of it, this is a very good idea. Money-market funds are low-risk instruments, but that one phrase hides many different possible meanings, which get unhelpfully elided in the minds of investors. Moving to what’s known as a “floating NAV” (the net asset value goes up and down over the course of each trading day) helps to make some of those distinctions explicit.

Most people intuitively think that “low-risk” means “you can’t lose much money”. In finance, however, “low risk” can also mean “there’s a very low probability that you’ll lose any money at all”. And the problem with $1 money-market funds is that if they “break the buck”, then all hell breaks loose, and investors can end up waiting months to get their money back. It’s classic tail risk.

Wall Street is good at massaging risk in this way: taking risk and shoving it off into the tails. Most triple-A-rated structured products were like that: part of the reason that they offered a big yield pickup was by effectively maximizing the loss given default in the (perceived unlikely) event that a default did occur. Of course, another huge problem with tail risk is that measuring it, ex ante, is pretty much impossible.

So I’m all in favor of a product which has small fluctuations in value every day, thereby helping to reduce the tail risk associated with putting a floor on the fund value.

There are good reasons not to go down this road, however, and if you look at section 8.1 of this report, you’ll find a lot of them. What’s more, there are bad reasons to go down this road, specifically the idea that it’s just nimble-footed regulatory arbitrage:

In a letter to the SEC this week, Deutsche Bank suggested that floating NAV funds have a starting price of $10 a share and that they don’t need to be subject to tighter money-fund rules recently proposed by the SEC.

Rolfe Winkler adds another wrinkle to all this, which is the whole idea of money-market funds being “cash equivalents”. I’m with FASB on this front, in believing that the whole concept of a “cash equivalent” is dangerous and unhelpful. There’s really no such thing as “cash”, beyond folding banknotes — and those literally come with a cost of carry. All other forms of cash carry some kind of counterparty, credit, or interest-rate risk. We should move to a world where those kind of small risks are embraced and understood, rather than being ignored by being lumped into the category of “cash equivalents”.

Whenever I write about banks’ rising Value-at-Risk, a bunch of commenters tells me that duh of course VaR is rising, because VaR is a function of volatility, and volatility has gone up. So here’s my question: can someone come up with a baseline VaR chart, for a hypothetical bank which had, say, a fixed $1 million investment in the S&P 500. What would its quarterly Value-at-Risk have looked like over the past couple of years?

Would the decrease in volatility this year have shown up as decreased VaR in say the second quarter? Or do the volatility calculations go back so far that only now are we losing the Great Moderation datapoints and using volatility numbers only from the era of increased volatility?

Armed with that kind of baseline chart, we’ll be able to tell much more easily, for any given bank, whether it’s actually increasing the size of its bets, or whether increased VaR is simply a statistical necessity given the recent history of volatility. Does such a chart exist?

Update: Phorgy comes through. All banks calculate VaR differently, but this is a really useful resource. Basically Var increased enormously in 2008, and after that slowed down sharply in 2009, possibly even dropping significantly. Which means, I think, that any significant increases in VaR in 2009 can’t be blamed on increased volatility.

Goldman Sachs bankers are generally smooth, urbane, and on-message. But these days they’re clearly flustered. Why else would Goldman president Gary Cohn say something as arrogant and tone-deaf as this to the NYT’s Jenny Anderson?

“Our risk appetite continues to grow year on year, quarter on quarter, as our balance sheet and liquidity continue to grow,” Mr. Cohn said.

This perfectly fits the Michael Kinsley definition of a gaffe — when a politician accidentally tells the truth. What Cohn should have said is exemplified by his colleague, CFO David Viniar, five paragraphs later:

“There are a few business units that are taking a little more risk. Most are taking less,” Mr. Viniar said.

But the cat’s out of the bag at this point — and even if Cohn hadn’t said it in as many words, Goldman’s soaring profits and VaR tell the story.

Goldman is a bank holding company now; it shouldn’t be able to thumb its nose at its new regulators in this manner. But it will clearly continue to do so unless and until one of those regulators takes a deep breath and cracks down on all this risk-taking and increased leverage. So, who wants to be the regulator who went up against Goldman?

Paul Wilmott has words of wisdom for anybody in the financial-services industry who’s putting a model together:

At every stage of valuation and model development you must be asking questions about risk and robustness. It is dangerous to come up with some fancy model and only afterwards start asking questions about model error. Anyone who has ever calibrated a model knows that the methods used to mitigate model risk almost come as an afterthought, and are totally inconsistent with the original model. This need not be the case.

The problem is that developing a model is the sort of thing which (a) quants are trained to do, and (b) can, eventually, make money. While mitigating model risk is a very recondite field which very few people have any expertise with; what’s more, it doesn’t really make money in and of itself. Where will all the model-risk modellers come from?

Algonaut asks whether the Financial Services Oversight Council will have a direct line to banks’ chief risk officers; I’m sure the answer is yes. But I also think that won’t be enough. What I’d love to see — and this could be put in place directly by the major banks, without the need for any legislation at all — would be a regular formal meeting of all the big banks’ chief risk officers, where they can talk about all the systemic risks they’re worried about which require coordinated response. Does anything like that exist? Is there some way in which the FSOC or the Fed could use its moral suasion to make it happen?

Update: It turns out that the IIF has a Markets Monitoring Group, chaired by Jacques de Larosière, which meets 2-3 times a year with the aim of “bringing together observations and assessments of various developments to build a systemic picture of current risks and their potential negative impacts and seeking to mitigate those risks by encouraging member firms to take the Group’s findings into account in their risk management and collaborating closely with the official sector”. (From page 108 of this document.) Chances of it doing any good at all? Very slim, I’d say, but then again I’m biased against the IIF so I’ll admit I’m not an impartial observer.

The first sukuk (Islamic bond) defaults have arrived, and no one has a clue how they’re going to shake out. Which might actually be a feature rather than a bug, going forwards.

Bondholders often have a large amount of complacency derived from the fact that an enormous amount of equity needs to be wiped out before they take any hit at all. And that complacency does the system no favors in the long term. If capital structures get muddied a little, and debt takes on more equity-like uncertainty — as seems to be the case in the sukuk market — then maybe investors will be more assiduous about examining underlying risks, rather than relying on capital structures to protect them.

Gillian Tett was just in the office to talk about her new book; I interviewed her for Reuters TV, and the results should be up soon. But we got to chatting afterwards, and she made a great point which we didn’t cover in the more formal interview and which she says she would have liked to have put in her book. But since it’s not there, I can at least put it on YouTube. She talks about the Bistro deal (see Jesse for background on that), and how it can be seen as a metaphor for the financial system more generally:

The point is similar to the one I made in my speech to the regional bond dealers: we were far too worried about risk, and not nearly worried enough about safety. And really it was the insatiable demand for safety in general, and triple-A risk in particular, which caused this financial crisis.

I had a short chat with Nassim Taleb this morning about his new paper with Charles Tapiero, entitled “Too Big to Fail, Hidden Risks, and the Fallacy of Large Institutions”.

There’s a great deal of mathematics in the paper, which is full of equations and greek letters, but the gist of it is explained in pretty plain English:

Societe Generale lost close to $7 Billions dollars, around $6 Billions of which came mostly from the liquidations costs of the (hidden) positions of Jerome Kerviel, a rogue trader, in amounts around $65 Billions (mostly in equity indices). The liquidation caused the collapse of world markets by close to 12%. The losses of $7 Billion did not arise from the risks but from the loss aversion and the fact that costs rise disproportionately to the size of the bank…

Consider the following two idealized situations.

Situation 1: there are 10 banks with a possible rogue trader hiding 6.5 billions, and probability p for such an event for every bank over one year. The liquidation costs for $6.5 billion are negligible. There are expected to be 10 p such events but with total costs of no major consequence.

Situation 2: One large bank 10 times the size, similar to the more efficient Société Génerale, with the same probability p, a larger hidden position of $65 billion. It is expected that there will be p such events, but with $6.5 losses per event. Total expected losses are p $6.5 per time unit – lumpier but deeper and with a worse expectation.

In other words, small mistakes we can live with. Large mistakes we can’t, because when a mistake the size of Kerviel’s is unwound, the costs are enormous — not only to SocGen, which lost upwards of $6 billion, but also to all shareholders globally, who saw the value of their holdings marked down by trillions of dollars thanks to the effects of SocGen’s enormous and chaotic forced unwind.

The lessons here are broader, and apply to the practice of M&A more generally: when industries consolidate, there might well be economies of scale — but at the same time tail risks increase. What happens when a massive amount of technology outsourcing is consolidated in Bangalore, or computer-chip manufacture is consolidated in Taiwan? Efficiency rises — but so does the risk that one disastrous event could have massive systemic consequences.

The solution for banks is relatively simple: just put a cap on their size. (I’ve been suggesting $300 billion.) What’s the solution for other industries, which also naturally tend to consolidate and cluster? I’m not sure, but in an increasingly interconnected and just-in-time world, the risks are greater than ever.

Update: A couple of good comments from dsquared; the first points out that the paper ignores problems of correlation, which is true. But as Rick Bookstaber is more than happy to point out (and Taleb is no fan of Bookstaber), correlations tend to pop up in the most unlikely places, and in general they just make everything more dangerous — not only the systemic risk of lots of small players failing at once, but also the systemic risk associated with one large failure. So add in correlations to Taleb’s model and I think it only becomes scarier.

Dsquared then asks whether we really want to move to a world of “Fewer SocGens, More Barings”. My memories of the systemic implications of the Barings collapse are hazy (maybe John Gapper or even Nick Denton can help out here), but I think the answer might well be yes: while the Barings collapse was bad for Barings, it didn’t have the kind of negative externalities that we saw with Kerviel. But I might be wrong on that front.

Malcom Gladwell kicked off this morning’s New Yorker summit with a talk about the causes of the financial crisis in general, and of the collapse of Bear Stearns in particular, and started provocatively, by saying that if his diagnosis of the problem is correct, then really “there aren’t any solutions”.

Gladwell’s diagnosis is simple: massive amounts of overconfidence, as revealed by its two most common symptoms, miscalibration and the illusion of control. Both of which can be seen in spades in the person of Jimmy Cayne, whose interviews with William Cohan for House of Cards show a man who’s really very deluded about what Cohan, and Cohan’s readers, are going to think of him.

More generally, said Gladwell,

What’s going on on Wall Street isn’t the result of experts failing to act as experts: it’s the result of experts acting exactly like experts act. It’s not a result of incompetence, it’s a result of overconfidence.

When we look for evidence of miscalibration in people, he said, we find it overwhelmingly in experts. We find it when people are in conditions of great stress and complexity and competitiveness. And we find it overwhelmingly with older, more experienced people, doing difficult things which they feel very strongly about.

Jimmy Cayne, said Gladwell, is the picture of overconfidence — and he’s quite typical when it comes to heads of Wall Street banks. And so, Gladwell concluded:

Our goal is not to enhance the expertise on Wall Street. Expertise they have in spades. Our goal is to rein in the expertise on Wall Street. Wall Street needs to be slower, less competitive, and a lot more boring.

This is undoubtedly true — the difficult thing, of course, is how to legislate it, in a world where banks are falling over themselves to repay TARP funds and start taking on lots of risk again. Here’s Matthew Richardson and Nouriel Roubini write in the WSJ this morning:

Consider also recent bank risk-taking. The media has recently reported that Citigroup and Bank of America were buying up some of the AAA-tranches of nonprime mortgage-backed securities. Didn’t the government provide insurance on portfolios of $300 billion and $118 billion on the very same stuff for Citi and BofA this past year? These securities are at the heart of the financial crisis and the core of the PPIP. If true, this is egregious behavior — and it’s incredible that there are no restrictions against it.

But if there were restrictions against this behavior in particular, the same banks, or other banks, would find other ways to chase risk, just because they’re so confident that they can make billions of dollars — and get themselves out of their present hole — by doing so. They might even be right: 95% of the time, they probably are right. But that’s the Rubin trade: it works until it doesn’t. And although it’s the easy solution to the problem, it’s also a very worrying solution to the problem, because it just sets up yet another inevitable meltdown at some unknown point in the future.