Alchemy of Finance

I was reading George Soros' book, the Alchemy of Finance, and was impressed by the fact that it has a Foreward to the second edition, a foreward to the First Edition, a new Preface, and a new Introduction. That's a lot of throat clearing.

Getting to his big insight, he posits to key 2 assumptions to reflexivity:
1) markets are biased in one direction or the other
2) markets can influence what they predict

Now, reflexivity is Soros's Big Idea, but I find it rather unexciting. Point #1 basically says markets are unbiased. Unless one can identify the characteristics of an upward bias, as in contrast to a downward bias, that is just a description of asset price fluctuations. That an efficient market researcher would say the asset price has a return equal to the risk free rate plus white noise, is observationally equivalent.

Many critics of efficient markets point to price changes as evidence this theory does not work. Only if one is offering a theory on the particulars of a bubble ex ante, without hindsight. Otherwise, its just another lament on our inability to predict price declines.

Observation #2 is true enough, just think about asset prices falling, leaving to insolvent banks, which creates a multiplier effect. But many models have that mechanism, where a crisis in confidence create self-fulfilling implosions. I think Soros' own experience pushing down the pound during the 1992 European Union currency crisis makes him think this is a bit more radical than it sounds. There are 'bear raids', and these happen, but they usually happen only when there is fundamental weakness. That is, Soros selling the pound in 1992, or John Paulson selling mortgages in 2007, would not have worked if these assets were not also inherently overvalued at that time. I think he gives his correct calls too much credit in creating their own success, as opposed to 'merely' forecasting them.

So, the latter observation could be interesting, but his mechanism for how speculators can create what they predict needs more structure. It's plausible, and surely every price bubble has its share of enthusiastic bulls on the way up and bears on the way down. But it is not clear to what degree they are conspicuous statistical correlates irrelevant to the process.

Lots of really smart people have pet Big Ideas. These are usually pretty lame. Of course, it's a high standard, a Big Idea, as there aren't a lot of new, true and important ideas out there.

Obama Might Allow GM to go Bankrupt

Great news. It would be nice to actually see a big company fail. Currently, GM bonds trade at an average price of 18 cents on the dollar. This would not shock financial markets. Anyone lending to them already has taken a big hit. The stock trades at a value of $1.7B, on $91B in assets--option value. Implied vols are around 220%, the short rebate is about -87% (you pay 87% annually on the proceeds generated from a short sale).

Thus, it's already dead. Bankruptcy would not 'disrupt' the firm, it would clarify the situation.

AIG Trader Writes Letter

Jake DeSantis explaining why he feels entitled to a $740K bonus (after tax!) rings a bit hollow. This article takes it apart pretty well. Basically he tells DeSantis:

1) There are only 400 employees in the AIGFP, with two offices. The statement you knew nothing rings hollow, because with that much money flying around, people talk about how it was made ($3.5B in last 7 years doled out to those 400 employees).
2) If you did know nothing, there is no reason to pay you $1MM to unwind these complex deals, which is supposedly why you are getting the big bonus.
3) You analogize that your plumbing work was ruined by an electrician that burned the house down. The plumber should still get paid. Not if they work for the same company.

I wish the government just let them fail, and we could avoid this. A capitalist can't whine about government messing with the free market when he is getting a bail out. Further, the AIG contagion effect is based on a domino theory that I do not buy. If you take out a bookie, don't be scared by notional obligations because the cancel out.

Is the Market Better than Regulation?

Someone asked if the market also would fail Geithner's objectives for new regulations. Surely not, if we define 'to serve, protect and reward' sufficiently. But the key point is regulation is rarely effective at what it supposedly does, just think about NYSE floor traders who screwed investors for years via their monopoly control of stock market trading for decades, and the lack of competition on commission until the 1970's, all while there were these 1930's era regulations that supposedly protect the investor (the SEC acts of 1934 and 1941). Public regulation enhances the ability of insiders to fleece the public because that's what happens to regulation, insiders use the regulations as barriers to entry, and write them for that purpose. Rahm Emmanuel types, the kind who make $13MM in 3 years while out of government, make regulation work for them. Those who merely try to innovate and compete, are an annoyance for the elites who hypocritically always talk about helping the poor stiff while making sure they are lining up patronage jobs for their cronies. Fannie Mae and Freddie Mac made a fortune for political hacks for decades, always for the pretext of helping the poor and historically under served.

The Market is filled with self interested people who have to convince people their service is actually better than its alternatives and is worth the cost. Regulation is filled with self interested people who simply tell people what to do. The most uncompetitive market is nothing compared to a legal mandate.

The chief difference between the market and regulation is that under the former a man pursues his own advantage openly, frankly and honestly, whereas under the latter he does so hypocritically and under false pretenses.

All this hullabaloo about mortgages ignores the fact that this mistake will not made again in our lifetimes. It will be a different mistake. Thus, we are now hiring thousands, and writing pages of regulations, specifically targeting spilled milk. This is just a waste of time.

Geithner Calls for Better Regulation

A bold stand, up there with a call for better health care and education.
Timmy's spreech contained this nugget:

To address this [crisis] will require comprehensive reform. Not modest repairs at the margin, but new rules of the game. The new rules must be simpler and more effectively enforced and produce a more stable system, that protects consumers and investors, that rewards innovation and that is able to adapt and evolve with changes in the financial market.

When was the last time government implemented regulations that met these criteria?

Is 'Experienced Mortgage Expert' an Oxymoron?

This week's Treasury plan notes 5 criteria for new investors in the PPIF, including this one:

2) Demonstrated experience investing in Elgible Assets, including through[sic] performance track records

Now, if there were investors with experience in mortgage backed securities (the Elgible Assets) with a thorough track record, what are the odds they were drinking the Kool-Aid about mortgage innovations? No money down, 'outdated' underwriting criteria, record increases in housing prices, etc., and nothing sounded an alarm. These are the guys we want to save us?

Most of us can comfort ourselves that we weren't in the business of looking at mortgages. The mortgage crisis caught us by surprise but we had no reason to really examine mortgages or housing price data carefully, other than to note anecdotally stories about housing prices. I think it is wrong to assume, with hindsight, this was an easy bubble to call. More likely, savvy people looking at this figured something did not seem right, so merely choose a different field because in general it does not pay well to be short, either as an investor, or attitudinally within an long-oriented organization or group. I imagine most who thoughtfully examined the trends merely weren't in the business of buying MBS as opposed to shorting them. But if this was your full time job, you have demonstrated a very large error in your analytics, because you were almost certainly a bull throughout. Surely a small portion got out, or went short, but of those who match the other Treasury Criteria (eg, you have $10B under management, and can fill out paperwork by April 10) and whose stock rose dramatically anticipating a huge government subsidy (eg, FIG, BKCC, JNS, EPHC, BX), they were the guys who screwed up!

Like a Sovietologist circa 1990, a Y2K expert in 2001, or an Internet Fund in 2003, there are times when your profession showed a complete lack of ability to capture the Most Important Thing in the subject of their expertise. If you were not considered a screwball renegade before events made things obvious, you are a fool, fraud or dup whose experience is damning. An expert would more likely be someone in a related asset class, not the class in question.

Not the Time to Own Good Junk

Currently, high yield bonds (aka junk bonds) have spreads of around 1200 basis points to Treasuries, though that is a rather unfair benchmark given that AA rated bonds trade at about 300 basis points to Treasuries. The graph is from Markit's B-rated bond index. Note spreads are 17%, which is insane. In today's crazy markets, everything is suspect.

But these securities trade with very large bid-ask spreads, many at 10 points. With a median price of around 68, that's a 15% loss if you buy Monday and sell Tuesday. This kind of bid-ask spread makes relative value trading impossible, because it is simply too expensive to go long and short a large number of securities and make money off any edge in forecasting future performance (even ignoring the difficulties of shorting many HYBs). Any reasonable relative value edge simply cannot overcome the costs here, because while if you pick and choose one bond, you can be patient, if you have to go long 30 and short 30, you will have to cross that spread a lot.

The only reason to be long a high yield bond is thus either 1) if they have a really good feeling about one particular company or 2) it is part of a basket of long HY Bonds. In the second case, going long HYBs as a sector, it is probably cheaper to simply buy a junk bond ETF (eg, JNK or HYG). Any edge in relative value would probably be eaten up in the idiosyncratic costs of overhead, bonus, and transaction costs. The only ones putting relative prices in place are those taking one-off bets, or the effect of tilts with large long-only portfolios. But here's a problem. If you are long a portfolio of HYBs, or a particular HYB, you are bullish. If you are bullish, you are expecting spreads to contract, prices to rise. The crappiest HYBs will rise faster than the better ones, because they are most distressed. In 2003, the best performing HYBs were the worst as measured by most objective models (eg, Merton Model, defprob). Similarly, one could have noted that in 2003 those bonds with the lowest prices rose the most proportionately--they have really high betas. This was a situation I was monitoring very closely at the time because I was contemplating a HYB strategy (luckily for me, I didn't implement it for reasons outside my control).

So, currently, as spreads are at a historic max, I think it would be imprudent to be long the better credits. Only in good times or the beginning of a recession, is it good to be long the cream of the crop.

I Love My Commenters

... but only in the way I love hot dogs. Ann Althouse recently got engaged to one of her longtime commenters.

Shiller Did Not Call the Bubble

In Shiller's Irrational Exubrance, 2nd edition, there is a section on the housing prices, and a graph showing housing prices rising. But there are literally pages of qualifications, about how this price rise cannot continue, but not much about housing prices falling much in nominal terms. I was struck by this graph from a blog that seems spot on. Unfortunately, the book had a picture that did not have anything after 2004 (see below), the prices just go up, so there's a healthy bit of photoshopping going on. I've seen him introduced various times as calling the housing bubble. If you actually read the book, you read about how “In cities where prices have gotten so high that many people cannot afford to live there, the price increases may start to slowdown, and then to fall. At the same time, it is likely the boom will continue for quite a while in other cities [page 206].” That's economese for prices are expected to fluctuate.

Bad Assumption More Than Bad Intentions

I listened to a bloggingheads by Bill Cohen, a former investment banker who wrote House of Cards. He seems to blame this on hubris, not understanding risk, taking too much risk. All true, but that's with hindsight, and there is little one can learn from that diagnosis because I doubt hubris, ignorance, and short-sightedness are in any company's mission statement. Many commentators note that there was significant 'moral hazard' caused by short term bonuses, as basically bankers were putting on trades that had zero or negative net present value, but paid a positive return over long periods. Think of a high yield bond that pays +1, +1, +1, +1, +1, -5. If you get in on that early, and lever up, by the time it tanks you have banked several healthy bonuses and shareholders and taxpayers are on the hook.

The problem with this line of thinking is that I have worked in banks and hedge funds, and never have I known those making the ultimate decision to ignore the over-the-cycle present value. They are often wrong, but even if a lower-level guy is trying to game the system this way, when the strategy or trade is pitched and discussed, it is over the cycle. When every bank is in on the same trade, it's not like everyone is being duped, rather, its a really subtle, powerful intellectual error. Some people were cynical opportunists--those pushing NINJA loans, turning the knob to 11--but generally I think people were just sincerely incorrect.

Thus, I do not see moral hazard as the main driver of the disastrous risks taken, rather, a collective, economy-wide underappreciation of the credit risk in residential mortgages. You had 200 full time regulators looking at Freddie Mac and Fannie Mae who never wrote about credit risk prior to 2007, and regulators had no big bonuses. Further, most of the investment banks retained significant exposure to the AAA rated pieces, so they weren't playing those they sold to--they believed it. It wasn't bad intentions, it was an honest error that seemed to hit almost everyone.

Kids think everything happens because of will. Bullies bully, storms rain, and rocks fall because they are like cartoons where everything is alive and has intentions. Unfortunately, bad things are usually the result of ignorance, though with hindsight every bubble has hubris almost by definition.

Prospect Theory Explains Everything, Nothing

I was reading this quote from Kahneman and Tversky, and found this part very revealing:

Low probabilities, however, are overweighted, and very low probabilities are either overweighted quite grossly or neglected altogether, making the decision weights highly unstable in that region.[page 8, Choices, Values and Frames]

Given this definition, I don't see why this theory is considered useful. If a disaster happens that seems to cause a lot of angst, one can say it was underweighted. If someone is paying a lot for insurance that seems to generate a positive return, one can say people are overestimating this risk. Ex post, the theory explains everything, and nothing. Looking a small probability event before the fact, it predicts everything, and nothing.

Geithner's Plan Not Bad

I really disliked Tim Geithner's 'stress test'. Taking over companies that could be insolvent in the future is a horrible precedent, setting a vague standard for solvency, because if you are insolvent in the future under the government's opinion, you are insolvent today. Thus, insolvency is not the exit criteria, rather one has to plan for future 'future' insolvency as defined by the government. This is a political football, meaning, it's all lobbying and appeasing regulators to maintain market power and beat down new entrants. I noted in his WSJ editorial, Geithner mentioned that people will be more confident in banks after having passed this vetting process, and that may have been the motivation, but passing a politically infused stress test is not reassuring.

On the other hand, his new plan is to basically match fund private investors in buying distressed securities, with over $500B set aside. This mitigates poor incentives, because they are not providing the first loss or senior piece, just sharing parri-passu. They are not giving purchasers leverage, even. An investor who thinks it is a bad risk-return investment will not be incented to invest, because this government involvement does not change the payoff space. This is just adding liquidity, and is not a subsidy, because the expected value of this is zero if we assume market prices are expected values of future payoffs. The cost is actually negative if we think the markets are in a panic, but costs are quite high if we think this is the mid point in a massive financial cataclysm.

Thus, Krugman thinks this is a huge subsidy because he thinks market prices are way too high for CMBS and RMBS securities, though I think this is really because he believes anything that would justify greater government control of economic activity. He has presented absolutely zero data on the prices and corresponding historical loss curves for the various vintage-product types (eg, Alt-A mortgages, 2006, average current price and losses). He doesn't have the data, he wouldn't know how to set it up. It's the kind of detail he is ignorant about but does not think is important. Details matter. Subprime, Alt-A, conforming,vintage, seasoning all matter. AAA 2007 subprime tranches trades at around 25% via the Markit ABX index. Is that really reasonable? What are the losses on the collateral? He just wants to take over the banks asap because asymmetries and imperfect information prove markets are inefficient (heh).

I found 94 subprime mortgage tranches, and some referred to the same underlying mortgage pool. You can find these by going to the Markit ABX index page, looking at the constituents, and see they refer to 20 tranches that vary by seniority for the various grades (eg, CWALT 2007-21CB M Mtge, BSABS 2007-AQ1 A1) . Anyway, the average cumulative 90+ delinquency is about 25%. That's pretty high historically, but after seasoning 21 months, this means a conservative estimate of total 90+ delinquency is going to be around 50%, and losses on those delinquencies no more than 50% (housing prices did not fall more than 50% in most places, on average). Thats for all of subprime in 2007. The market price for AAA rated assets (better than average) is a mere 25 cents on the dollar, suggesting the average subprime mortgage is priced below that, say 10 cents on the dollar. This is way too low.

I suspect most banks will be unwilling to sell off assets at market prices, because the market prices are so low. In that case the plan 'fails', but it would also then cost us nothing, and in the meantime not screw anything up (in contrast to the stress test).

Economic Inference With Little Data

Interest rates fell sharply last week as news came out about the Fed's new program of buying long term bonds. 10 year yields went from 3.0% to 2.5% last Wednesday.

Bonds are a funny asset. Looking at a time series of long term interest rates from 1950, we see a simple pattern: it rises to 1980, and falls to today. How the heck do you extrapolate from that?! In a sense, it looks like we have two observations, the increasing regime from 1950 to 1980, and then a decreasing regime from 1980. Under that interpretation, you don't really have enough data to really draw any conclusions.

I've noted many bond strategies that people simulate generate nice Sharpe ratios if they are implicitly long, going back 30 years seems like a large data set. Clearly, this then begs the bigger question, about whether the secular decline in interest rates will continue. Thus, like housing derivatives, many sophisticated bond strategies can make mistaken assumptions, but even a non-quant can ask the simple question: what is the effect of the sample time trend on your trading strategy?

I would just say that given our government is bent on doing everything possible to inflate asset prices again--government borrowing and spending, monetary expansion--it seems likely that inflation, and thus interest rates, will rise. We are like people who drink hard alcohol to get drunk, where the first sensation of inebriation is well past the point of moderation. Plus, there's a lower bound on interest rates, and we are pretty close to it.

Experimenting with Classes

I read the following story, probably apocryphal:

An economics professor at Texas Tech said he had never failed a single student before but had, once, failed an entire class.

The class had insisted that socialism worked and that no one would be poor and no one would be rich, a great equalizer. The professor then said, "OK, we will have an experiment in this class on socialism."

All grades would be averaged and everyone would receive the same grade so no one would fail and no one would receive an A. After the first test the grades were averaged and everyone got a B. The students who studied hard were upset and the students who studied little were happy.

But, as the second test rolled around, the students who studied little had studied even less and the ones who studied hard decided that since they could not make an A, they studied less. The second Test average was a D! No one was happy.

When the 3rd test rolled around the average was an F.

Students remember very little from specific classes. Even though this experiment is obviously going to generate horrible incentives, the lesson learned probably would be more long lasting and profound than any mastery of problem sets with indifference curves and linear programming.

2009 NCAA Wrestling Results

The big result was that dominating Brent Metcalf was defeated by Darion Caldwell in the finals at 147 pounds. Caldwell had pinned Metcalf back in 2007 in a freak move called a 'spladle', and it is really fun to watch on YouTube. But this was considered a lucky accident. Metcalf went on to win 69 matches in a row, including a national championship in 2008, and a dominating performance in the qualifying tournament. Caldwell was still very good, but no one thought he could beat Metcalf again. In the finals Caldwell was clearly the better athlete, with greater natural quickness and flexibility. He threw a headlock, and actually got a takedown out of it, a move that clearly shows no fear (usually throwing a headlock against a really good wrestler opens one up to a counter, it's a high risk, high reward move). It was a shock, and Caldwell won Outstanding wrestler of the tournament. See match here.

Unfortunately, as much as I would have liked to cheer for Caldwell's greater ability, he was a classic 'poor sport'. He took extended injury time to catch his breath. He ran away at the end of the match and did a back flip. As Caldwell was celebrating, the TV announcer said 'he's got to get off the mat', as the announcer was clearly anxious about the fact that he was potentially going to ruin a great moment. We know you are happy, but winning a competition should not just be about you, because the competitor and his supporters are all there. To celebrate excessively assumes the competitor does not exist.


There was the case of Anthony Robles, a one-legged wrestler from Arizona, which is rather amazing. He was born without a leg, and so clearly has a disadvantage. On the other hand, he gets another 10-15 pounds of weight for his upper body. One would think this is insufficent, yet he placed 3rd in the NCAAs. That's not charity.

Then there was Paul Donahoe, who won the championship in 2007, but was dismissed from Nebraska because he was in some naked pics with another wrestler for some gay magazine (he's not gay himself). It sounds at first like homophobia, but I think the issue was that he was exposing himself while wearing school uniform. I think it's a reasonable request that a school require its athletes not to pose naked with school colors on, because its a PR nightmare. He went to Edinboro, and lost a close match in the finals.

How to Cature Rents Without Seeming To

In many cases, one has something of value, but it is considered impolitic to seize this value. Over on Offsetting Behaviour, Eric Crampton notes that bands face a quandry in that front row seats sell for $1000 for top bands, yet bands do not want to appear to charge this much. Trent Reznor of the band Nine Inch Nails, explains that in practice the ticketing agents have already made a deal with the scalpers to split the surplus without appearing like jerks by having high posted ticket prices. The band, meanwhile, negotiates with the ticketing agents, and this ticket agent revenue is factored in the negotiations. (He then goes on to note his particular band is willing to give up this money to get real crazed fans in the front row, a logical reason to let the front row keep the consumer surplus).

This method of capturing value without seeming to reminds me of how investment banks capture the value from initial public offerings (IPOs). The IPO game is basically a way for brokers to capture the one-day pop in IPO prices. IPO’s predictably generate 12% return on their first day of trading, and most IPO investors sell in the first couple of days (though, of course, their broker discourages this to little avail).

For the broker issuing the IPO, by giving these only to clients who pay extra commissions, that first-day return is all capturable. Generally, in 2001 a hedge fund might pay 0.1 cents a share for bare bones trading, and 3 cents a share for trading bundled with ‘research’ and ‘trade ideas’. Of course, this research is worthless on average and the hedge fund knows it, but it leads to getting on the IPO list. Thus, the investment bank capture the one-day pop via the implicit overcharge on commissions to get access to the IPO.

To summarize: the investment bank captures the 12% one-day spike in the IPO price via overpriced research sold to a fund, which is known worthless. This quid pro quo is needed because the equity issuing firm would not appreciate paying the broker an 8% fee plus giving them the benefit of the first-day pop. The hedge fund trades commission dollars for the one-day return from IPOs because it is a basically even trade, and generally helps the portfolio manager point to 'great trades' useful for narratives about their savvy investing prowess, whereas the commissions are spread like string beans on a kid's dinner plate.

There are lots of trades like this, and often, like in the IPO trade, a key to participating is to never acknowledge to anyone in the chain the blatant logic at work. That is, a hedge fund would never ask explicitly for this quid pro quo, or if one did, one would not get a positive response. One merely recognizes the game and then smoothly joins, asking about IPOs say a couple months after paying for 'research'. As disgraced former Illinois governor Blagojevich found out, the first rule of trading favors to avoid explicit payment schemes is never to say or write this is what you are doing. It is a feasible equilibrium because as a repeated game, one can punish cheaters.

Fama on Taleb

From French and Fama's website:

Q: It would be very enlightening if you would comment on the Nassim Nicholas Taleb ("The Black Swan") attack on the use of Gaussian (normal bell curve) mathematics as the foundation of finance. As you may know, Taleb is a fan of Mandelbrot, whose mathematics account for fat tails. He argues that the bell curve doesn't reflect reality. He is also quite critical of academics who teach modern portfolio theory because it is based on the assumption that returns are normally distributed. Doesn't all this imply that academics should start doing reality-based research?

EFF[Eugene Fama]: Half of my 1964 Ph.D. thesis is tests of market efficiency, and the other half is a detailed examination of the distribution of stock returns. Mandelbrot is right. The distribution is fat-tailed relative to the normal distribution. In other words, extreme returns occur much more often than would be expected if returns were normal.

There was lots of interest in this issue for about ten years. Then academics lost interest. The reason is that most of what we do in terms of portfolio theory and models of risk and expected return works for Mandelbrot's stable distribution class, as well as for the normal distribution (which is in fact a member of the stable class). For passive investors, none of this matters, beyond being aware that outlier returns are more common than would be expected if return distributions were normal.

Charles Murray at the AEI

Charles Murray was honored by the AEI last week, and gave a talk on happiness in the context of modern America. His talk hit on an interesting paradox of welfare programs aimed at the poor, that it negatively affects the satisfaction of life for those who are most likely to gain life satisfaction via non-vocational activities. Most liberals see faith as authoritarian delusions, and family and community needs as the responsibility of the government. That's not horrible if you have an great job and are good at it  because you can bask in the status from that job, but if you are merely a hard working mensch your path to a meaningful and satisfying life is diminished:

To become a source of deep satisfaction, a human activity has to meet some stringent requirements. It has to have been important (we don't get deep satisfaction from trivial things). You have to have put a lot of effort into it (hence the cliché "nothing worth having comes easily"). And you have to have been responsible for the consequences.

There aren't many activities in life that can satisfy those three requirements. Having been a good parent. That qualifies. A good marriage. That qualifies. Having been a good neighbor and good friend to those whose lives intersected with yours. That qualifies. And having been really good at something--good at something that drew the most from your abilities. That qualifies. Let me put it formally: If we ask what are the institutions through which human beings achieve deep satisfactions in life, the answer is that there are just four: family, community, vocation, and faith.
...
the sources of deep satisfactions are the same for janitors as for CEOs, and I also said that people needed to do important things with their lives. When the government takes the trouble out of being a spouse and parent, it doesn't affect the sources of deep satisfaction for the CEO. Rather, it makes life difficult for the janitor. A man who is holding down a menial job and thereby supporting a wife and children is doing something authentically important with his life. He should take deep satisfaction from that, and be praised by his community for doing so. Think of all the phrases we used to have for it: "He is a man who pulls his own weight." "He's a good provider." If that same man lives under a system that says that the children of the woman he sleeps with will be taken care of whether or not he contributes, then that status goes away. I am not describing some theoretical outcome. I am describing American neighborhoods where, once, working at a menial job to provide for his family made a man proud and gave him status in his community, and where now it doesn't. I could give a half dozen other examples. Taking the trouble out of the stuff of life strips people--already has stripped people--of major ways in which human beings look back on their lives and say, "I made a difference."

Just as you can't give someone respect, you can't give them security, shelter and clothing, without taking away much more. Sure one can imagine situations where a helping hand is appropriate--pathologies, temporary crises--but these are exceptions, perhaps one tenth of what the modern state addresses.

Retention Bonus in Cash?

AIG paid 22 people over $2MM each as retention bonuses, even though they worked in the Financial Products Division that basically sets the standard for bad investing. If you want a key employee to stay, your pay is in exchange for future services. If they have the option to leave right after the bonus, this is not a retention bonus, but rather, a bonus for performance, such as a percent of commissions or revenues generated.

Thus, it makes zero sense to pay someone cash as a retention bonus. You should pay them in restricted stock, or call it something else. As part of a unit that basically bankrupted the company, I do not see any reason why one should pay a premium for these people, because when a unit like that fails so massively, the option to cherry pick trades that made money and lobby for a piece of those profits is worthless. The Financial Products group is so worthless, such tendentious pleading should fall on deaf ears. Further, paying them cash makes no sense for shareholders. It seems like an "agency problem" is at work.

This just highlights the ability of corporate insiders to appropriate value from shareholders. I wouldn't give them a special tax, as a government agent I would just liquidate the company, unless they can pay back my investment immediately. The franchise value should go to zero, and debt holders may bear some losses. If this happens, perhaps insiders will not try this as much in the future, because capital providers would care about such things. In this market there are a lot of smart people, knowledgeable about derivatives and financial products, looking for work. The notional amounts are scary, but it is straightforward, and the current management is clearly not operating in 'good faith', and once you know that, you need to excise them asap. Breaking promises is warranted because basically this company is bankrupt, and employees are unsecured creditors. In the same way I think Ford and GM need to abrogate their old UAW contracts, AIG should abrogate million dollar cash retention bonuses. Both are not in the capital provider's best interest, and as these people need capital, it should present such firms with a choice: adjust your contracts or get in line with everyone else to pick over the company's assets.

Value at Risk, Credit Default Swaps, Copulas...Harvard MBAs!

In the ever expanding effort to get down to the root causes of this crisis, journalists are facing a very tough but exciting problem. Perhaps the solution is like an episode from 'House', where the patient is experiencing horrible symptoms, and at first the doctors think liver failure or cancer, but the real cause is a cat allergy combined with genetic inability to synthesize vitamin D from sunlight. The solution is obscure and highly specific. Wouldn't it be cool if the answer were like that to real important problems? We just have to add a parameter to capture leptokurtic deviations from the naive Gaussian assumption, and we can get back to talking about Britney's latest mental breakdown.

The latest is an attempt to blame this on the Harvard MBA program, because a disproportionate share of Harvard MBAs are in major financial positions...and even a a journalist knows that correlation is causation (except when talking about pathologies of the poor). Perhaps a follow up will isolate whether it is Harvard or the MBA degree as the prime mover, but clearly, pinning this on Harvard MBAs would not bother me. I say we humiliate them on a reality TV show, like the one where Paris Hilton tried to her hand at working class jobs.

The problem with all these highly specific accelerators is they neglect the fact that assuming housing prices would not fall was a necessary and sufficient mechanism for the explosion in credit to unworthy borrowers: if the collateral was not falling, it didn't matter the probability the borrower can afford the loan. This assumption was ubiquitous and understandable to everyone.

AIG Bonuses

A lot of outrage over $450MM in bonuses, but with 115,000 employees, that's only about 4k per employee. Some are contractual payouts from revenues, such as commissions. I don't see how you can stop this.

Now, for those managing people who generate revenues, or managing people who manage people, I agree that these people's bonuses might be inappropriate. But if your base salary is $100k plus x% of commissions, I don't that's excessive or problematic.

Closed End Fund Discounts

There are problems with using historical cost accounting, and the move to accounting based on market values seems at first glance to be more accurate. Market values change every day, and so they are not as prone to a particular tendentious bias, especially, the hope that bad asset will rebound in price even though everyone knows it is severely impaired.

Yet, as every critic of this crisis notes, the market is hardly perfect. The same market priced these same mortgages as if they had basically zero credit risk in 2006, is predicting massive future default rates. If one thinks that the marking to market gives the best assessments, then one can not really say that regulators, or anyone, failed pre 2007. The market suggested no risk, as implied by the market value, or spreads, of these instruments.

Currently, many closed-end funds with market-traded instruments trade at a substantial 20% discount. That is, you can trade there constituents, and they are worth 20% more than the entity that holds them. Above we see Nuveen's convertible bond portfolio (JPC), and this trades at a 20% discount to the value of its portfolio. Is it wise to therefore value these assets at their net asset value, or the value implied by the closed-end fund? Further, this is not specific to bond closed end funds, as closed end funds with stocks have similar discounts (see Adams Express, ADX). Market values, clearly, are not merely unbiased present valuations, because this discount varies over time. If the market has a 20% risk premium assigned to mortgage related products, is it optimal to impute this into book asset valuations?

The bottom line is that if one argues that the market should set book asset values, and thus risk parameters for a solvency exercise, this goes both ways. No one thinks that the market correctly priced mortgage risk in 2006, however, so what does one do?

Why We Make Mistakes

There are many books on 'behavioral economics', but Why We Make Mistakes by a journalist is a pretty good summary. Indeed, I was looking at Ariely's Predictably Irrational, and found this book much more succinct. Fun facts from the book:

• There is a 1 in 1 million chance of finding a gun in an airport check
• people don't remember names, as opposed to the jobs or families of a person
• 80% of calls to a corporate help desk are for lost passwords
• Simply changing pill colors from white to red and black makes them more distinctive
• People recall their specific grades in school with an upward bias
• Men report a median of 7 sex partners, women 4
• 84% of doctors thought others were biased by self interest, whereas only 16% thought they were biased by self interest
• The most common airplane accident is 'controlled flight into terrain', or flying a plane into the ground
• When asked to pick a movie viewed later, more choose highbrow movies; choosing movies now we choose lowbrow movies
• being first on the ballot adds about 3% to a candidates vote
• As something becomes familiar, the more we tend to notice it less
• We see things not as they are, but as they ought to be.
• Experts make mistakes expecting patterns that aren't there.
• Depressed people are realists, happy people are overconfident
• People learn more from summaries than from reading entire chapters
• A horse race handicapper does as well with 5 bits of information as having 10, 20, or 40, though his confidence increases with the number of information bits available
• Hope impedes adaptation. Someone with a potentially reversible colonostemy is more unhappy after 1 year than someone with a 1 year irreversible colonostemy.
• When you are trying to make judgments about complex systems, things that are easily observed are overweighted.
• Money does not improve efficiency of large organizations (ie, giving everyone more money).
• Money does increase the ability of individuals to withstand discomfort in tests.

Review of Taleb's The Black Swan

I wrote this a while ago, mainly based on posts I had done over at Mahalanobis, and posted it on my website. I figure I'd update it and put it out here where more people might see it, as the book in question is still quite popular.

Nassim Taleb is a former trader who wrote a textbook on option and market making, and then became more philosophical in his best seller Fooled by Randomness, and now in The Black Swan. His big idea is that sometimes, unexpecting things happen: countries dissolve into anarchy, wars start, unknown authors become famous. His secondary ideas are variations on this theme, that people, especially experts, are generally biased, overconfident, and rationalize past event so they appear deterministic. Stated baldly, these assertion are hardly novel but true enough, and one can argue about their relevance in various cases. As a highly popular presentation of ideas near to my interests and vocation, I think it is worth critically examining if there is anything to his particular contribution to the literature on cognitive biases or social failures. My conclusion, in short, is no.

Taleb’s style is to severely criticize experts and authorities--lots of 'morons', 'idiots', and 'fools' out there--while implying that both he and his reader or listener are exempt from their many biases. Reading someone deflating puffed-up egos, criticizing the insular world of academics, and suggesting the experts have a huge blind spot on something important, can be fun reading. But it has to be making points that are true if new, or important if true, and here he fails to deliver.

For someone advocating doubt and criticizing expert and 'regular' people’s overconfidence and arrogance, Taleb’s writings are filled with certainty, anger, and immodesty, having the Godelian impossibility of someone shouting 'I am the most humble!' Indeed, his current popularity based on prescience in forecasting recent events, and his emphasis that this proves him correct is exactly the kind of naive confirmation based on small samples that he argues is sloppy thinking. Consistency is not a hobgoblin in Taleb's mind.

While people are generally overconfident about their diving ability or common sense, does that same overconfidence lead people to underestimate the probability of market crashes, and thus the price of insurance (eg, put options?) The data suggest the opposite is true, that is, that people overpay for such improbabilities based on hope. Survey data on beliefs are not necessarily economically important, because markets elicit results not from unmotivated an ignorant masses, but from a highly motivated and informed subset. People willing to offer ‘a side’ to such a bet tend not to be biased, and also pad their bets with a considerable safety margin so that their errors are not catastrophic, which in practice means you obtain much lower odds for improbable events than what simple surveys would imply.

A major theme of Taleb is that models of uncertainty are too precise, and this thread has a long history. Taleb's sometime co-author Benoit Mandelbrot has been trying to sell the world on the big idea of fractals in finance for several decades. James Gleick’s Chaos outlined the essence of Benoit Mandelbrot’s fractals, which takes a simple few lines of inputs to create graphics of insane complexity yet also beautiful recursive symmetry, in many cases eerily similar to nature (eg, ferns, snowflakes). In dynamic systems, you have chaotic systems that are purely deterministic though sufficiently complex that they appear random. These systems have large jumps, or phase shifts, reminiscent of market crashes or sudden bankruptcies; they have butterfly effects where small changes produce big differences in outcomes. Mandelbrot and others have been trying to apply these ideas to financial markets for many decades now (since 1962!), and the effort has not gained any traction, in spite of many papers applying this concept (search skew or kurtosis in any financial journal and you will see many papers). Mandelbrot’s big idea in finance is that finance relies on a profoundly flawed assumption, mainly that market prices are normally distributed. Mandelbrot argues market prices have much fatter distributions described by Cauchy distributions, as evidenced by the high number of 5+ standard deviation moves in financial markets.

The result of these mistaken assumptions is to understate risk, according to Mandelbrot, and so overprice stocks and underprice options, and also understate the capital cushion financial institutions need to withstand market risk. Mandelbrot’s alternative approach is based on new parameters that would replace the mean and standard deviation. His first parameter is Alpha, derived from Pareto's Law, is an exponent that measures how wildly prices vary. It defines how fat the tails of the price change curve are. The second one, the H Coefficient, is an exponent that measures the dependence of price changes upon past changes. Unfortunately, Mandelbrot himself acknowledges in The Misbehavior of Markets that no two individuals calculate the same Alpha and H Coefficient when using the exact same historical data: there is no unique way to calculate these two parameters. Thus, using one method, you could derive Alpha and H coefficients that suggest a stock is risky, using another method you would reach the opposite conclusion. This flaw probably has some bearing on its lack of practitioner popularity.

Frank Knight, meanwhile, in his classic Risk, Uncertainty, and Profit in 1921, outlined the basic idea that it is uncertainty, in the form of non-quantifiable dispersion, that is at the root of profits. The basic idea is that risk, once quantified, is diversifiable, and thus becomes risk-free. If you know that your champagne bottle could burst while fermenting with probability p, that number becomes very manageable the larger your operation via the law of large numbers. Economists have been intrigued by this notion ever since, but by definition it is unquantifiable so when you write down a random process, it is no longer Knight-like, making it rather elusive. However, when we come up with uncertainty proxies, such as volatility (surely more volatile assets are generally more uncertain), leptokurtosis (asymmetric tails), or analyst or investor disagreement, the results do not have any obvious empirical implication beyond the fact that they exist. That is, assets with greater downside tail, or analyst disagreement, conditional upon gaussian volatility measures, are not predictive of future returns.

Taleb’s career as a talking head started in 1996 when, as the author of a niche derivatives text, his claim in Derivatives Strategy magazine that the new Value-at-Risk phenomenon was worse than useless made for great debate in risk management circles. I was leading a Value-at-Risk project at the time, so of course I found his criticisms of interest. JPMorgan had just introduced this method of aggregating risks in a highly popular practitioner brief. Their approach, RiskMetrics, outlined in detail the methods of estimating volatility when you had a portfolio of currencies, bonds, equities, and even options. Previously, financial books that contained bonds, currencies, equities, etc., each had little silos of risk reports, but this showed how they could be combined, basically by putting everything into a factor approach, in which every asset has a sensitivity to a factor, and every factor has a certain correlation and volatility. This was not new—factor analysis had been around for a while—but its clear application to a tangible problem was insightful, and created a lot of buzz.

Value-at-Risk was not a panacea, but it was an improvement (the only people who use the word 'panacea' are critics). Taleb’s criticisms of VAR then are similar to his criticisms now: that a metric is not flawless, and those who believe parametric applications of VAR are fools. In a trivial sense he is right, but in the case of VAR, or specific parametric statistics, or expectations in general, there are many users who understand that tools need to be supplemented by judgment, adjustments for the parochial realities of various asset classes with their various deviations from pure 'normality'. It is a cliché on the risk management lecture circuit that you need not just technical knowledge, but judgment, mainly by senior executives who don’t have any technical knowledge. Even in these stressed times, Taleb was dead wrong on VAR, in that in spite of his criticisms it is ubiquitous as a method for amalgamating short-term risks from different instruments into a single metric.

VaR is not useful for allocating capital, or estimating the cost of equity, but it is useful in keeping your traders honest. It allows one to measure risk given various assumptions, and like any model it is garbage in-garbage out. The recent financial crisis has often been blamed on VaR. To the extent certain banks applied VAR to mortgages, using, say, a 10-day VAR based on data from the benign 1990s, was an error. Yet, the ubiquity of this error suggests it was not a mathematical mistake (math errors are random and go in both directions), rather a flawed assumption that implied benign VAR exercises: the fact that housing prices do not decline. One can say with hindsight, this was incredibly stupid, yet no one was arguing for financial institutions must be robust to this scenario prior to 2007, and the government regulators were actively encouraging no downpayment, no documentation loans as part of a multipronged effort to increase home ownership. That is, the mistaken assumption was part of a broader mistake, comprehensible to all, not some technical error by risk managers, because that assumption was not theirs to make; it was part of a zeitgeist that people seem to forget like all those who forgot voting for Nixon after he resigned. Most importantly, VAR is not perfect, nor a panacea, but the onus is on critics to describe a better alternative. Using 'judgment' or 'all one's information' seems better with hindsight, yet as foresight this is so undefinable it would be a signficant step backward.

If you were to list all the financial company bankruptcies, the one common thread would be that they blindsided investors with their exposures. Who knew Orange County had such a position against interest rates ex ante in 1994? Who knew Barings had such an exposure to a trader in Singapore in 1997? These were not properly calculated risks that went awry, nor were they outright fraud where an unauthorized intraday position blew up. They were the result of investors or management not fully understanding the risks that were being taken, which often a correctly calculated VAR number, correctly communicated, would have easily shown. The errors were problems in getting an accurate VAR, which clearly needs people getting accurate data on positions.

If operating risk is the primary reason why trading operations fail, emphasis on refining VAR seemingly misses the point. Operating risk is neglected for good reason, however, in that it is extremely difficult to quantify existing operating risks, which in turn makes it nearly impossible to evaluate methods of monitoring and reducing these risks. Just as Eisenhower stated it is essential to plan prior to battle even though once a battle has commenced the plan is useless, VAR is essential in planning the allocation of capital, yet in risky situations becomes useless. This is not a paradox, but merely the fact that when we train for competition, we practice tactics and strategies. Inevitably competition, especially competitions we ‘lose’, will bring forth situations we have not prepared for, but the best preparation for such an occurrence is not nihilism, but more practice. And indeed many new situations are avoided by practice, which is why we learn math by solving old problems, because we think these tools are useful to unknown new problems. The alternative, to instead focus on operational risk, is such an undefined objective, that it is much less salutary.

Taleb argues that the unpredictability of important events implies we should basically forget about all that is predictable, because that’s not where the real money or importance is. So from a risk management perspective, we should ignore Value at Risk, which measures anticipated fluctuations. Further, we should ‘go long’ on these unanticipated events by engaging in quirky activities on the off-chance that we randomly find something, or someone, really valuable.

Success in markets, like life, is a combination of ability, effort, and chance. Much of intelligent thought is distinguishing between what is predictable versus what is unpredictable; it is to any organism's advantage to find out what we can figure out and change, and what is forever mysterious and unalterable (eg, the Serenity Prayer). The brain is constantly predicting, trying to figure out cause and effect so it can better understand the world. Most of what humans process is predictable, but because we take predictable things for granted, they are uninteresting. We can't predict some things, but instead of resorting to nihilism, we merely buy insurance or manage
our portfolios--in the broad sense of the term--to have an appropriate robustness. Discovering certain things are basically unpredictable does not diminish our constant focus on trying to predict more and more things. People will disagree on which risks at the margin are predictable, but that's to be expected, and we all hope to be making the right choices that optimize our serenity at the margin of our predictable prowess.

From Taleb's Wikipedia entry circa July 2006, we see where Black Swan thinking goes when applied to an investment strategy:

When he was primarily a trader, he developed an investment method which sought to profit from unusual and unpredictable random events, which he called "black swans." His reasoning was that traders lose much more money from a market crash than they gain from even years of steady gains, and so he did not worry if his portfolio lost money steadily, as long as that portfolio positioned him to profit greatly from an extremely large deviation (either a crash or an unexpected jump upwards).

In fact, Mandelbrot also argues for this strategy. Taleb co-authored a paper arguing that most people systematically underestimate volatility. Furthermore, he argues there exists not only a lack of appreciation of fat tails, but a preference for positive skew, in that people prefer assets that jump up, not down, which would imply the superiority of buying out-of-the-money puts as opposed to calls because those negative tails that increase the price of puts are unappreciated.He is affiliate with some fund that tend to be long tail risk, presumably by being long deep out-of-the-money options, but selling at-the-money options, a locally delta and vega neutral strategy.

These assertions present some straightforward tests, which a Popperian like Taleb should embrace. Specifically, buying out-of-the-money options, especially puts (because of negative skew), should, on average, make money. But insurance companies, which basically are selling out-of-the-money options, tend to do as well as any industry (Warren Buffet has always favored insurance companies, especially re-insurers, as equity investments). Studies by Shumway and Coval (2001) and Bondarenko (2003) have documented that selling puts is where all the extranormal profit seems to be. Of all the option strategies, selling, not buying, out-of-the-money puts has been the best performer historically. Further, Sophie Ni finds that out-of-the-money options are more overexpensive the degree they are out-of-the-money.

Malcom Gladwell wrote a 2002 New Yorker article contrasting the thoughtful, pensive Taleb versus the brash cowboy Victor Niederhoffer: Taleb buys out-of-the-money puts, Niederhoffer sells them. Taleb is betting on the big blow up, Niederhoffer on the idea that people overpay for insurance. Who was right? Well, Niederhoffer ran his flagship fund until September 2007 from a chalet-style mansion in Weston Connecticut . Taleb shut down his Empirica Kurtosis fund at the end of 2004, and the only public data on it suggest a rather anemic Sharpe ratio (up 60% in 2000, but then fluttered). Later Taleb described the fund as a hedge or laboratory. While neither strategy was great, and returns are proprietary, I venture that Niederhoffer's was better if you would just look at their lifetime Sharpes. Taleb's latest funds, which he is less involved with day-to-day but implement his basic beliefs in extremes, were up significantly in 2008, though this is to be expected given the extreme decline, and is similar to how Empirica started.

Taleb's big problem is that he misinterprets the mode-mean trade. A mode-mean trade is where a trader finds a strategy with a positive mode, but zero or negative mean. He then uses someone else’s capital to make money off several years of good returns, making good money for creating or managing the strategy, then, when the strategy gives it all back, the investor bears all the loss. The zero mean means that all the modal returns come crashing down in short time, generating large losses, and the manager walks away with his il-gotten bonuses from the benign modal periods. That’s a bad strategy for the investor, and the trader who manages it is either naïve or duplicitous. High Yield debt is a good example, as the stated yields are quite high, but the total returns to B rated bonds is the same as for BBB rated bonds, at several times the risk (and very concentrated in recessions). However, just because selling puts is a bad strategy, it doesn't mean buying puts is a good strategy. A Sharpe of 0.2 is a bad long position, but a worse short.

A ‘Black Swan’ is something that is totally unexpected and important. [European] people assumed all swans were white, but then they saw a black swan, and everyone certain all swans were white was wrong! That’s a 'gotcha game' for people who really take seriously someone’s assertions on the color of birds. But when there’s a price involved, the payoff to such an insight is not obvious, if not totally absent. For example, London bookmakers offer ‘only’ 250-1 odds a perpetual motion machine will not be discovered, and 100-1 odds aliens won’t be contacted: longshots ignored in a casual context are usually overpriced in actual markets.

In option markets, there is a volatility smile, whereby out-of-the-money options have higher implied volatilities, especially on the downside. For example, in May 2006 when rumors of GM's woes were large and its stock price was around 32, GM options had a one-year at-the-money implied volatility of 60, but down at a strike price of 15 its volatility is a much higher 140. The fact that Black-Scholes assumes lognormal returns does not imply market participants think likewise, so it is simply incorrect to assert that a market collapse of 23 standard deviations has a infintesimal probability based on the normal distribution, because real markets are aware of fat tails. Perhaps options were priced this way in the 1980's, but since then, there is a volatility smile that directly captures non-nomality. You can't profit from the idea that market returns have fat tails because that's priced into the market via the volatility smile, and this volatility smile shows up in 'disaster' insurance of all types: People pay a lot to sleep easy. Many people have looked at option prices, and they all find that out-of-the-money puts are the most overpriced of all options—people are expecting ‘Black Swans’ too much on average.

Taleb responds by noting that the 1987 stock market crash changes everything, because if you bought puts then, you would have made enough money to make up for decades of otherwise weak performance. While Shumway and Coval do not include 1987 in their academic study, Bonderanko does, and gets the same results. Taleb points out several anecdotes of financial market crises as further evidence of the importance of financial debacles, such as the 1998 crisis related to Long Term Capital Management (implied vols, libor spreads, skyrocked), or the emerging markets blow up of 1997. These events made money for people with long volatility, or specifically long puts, but the plural of anecdote is not data, so he should have cited an empirical paper showing the positive abnormal returns to taking on fat-tailed or asymmetric risk. Though it is easy to recall extreme events that would generate large fortunes to those on the correct side, one has to put them in full context, against the cost of insuring against these events over long periods of time. What is the sample space of all things one is insuring against? Stasis is data, as Stephen Jay Gould used to say. The volatility smile, and large bid-ask spreads in the extremes as a function of price, imply you can’t make extranormal profits over the long run by going long ‘Black Swans’ - at least in the markets where Taleb has the most experience (though not, according to him, expertise, which is more philosophically oriented).

The bottom line is that people tend to underappreciate low probability events when they are immaterial--because they are immaterial! So they underestimate the prevalence of Black Swans because if you find one, who cares? But hurricane insurance, a 3-delta put option on GM? You will pay up for that.

In the end, he promises to teach us how to take advantage of these Black Swans. His strategy is pretty simple. He argues for a barbell strategy of much safety, and a dollop of wild risks, which is, basically, an exposure to something totally unquantifiable, like Llama farms, or any of the myriad opportunities neighbors, spammers, and late-night paid-TV tout. In the context of Tobin’s two fund separation theorem, this means the ‘efficient’ risky portfolio is the most insanely unquantifiable and risky portfolio you can imagine, tempered by its modest allocation. Yet this implies the unquantifiable and risky portfolio has very good returns, which by definition (unquantifiable) is merely an assertion. As per the super safe assets, the only consistent risk premiums are from extending from overnight to a couple years in bond maturity, and from going from AAA to BBB credit risk. Super safe, is generally 'too safe', in that economists find this risk premium outsized relative to its volatility or covariance difference.

There is good reason to suspect one loses money, on average, on the wildest risks. Consider longshot odds at the racetrack and the highest payout (and thus riskiest) lottery tickets. Researchers have found a negative return premium for highly volatile stocks. Applied to ‘uncertainty’, this same pattern holds, as stocks with the most earnings forecast estimation error also have the most volatility, so it is no surprise they too have a negative premium. Truly improbable scenarios generally involve more hope than rational investment, as people will pay you to help them dream of the chance to become incredibly rich in the same way that the biggest lotteries, with 100 million to 1 odds, have the highest jackpots and the lowest mean returns. There are an infinite number of companies that directly target people wishing to make an end run around the rat race, and most of these companies are engaged in selling nothing more than hope (estimates are that only 2% of proposed home-based businesses touted on the internet are legitimate business opportunities).

Black Swan argues that standard statistics is flawed because it is backward looking — it uses ‘historical’ data — and argues that standard measures of risk like the normal distribution are ‘frauds’. I too prefer future data, but it is hardly a practical alternative. The Gaussian distribution is common in theory because it is so analytically tractable; it often creates closed form solutions that allow one to see how one variable affects another, and has nice properties, such as the fact that two Gaussian random variables added together is also a Gaussian random variable. In practice, no one actually believes in this view, and makes ad hoc adjustments, such as the volatility smile for option prices. The key is that from an expositional point of view, the Gaussian distribution usually gives one the gist of the true ‘fatter-tailed’ distribution, and allows easy exposition. Non-economists often giggle at the term ‘fat-tailed’ or homoskedasticity, but indeed most real world distributions are not ‘Normal’ or Gaussian, they simply have fatter tails than average. Does this imply statistics is a fraud? Well, if you mistake the map for the territory, indeed, this is news. For everyone with some common sense it’s an approximation or expositional device.

Taleb belittles predictions that have large or unmentioned error rates, yet any specific error metric (standard deviation, value-at-risk, correlation, R2, etc) is, in his mind, a fraud and useless because it relies on an assumption, one that is 'wrong'. He argues we reward those who imagine the impossible, but what does that mean in practice? That we encourage people to enumerate everything possible no matter how improbable? In finance, these risk reports are all too common because they reflect a lot of work, in that generating a list of unprioritized things that could happen is easy but practically useless, because you simply can’t address all the points and so must leave them as mere ‘I told you so’ observations. One can remember Richard Clarke’s vague warning about Al Qaeda prior to 9/11, which in no way suggested that changes to hijacking protocols or airline boarding should be made, but rather that something could happen, true but unhelpful.

Getting people to highlight wild risks comes easy, which I think is a big part of his book’s appeal. Legislators and personal-injury lawyers eagerly hype risks with negligible real impact, like secondhand smoke, or getting cancer from trace amounts of chemicals. Sometimes they create considerable public concern about risks that don't exist, like that of contracting anti-immune disease from breast implants, or cell phones causing cancer. Newsrooms are full of English majors who make confident pronouncements about global-warming or some other complicated process, all in hopes of getting viewers or readers activated.

I could imagine Taleb teaching a statistics class to freshman and instead of starting with the arithmetic mean and standard deviation, asking 'what was the probability of an airplane taking down the World Trade Center on September 10, 2001?', and waxing poetic about how ‘we just don’t know!” Students might think such talk is much "cooler" than boring formulas, but such confused thinking leads nowhere in particular and can be indulged indefinitely without producing anything useful, as Taleb demonstrates. Of course one needs technical knowledge and common sense in anything, but while you can teach one, you can't teach the other. We teach statistics, calculus, etc., not because it solves every problem, but because it can help in many problems to delineate and potentially manage that which we can change from that which we can’t. Surely a college department of 'wisdom' or 'good judgment' would be a valuable thing, unfortunately no one can agree on the curriculum.

Martin Gardner wrote a popular column for Scientific American, and in the process received a lot of mail from ‘cranks’ telling him about perpetual motion machines and the like. So he wrote a book called Fads and Fallacies. In the book he describes "cranks" as having five invariable characteristics:

1. They have a profound intellectual superiority complex.


2. They regard other researchers as idiotic, and always operate outside the peer review


3. They believe there is a campaign against their ideas, a campaign compared with the persecution of Galileo or Pasteur.


4. They attack only the biggest theories and scientific figures.


5. They coin neologisms.

On his personal website, Taleb once described himself as being "an essayist, belletrist, literary-philosophical-mathematical flâneur," a conception that some people finding endearing, me not so much. Literary-philosophical-mathematical types,- especially flâneurs - tend to be 'full of themselves,' supporting Gardner ’s characteristic #1. He prides himself on not submitting articles to refereed journals, considers most people who are indifferent to him as fools, and disdains editors, even spellcheckers (#2). He proudly notes that someone told him “in another time he would have been hanged [for what, inanity?].” Wilmott Magazine, a quant publication published by his colleague Paul Wilmott, wrote a fawning article about him in which they noted that he is “Wall Street’s principal dissident. Heretic! Calvin to finance’s Catholic Church” (#3). His website states his modest desire to understand chance from the viewpoint of “philosophy/epistemology, philosophy/ethics, mathematics, social science/finance, and cognitive science”, supporting #4. Lastly, for #5, he has gone so far as to print a glossary for his neologisms (eg, “epistemic arrogance” for “overconfidence”). In Martin Gardner’s taxonomy, Taleb is a classic crank.

Clearly his experience as an options trader gives him credibility, but I think this is a big issue, that of successful brokers thinking they made their money off investing insights. Before he became a regular on the talking-head circuit and expert on Judeo-Arabic philosophy, he was primarily a trader for large market makers. These are not speculators investing their wealth based on insights, but more like brokers, making money off customer flow, only their buyers and sellers are the guys on the phones talking to retail clients. Such traders spend most of their time looking at a model such as Black-Scholes that tells them what price to buy and sell based on some underlying parameters. These models are more or less standard, and so the main thing the market maker has to do is keep his model inputs fresh, post prices to potential buyers and sellers, fill market orders, and pick off stale limit orders. Customers generally have access to older prices, and in a situation where the current price moves every second, this clearly puts a trader at an informational advantage, which is why it was such a lucrative field, especially in the days before the internet became big (ie, Taleb's time). The trader makes money irrespective of movements in the underlying model price, as in general he keeps his exposure to first-order (eg, delta) and second order (eg, vega) risks as close to zero as possible.

But such trading skill is quite distinct from what a speculator or investor does, which involves a directional bet on the first or second order risks that traders normally try to erase. Traders know as much about what makes prices move as plankton knows about what makes the tides move. Much of being a trader is encouraging trading activity from a hesitant broker, and so many traders are quite adept at presenting themselves as more than middlemen, but also men with an angle or a story. A good trader is probably truly delusional about his prognostic abilities because this allows him to appear sincere in his sales pitch for the latest trade idea; those who don't believe their own stories make weak sales pitches (see Robert Trivers, who Taleb mentions favorably in The Black Swan, and note the irony endemic in his writings). Most of these traders are certain they could make money without their customer flow, because the same self-deception that serves them well chatting up brokers or impressing their boss generates delusions of strategic grandeur. Supreme self-assurance, even if undeserved, just as much as knowing your Greeks, makes for a good trader . Thus Taleb’s ‘narrative fallacy’ argument plays right into his own biases, that is, he has fooled himself into thinking he knows 'the big picture' because that delusion was helpful in his own career.

Rich investor or rich broker: Who is the more easily fooled about his alpha? Notice the relation to the theme of Fooled by Randomness? Taleb is consistently amusing because his criticisms of others apply so neatly to himself: he claims he is an empiricist yet supports his points with anecdotes. The Black Swan makes fun of ‘experts’ with credentials, but he states he does not deign to engage with anyone not sufficiently expert; he states he is not interested in being a speaker-bureau commodity , but routinely travels the rubber chicken circuit; he derides forecasters who don't give a full accounting of their prior forecasting history, yet delinks old remarks about Value-at-Risk, and recategorized his extinct Hedge Fund as a hedge, not a fund; he claims to prize humility, yet is most immodest; he argues against applying the law of large numbers, and also of inferring too much from small samples; people apply models to reality in biased manner, people naively extrapolate data without the appropriate theory; forward thinking is adaptive, forward thinking is error-laiden. Some people think inconsistency is a sign of genius; I think it just reflects confused thinking.

Inconsistency is the major problem with Taleb's oeuvre. For example, he often praises the work of Danny Kahneman as one of the uniquely prophetic economists, famous for his 'prospect theory' that explains why people will be risk seeking in small losses in but risk loving over large gambles. That is, Prospect Theory was invented to explain why people will pay small amounts to gamble, but are risk averse over gains. Yet Taleb argues that a predominant financial vice is the mode-mean trade, where people desire to make a little bit every day, often at the expense of blowing up on 'fat tail' events. These are opposite theories, which would not be a big deal if they were minor assertions from these men, but in fact they are the signature financial hypotheses of each. Taleb may appreciate Kahneman's diverse work, but one would expect him to be a harsh critic of this seminal idea, not the huge unqualified fan he is.

To be popular it is helpful to make people think they are learning something new about something novel and important. Yet the masses do not really like novelty, they like affirmation of their inchoate prejudices. Thus, a reader can leave The Black Swan thinking that any expert is either a charlatan or a fool except Taleb and those smart enough to appreciate him, a group that prides itself on knowing what they don't know, that any specific model is imperfect and therefore evidence is naive Platonism. The current financial crisis may make radical theories that suggest junking existing theory more attractive, but remember that the Great Depression was a Black Swan, and this did not help macroeconomic theory so much as lead it into the desert for 40 years, giving many a wasted life championing not merely a welfare state, but socialism and all its unintended horrors. If something really unpredictable happens, the large number of perennial disparate forecasters of disaster, combined with bayesian statistics, still implies those calling for the end of times are probably 'lucky fools', as Taleb would say. I do agree his claims of an extreme event were spot on over the past year, but this is no less impressive that Henry Blodget's Amazon call in 1998, Elaine Garzarelli calling the 1987 stock market crash, or Angelo Mozilo's subprime investment success up to 2006 made him a business visionary. I look to broader historical data and see buying out-of-the-money options is poor investment strategy, so I don't consider recent events proof of some really useful truth.

To the degree The Black Swan has arguments about the essence of risk they are at least a generation old, even if many are pleasantly introduced to them for the first time (fat tails see Mandlebrot (1962), nonquantifiable risk see Knight (1921), for various cognitive biases see Kahneman, Slovic and Tversky (1982) which was a compilation of papers mainly done in the 1970's), and these books have spawned, or are clearly referenced, by literally thousands of books. The Black Swan may popularize the concept of low probability events, what were called 'peso problems' (see Rietz 1988), and that would be a good thing. But ultimately, the bumper sticker "shit happens" is kind of funny, kind of true, but hardly profound.

Stewart Lectures Cramer

If you haven't seen it, Jim Cramer went on The Daily Show and was totally owned by John Stewart. Cramer went on hoping to merely apologize and then get in Stewart's good graces, but Stewart didn't let him off the hook. Stewart played some clips showing Cramer bragging about manipulating markets. Specifically, Cramer bragging about how easy it was to push the S&P futures down! Cramer is clearly exagerrating there, as this market is too large for Cramer to profitably move around, like you thinking you can push IBM up or down $10. He also disavowed Rick Santelli's rant against bailing out renters (oops! homeowners), saying "I don't know where he grew up, but I've lived out of my car", in a clear attempt to pander to the audience as if he grew up in some great hardship (if you graduate from Harvard and then sleep in your car as a journalist during your first job, I don't think that's the same as growing up in Detroit, or being truly homeless). Clearly, Cramer is a braggart. He's also overconfident about his opinions. He does not appear to have a good batting average. After this performance, I would add he's a moral and intellectual coward. He didn't defend his behavior, he tried to suck up to a celebrity bigger than him in a sycophantic way, and it didn't work.

Nevertheless, Stewart is still profoundly wrong in his assumptions about this crisis. Stewart seemed to think that Cramer and CNBC knew that the market was a pure 'greater fool' play all along, where people are selling worthless crap to the next guy in a pure ponzi scheme. The implication was that CNBC had a financial incentive in hyping stocks, even though they knew it was worthless (I guess he thinks they are evil and stupid, because it would have to bust). But I don't think the people at CNBC 'knew' the market was overvalued. There are bears on the show every day, but there are always bears. If CNBC knew about 2008 in 2007, they would have been very prescient, but they did not. Its a very simplistic view of the world to think bad things happen out of bad faith, as with individuals this is often the case, with the madness of markets, it is much more complex.

Further, Stewart emphasized the 30 to 1 leverage, as if this highlighted the investment banks were being imprudent. With hindsight, that was a bad call. But as I mentioned earlier (see here and here), many investment banks were at that level of leverage for over a decade. Only a handful of investment banks really increased their leverage (not commercial banks) over the past decade, and the market decline occurred throughout the financial sector of thousands of firms.

So, as frustrated as Stewart is with this crisis, his premise that this was caused by bad faith and 30 to 1 corporate leverage, is simply wrong. Most of the banks selling these mortgages had them on their balance sheets. They incorrectly believed in the business model. Stupid, but not a conspiracy. As per 30 to 1 leverage, yes this is a bad idea, and I went over why this is so in my earlier post, but many investment banks had been doing this for over a decade so it is not specific to this crisis, just a perennially bad corporate decision.

Government Incentives

In abstract, a company run by the government is better than the private sector, because they operate maximizing total social welfare, not just that of the shareholders. Thus, the community, employees, even global warming, are simultaneously considered in their calculus. This is clearly better than merely maximizing shareholder profits.

That's the logic of socialism, a logic that was compelling to most intellectuals from, say, 1930 to 1970. Einstein, like many other smart, but economically ignorant writers, noted that "production for use" is obviously better than "production for profit", and legions of college students think that getting rid of profits would simply lower costs, and create a better focus on serving people rather than profits. The problem as Hayek pointed out, is that only a price rationing system in a free economy incents the right people, at the right time, to make the right decisions. It decentralizes decision making. The alternative is a political clusterfluck, as interests wrestle for turf over a perceived fixed economic pie. Hayek mentions Einstein specifically in his Fatal Conceit about this common misperception. With hindsight, this is clearly balderdash, as the difference between the prosperity, and freedom, of Taiwan vs. China, North vs. South Korea, East vs West Germany shows.

Consider the regulation of banks, which many Democrats think needs to be stepped up. Is regulation disinterested? Maxine Waters can be counted on for making all sorts of paranoid accusations, as she represents her inner city Los Angeles district in a way that would make Huey Long proud. But she and her husband have ties to OneUnited, the largest black owned bank in the US. Her husband is a director. The Wall Street Journal and New York Times report she owned $250 to $500k in bank stock, and also received "received interest payments from a separate holding at the bank, also worth between $250,000 and $500,000". Now, that's a return on capital!

Interestingly, OneUnited (an unlisted company) seems to have had most of its assets in Fannie Mae and Freddie Mac stock, obvious a bad investment, but also, suggests a fundamental lack of true banking, making loans, as opposed to merely investing in the stock market, which is a poor use of bank capital. it's privately held, so who knows what the solvency of this bank truly is, but if they had a lot of Fannie stock, they are in big trouble.

If they gave her a special dividend of $500k, she's worth it. At a hearing on minority lending in 2007, Ms. Waters criticized regulators for not doing enough to help minority banks stave off mergers with non-minority institutions. A provision designed to aid OneUnited was written into the federal bailout legislation by Mr. Frank, who is chairman of the financial-services panel. Meanwhile, it was disclosed that OneUnited pays for a Porsche used by one of its executives and its chairman's $6.4 million beachfront home in Pacific Palisades, Calif., a luxury enclave between Malibu and Santa Monica.