The American subprime market meltdown started in the summer 2007 has caused a terrible shock wave effect on the US economy as well as on the world economy. Many financiers and financial institutions cried and blamed at each other for having caused this mess. But who are really the criminals, and maybe *heroes*, during this economic war time?
1. Black Swan Prophecy
Since the fall 2007, it’s very probable that whenever there is a crisis, people will cry out the name Nassim Taleb. The option trader who got his initial fame for pocketing of $35-40 million on the Black Monday (1987) is now even more famous as a best-selling author and as a philosopher of randomness as he calls himself. Since Bloomberg has recently repainted a glamorous picture of Taleb, I have not much more to talk about him.
| Originally Posted by Bloomberg
On a freezing day in March 2007, Nassim Taleb walked into a conference room at Morgan Stanley’s Manhattan offices on 47th Street and Broadway to address a group of the firm’s risk managers. His message: Your models don’t work.
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Only six months later, Morgan Stanley experienced its own rout. The world’s second-biggest mergers adviser announced in December that it had written down its subprime-related holdings by $9.4 billion after the firm’s traders misjudged how fast and far prices of the debt would fall. Their risk management had failed.
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Is Taleb just a regular philosopher of randomness or is he himself an almighty prophet? What makes Black Swan popular may be not the philosophy itself but instead his inexplicable timing, from the 1987 crash to Societe Generale’s huge trade loss to Morgan Stanley’s $9.4 billion writedown (all described in Bloomberg’s article). Note that he published his Black Swan book in May 2007, just a couple of months before the subprime meltdown (which is a Black Swan event according to his theory) began.
It’s quite possible that Taleb is merely obsessed with Black Swans and make black-swan bets on everything. It just happens that when something extremely bad happens, the human reaction makes it even worse than it was typically modeled. That makes Taleb win big on average.
There’s undoubtfully a lot of hype about the guy right now. It’s just hard to decrypt this hype in its full glory. The only lesson we can take for granted from this controversial figure is: don’t be fooled by randomness.
2. The Criminals
Financial modelers (or quants) have recently been placed under strong criticism for the handling of the subprime market, for example as in Daniel Carroll’s article “When Quants Fail”. This is in some sense aligned with the comments of Julian Shaw in How I became a quant. I in fact highly rate Julian’s story out of a bunch of other stories in that same book.
| Originally Posted by Daniel Carroll
People just get impressed with complex mathematics, especially when they don’t understand it. As a trained mathematician, I often have a hard time understanding why. I don’t, however, have a hard time understanding why these models fail periodically.
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On the other hand, Professor Nicole El Karoui (see also a featured article about her on WSJ) had an interesting interview with Le Monde in which she affirms Mathematics shouldn’t be blamed for the mortgage bubble.
Mathematics and Sciences should never be blamed. The problematic reality is … most of us don’t fully grasp their true spirit. Perhaps more than 90% of mathematical reseach is trash or even totally wrong. In academia, this results in papers with low number of citations and then no one really cares about it. However, in an investment bank, an incomplete model (let alone bullshit models) may be disastrous. With the 1987 crash and the subprime meltdown in the pocket, quants on average may look more like monsters rather than protagonists.
The bigger criminals here of course would include the managers who gave too much power to their quants that are obsessed by and over-confident about their wrong models. Let me end this short discussion by quoting a nice summary of who and what to blame for the subprime crisis, posted on Wilmott:
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We have to blame the whole system:
- The managers (investors) that followed quants blindly just cos they can really do awesome maths
- Central Banks that don’t understand a sh** about financial behavior and are the first to make a mess with the rules
- Some Quants that are so arrogant that followed their models blindly just because it had a really nice fit to historical data. so they feel like Gods sometimes until they find they were fooled by randomness
- Inputs and assumptions are more important than the mathematical quality of the model (of course this is also important to get the correct outputs)
- University degrees in finance are not as well designed as they should be
- Lots of people in Banks and Central Banks come from Economy, Engineering, Maths instead of Management and Finance (Management is really under rated nowadays)
- People care a lot with complex models instead of looking for simple strategies that can make awesome trades. In management and Finance we say that complexity must me charged with extra fee. What we’re seeing was the opposite though. Complexity were being priced at low cost
- Most people like mysticism and don’t believe in their skills. They are willing to put a lot of money in a black box trading algorithm or in a fund instead of investing by themselves
- Greedy managers that don’t understand the risk-return trade-off
- Trading bonuses which sometimes encourage traders to behave very differently than if they were to invest their personal capital
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. On the other hand, with the population of 1.3 billion, it is increasingly visible that whenever the Chinese sneezes, the whole world catches cold.
. But I’m sure that they’re well-known in the Economics literature. Anyway, I guarantee these’re interesting questions 
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