
How Wall Street Lied to Its Computers - robg
http://bits.blogs.nytimes.com/2008/09/18/how-wall-streets-quants-lied-to-their-computers/
======
mynameishere
Well, that explains that. Now explain this: If these MBSes were so complex
that Wall Street MIT-trained quants and Wharton-trained traders and their
computers didn't see it coming...how exactly did _I_ see it coming? Me.

I mean...liar loans and ARMs starting at record-low rates and housing prices
that looked like the NASDAQ right around AD 2000? I mean, the reason they
didn't see it was...because they _did_ see it, but the hand that picked up the
commissions had a mind of its own.

~~~
byrneseyeview
In the short run, these markets selected for people who didn't properly
analyze the risk. If the average CDO makes you 7% a year until one day it
loses 20%, it's not a prudent investment -- but if you somehow estimate that
the maximum loss is 2% instead, you will be willing to buy many more of them,
and your return on capital will look a whole lot better. If you're not the
only one doing this, the flow of all that money into risky products will give
you returns even higher than you expected -- and if you're like the average
investor, you will adjust your reasoning in retrospect to make yourself as
brilliant as possible.

So it's actually unsurprising that people outside of the finance business were
disproportionately aware that the whole real estate bubble was crazy. Someone
with your views working for a big bank would be the equivalent of a peacock
who realizes who impractical those feathers are.

~~~
ReverendBayes
Not a web connection or mag subscription among the lot of them, eh?

[http://www.marketoracle.co.uk/index.php?name=News&file=a...](http://www.marketoracle.co.uk/index.php?name=News&file=article&sid=1661)
<http://www.forbes.com/2005/02/21/cz_0221oxan_default.html>
[http://money.cnn.com/magazines/fortune/fortune_archive/2006/...](http://money.cnn.com/magazines/fortune/fortune_archive/2006/11/13/8393160/index.htm)

~~~
nostrademons
It's pretty easy to ignore what you read on the web when it doesn't fit your
preconceptions.

~~~
eru
Yes, and to everyone who now claims he was really sure of the bubble back
then: why didn't you make a fortune in short selling?

~~~
nostrademons
Shorting is generally a bad idea because even if you're right, if your timing
is wrong, you can still lose everything. Say that you call "overvalued" and
short the market. You're right, but the market gets _more_ overvalued before
it corrects. You can get short-squeezed out of your positions because with the
new, bubble-inflated prices, you don't meet margin requirements. Then the
market corrects, you're vindicated, but you've lost everything already.

Same goes for buying on margin when the market undershoots. You can be right,
but if the price continues to drop past rationality (as it often does), you
can lose everything.

And I _did_ make a pretty good return, both in 2001 and 2007, simply by
holding money in cash when people were greedy and investing when they were
fearful. Not a fortune (I was a poor college student in 01/02, and only had 2
years of accumulated work savings in 07), but enough to fund my year-long
startup adventure, and to fund a few more years of it if I had a decent idea.

~~~
eru
Yes, timing is a problem. The market can stay irrational for longer than you
can stay solvent.

Good luck with your ventures!

------
raganwald
This is really rather simple to understand: Part of the motivation for
inventing complex new derivatives is to create things that look conservative
to the model but are actually risky.

The personal incentives for traders are to get big returns, which implies
making risky bets. But your risk management system won't let you make risky
bets directly. So instead, you make risky bets indirectly through instruments
specifically engineered to game the risk management system.

It's nothing new. Michael Lewis' excellent book "Liar's Poker" describes how
Solomon Brothers invented ways to obtain triple-A credit ratings for
incredibly risky forex trades so that they could be sold to S&L's with strict
rules about the credit-worthiness of their investments. And that was at least
twenty years ago.

~~~
j2d2
_Part of the motivation for inventing complex new derivatives is to create
things that look conservative to the model but are actually risky._

Nailed it. Things like FX, commodities and equities are closed systems. These
markets make their money by volume and it's not particularly interesting.

Take something like a CDS where you don't really know what the risks are and
it becomes easier to set prices fairly arbitrarily. Maybe some cpty has a
stellar rating. Does that mean they'll always be stellar? Who knows?!

But this is still missing the real killer. Leverage. Everyone forgot the
lesson of LTCM.

It was a bitter irony that the only bank to tell LTCM "fah q!" was the first
to go. It's not so ironic now that Lehman, Merrill and possibly Morgan are
gone now too.

------
olefoo
I'm going to draw the obvious conclusion that most of the models were built on
the premises of mediocristan, when in fact the world they were modeling lived
in extremistan.

The thing is that quants who come up with models showing large amounts of risk
to otherwise profitable investments aren't as popular as ones who say
everything is just fine. So there is a clear incentive for models to be
optimistic.

~~~
jimbokun
I thought this was a great analogy to express your conclusion:

"It was like a weather forecaster in Houston last weekend talking about the
onset of Hurricane Ike by giving the average wind speed for the previous
month."

------
josefresco
The impression I got was not that they lied to their own computers, but rather
those who programmed the alarms did so inadequately and could not handle the
complexity of the transactions.

His doctor analogy is good, but not exactly perfect. Something more along the
lines of hiring a med student for your physical instead of a grey-haired
professional.

~~~
jimbokun
Not so.

"So some trading desks took the most arcane security, made of slices of
mortgages, and entered it into the computer if it were a simple bond with a
set interest rate and duration."

I find the lying to your doctor analogy very good to describe this kind of
behavior.

------
sethg
_The models should penalize investments that are complex, hard to understand
and infrequently traded, she said._

...by how much?

------
bestes
It seems to me that the root cause to the computer models failing was that the
government stepped in to "help."

Once government requirements were put in place, I can only imagine the level
of red tape required to make changes to what was a dynamic system before.

None of this was mentioned in the article. Does anyone have any facts on this?

~~~
bokonist
Nothing I have read indicates that was the case. I believe Raganwald above is
mostly correct. The major roll that government played, is that by setting the
precedent of "too big too fail" starting twenty years ago, and by setting
interest rates too low, it enabled Wall St to play with far more risk than was
wise.

------
aswanson
100 year flood. Brilliant, quants. Quick investment tip: Never, ever, invest
in a prospectus that has the word "Gaussian" in it.

------
time_management
Traders and bankers knew, philosophically, that the risk in these products was
much higher than the models would admit. "25 sigma", to use Goldman's excuse,
means nothing when the distribution is not normal. For a 20-year-old to die
(death being a 0/1 event) within a year is "30 sigma", and yet it is not
uncommon for a college student to die.

My lay explanation of the risk-management failure is as follows. Let's say
that you're of average means, with a net worth of $25,500. You've decided that
"fuck you" money is $10 million, and you want to get there by (wait for it)
betting on coin flips, pursuing the Martingale betting strategy. You'll stop
flipping when either (1) you lose everything, or (2) you get to the fuck-you
mark of $10m.

Martingale works as follows: start with a small bet (say, $100). If you win,
bet again at the small size. If you lose, bet again, doubling your size.
You'll win almost all of the time, losing only on an improbable string of
losses. When you win, you'll be up exactly $100.

Obviously, this is an extremely stupid strategy. On the first go, you lose
everything on a string of 8 failures (1/256). You win $100, 255/256 of the
time. Expectancy is still zero, and although a blow-out loss is unlikely on a
single round, you're going to progress to $10m so slowly that you'll almost
certainly fail out beforehand. You have, roughly, a 0.255% chance of getting
the "win" outcome of $10m. This doesn't improve if you change the size of the
bet.

If you're able to borrow $1 billion, in addition to your meager $25.5k, this
strategy makes perfect sense. Let's assume that the coin-flips are
instantaneous, and interest is agreed-upon to be a flat 1%/$10m, meaning that
you need to win $20 million to have your "fuck you" money. Now your blow-out
probability is extremely low. The probability of getting to +20m before -1000m
is _about_ 98%. So, you have a very high chance of reaching your goal, and a
low chance of losing your few-months'-salary bankroll (plus a lot of someone
else's money). Of course, the billionaire is getting screwed.

This is a toy example, but it's not far off from what actually happens. Much
of the money made in finance has been obtained by borrowing others' money to
bet against "black swan" events, so infrequent that no one can accurately
model their likelihood and impact. This is what "rock star traders" try to do
their banks, and what banks try to do to their customers, and we've now seen
the resulting clusterfuck.

