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Submitted by mute on Tuesday, 14 August, 2007 - 13:05

Stanley Morgan

With the prospect of earning over the odds on derivatives trading, hedge fund managers are employing ever more high-tech means to calculate risk and predict stock market activity. But Wall Street’s faith in its own predictive powers often blinds investors to the fundamental laws of investment, says risk specialist Stanley Morgan

A friend of mine was working as a quant at a Wall Street investment bank when a large and well-known hedge fund, Long Term Capital Management, went bust in 1998. Experts from a number of top financial firms were called in to help stanch the bleeding and prevent the disaster from spreading to the larger financial system. My friend was one of the people enlisted to sift through the mess and figure out exactly where the fund stood. Afterward, when I asked him how things looked, he shook his head in amazement: the people he’d spoken with at the fund had no clue about half of what they owned or what it was worth. Granted, complex derivative securities (the kind this fund had been miserably unsuccessful gambling with) can be exceedingly hard to price even when you’re not in the midst of financial turmoil, but that’s something you need to take into account when you’re managing billions of dollars of other people’s money. The fact that this fund lost enough in a week to nearly bring down the economy was a sign that its managers were playing Russian roulette with bazookas, not simply ‘investing’.

This kind of financial brinkmanship is becoming increasingly popular. Warren Buffett has called derivatives – which often encapsulate extremely complex relationships between multiple products or events, and allow you to take on risk many times greater than the actual money you have invested – ‘financial weapons of mass destruction’. Derivatives are over-used and routinely mispriced such that companies are often giving an inaccurate accounting of the value of their holdings. And when things don’t work out the way you expect, derivatives can cause staggering losses. There will be more and bigger blowups. You don’t have to be Chicken Little to acknowledge that large pieces of the sky are falling all the time – from Barings Bank (‘95) to hedge funds Long Term Capital Management (‘98), Julian Robertson’s Tiger Fund (‘02) and Amaranth (‘06). The particular excuse is almost irrelevant: ‘That surprise move in Brazilian interest rates was a 1 in 1,000,000,000,000,000 occurrence’; ‘The liquidity in that Russian mining stock suddenly dried up, so I couldn’t unwind my position’ – sure, but that’s not going to bring your money back (or mine, if I was unlucky enough to be one of your investors). Trading desks are increasingly speculating in products they don’t fully understand, using computer models that don’t account for that deadly one-in-a-trillion possibility (what author/trader Nassim Nicholas Taleb calls a ‘black swan’), and at the same time generally shunning anything that appears too simple and comprehensible. Why?

One culprit is a familiar one on Wall Street: greed. If you think Dell will go from $25 to $75, you can buy a thousand shares and make $50 thousand, or you can buy some call options and make many times that amount with the same investment. Or you can use borrowed money to increase your leverage even more. Yeah, but what if Dell ends up dropping to $15? Hedge funds have brought the use of leverage to a point never dreamed of before, while hedging the resulting risk in ways that are not necessarily foolproof. But precisely because of the massive leverage they use, hedge funds hold out the promise of returns that dwarf the boring S&P 500 or FTSE. And they often deliver them – until that statistically impossible move in Brazilian interest rates happens. Like the entrepreneurs who sold shovels during the California gold rush, the smart money knows that the best way to get rich from a hedge fund is by running one. Fund managers take their cut off the top: they get 2 percent of your money no matter what their performance. The fund’s other investors take their chances, and feel most of the pain if the fund’s bets don’t pan out. Still, people who can afford the price of admission are drawn to hedge funds’ potential returns, their exclusivity, and their general sexiness like moths to a flame, adding billions of hopeful dollars a week to the pool. The result: more pressure to pump up returns, more leverage, more borrowing, more complex derivatives, more precarious and hard-to-quantify dependencies between products and trading desks. And more risk.

A less obvious reason for the explosion in the use of leverage, and the concomitant increase in ‘systemic risk’, is 21st century Wall Street’s love of technological solutions almost for their own sake. Sure, it costs a lot of money to hire an army of physics PhDs and build computer models that can run through a million scenarios a second, but who wants to be seen scratching out calculations on a yellow legal pad? If you’re marketing yourself as a financial genius – or if you ‘are’ one, like the Nobel Prize winners who founded Long Term Capital – you’d better have a flashier plan to show your investors than ‘these three stocks look really cheap’. But while strategists crank out incomprehensible new products and Rube Goldberg-esque mechanisms for managing their inherent risk (usually imperfectly), there is plenty of money being made using the mundane strategy of looking for mispriced securities – ‘Buy low, sell high’ – with no chance of losing three thousand times your initial investment.

Debt Fist by John Wollaston

Image: Debt Fist by John Wollaston

The annual ‘rich lists’ continue to be dominated by traditional businessmen (technology, steel, retail, media) who make money in ways that would be recognisable to a 19th century capitalist and old-style investors like Warren Buffett, who claims not to even have a quote machine in his office. For the most part, the rich continue to get richer in the traditional ways. As for the new hedge-fund billionaires, the financial rock stars of the moment (with earnings in the hundreds of millions of dollars a year), they make their money largely from fees paid to them by very rich people – not a very high-tech way to earn a living, but they don’t seem to be complaining.

Stanley Morgan builds risk management systems for a Wall Street investment bank



Bad math
mute - Thu, 23/08/2007 - 1:45am

This piece by Martin Hutchinson is a useful addendum to Stanley Morgan's piece - particularly regarding the mathematics...
B

Helicopter over Wall Street
August 12, 2007

Martin Hutchinson is the author of "Great
Conservatives" (Academica Press, 2005) -- details can
be found on the Web site www.greatconservatives.com

Federal Reserve Chairman Ben Bernanke first achieved
fame with a November 2002 speech in which he repeated
Milton Friedman’s assertion that the Fed could “drop
money out of helicopters” if deflation or a credit
crunch occurred. The Fed and the European Central Bank
now appear to be doing this, having injected $300
billion into the world monetary system in the last two
business days. What Bernanke didn’t tell us in 2002
was that his helicopter would hover only over Wall
Street.

Friedman and Bernanke were quite right that dropping
money from helicopters would provide reflation,
although since 1931-32 the United States has not had
an economy in which such an action would have been
remotely appropriate (fiat currency central banks,
being political creatures, universally err on the side
of too much, not too little money in the system.)

One can indeed imagine in a difficult economy the
welcome whirr of chopper blades as the Bernanke
helicopter carried out its mercy mission. It would
hover lengthily over the rusting steel towns of Ohio
and Western Pennsylvania, would circle twice over the
wasteland of downtown Detroit, would avoid the major
farm states, already excessively subsidized by the
U.S. taxpayer, but would provide welcome relief to the
ghettoes of Watts and the South Bronx.

What it wouldn’t do, in a world of even reasonable
equity, is spend any time over Wall Street.

The injection of money by the Fed and the ECB feeds
directly into Wall Street. It’s huge in amount -- $215
billion by the ECB and $58 billion by the Fed – and it
consists of short term loans granted by the central
banks to banks and investment banks which had been
unwilling to make interbank deposits except at a
substantial premium over the central bank’s target
short term interest rate. Admittedly the injections
are only loans – but if they are not quickly removed
they will have added around 2% to the US and EU broad
money supply. This will worsen the already serious
global inflation problem, thus exacerbating the
difficulties the world economy already faces. They
will however bail out Wall Street and its European
competitors.

The level of panic in financial markets is quite
extraordinary. Stock prices are down less than 10%
from their all time peaks, and still up on the year,
while bond yields have retreated substantially from
their recent highs and are well within their trading
ranges of the year. The only general market factor
that has changed significantly is that volatility has
increased, in other words instead of going up and down
50 or 100 points each day the Dow Jones index is now
zooming up and down 200 or 300 points, even though at
the end of the week it has gone nowhere very much.

The increased volatility is key to the entire market
turbulence, because of what can only be described as a
gross misuse of mathematics in the trading rooms of
the world.

In the capital markets of the 1960s and earlier, banks
would no more have considered hiring mathematicians
than they would have bet their entire capital in short
term speculation. With the valuation methods of that
period, mathematicians were superfluous – any
reasonably numerate accountant could understand them.
However, after the invention of the Black-Scholes
options valuation model in 1973, mathematicians came
into fashion.

The model offered the enormous benefit of providing a
“value” however spurious for any option position. This
allowed banks to offer their clients options both
direct and disguised while ”marking to market” their
trading positions at the close of each business day.
The model was however completely incomprehensible to
non-mathematicians. Bank managements therefore decided
to import some mathematicians to interpret it and act
as risk managers. This proved a sensible move; Barings
tried to run a modern trading desk with large options
positions with only Old Etonian liberal arts majors to
manage the traders, with catastrophic results

Having imported mathematicians, and recognized that if
they were going to take on these huge risks they
needed to be able to manage them, bank managements
then asked the mathematicians to produce a risk
management metric. Unfortunately bank managements did
not suspect mathematics’ most closely guarded guilty
secret: only a tiny minority of possible equations are
solvable using currently existing mathematical
techniques.

Rather than confessing failure and losing their jobs,
which were paid beyond the wildest dreams of
mathematical academia, the mathematicians therefore
bent the reality to fit the equations they could
solve, and came up with the “Value at Risk”
methodology. By assuming that securities prices move
continuously with no jumps, that they are random and
normally distributed, and that market trends don’t
exist, mathematicians were able to produce a risk
management model that was convincing to top management
and worked most of the time. The occasions on which
the models didn’t work were dismissed as market
anomalies, although in reality it was the models not
the markets that were anomalous.

Value at Risk suffers from two main defects. One is
that it breaks down in times of market turbulence; the
theoretical maximum “value at risk” can be an
arbitrarily small fraction of the true risk when
things go wrong.

The other is the way VAR deals with volatility. Under
VAR, the risk of a position depends on its volatility,
so that if volatility changes suddenly the risk
changes also. Banks measure volatility either based on
the past average over a 30 day period, or from the
prices of some widely traded option contracts (these
two methods can produce widely different estimates of
volatility.) When volatility changes – either very
volatile days are introduced into the average or
options prices jump – the VAR of the position changes
also.

If as in the last few weeks markets suddenly become
more volatile after a lengthy period of calm the VAR
of every position held by a large bank suddenly jumps,
generally to a multiple of its previous level. In such
cases, even if markets don’t overall move that much
(as they haven’t in equities markets, down less than
10% from their peak) the bank has to reduce its
positions. Since all participants are looking at the
same volatilities, every bank and hedge fund is forced
to unwind its trades and reduce its positions at the
same time. Needless to say, this produces highly
unstable markets, which themselves increase volatility
and exacerbate the problem.

This is the first time the markets have done this
since the introduction of VAR in the early 1990s, with
the limited exception of the Long Term Capital
Management crash in 1998. In 2000-2002, the equity
bear market was not accompanied by any increase in
volatility in other markets and was fairly orderly.
This was a sign that the cathartic effect of the bear
market, aborted by Fed Chairman Alan Greenspan’s
massive injection of liquidity into the US economy,
did not go nearly far enough to wipe out the
over-optimism and gullibility of the late 1990s
bubble.

Needless to say this bizarre effect of current risk
management techniques has now resulted in a market
panic, quite unjustified given the modest movements in
the stock and bond markets themselves. The ECB and the
Fed have reacted to the panic rather than the markets,
and have bailed out European and US banks with oceans
of additional liquidity. This of course has introduced
moral hazard into the system in large amounts, if we
are unlucky and the central banks’ liquidity
injections stabilize the market and allow unjustified
speculation to resume. Hopefully the liquidity
injections won’t work and the long overdue corrective
market crash will overwhelm the speculators.

Whether this somewhat artificial panic will cause the
Fed to abandon inflation control altogether and drop
interest rates remains to be seen. If it does so the
rest of the world will suffer from a 1970s style
stagflation in which savings, jobs and above all
retirement incomes become highly insecure. At that
point we can reflect gloomily upon the second rate
mathematicians hired by Wall Street and the second
rate central bankers whose helicopters never assist
the middle class or the poor.

Contrary to populist theory, it is fiat money,
controlled by politicians and unaccountable central
bankers, and not the deflationary but mechanistic Gold
Standard, that is the true instrument of Wall Street.

Bad math
digit - Thu, 23/08/2007 - 1:28pm

Nice piece. I recognise the dodgy maths from my days writing financial training for an e-learning company. The equation that popped up over and over was the dividend discount formula, described by the finance experts briefing me as the method for calculating (not estimating) the long-term value of an investment. It took me quite a while to figure out that the whole thing was just an elaborate form of guesswork, largely because the experts themselves had such a well developed blind spot obscuring this fact. The figures plugged in for annual dividends were guesses. The question of what those figures were supposed to be based on was one the experts seemed not to have considered. Effectively, the only way the DDM was of any concrete use was as a way of working out the value to you now of money you knew for certain you were going to get in the future...or perhaps of convincing someone who wants to believe you that you're worth investing in. First rule of prestidigitation: the audience wants to believe.

Risk
games.Martin - Sat, 08/09/2007 - 7:10pm

the financial sector has spent much of this decade operating with a short-term view that was focused on the future, not the past. Indeed, as recently as this spring, it was rare to find any financial trader who spent much time pondering events more than a decade old – or beyond the data points typically found on a trading terminal.

That partly reflected the fact that financial traders are often too young to remember many economic cycles. However, more importantly, many of the instruments that have been in the eye of the recent market storm have only risen to prominence this decade. Thus the “historical” data bankers feed into their computer models to assess market swings, or measure their levels of risk-taking, is often based on just a few years of records. That can potentially distort the way these computer models work, since it means that bankers are effectively presuming that the future will be similar to the past – but based purely on very recent experience.

“What is remarkable is that the risk models currently applied [in some markets] do not reflect the experience of the autumn of 1998, only a few years ago,” says Harald Malmgrem, a Washington-based economist.

Another crucial distinction is the sheer speed at which shocks now tend to move round the world, and between asset classes, as computing power links markets more closely than ever before. Back in the 19th century, for example, it could take days for news about railroad problems in America’s Midwest to reach London; but this summer, bad news of subprime losses has often hit trading screens round the world in seconds.

Excerpts from:
Wall Street’s crash course, By Gillian Tett, Financial Times,August 26 2007

More at: http://www.ft.com/cms/s/0/f54fd878-5400-11dc-9a6e-0000779fd2ac.html

Adding to the bearish sentiment, a survey by the National Association of Business Economics showed that economists thought credit worries were more of an immediate threat to the US economy than terrorism.

From; Wall St falls on poor homes sales, By Hal Weitzman in New York, FT, August 27 2007

More at: http://www.ft.com/cms/s/0/048a5462-5497-11dc-890c-0000779fd2ac.html



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