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By Richard Anderson Business reporter, BBC News
Mathematicians and their trading programs are increasingly taking the place of
professional investors in financial centres across the world.
Trading floors were once the preserve of adrenalin-fuelled dealers aggressively
executing the orders of brokers who relied on research, experience and gut
instinct to decide where best to invest.
Long ago computers made dealers redundant, yet brokers and their ilk have
remained the masters of the investment universe, free to buy and sell wherever
they see fit.
But the last bastion of the old order is now under threat.
Investment decisions are no longer being made by financiers, but increasingly
by PhD mathematicians and the immensely complex computer programs they devise.
Fundamental research and intuition are being usurped by algorithmic formulae.
Quant trading is taking over the world's financial capitals.
New paradigm
Mathematicians have long played a vital role in risk management at financial
institutions, but their skill set is increasingly being used to make money, not
just to stop losing it.
Ian Ellis, director at Ride Arcade Limited, explains how electronic trading
works
Firms are now employing gifted academic statisticians to track patterns or
trends in trading behaviour and create formulae to predict future market
movements. These formulae are then fed into powerful computers that buy and
sell automatically according to triggers generated by the algorithms.
These so-called quantitative trading programs underpin all quickfire trades -
known as high-frequency trading (HFT) - in which stocks can be held for just a
matter of seconds.
They are also used in more traditional trading, where the holding period can be
days, weeks or months.
Some are fully automated, but most require human oversight to ensure nothing
goes too drastically wrong.
Scott Patterson, a Wall Street Journal reporter and author of The Quants, uses
the analogy of a plane on autopilot, which can fly itself but where a
specially-trained pilot can step in at any moment.
Continue reading the main story
Flash Crash
Chart showing the flash crash of 6 May 2010
On 6 May 2010, the Dow Jones tanked 700 points then recovered within minutes.
The culprit? A cascade of sales by quant trading programs.
Had the losses not been recovered when the programs were overridden, the Dow
would have suffered one of its biggest one-day falls in history.
These programs are immensely powerful, constantly monitoring market movements,
trading patterns and news flows and are capable of changing strategies within
fractions of a second.
The most powerful even have artificial intelligence that can adapt strategies
of their own accord.
No-one can be sure quite how successful these quant programs are, but as Mr
Patterson says: "They have been around long enough now to assume they are
extremely profitable".
Their proliferation would certainly suggest so. One commentator says two of the
biggest HFT firms, Tradebot and Getco, alone account for about 15%-20% of all
equity trading in the US.
As they are private companies, it is hard to know precisely how far their
influence extends.
Indeed, a recent government-backed study in the UK estimated that between a
third and a half of all share trading in Europe, and more than two-thirds in
the US, was HFT.
"The vast majority of firms use quantitative trading," says Mr Patterson.
"It drives almost everything that goes on on Wall Street."
Chain reaction
The impact and ramifications of quant trading are widespread, but ultimately
unclear.
The UK study, conducted by the Foresight programme, found that quant trading
helped to reduce dealing costs and improve liquidity, and did not harm overall
market efficiency.
In fact, it found that HFT and quant trading have "generally improved market
quality".
However, it did highlight one important concern, known in the trade as
self-reinforcing feedback loops.
This essentially means a small trigger leading to a series of similar events,
each amplifying the last, until the overall impact is significant.
Imagine a share falls in value, triggering a sale on one quant program, pushing
the share price even lower. This in turn triggers a sale on another program,
pushing the price lower still, and so on and so on.
The problem is exacerbated by the fact that many programs run on the same
formulae, and so are piling in and out of the same stocks.
Feedback loop on the financial markets
Nowhere is this better demonstrated than by the so-called Flash Crash of May
last year, when the US stock market plummeted 700 points in less than five
minutes, wiping out about $800bn ( 517bn).
When the auto-pilot switches were turned off and the systems overridden, order
was restored and the market bounced back within half an hour.
An unfortunate one-off, some say. Others point to far more damaging
consequences, citing quant trading as a key contributor to the massive sell-off
in stocks in 2008 that saw the US market almost halve in value.
Hedge funds, they say, sold equities fast in order to balance heavy losses on
their mortgage investments following the collapse of the US property market,
triggering a domino effect across quant trading systems with devastating
consequences.
The Foresight study found no direct evidence that automated trading has
increased volatility in equity markets, but many disagree, Mr Patterson among
them.
Stock market historian David Schwartz is another who is in no doubt that HFT
has unsettled markets.
"I believe [certain types of HFT] cause a great deal of damage," he says.
"I've seen too many instances during the recent sell-off where a sudden spurt
of frequent trades has sent share prices bouncing down."
The problem is proving it. No-one knows exactly who is making the trades, while
the exchanges have no incentive to find out as they are making a great of money
from them, Mr Schwartz says.
'Unintended consequences'
Others argue the problem is more fundamental. Mathematicians, they say, do not
understand markets. They deal in absolutes, not the irrational human behaviour
that drives so many investment decisions.
New York trader Traders are under threat from ever-more complex computer
programs
As one leading actuary says: "Prices are determined by supply and demand, not
by mathematics."
Could it be, then, that academic statisticians are congenitally unsuited to the
job they are being paid to do?
Paul Wilmott, a prominent lecturer in quantitative finance, has questioned
whether they are "capable of thinking beyond maths and formulas".
"Do they appreciate the human side of finance, the herding behaviour of people,
the unintended consequences?"
And if mathematicians do not, there is little chance the computer programmes
they create will.
As the Foresight report concludes: "Future trading robots will be able to adapt
and learn with little human input. Far fewer human traders will be needed in
the major financial markets of the future".
No bad thing, some may say, particularly given recent cases of insider trading
and fraud, but Mr Patterson is in no doubt that the proliferation of quant
trading is both "inevitable and dangerous".
Far-fetched it may seem, given the widespread disdain in which traders are
currently held, but if mathematicians and their algorithm programs prove a poor
substitute, we could find ourselves clamouring for their return.