Copyright Ian Pearson, BT Futurologist
Click here for contact details, other articles and personal details
IT and the Future of the City, June 1998
Fast computing and geographic location
In the next 10 years, we will probably see a factor of
1000 in computer speed and memory capacity. In parallel with hardware
development, there are numerous research forays into software techniques that
might yield more factors of 10 in the execution speed for programs. Tasks that
used to take a second will be reduced to a millisecond. As if this impact were
not enough, software will very soon be able to make logical deductions from the
flood of information on the internet, not just from Reuters or Bloomberg, but
from anywhere. They will be able to assess the quality and integrity of the
data, correlate it with other data, run models, and infer likely other events
and make buy or sell recommendations. Much dealing will still be done
automatically subject to human-imposed restrictions, and the speed and quality
of this dealing could far exceed current capability.
Which brings problemsÉ
Firstly, the speed of light is fast but finite. With
these huge processing speeds, computers will be able to make decisions within
microseconds of receiving information. Differences in distance from the
information source become increasingly important. Being just 200m closer to the
Bank of England makes one microsecond difference to the time of arrival of
information on interest rates, the information, insignificant to a human, but
of sufficient duration for a fast computer to but or sell before competitors
even receive the information. As speeds increase further over following years,
the significant distance drops. This effect will cause great unfairness
according to geographic proximity to important sources. There are two
solutions. Either there becomes a strong premium on being closest, with rises
in property values nearby to key sources, or perhaps network operators could be
asked to provide guaranteed simultaneous delivery of information. This is
entirely technically feasible but would need regulation, otherwise users could
simply use alternative networks.
Secondly, exactly simultaneous processing will cause
problems. If many requests for transactions arrive at exactly the same moment,
computers or networks have to give priority in some way. This is bound to be a
source of contention. Also, simultaneous events can often cause malfunctions,
as was demonstrated perfectly at the launch of Big Bang. Information waves
caused by such events are a network phenomenon that could potentially crash
networks.
An interesting future side effect of this is that the
predicted flood of people into the countryside may be averted. Even though people
can work from anywhere, their computers have to be geographically very close to
the information centres, i.e. the City. Automated dealing has to live in the
city, human based dealing can work from anywhere. If people and machines work
together, they must both work in the City.
Consumer share dealing and software
Ultra-powerful palmtop computers will soon have built
in access to networks so will pick up and analyse information all day long, while
organising every aspect of their owners' lives. They will be so useful that
most people will carry one. There may be millions in London for instance.
People with these computers will be able to
continuously see which shares are doing well, spot trends and act on their
computerÕs advice at a button push. Markets will grow for tools to profit from
shares, whether they be dealing software, advice services or visualisation
software.
However, as we see more people buying personal access
to share dealing and software to determine best buys, or even to automatically
buy or sell on certain clues, we will see some very negative behaviours.
Firstly, traffic will be highly correlated if personal computers can all act on
the same information at the same time. We will see information waves, and also
enormous swings in share prices. Most private individuals will suffer because
of this, while institutions and individuals with better software will benefit.
This is because prices will rise and fall simply because of the correlated
activity of the automated software and not because of any real effects related
to the shares themselves. Institutions may have to limit private share
transactions to control this problem, but can also make a lot of money from
modelling the private software and thus determining in advance what the
recommendations and actions will be, capitalising enormously on the resultant
share movements, and indeed even stimulating them. Of course, if the
share-dealing public generally perceives this problem, the AI software will not
take off so the problem will not arise. What is more likely is that such
software will sell in limited quantities, causing the effects to be
significant, but not destroying the markets.
A money making scam is thus apparent. A company need
only write a piece of reasonably good AI share portfolio management software
for it to capture a fraction of the available market. The company writing it
will of course understand how it works and what the effects of a piece of
information will be (which they will receive at the same time), and thus able
to predict the buying or selling activity of the subscribers. If they were then
to produce another service which makes recommendations, they would have even
more notice of an effect and able to directly influence prices. They would then
be in the position of the top market forecasters who know their advice will be
self fulfilling. This is neither insider dealing nor fraud, and of course once
the software captures a significant share, the quality of its advice would be
very high, decoupling share performance from the real world. Only the last
people to react would lose out, paying the most, or selling at least, as the
price is restored to ÔcorrectÕ by the stock exchange, and of course even this is
predictable to a point. The fastest will profit most.
The most significant factor in this is the proportion
of share dealing influenced by that company's software. The problem is that
software markets tend to be dominated by just two or three companies, and the
nature of this type of software is that their is strong positive reinforcement
for the company with the biggest influence, which could quickly lead to a
virtual monopoly. Also, it really doesnÕt matter whether the software is on the
visualisation tools or AI side. Each can have predictability associated with
it.
It is interesting to contemplate the effects this
widespread automated dealing would have of the stock market. Black Monday is
unlikely to happen again as a result of computer activity within the City, but
it certainly looks like prices will occasionally become decoupled from actual
value, and price swings will become more significant. Of course, much money can
be made on predicting the swings or getting access to the software-critical
information before someone else, so we may see a need for equalised delivery
services. Without equalised delivery, assuming a continuum of time, those
closest to the dealing point will be able to buy or sell quicker, and since the
swings could be extremely rapid, this would be very important. Dealers would
have to have price information immediately, and of course the finite speed of
light does not permit this. If dealing time is quantified, i.e. share prices
are updated at fixed intervals, the duration of the interval becomes all
important, strongly affect the nature of the market, i.e. whether everyone in
that interval pays the same or the first to act gain.
Also of interest is the possibility of agents acting
on behalf of many people to negotiate amongst them to increase the price of a
companyÕs shares, and then sell on a pre-negotiated time or signal.
Such automated systems would also be potentially
vulnerable to false information from people or agents hoping to capitalise on
their correlated behaviour.
Who would be liable if I write, and sell to a company,
some AI share dealing software that deduces by itself how stock market
fluctuations arise, and if it then commits a fraud such as insider dealing?
What if the law had changed since it was written?
Of course, the City would eventually react to
destructive trends and preventative measures will hopefully be imposed.
Meanwhile, we can expect problems.