www.the-actuary.org.uk
Actuaries versus quants
Soapbox Paul Wilmott
Professor Paul Wilmott says quantitative egotists
could learn much from actuaries
10 October 2008
T
hose working in the fields of
actuarial science and quantitative
finance have not always been
totally appreciative of each
others' skills. Actuaries have been dealing
with randomness and risk in finance
for centuries. Quants are the relative
newcomers, with all their fancy stochastic
mathematics. Rather annoyingly for
actuaries, quants came along late in the
game and thanks to one piece of insight
in the early 1970s completely changed the
face of the valuation of risk.
The insight I refer to is the concept
of dynamic hedging, first published by
Black, Scholes and Merton in 1973. Before
1973, derivatives were being valued using
the `actuarial method', in a sense relying,
as actuaries always have, on the Central
Limit Theorem. Since 1973 all that has been
made redundant. Quants have ruled the
financial roost.
However, this might just be the time for
actuaries to fight back.
Stopped working
I am putting the finishing touches to this
article a few days after the first anniversary
of the `day that quant died'. In early
August 2007, a number of high-profile and
previously successful quantitative hedge
funds suffered large losses. People said that
their models "just stopped working". The
year since has seen a lot of soul searching
by quants -- how could this happen when
they've got such incredible models?
In my view, the main reason why
quantitative finance is in a mess is because
of complexity and obscurity. Quants
are making their models increasingly
�It's about time that actuaries
got more involved in quantitative
finance and brought some common
sense back into this field �
complicated, in the belief they are making
improvements. This is not the case. More
often than not each `improvement' is a
step backwards. If this were a proper hard
science then there would be a reason for
trying to perfect models. But finance is
not a hard science, one in which you can
conduct experiments for which the results
are repeatable. Finance, thanks to it being
underpinned by human beings and their
wonderfully irrational behaviour, is forever
changing. It is, therefore, much better to
focus attention on making the models
robust and transparent rather than ever
more intricate.
As I mentioned in a recent blog, there
is a maths sweet spot in quant finance.
The models should not be too elementary
so as to make it impossible to invent new
structured products, but nor should they
be so abstract as to be easily misunderstood
by all except their inventor (and sometimes
even by them), with the obvious and
financially dangerous consequences. Our
goal is to make quant finance practical,
understandable and, above all, safe.
When banks sell a contract they do so
assuming it is going to make a profit. They
use complex models, with sophisticated
numerical solutions, to come up with the
perfect value. Having gone to all that effort
they then throw it into the same pot as all
Paul Wilmott is a financial consultant, specialising in
derivatives, risk management and quantitative finance.
He is the proprietor of www.wilmott.com, Wilmott
magazine, and is the course director for the Certificate
in Quantitative Finance.
the others and risk-manage en masse. The
funny thing is they never know whether
each individual contract has "washed its own
face". Sure they know whether the pot has
made money, their bonus is tied to it. But
each contract? It makes good sense to risk-
manage all contracts together but not to go
into such obsessive detail in valuation when
ultimately it's the
portfolio that makes
money, especially if
the basic models are
so dodgy. The theory
of quant finance and
the practice diverge.
Money is made by
portfolios, not by individual contracts.
A respect for risk
In other words, quants make money
from the Central Limit Theorem, just like
actuaries, it's just that quants are loath to
admit it! Ironic.
It's about time that actuaries got more
involved in quantitative finance and
brought some common sense back into
this field. We need models people can
understand and a greater respect for risk.
Actuaries and quants have complementary
skill sets. What high finance needs now
are precisely the skills that actuaries have,
a deep understanding of statistics, an
historical perspective, and a willingness to
work with data.

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