Evolutionary Computation in Financial Decision Making
Created by W.Langdon from
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- @PhdThesis{Saks:thesis,
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author = "Philip Saks",
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title = "Evolutionary Computation in Financial Decision
Making",
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school = "University of Essex",
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year = "2008",
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address = "UK",
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keywords = "genetic algorithms, genetic programming, optimisation,
trading strategies, market efficiency, intraday data,
statistical arbitrage, portfolio construction, foreign
exchange and money management",
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URL = "http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.495562",
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size = "354 pages",
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abstract = "This thesis considers genetic programming (GP) for
evolving financial trading strategies. The traditional
approach in the literature is to represent a trading
strategy, or a program, as a single decision tree. This
thesis proposes a general multiple tree framework for
dynamic decision making, where evaluation is contingent
on the previous output of the program. The conditional
multiple tree structure nests the single tree as a
special case. Theoretically, it is a superior
alternative, but in practice this is not always the
case. It depends on the underlying problem, and is
basically a manifestation of Ockham's razor (Occam).
The framework is validated on artificial data, and
hereafter it is applied to two real financial problems:
statistical arbitrage and high-frequency foreign
exchange trading. In contrast to a pure arbitrage, that
guarantees a sure profit, a statistical arbitrage
strategy only produces a risk less profit in the limit.
Both schemes are self-funding. In this thesis, single
and dual trees are used to evolve statistical arbitrage
strategies on banking stocks within the Euro Stoxx
index. Both single and dual trees are capable of
discovering significant statistical arbitrage
strategies, even in the presence of a realistic market
impact. A finding that points to weak form market
inefficiencies. Moreover, it is found that the dual
trees provide a more robust response, compared to the
single trees, when the market impact is increased. The
foreign exchange application considers a novel quad
tree structure for evolving trading strategies. Each of
the four trees serve different functions, i.e., long
entry, long exit, short entry and short exit. Within
this framework, the effects of money management are
investigated for investors with different utility
functions. Money management refers to the way in which
practitioners use stop orders to control risk and take
profits. Despite being widely used, it is found that
money management has a detrimental effect on utility.",
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notes = "EThOS Persistent ID: uk.bl.ethos.495562 JEL
classifications: CO, CI5, C45, C53, C6I, C63, GIl",
- }
Genetic Programming entries for
Philip Saks
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