publisher_address = "New York, NY, 10286-1405, USA",
month = "8-12 " # jul,
organisation = "ACM SIGEVO (formerly ISGEC)",
keywords = "genetic algorithms, genetic programming: Poster,
connectionism and neural nets, ANN, finance, high-order
statistical function set, language acquisition,
parameter learning, prediction/forecasting, time series
analysis, trigonometric function set",
size = "2 pages",
abstract = "This paper describes an extension of the traditional
application of Genetic Programming in the domain of the
prediction of daily currency exchange rates. In
combination with trigonometric operators, we introduce
a new set of high-order statistical functions in a
unique representation and analyse each system
performance using daily returns of the British Pound
and Japanese Yen. We will demonstrate that the
introduction of high-order statistical functions in
combination with trigonometric functions will
outperform other traditional models such as Genetic
Programming with the basic function set and ARMA
models. Performance will be measured on hit percentage,
average percentage change, and profit.",
notes = "GECCO-2006 A joint meeting of the fifteenth
international conference on genetic algorithms
(ICGA-2006) and the eleventh annual genetic programming
conference (GP-2006).