Author: Wu, Shanlei
Title: GP-based financial market forecast
Degree: M.Sc.
Year: 2011
Subject: Hong Kong Polytechnic University -- Dissertations
Genetic programming (Computer science)
Stock price forecasting
Stock exchanges -- Forecasting
Department: Faculty of Engineering
Pages: 67 leaves : ill. (some col.) ; 30 cm.
Language: English
Abstract: Genetic programming is a technique to automatically discover computer programs using the principles of Darwinian evolution. Since its inception, genetic programming has been used to solve many practical problems, producing a number of human competitive results and even patentable new inventions. This dissertation first presents the theory of genetic programming, and introduces its basic process for solving problems. Then we explain the fundamental idea of technical analysis in stock trading and discuss some important technical indicators that can be used in price prediction with genetic programming. In the experiments, we use the historical data together with the technical indicators extracted from the data for the price prediction with genetic programming. Hang Seng Index (HSI) between 2000 and 2008 are used as the training data and different window sizes are investigated. As a comparison, other computational intelligence methods including K-Nearest Neighbor (KNN), Support Vector Machine (SVM), Back Propagation (BP) network, and Genetic Algorithm (GA) are also evaluated on the same data. Experimental results show the genetic programming can produce a comparable performance with some attractive features.
Rights: All rights reserved
Access: restricted access

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