Repository method to suit different investment strategies

— This work is motivated by the interest in finding significant movements in financial stock prices. The detection of such movements is important because these could represent a good opportunity to invest. However, when the number of profitable opportunities is very small the prediction of these cases is very difficult. In previous works Repository Method (RM) was introduced. The aim of this approach is to classify financial data sets in extreme imbalanced environments. RM offers a range of solutions to suit the risk guidelines of the investor. The aims of this paper are 1) to show that RM can produce a range of solutions to suit the investor requirements and 2) to analyze the influence of the evolutionary process in the RM performance. Three series of experiments were performed, RM was tested using two artificial data sets whose solutions have different level of complexity. Finally RM was tested in a data set from the London stock market. Experimental results show: 1) RM off...

• Type: Conference
• Year: 2007
• Where: CEC
• Authors: Alma Lilia Garcia-Almanza, Edward P. K. Tsang
• Keywords: Artificial Intelligence, CEC 2007, Data Set, Evolutionary Process, Risk Guidelines