Portfolio Selection of Electron Sector Stock Based on Rough Set and Grey Theory

Abstract

This paper illustrates that rough set theory (RS), allied with the use of Grey Prediction, GM(1,N), K-means and Grey Relation, can out-perform the more standard approaches that are employed in economics, such as a Probit model. This study focuses on electron sector stock to select the optimal stock portfolio out applying the financial statement datum from the New Taiwan Economy database(TEJ). Firstly, we collect relative financial ratio datum as the conditional attributes selection and then use GM(1,1) for predicting, GM(1,N) for choosing the more important conditional attributes, and rough set for figuring the best portfolio out. Finally, conduct fund weight distribution using the grey relational method to reduce the investment risk. This study will demonstrate that rough sets model is applicable to stock portfolio. The empirical result in Taiwan: During five years (2003-2007), the average annual rate of return was 20.41%, the accumulated rate of return for nine-quarter was 61.22%. The portfolio determined by the model is a promising alternative to the conventional methods for economic and financial prediction.