• DocumentCode
    1679548
  • Title

    The prediction performance of independent factor models

  • Author

    Chan, Lai-Wan

  • Author_Institution
    Comput. Sci. & Eng. Dept., Chinese Univ. of Hong Kong, Shatin, China
  • Volume
    3
  • fYear
    2002
  • fDate
    6/24/1905 12:00:00 AM
  • Firstpage
    2515
  • Lastpage
    2520
  • Abstract
    In the literature, independent component analysis (ICA) has been proposed to construct factor models in finance. According to the basic principle, the factors extracted using ICA are expected to be independent of each other. This factor model is hence called the independent factor model, in contrast to the traditional factor models which assumes uncorrelated factors. We analyze and compare the performance of the independent factor model and the traditional factor model based on the prediction ability of the factors. Two examples are given to show that the independent factor model would reduce loss if we have good predictability on one of the factors. On the contrary, the uncorrelated factor model may not benefit from an accurate factor prediction
  • Keywords
    finance; forecasting theory; probability; finance; independent factor models; prediction ability; prediction performance; Accuracy; Computer science; Electronics packaging; Equations; Finance; Independent component analysis; Performance analysis; Portfolios; Predictive models; Security;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2002. IJCNN '02. Proceedings of the 2002 International Joint Conference on
  • Conference_Location
    Honolulu, HI
  • ISSN
    1098-7576
  • Print_ISBN
    0-7803-7278-6
  • Type

    conf

  • DOI
    10.1109/IJCNN.2002.1007539
  • Filename
    1007539