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Stochastic modelling for evolution of stock prices by means of functional principal component analysis

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  • Ana M. Aguilera
  • Francisco A. Ocaña
  • Mariano J. Valderrama

Abstract

The objective of this paper is to apply functional principal component analysis to model and forecast financial prices of the banking in Madrid Stock Market from weekly observations of a random sample of banks. It is well known that direct statistical analysis of stock prices is difficult, therefore principal component prediction models for weekly returns are performed to give appropriate forecasts for prices. Copyright © 1999 John Wiley & Sons, Ltd.

Suggested Citation

  • Ana M. Aguilera & Francisco A. Ocaña & Mariano J. Valderrama, 1999. "Stochastic modelling for evolution of stock prices by means of functional principal component analysis," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 15(4), pages 227-234, October.
    • Handle: RePEc:wly:apsmbi:v:15:y:1999:i:4:p:227-234
    DOI: 10.1002/(SICI)1526-4025(199910/12)15:43.0.CO;2-C
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    Cited by:

    1. Moliner, Jesús & Epifanio, Irene, 2019. "Robust multivariate and functional archetypal analysis with application to financial time series analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 519(C), pages 195-208.

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