A dynamical system and neural network perspective of Karachi stock exchange

Syed Nasir Danial, Syed Raheel Noor, Bilal A. Usmani, S. Jamal H. Zaidi

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


This study discusses the evolution of KSE-100 index returns as a dynamical system. We present application of nonlinear time-series analysis. Our results show that estimation of correlation dimension for the case of KSE-100 index returns is not possible. We further go into nonlinear analysis and construct a model of the series based on feedforward neural network with backpropagation training. We construct many neural networks and the one with Levenberg-Marquardt backpropagation is found to give slightly better results compared to ARMA/ARIMA models. Neural networks are found to be applicable in those cases when nonlinear time-series analysis is at failure.

Original languageEnglish
Title of host publicationWireless Networks, Information Processing and Systems - International Multi Topic Conference, IMTIC 2008, Revised Selected Papers
PublisherSpringer Verlag
Number of pages12
ISBN (Print)3540898522, 9783540898528
Publication statusPublished - 2008
Externally publishedYes

Publication series

NameCommunications in Computer and Information Science
Volume20 CCIS
ISSN (Print)1865-0929


  • KSE-100 index returns
  • Neural network
  • correlation dimension
  • non-linear time series analysis


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