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

2 Citations (Scopus)


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 back-propagation 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 publicationCommunications in Computer and Information Science
EditorsD.M. Akbar Hussain, Abdul Qadeer Khan Rajput, Bhawani Shankar Chowdhry, Quintin Gee
Number of pages12
Publication statusPublished - 2009
Externally publishedYes

Publication series

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


  • Correlation dimension
  • KSE-100 index returns
  • Neural network
  • Non-linear time series analysis


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