Publication Type : Book Chapter
Publisher : Springer, Dordrecht
Source : Innovations and Advanced Techniques in Computer and Information Sciences and Engineering
Url : https://link.springer.com/chapter/10.1007/978-1-4020-6268-1_19
Keywords : Time Series Signal Analysis Time Series Analysis Deterministic Stochastic.
Campus : Coimbatore
School : School of Engineering
Department : Computer Science
Year : 2007
Abstract : A discrete- time signal or time series is set of observations taken sequentially in time, space, or some other independent variable. Examples occur in various areas including engineering, natural sciences, economics, social sciences and medicine. Financial time series in particular are very difficult to model and predict, because of their inherent nature. Hence, it becomes essential to study the properties of signal and to develop quantitative techniques. The key characteristics of a time series are that the observations are ordered in time and that adjacent observations are related or dependent. In this paper a case study has been performed on the BSE and NSE index data and methods to classify the signals as Deterministic, Random or Stochastic and White Noise are explored. This pre-analysis of the signal forms the basis for further modeling and prediction of the time series.
Cite this Research Publication : Dr. Bhagavathi Sivakumar P. and Mohandas, V. P., “Evaluating the Predictability of Financial Time Series - A case study on SENSEX data”, in Innovations and Advanced Techniques in Computer and Information Sciences and Engineering - Edited by Tarek Sobh, Springer, 2007, pp. 99–104.