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Paper Information

Journal:   MODARRES HUMAN SCIENCES   Fall 2003 , Volume 7 , Number 3(Tome 30); Page(s) 61 To 88.
 
Paper: 

EVALUATING METHODS OF THE SHARE PRICE FORECASTABILITY IN TEHRAN STOCK EXCHANGE

 
 
Author(s):  KHALOUZADEH H.*, KHAKI SEDIGH A.
 
* Mashhad, Iran
 
Abstract: 
In this paper, we deal with several time series of daily share prices and daily returns ‎of different companies which are members of the Tehran Stock Exchange. Three ‎forecastability methods as nonlinear mathematical analysis were applied to the data ‎obtained for daily share prices and daily returns in Tehran Stock Exchange during ‎three and half years. The characteristics of the process associated with these time ‎series were analyzed‏. ‏‎
‎ Analyzing the behavior of the time series associated with these companies is ‎indicative of their short-term predictability nature. However, using analysis regarding ‎the correlation dimension estimate, indicated that only the time series information are ‎not adequate for prediction and other appropriate variables must also be used. Also, ‎using a Rescaled-range analysis, showed that past information have long term effects ‎on the market and are useful in the process of prediction. Also, the analysis of the ‎Largest Lyapunov Exponent estimate revealed a weakly chaotic behavior and ‎indicated that time series data cannot be used in the prediction process after a certain ‎time‏.‏‎
‎ It is shown the time series generator process of these companies are complex ‎nonlinear mappings and the methods based on the various linear modeling strategies ‎are unable to identify these dynamics‏.‏
 
Keyword(s): TIME SERIES, FORECASTABILITY, NONLINEAR ANALYSIS OF TIME SERIES, NONLINEAR, CHAOTIC AND STOCHASTIC PROCESS, LYAPUNOV EXPONENT, CORRELATION DIMENSION ESTIMATE.
 
References: 
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