Chaos Process Testing (Time-Series in The Frequency Domain) in Predicting Stock Returns in Tehran Stock Eechange

Abstract

Nowadays, the benefits of predicting are undeniably accepted in decision and policy making from different dimensions. Recently, structural models which were relatively successful in explaining the current situation have not been paid much attention in the field of forecasting. Most statistical observations have applied the tests which brought about wrong findings, and made them draw this conclusion that the obtained data from chaos-basis tests are random. However, these data are derived from systematic regulations which are accompanies with trivial disorders. Therefore, some other tests such as time-series tests in the frequency domain have been proposed. This test was utilized to assess the existence of chaotic processes in daily time-series on Tehran Stock Exchange over a period from 2007 to 2013. The achieved findings clearly demonstrate such processes during the process of this indicator.