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Title

CHAOS AND NONLINEAR STOCK PRICE INDEX OF TEHRAN STOCK EXCHANGE

Pages

 Start Page 55 | End Page 74

Abstract

 The stock price indices are indispensable variables in economic systems, these usually complicated time series are almost stochastic, and hence their variation is assumed unpredictable. For this purpose, nonlinear and PREDICTABLE examinations are used to test the existence of determined chaotic trend and NONLINEAR PROCESS in daily time series of Tehran’s stock index from 1387/4/8 to 1392/7/10.The results reflect that sign test proves the non-stochastic nature of price index. The BDS’ results and those of sign test show that stock price index follows a NONLINEAR PROCESS. The independence tests like BDS test, White test, Chow test, test the correlation between observations in which the results are affirmative. Moreover, the cointegration-adjusted tests are used for testing the chaotic process of the price index and the results of both are affirmative. For predicting the stock price index in ongoing periods, we have used ARFIMA, FIGARCH, LSTAR, and ESTAR. Among those models, which examine the existence of long run memory in stock price index, FIGARCH, which tests the long run memory and variance, has the most capacity of accurate prediction. Among the nonlinear models, ESTAR has the most capacity. At the last, prediction is reported for ten periods with the one head process.

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