Munich Personal RePEc Archive

Estimation of Fractal Parameters of Tehran Stock Market Groups Time Series Using Discrete Wavelet Transform

Golmohammadpoor Azar, Kamran (2014): Estimation of Fractal Parameters of Tehran Stock Market Groups Time Series Using Discrete Wavelet Transform. Published in: First National Conference of Applied Statistics, Department of Statistics, Islamic Azad University of Tabriz, Tabriz, Iran. (23 June 2014)

[img]
Preview
PDF
MPRA_paper_58597.pdf

Download (506kB) | Preview

Abstract

Nowadays financial markets such as stock markets, gold and currency because of their significant returns are the investors’ main target. Their aim is to invest in a way that they can earn the highest profit. Among these markets, the stock market is of utmost importance since it deals with buying and selling the shares of diverse companies. Thus using the approaches that yield the highest profit and the lowest risk is the greatest priority of investors. This paper wants to calculate the chaotic indicators in different groups of Tehran’s stock market using Discrete Wavelet Transform. For this purpose, by utilizing the wavelet toolbox of Matlab software, Hurst exponent and Fractal Dimension and Predictability index of Tehran stock market’s groups time series were estimated. Results prove that almost all of the group’s time series are demonstrating Non-Gaussian behavior. And the type of time series’ memories whether they are short-term or long-term were identified. Furthermore, Predictability indices of time series were calculated which is also useful in investor’s decision making.

UB_LMU-Logo
MPRA is a RePEc service hosted by
the Munich University Library in Germany.