جستجوی مقالات مرتبط با کلیدواژه « بعد فرکتالی » در نشریات گروه « اقتصاد »

The behavior of exchange rate in various exchange markets is not seemingly predictable, while there are different forecasting methods to do so. One of these methods is to use fractals to identify exchange rate behavior. This paper has made attempts to explore the properties of fractals in Iran’s exchange market in order to it can predict and analyze the trend of exchange rate. Accordingly, three factors of fractals have been introduced and measured. Then these factors have been examined for the Iranian currency (Rial) against the US dollar so that there are the fractal properties in the behavior of the exchange rate in Iran.

In this paper, we deal with several time series of share prices and daily returns of different companies which are members of Tehran Stock Exchange. Three prediction methods are used for time series forecasting. The first method is based on the linear models (ARIMA) for short-term and long-term forecasting. The second method is based on the nonlinear neural networks model and the third method is a neural networks model with a special structure. It has been shown that the time series generator process of these companies are complex nonlinear mappings and the methods based on the various linear modelling strategies are unable to identify these dynamics. Also, it has been shown by using the conventional structure of the nonlinear neural networks that one can not obtain a satisfactory result for long term forecasting. Finally, it is shown that the proposed structrure provides accurate next step and the long term share prices and daily returns forecasting.