The Sierpinski triangle is a fractal that is commonly used due to some of its characteristics and features. The Forex financial market is among the places wherein this trianglechr('39')s characteristics are effective in forecasting the prices and their direction changes for the selection of the proper trading strategy and risk reduction. This study presents a novel approach to the Sierpinski tr...

modelling and forecasting stock market is a challenging task for economists and engineers since it has a dynamic structure and nonlinear characteristic. this nonlinearity affects the efficiency of the price characteristics. using an artificial neural network (ann) is a proper way to model this nonlinearity and it has been used successfully in one-step-ahead and multi-step-ahead prediction of di...

Abstract: It is very important to minimize the risk in portfolio selection. For minimizing risk of portfolio at a given expected returns, it is efficient to compose portfolio with stocks which have low cross-correlation among them. In this regard, forecasting the cross-correlations among stock prices has attracted much interest among investors and financial market researchers. Most of studies i...

â â â  â â â  abstract â  using a structural var with block exogeneity, diagonality and identifying restrictions, this paper analyzes: first, the macroeconomic linkages among the oil price, u.s. output, interest rate, money supply, general price level and exchange rate and second, the relationships of the macroeconomic variables with the price indices of ten international nonfuel commodity grou...

An important financial subject that has attracted researchers' attention for many years is forecasting stock return. Many researchers have contributed in this area of chaotic forecast in their ways. Among them data mining techniques have been successfully shown to generate high forecasting accuracy of stock price movement. Nowadays, instead of a single aspects of stock market, traders need...