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This paper surveys recent literature in the area of Neural Network, Data Mining, Hidden Markov Model and Neuro-Fuzzy system used to predict the stock market fluctuation. Neural Networks and Neuro-Fuzzy systems are identified to be the leading machine learning techniques in stock market index prediction area. The Traditional techniques are not cover all the possible relation of the stock price f...

The behaviour of multiple stock markets can be described within the framework of complex dynamic systems (CDS). Using a global model with the Kalman Filter we are able to extract the dynamic interaction network (DIN) of these markets. The model was shown to successfully capture interactions between stock markets in the long term. In this study we investigate the effectiveness of two different p...

We investigate the fluctuation behaviors of financial stock markets by Zipf analysis. In the present paper, the empirical research is made to describe ensembles and specifics of stock price returns for global stock indices, and the corresponding Zipf distributions are given. First we study the fluctuation behavior of global stock markets by m, k -Zipf method. Then we consider a dynamic stock pr...

T his paper investigates the movement between stock market bubbles and fluctuations in aggregate variables within a DSGE model for the Iranian economy. We apply a new Keynesian monetary framework with nominal rigidity in wages and prices based on the study by Ikeda (2013), which is developed with appropriate framework for the Iranian economy. We consider central bank behavior differe...

Although stock option markets have grown dramatically over the past several decades, the relation between an option and its underlying asset, especially bidirectional conduction, is not particularly clear. So far, there have been many debates about this topic. We try to investigate this problem from a novel angle: an artificial stock market including a stock option is constructed in this paper....

abstract the purpose of this paper is to investigate the relationship between capital stock and increasing the productivity of labor and total factor productivity (tfp) in industrial groups of khorasan razavi province from 2003 to 2007. in order to this first, the available literature in this area and the importance of productivity was reviewed, also the history of productivity in asia and the ...

In this paper, we consider the statistical properties of chain reaction of stock indices. The theory of interacting systems and statistical physics are applied to describe and study the fluctuations of two stock indices in a stock market, and the properties of the interacting reaction of the two indices are investigated in the present paper. In this work, stochastic analysis and the two random ...

Stock prices have the characteristics of nonlinearity, randomicity and uncertainty, so It is difficult to accurately depict the change rules of stock prices using traditional linear forecasting methods, which lead to low stock price prediction accuracy. In order to improve the stock price prediction precision , this paper proposed a stock price predicting model using SVM optimized by particle s...

In this paper, we propose a Hybrid Kansei-SOM model, using Kansei Evaluation integrated with Self-Organizing Map (SOM) for stock market investment strategies. The proposed approach, using a group Decision Support System (DSS), aims to aggregate experts’ preferences with the selection of the most suitable stocks, matching with investing strategies to achieve investment returns by dealing with co...