We present an empirical study of the subordination hypothesis for a stochastic time series of a stock price. The fluctuating rate of trading is identified with the stochastic variance of the stock price, as in the continuous-time random walk (CTRW) framework. The probability distribution of the stock price changes (log-returns) for a given number of trades N is found to be approximately Gaussia...

the goal of this research was prioritize effective financial factors on price stock in tehran stock exchange with using topsis method. based on, it was reviewed literature and interviews and specially questionnaire obtain, effective financial factors to analysis with emphasize on topsis technique. the results shown in the entire ratio price to income, historical event share, eps and return on a...

This paper aims to determine the impact of dividend policy on stock price volatility by taking firms listed on Tehran stock exchange.  A sample of 68 listed companies from Tehran stock exchange is examined for a period from 2001 to 2012.  The estimation is based on cross-sectional ordinary least square regression analysis to find the relationship between share price volatility and dividend poli...

U sing daily data, this study examined asymmetric pass-through of Iran’s oil price to banking stock index in Tehran Stock Exchange at different time horizons. Based on the results, the coefficient of long-run pass-through of oil price to banking stock index was estimated to be 0.63. Furthermore, based on the short-term ARDL-CECM models, the relationship between the positive component...

Stock price prediction is an important and challenging problem in stock market analysis. Existing prediction methods either exploit autocorrelation of stock price and its correlation with the supply and demand of stock, or explore predictive indictors exogenous to stock market. In this paper, using transaction record of stocks with identifier of traders, we introduce an index to characterize ma...

in this study, 3 models of time-varying parameters (tvp), dynamic model selection (dms) and dynamic model averaging (dma) and a comparison with the ordinary least squares (ols) method in matlab in the time period 2003-2013 (with data on a monthly basis) are discussed. in the present study, the variables of unofficial exchange rate changes, interest rate changes and inflation in oil price foreca...

This paper describes the prediction scheme of stock price by using multiagent systems. Agents predict the stock price according to their strategies which is defined from technical and fundamental parameters such as some index related to the stock price, the currency exchange rate of the Japanese Yen (JPY) against the US Dollar and so on. Agents are randomly generated to construct population and...

In this paper, the effects of oil and gold prices on stock market index are investigated. We use a cointegrated vector autoregressive Markov-switching model to examine the nonlinear properties of these three variables during the period of January 2003 - December 2014. The Markov-switching vector-equilibrium-correction model with three regimes representing "deep recession", "mild recession" and ...

In this study, a novel adaptive learning algorithm for feed-forward network based on optimized instantaneous learning rates is proposed to predict stock market movements. In this new algorithm, the optimized adaptive learning rates are used to adjust the weight changes dynamically. For illustration and testing purposes the proposed algorithm is applied to two main stock price indices: S&P 500 a...