The jamor purpose of the present research is to predict the total stock market index of Tehran Stock Exchange, using a combined method of Wavelet transforms, Fuzzy genetics, and neural network in order to predict the active participations of finance market as well as macro decision makers.To do so, first the prediction was made by neural network, then a series of price index was decomposed by w...

to achieve the optimal model for capital asset pricing has always been a central issue in studies of the financial field. in this study we consider fama and french three-factor model augmented by the pastor and stambaugh (2003) liquidity risk factor. unlike most previous studies in this model, stock level beta is allowed to vary with firm-level size and book-to-market value. to verify the above...

We report an empirical study of Tehran Price Index (TEPIX). To analyze our data we use various methods like as, rescaled range analysis (R/S), modified rescaled range analysis (Lo’s method), Detrended Fluctuation Analysis (DFA) and generalized Hurst exponents analysis. Based on numerical results, the scaling range of TEPIX returns is specified, long memory effect or long range correlation prope...

there have been several efforts in the literature to extract as much information as possible from the financial networks. most of the research has been concerned about the hierarchical structures, clustering, topology and also the behavior of the market network; but not a notable work on the network filtration exists. this paper proposes a stock market filtering model using the correlation - ba...

this paper investigates the asymmetry in volatility of returns for the iranian stock market using the daily closing values of the tehran exchange price index (tepix) covering the period from march 25, 2001 to july 25, 2012, with a total of 2743 observations. to this end, two sets of tests have been employed: the first set is based on the residuals derived from a symmetric garch (1,1) model. the...

the jamor purpose of the present research is to predict the total stock market index of tehran stock exchange, using a combined method of wavelet transforms, fuzzy genetics, and neural network in order to predict the active participations of finance market as well as macro decision makers.to do so, first the prediction was made by neural network, then a series of price index was decomposed by w...

because of its extensive applications in financial analysis, stock market volatility modeling is a significantly important issue for stock market practitioners and academicians. using garch models to formulate the conditional variance heteroskedasticity and the taking advantages of panel data technique such as higher degrees of freedom, more flexibility in the control of the omitted or unobserv...