This paper analyses the performance of machine learning models in forecasting Tehran Stock Exchange's automobile index. Historical daily data from 2018-2022 was pre-processed and used to train Linear Regression (LR), Support Vector (SVR), Random Forest (RF) models. The were evaluated on mean absolute error, squared root error R2 score metrics. results indicate that LR SVR outperformed RF predic...

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...

in this paper, we have estimated the memory of thetehran stock exchange indices. the estimation of fractional differencing parameter is carried out by various methods such as mle, nls, hurst exponent, gph, lo, whittle and wavelet. the estimation results of whittle, wavelet, hurst, and lo methods allow us to conclude that the returns on stock indices (tepix, tedpix, tedix, financial index and in...

us 2008 financial crisis, spreaded out across the international stock markets in the second half of the year 2008. the crisis decreased the returns and increased the volatilities of almost all of the stock indices, however, its effects on iran’s stock markets were unexplored. financial limitations create an exclusive situation in iran’s stock market. using weekly data on the stock indices from ...

the goal of this research is to predict total stock market index of tehran stock exchange, using the compound method of arima and neural network in order for the active participations of finance market as well as macro decision makers to be able to predict trend of the market. first, the series of price index was decomposed by wavelet transform, then the smooth's series  predicted by using...

One of the best ways to make money on capital market is buy shares stock exchange. The has a nonlinear and chaotic system that influenced by political, economic, psychological conditions, systems such as regression can be used predict prices. In this research, different models are used, each which measures information in way tests ability behaviour index prices with information. This paper exam...

The purpose of this research is to predict stock returns and the purpose of the least squares regression and neural network approach is used. The potential financial ratios based on the historical cost and financial ratios based on Adjusted Cost predict stock returns are investigated. Independent variables and the dependent variable in this study and financial ratios and stock returns is for th...

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...