List of Articles reza tehrani

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  1 - Nonlinear Dynamic Modeling of Factors Affecting the Stock Market: Baysian Quantile Threshold Regression - GARCH approach
  Reza Tehrani Mohammad Osoolian Saeed Bajalan Vahid Abbasion
  20.1001.1.22519165.1399.11.45.15.2
  During the last decade, studies on the factors affecting stock market returns have reached a peak with the advances of financial economics in the field of statistics and mathematics, and modeling is of great importance in this regard. Accordingly, this study seeks to pr More

  During the last decade, studies on the factors affecting stock market returns have reached a peak with the advances of financial economics in the field of statistics and mathematics, and modeling is of great importance in this regard. Accordingly, this study seeks to present a new approach to modeling the nonlinear relationship between financial variables and stock returns.This paper employs Bayesian Markov chain Monte Carlo (MCMC) sampling methods for updating the estimates and quantile threshold regression with heteroscedasticity. To study and model this approach, we used returns of the Tehran Stock Exchange, Coin Price, Oil, and Gold Price from 2011 to 2019. The results show that these variables have different effects under low and upper quantile levels. Also, the impact of the financial variables on the stock returns is different under higher and lower threshold amount for each quantile levels. Based on the result, we can say that stock returns have a nonlinear relationship with other markets in the bullish and bearish market. Manuscript profile
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  2 - Long Memory usage in Portfolio Optimization using the Copula‌ Functions: Empirical evidence of Iran and Turkey Stock Markets
  Hasti Chitsazan Motahareh Moghadasi Reza Tehrani Mohsen Mehrara
  20.1001.1.22519165.1400.12.49.20.2
  The main objective of this paper is to optimize and manage the portfolio by using copula functions. Copula function has been using as a powerful and flexible tool for the determination of dependency structure. Research data include the Iran stock market index and the Tu More

  The main objective of this paper is to optimize and manage the portfolio by using copula functions. Copula function has been using as a powerful and flexible tool for the determination of dependency structure. Research data include the Iran stock market index and the Turkey stock market index. The present study seeks to find the effect of long memory on the structure of dependence between returns and optimal portfolio structure. In the first step, we compare the dependence structure between the net returns and the filter generated from the ARFIMA-GARCH process returns to investigate the impact of long memory on them. In the second step, the influence of the dependence structure between net returns and filtered returns on portfolio optimization has been investigated. The results indicated that the model can be fitted to the return of time series and the best pattern is the frank pattern. The results also indicated the existence of long memory in the mean and variance of stock return on the Iran stock market and the existence of long memory in the variance of the Turkey stock market. All models allocate more percentage of capital to Iran stock market and lower percent to Turkey stock market. Manuscript profile
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  3 - Multiperiod portfolio selection with higher-order moment
  reza tehrani saeed Fallahpour Mohammad reza Rostami mehdi biglari kami
  20.1001.1.22519165.1397.9.37.1.8
  risk & return are two main factors that affect financial decisions. The trade off between risk & return create different investment strategies. In other words investment decisions are all based on risk & return. In this research we used multiperiod selection More

  risk & return are two main factors that affect financial decisions. The trade off between risk & return create different investment strategies. In other words investment decisions are all based on risk & return. In this research we used multiperiod selection method in order to maximize investors utility. In this model we used not only variance but also higher order moment –skewness- for optimization. For emprical test of the model we used return of first 50 companies stored by market capitalization in tehran stock exchange during 1386-1395. We used skewness & transaction cost to introduce a moltipriod model in asset allocation to minimize variance of investors utility. Comparing the result of this model with markowitz model & simpel model considering investor preferences shows that based on performance evaluation criteria, the suggested model perform much better than the two other. Manuscript profile
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  4 - High frequency pair trading with using Fuzzy SPC
  Mojtaba Dastoori saeed Fallahpour reza tehrani Mohamadreza Mehregan
  20.1001.1.22519165.1397.9.37.2.9
  In today's world, capital markets have increased the possibility to generate profits through high-frequency transactions due to the advancement of computer technology and the use of IT infrastructure. The main objective of this research is to examine and provide a model More

  In today's world, capital markets have increased the possibility to generate profits through high-frequency transactions due to the advancement of computer technology and the use of IT infrastructure. The main objective of this research is to examine and provide a model of paired trading algorithms that can generate higher returns than coherent algorithms. In the background study, one of the limitations of the paired trading algorithm is the use of constant limits and rules that cannot model the dynamics of the system. This research based on the purpose is applied research and in terms of collecting data in the form of descriptive research with the approach of presenting a model. In order to test the model, using the data of 1395, intraday stock prices was used. The statistical population of this study was the top 50 Tehran Stock Exchange companies, using filtering the stocks to create a pair of shares decreased to 33, these shares was selected as sample. The results of the study were presented by implementing two algorithms of paired trading algorithms and paired trading algorithms statistical process fuzzy control. Finally, the results showed that the modified algorithm during the similar period  of the investment  could produce 57.95% of the return, while the base model had 46.17% returns on investment. Manuscript profile
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  5 - Foster-Hart Optimal Portfolio
  sepehr asefi reza eivazlu reza tehrani
  20.1001.1.22519165.1398.10.39.11.9
  This essay is going to optimize the portfolio of stocks similar to the Markowitz approach. Nonetheless, the way in which the risk is measured is Foster-Hart risk. This measure was proposed by Foster and Hart in 2009. It takes into account the extreme events of losses. T More

  This essay is going to optimize the portfolio of stocks similar to the Markowitz approach. Nonetheless, the way in which the risk is measured is Foster-Hart risk. This measure was proposed by Foster and Hart in 2009. It takes into account the extreme events of losses. The theoretical definition could be as a minimum wealth that an investor should have in order not to face with bankruptcy. Our sample consists of adjusted daily data from thirty-four companies chosen from Tehran Stock Exchange’s Top 50 Index in the period between 1391/07/01 and 1396/06/31. Data has been collected from Rahavard Novin software which is widely used in finance studies in Iran. Different optimal portfolios has been achieved in this essay. Each of which uses a different method of risk like Cvar and Semi-Variance besides Foster-Hart. Results of this essay show that Foster-Hart optimal portfolio could have higher sharp ratio in comparison with the others. Manuscript profile
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  6 - A Comparison between Fama and French five-factor model and artificial neural networks in predicting the stock price
  reza tehrani Milad Heyrani Samira Mansuri
  20.1001.1.22519165.1398.10.39.13.1
  One of the most important issues of financial markets is the prediction of price and stock returns. In this paper, we try to find the best model and stock price prediction approach based on the mean square error (MSE), root-mean-square error (RMSE), R-squared, standard More

  One of the most important issues of financial markets is the prediction of price and stock returns. In this paper, we try to find the best model and stock price prediction approach based on the mean square error (MSE), root-mean-square error (RMSE), R-squared, standard deviation (SD), Mean absolute error and the mean absolute percent error (MAPE) for the Fama and French five-factor model. For this purpose, after the formation of a portfolio based on the Fama and French model during the period from 2009 to 2017, stock price is estimated by econometric model, neural network and Fuzzy Neural Networks, so the accuracy of each approach was compared. The results of the prediction the efficiency of the generated portfolios show that the prediction accuracy of the radial base function network (RBF) is very high compared to other ARMA models and other neural networks. Manuscript profile
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  7 - Performance Evaluation of Stocks in Different Time Periods under Uncertainty: Fuzzy Window Data Envelopment Analysis Approach
  Pejman Peykani Emran Mohammadi farhad hosseinzadehlotfi reza tehrani Mohsen Rostamy-Maslkhalifeh
  20.1001.1.22519165.1398.10.40.14.4
  The purpose of the present study is to provide a fuzzy window data envelopment analysis (FWDEA) model in order to financial performance evaluation of stocks over different time periods under the uncertainty of the data. In other words, in this research, we will try to p More

  The purpose of the present study is to provide a fuzzy window data envelopment analysis (FWDEA) model in order to financial performance evaluation of stocks over different time periods under the uncertainty of the data. In other words, in this research, we will try to present a new approach to assess the stock's performance with the ability to be implemented in the presence of uncertain panel data. Because the use of information about several time periods rather than a time period, as well as taking into account the uncertainty in the data, can lead to more reliable results in the process of stock evaluation. It is necessary to explain that in modeling and presenting the mentioned approach, data envelopment analysis, window analysis and possibilistic programming have been used. Finally, the fuzzy window data envelopment analysis model was implemented on 5 stocks of the chemical industry in Tehran stock exchange for four periods from 2013 to 2016, and the results indicate that the FWDEA method is effective. Manuscript profile
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  8 - Tehran Stock Exchange Overal Index Prediction using Combined Approach of Metaheuristic Algorithms, Artificial Intelligence and Parametric Mother Wavelet
  Alireza Saranj Madjid Ghods reza tehrani
  20.1001.1.22519165.1397.9.35.17.0
  Understanding and the investigating the behavior of stock prices, has always been one of the major topics of interest to the investors and finance scholars. In recent years, various models for prediction using neural network and hybrid models have been proposed which ha More

  Understanding and the investigating the behavior of stock prices, has always been one of the major topics of interest to the investors and finance scholars. In recent years, various models for prediction using neural network and hybrid models have been proposed which have a better performance than the traditional models. Here a hybrid model of neural network and wavelet transform is proposed in which genetic algorithm has been used to improve the performance of wavelet transform in optimizing the wavelet function. Daily stock exchange rates of TSE from April 21, 2012 to April 19, 2017 are used to develop a prediction model. The results show that it is possible to find a wavelet basis, which will be appropriate to the intrinsic characteristics of time series for prediction and the prediction error in this model is reduced comparing to the neural network and hybrid neural network and wavelet models. Manuscript profile
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  9 - Application of Real Option approach for optimizing Venture Capital
  farshid moradi reza tehrani Mansour Momeni Shahabeddin Shams
  20.1001.1.22519165.1398.10.41.16.8
  Application of traditional approaches based on Discounting the cash flow in order to evaluate and comparing investment opportunities including Venture Capital in most industries is a very common issue. Due to the lacking deep certainty in this sort of venture, relying o More

  Application of traditional approaches based on Discounting the cash flow in order to evaluate and comparing investment opportunities including Venture Capital in most industries is a very common issue. Due to the lacking deep certainty in this sort of venture, relying on traditional approaches could end up with inappropriate decision making, because of ignoring the managerial flexibility. At this study the real option approach in estimated capital budgeting was compared with traditional approach based on Discounting the income. The research hypothesis was that the real option approach could improve the quality of decision making and optimize the investing portfolio from the high risk projects. Accordingly, a venture capital company in the field of pharmaceutical products and medical and therapeutic equipment was chosen for applying the model considering two indicators of the availability and completeness of the financial information of the plans by using the case study approach. The results indicated that considering the value of flexible deciding, the efficacy of the capital budgeting model based on dynamic planning and real options shows more precision than traditional budgeting approach. Manuscript profile