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Open Access Article
1 - Portfolio Optimization Based on Semi Variance and Another Perspective of Value at Risk Using NSGA II, MOACO, and MOABC Algorithms
Reza Aghamohammadi Reza Tehrani Abbas RaadThis study examines the criterion of value at risk from another perspective and presents a new type of mean-value at Risk model. To solve the portfolio optimization problem in Tehran Stock Exchange, we use NSGA II, MOACO, and MOABC algorithms and then compare the mean-p MoreThis study examines the criterion of value at risk from another perspective and presents a new type of mean-value at Risk model. To solve the portfolio optimization problem in Tehran Stock Exchange, we use NSGA II, MOACO, and MOABC algorithms and then compare the mean-pVaR model with the mean-SV model. Given that, finding the best answer is very important in meta-heuristic methods, we use the concept of dominance in the discussion of multi-objective optimization to find the best answers and show that, at low iterations, the performance of the NSGA II algorithm is better than the MOABC and MOACO algorithms in solving the portfolio optimization problem. As the iteration increases, the performance of the algorithms improves, but the rate of improvement is not the same, in a way, the performance of the MOABC algorithm is better than that of the NSGA II and MOACO algorithms. Then, to compare the performance of the “mean-percentage of Value at Risk” model and the “mean-semi variance” model, we examine both models in the standard mean-variance model and show that the mean-pVaR model, compared to the mean-SV model, Has better performance in stock portfolio optimization. Manuscript profile -
Open Access Article
2 - The Effect of JCPOA on the Network Behavior Analysis of Tehran Stock Exchange Indexes
Salman Abbasian-Naghneh Reza Tehrani Mohammad TamimiThe purpose of this paper is investigating the effect of JCPOA on the network behavior analysis of Tehran Stock Exchange indexes using the minimum spanning tree (MST) and hierarchical clustering. By simplifying a complex system, network analysis allows for the extractio MoreThe purpose of this paper is investigating the effect of JCPOA on the network behavior analysis of Tehran Stock Exchange indexes using the minimum spanning tree (MST) and hierarchical clustering. By simplifying a complex system, network analysis allows for the extraction of important and essential information from that system. In this paper, using network analysis the simultaneous behavior of 38 industry indexes in Tehran Stock Exchange in manufacturing, service and invest-ment sectors during 2012-2017 was investigated. These analysis included identi-fying the main indexes in the direction of moving other indexes using the MST, providing a classification using hierarchical clustering for the behavioral similarity of the indexes as well as examining the degree of integration (behavioral similarity) of market indexes over time. The results showed that investment, automobile, industry and medicine indexes in the research period had a major role in guiding other indexes and indexes can be classified into six groups in terms of behavioral similarity. The market has also been moving toward integration of indexes since early 2015 and beginning the executive steps of Joint Comprehensive Plan of Action (JCPOA). This reflects the investors' hope for the promotion of all indexes. Manuscript profile -
Open Access Article
3 - Approach of Maximal Overlap Discrete Wavelet Transforms to Stock Return in the Iran Capital Market
Roghayeh Samadi Mohammad Ezazi Reza Tehrani Seyed aligholi Roshan Mohammad Nabi Shahiki TashThe main purpose of this study is to determine the real and dynamic relationship between returns and stock market fluctuations in different time horizons so that its key results can measure the predictive power of returns and stock market fluctuations in determining the MoreThe main purpose of this study is to determine the real and dynamic relationship between returns and stock market fluctuations in different time horizons so that its key results can measure the predictive power of returns and stock market fluctuations in determining the level of economic activity of investors. Accurate measurement of these relationships helps investors predict stock market movements in the future and Develop, plan and implement their own investment strategies in each time horizon. In this research Maximal overlap discrete wavelet transform has been used to investigate the relationships between industries return fluctuations and stock main indices in different time horizons from 2011 to 2020 have been estimated. The results showed that the wavelet variance of the rate of return varies in different industries. The return of investment companies on various time scales is equal to the investment return of the banking industry. The variance of the total index is less on different time scales than the value of the cash index. Manuscript profile -
Open Access Article
4 - Provide an improved factor pricing model using neural networks and the gray wolf optimization algorithm
Reza Tehrani Ali Souri Ardeshir Zohrabi Seyyed Jalal Sadeghi SharifThe issue of asset pricing in the market is one of the most important and old issues in the financial world. Factor pricing models seek to be able to determine a significant relationship between return on assets based on the risk parameters of that asset. A wide range o MoreThe issue of asset pricing in the market is one of the most important and old issues in the financial world. Factor pricing models seek to be able to determine a significant relationship between return on assets based on the risk parameters of that asset. A wide range of factors can be found in the literature that can be an element for measuring the risk of an asset, but the big question is which of these models will work better. The factors studied in this research include factors that cover market risk, valuation risk, psychological (technical) market risk, profit quality risk, profitability, investment, etc. In this study, we have tried to Using machine learning techniques and optimization tools is a way to derive adaptive-robust nonlinear models that can reduce the risk of model error as much as possible. In this research, two models have been developed. In the first model, using the feature extraction technique and optimization of models based on neural network, a non-linear and adaptable model has been developed for each asset. In the second approach, a portfolio of improved neural network-based models is used in the first stage, which can be used to minimize the risk of model error and achieve a model that is resistant to different market conditions. Finally, it can be seen that the development of these models can significantly improve the risk of error and average error of the model compared to traditional CAPM approaches and the Fama and French three-factor model. Manuscript profile -
Open Access Article
5 - Effect of Business Groups Affiliation on Cash Holdings and Return on Equity
Reza Tehrani Roohallah ArdakaniNowadays, business groups play an outstanding role in financial markets. Corporates in the trading groups are able to use technology, capital, human resources, productions and services of other members in the group in addition to their own resources and capabilities. Th MoreNowadays, business groups play an outstanding role in financial markets. Corporates in the trading groups are able to use technology, capital, human resources, productions and services of other members in the group in addition to their own resources and capabilities. Thus, this paper studies the effect of business group affiliation on cash holdings and return on equity. The sample involves 94 corporates among those accepted in Tehran Stock Exchange. In this research, the effect of business group affiliation on cash holdings and return on equity during 2010-2015 has been investigated; in total, it includes 564 observations for the research. Statistical method applied here is the multivariate regression in the data panel way. Results achieved by the research hypotheses indicate that there is a significant relationship between business group affiliation, cash holdings and return on equity. Manuscript profile -
Open Access Article
6 - Does Exchange Rate Non-Linear Movements Matter for Analyzing Investment Risk? Evidence from Investing in Iran’s Petrochemical Industry
Alireza Khosrowzadeh Aboutorab Alirezaei Reza Tehrani Gholamreza Hashemzadeh KhourasganiThe present study models the risk of investment in the petrochemical industry considering the impacts of exchange rate (US dollar to Iran's Rial) movements using the time series data from November 2008 to March 2019 and ARFIMA-FIGARCH framework. The empirical results pr MoreThe present study models the risk of investment in the petrochemical industry considering the impacts of exchange rate (US dollar to Iran's Rial) movements using the time series data from November 2008 to March 2019 and ARFIMA-FIGARCH framework. The empirical results prove the existence of the Fractal Market Hypothesis, FMH, and the Long Memory property in both the risk and return of the petrochemical stock index. These findings can be culminated in reaching a reliable and significant model to evaluate the investment risk in the petrochemical industry. In line with this, to analyze the idea whether considering the exchange rate movements matter for assessing the risk management in the petrochemical industry, the effects of exchange rate movements as a crucial source of systematic risk in Iran has been taken into consideration in the process of modelling the risk of investment in that industry. Our results demonstrate that the exchange rate movements have had a direct and significant effect on the investment risk of that industry so that if, on average, one percent change occurs in the exchange rate, the investment risk in this industry changes by 57% in the same direction. Manuscript profile
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