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Open Access Article
1 - Assessment and Presentation of a Proper Paradigm to Identify, Measure, and Control Financial Risks in Financial and Credit Institutions (Case Study of Mellat Bank)
M. Taghavi M. Khodaei ValahzaghardFinancial and credit institutions are threatened by different types of risks. The main objective in thisresearch is to assess and present a proper paradigm to identify, measure, and control financial risks infinancial and credit institutions. The method of research acco MoreFinancial and credit institutions are threatened by different types of risks. The main objective in thisresearch is to assess and present a proper paradigm to identify, measure, and control financial risks infinancial and credit institutions. The method of research according is applied upon implementation andcorrelation methods, and ex-post facto is accomplished in Bank Mellat. Sampling is intentional, andthe sample volume was determined by the researcher. Required data for this research were collecteddaily from 39 regional offices of Mellat Bank between 2005 and 2007. Structural Equation Modeling(SEM) and Linear Structural Relationships (LISREL) were used to analyze the research data. Thisstudy shows that the impact of loans and investment on liquidity risk, the impact of assets and foreigncurrency debts on foreign currency risk, and the impact of interest sensitive assets and debts volatilityvariant on interest risks are meaningful. Manuscript profile -
Open Access Article
2 - Survey on the Fisibility of Substitution Catastrophe Securitization and Current Reinsurance in Iranian Insurance Industry
Kambiz Peykarjou hanieh davodiAfter 2004, Alternative Risk Transfer (ART) has been more popular in the Litriture of Financial Economics & Financial Management. For using ART, many Researches Pursue Resolution, which Minimize Claims of this Catastrophe, through Risk Distribution Cycle, or if any MoreAfter 2004, Alternative Risk Transfer (ART) has been more popular in the Litriture of Financial Economics & Financial Management. For using ART, many Researches Pursue Resolution, which Minimize Claims of this Catastrophe, through Risk Distribution Cycle, or if any Profitability, find Subsititutions of ART; such as Insurance. However, we study about this, by Estimating Nnon-linear relation between Claims of Catastrophe and Insured Risk Capitals(IRC), Accounting Loss Distribution Function(LDF), given Historical Data(HD) & using Monte Carlo Simulation(MCS) and then, Stimating Value at Risk(VaR) of Conditional Loss Distribution Function of Catastroph(CLDFC), which has almost Optimal Profitability. Manuscript profile -
Open Access Article
3 - Estimating Conditional VaR Using Symmetric and Non-Symmetric Autoregressive Models in Old and Oil Markets
Saeid Fallahpour Fatemeh Rezvani Mohammadreza RahimiPrice volatility on gold and oil market is the top news all the time. Global economy isaffected by those markets volatility. Because of the domestic investor tendency in goldmarket and feasibility of investing on oil by Energy Exchange in Iran, in this paper wefocus on MorePrice volatility on gold and oil market is the top news all the time. Global economy isaffected by those markets volatility. Because of the domestic investor tendency in goldmarket and feasibility of investing on oil by Energy Exchange in Iran, in this paper wefocus on the volatility of gold and oil return. The implemented method is one-day aheadout of sample forecast by the conditional value at risk.The goal of this paper is to answer which of the models; GARCH, ECHARCH, andTARCH is best at forecasting the CVaR for gold and oil return. We estimate the value byassuming normal and t-student distribution.The results show that the TGARH(1,1) model specifications are good option forforecasting the CVaR in oil market by t-student distribution Manuscript profile -
Open Access Article
4 - Fuzzy Mean-CVaR Portfolio Selection Based on Credibility Theory
S. Babak Ebrahimi Amirsina Jirofti Matin AbdiThis paper develops a fuzzy portfolio selection problem that minimizes conditional value-at-risk (CVaR) and estimates CVaR by fuzzy credibility theory and also calculates expected return by fuzzy credibility mean. Using fuzzy techniques makes the model more precise and MoreThis paper develops a fuzzy portfolio selection problem that minimizes conditional value-at-risk (CVaR) and estimates CVaR by fuzzy credibility theory and also calculates expected return by fuzzy credibility mean. Using fuzzy techniques makes the model more precise and accurate due to uncertainty of financial data. The use of CVaR helps investors make better decisions because it indicates the size of loss. This study considers some constraints for model including liquidity, cardinality, minimum and maximum investment proportion. The liquidity constraint is measured by turnover of each asset as a trapezoidal fuzzy number. The liquidity constraint converts to a linear constraint by using fuzzy credibility theory. Using CVaR as a risk measurement and efficient constraints makes the model appropriate and adequate for portfolio selection. Finally, a numerical example is provided by 10 stocks chosen from Tehran Stock Exchange Market in 2015 and it shows the effectiveness and applicability of the proposed model Manuscript profile -
Open Access Article
5 - Portfolio optimization with differential evolution and conditional value at risk approach
Shahin Ramtinnia Romina AtrchiPortfolio selection, in order to maximize the profit from investment, is an important concern for minor and institutional investors.Therefore; efficient and secure optimization of financial assets is one of the most important new and modern, financial topics, trying to MorePortfolio selection, in order to maximize the profit from investment, is an important concern for minor and institutional investors.Therefore; efficient and secure optimization of financial assets is one of the most important new and modern, financial topics, trying to improve the portfolio performance using modern approaches of other sciences. Accordingly, this article aimed to optimize the index returns of top 10 companies of Tehran Stock Exchange from 2011 to 2015 using portfolio risk minimization approach with the maximum yield according to conditional value at risk and differential evolution algorithm(DE-CVaR) on a monthly basis. The results showed that differential evolution algorithm with the conditional value at risk approach, had better Sharpe and returns ratios by CVaR value compared to the random algorithm. The results of posttest with monthly approach also showed that DE-CVaR was better than random algorithm in terms of the criteria for selecting the optimal portfolio. Manuscript profile -
Open Access Article
6 - تعیین سبد بهینه سرمایهگذاری در صنایع مختلف بورس اوراق بهادار تهران با استفاده از رویکرد VAR-Multivariate GARCH و در نظرگیری ریسک نقدشوندگی
سید احمد حسینی امینی امیر عباس نجفی -
Open Access Article
7 - Risk Analysis & Financial Evaluation in Power Plant BOT
Faramarz Nouri Parastoo Mohammadi Esmaeil VassafThe aim of this thesis is identifying and modeling the risks of the power plant BOTprojects. Main identified risks in this study are project financing risk(equity ratio risk)and the risk of revenue of project. In order to model the risks, we used the MartingaleVariance MoreThe aim of this thesis is identifying and modeling the risks of the power plant BOTprojects. Main identified risks in this study are project financing risk(equity ratio risk)and the risk of revenue of project. In order to model the risks, we used the MartingaleVariance Model (MVM) for the revenue risk and the Triangular distribution function forthe equity ratio risk. We applicated the Monte Carlo simulations method for obtainingthe probability distribution function and critical values of the decision index (Net PresentValue, Internal Rate of Return, Debt Service Coverage Ratio). The one of thermal powerplant projects data prepared by MAPNA, has been implemented in this study. The resultsof the simulation indicate that the risk of negative NPV of project is 13.41 percent and therisk of DSCR lower than 1.2 is 8.65 percent. Therefore, the sponsors suffering more risksthan lenders in the studied project. Manuscript profile -
Open Access Article
8 - Using intelligent methods in Solving Constrained Portfolio in Tehran Stock Exchange
Esmat Jamshidi Eyni Hamid KhaloozadehThe optimal portfolio selection problem to find an optimal way to allocate a fixed amount of capital to a set of available asset swhich aims to maximize expected returns and minimize risk at the same time, to take place. In this Study is shown that an investor with n ri MoreThe optimal portfolio selection problem to find an optimal way to allocate a fixed amount of capital to a set of available asset swhich aims to maximize expected returns and minimize risk at the same time, to take place. In this Study is shown that an investor with n risky share, how to reach certain profits with minimal risk. Such a portfolio, efficient portfolio is called. For this purpose, the study of evolutionary algorithms, Genetic Algorithm, Imperialist Competitive Algorithm and Particle Swarm Optimization algorithm, also with regard to the basic constraints on the investment, we use these practical methods to solve the portfolio optimization problem. Practical results for the portfolio optimization problem in the Tehran Stock Exchange, of the30 company' sactivein the industry with the selection of20companies along with their validation, is obtained. Aims to help investors better and more practical to select different stocks and thus is an effective investment. Manuscript profile -
Open Access Article
9 - Using intelligent methods in Solving Constrained Portfolio in Tehran Stock Exchange
Esmat Jamshdi Eyni Hamid KhaloozadehThe optimal portfolio selection problem to find an optimal way to allocate a fixed amount of capital to a set of available assets which aims to maximize expected returns and minimize risk at the same time, to take place. In this Study is shown that an investor with n ri MoreThe optimal portfolio selection problem to find an optimal way to allocate a fixed amount of capital to a set of available assets which aims to maximize expected returns and minimize risk at the same time, to take place. In this Study is shown that an investor with n risky share, how to reach certain profits with minimal risk. Such a portfolio, efficient portfolio is called. For this purpose, the study of evolutionary algorithms, Genetic Algorithm, Imperialist Competitive Algorithm and Particle Swarm Optimization algorithm, also with regard to the basic constraints on the investment, we use these practical methods to solve the portfolio optimization problem. Practical results for the portfolio optimization problem in the Tehran Stock Exchange, of the30 company's active in the industry with the selection of20companies along with their validation, is obtained. Aims to help investors better and more practical to select different stocks and thus is an effective investment. Manuscript profile -
Open Access Article
10 - Comparing the Frechet Distribution and the Generalized Pareto Distribution in Estimating Value at Risk and Conditional Value at Risk in Tehran Stock Exchange
Azadeh Meharani Ali Najafi moghadam Ali BaghaniSelecting the most accurate method of risk measurement is the main challenge in risk estimation. This study aims to measure value at risk (VaR) and conditional value at risk (CoVar) in Tehran Stock Exchange (TSE) using the Frechet distribution (FD) and the generalized P MoreSelecting the most accurate method of risk measurement is the main challenge in risk estimation. This study aims to measure value at risk (VaR) and conditional value at risk (CoVar) in Tehran Stock Exchange (TSE) using the Frechet distribution (FD) and the generalized Pareto distribution (GPD). It used the data from 21 and 63-day time series of TEPIX, free-float, and the indices of the top 50 TSE companies between 2012-3-20 and 2020-3-19. It used COPIC post-test and Christoffersen’s conditional coverage test for models statistical confirmation. It applied Lopez and Blanco-Ihle’s second loss functions for model comparison. The CoVaR models were ranked by two loss functions, including Mean Absolute Error (MAE) and Root Mean Square Error (RMSE). Results indicated according to the statistics measured in Lopez’s second loss function, GPD performed better than FD in measuring VaR of TEPIX and the return index of the selected 50 companies, however, FD performed better for the free-float index. Blanco-Ihle’s loss function results contradicted the ones derived from Lopez’s second loss function. MAE and RMSE results indicated FD is better in estimating CoVaR. Manuscript profile -
Open Access Article
11 - Ranking of exchange-traded funds (ETF) And value at risk approach (EVT) based on value-generating theory (VaR) risk approach
Gholamreza Zomorodian Maryam SohrabiGiven the importance of exchange-traded funds and their ever-increasing advancement in financial markets, it is important to review and explain their ranking based on criteria beyond the examination of returns. Also, considering that broad distribution sequences in fina MoreGiven the importance of exchange-traded funds and their ever-increasing advancement in financial markets, it is important to review and explain their ranking based on criteria beyond the examination of returns. Also, considering that broad distribution sequences in financial data are of particular importance in measuring financial risk, in this study, based on criteria beyond the efficiency and considering the value of risk, based on the Extreme -Value Theory (EVT) and the modified Sharpe Ratio, the rating of exchange-traded funds has been dealt with. Then evaluation their models with different back testing such as Kupiec test, Christoffersen test. For the purpose of this study, the first period of September 2014 until the end of September 2017 was considered for the funds that were active in the capital market during this period. The results indicate the proper capabilities of VaR models which is based on GHARCH-EVT approach. Manuscript profile -
Open Access Article
12 - Comparative Analysis of Stock Portfolio Optimization in Fireworks and Genetic Algorithms Using Conditional Value at Risk
Ali Asghar Shahriari saeed Daei-Karimzadeh Reza BehmaneshDevaluation of assets in the future is one of the most important investment concerns that has led investors to choose the set of assets that have the lowest risk and highest return. The present study deals with the problem of stock portfolio optimization according to th MoreDevaluation of assets in the future is one of the most important investment concerns that has led investors to choose the set of assets that have the lowest risk and highest return. The present study deals with the problem of stock portfolio optimization according to the Conditional Value at Risk based on the new and intelligent fireworks algorithm and compares it with genetic algorithm with the historical simulation method using MATLAB software. The parameters of meta-heuristic algorithms were adjusted by Taguchi method using MINITAB software. Not suspended, used. For reliability of the study, generalized Dickey-Fuller test and Phillips-Prone test were used. To evaluate the accuracy of the Conditional Value at Risk model, the kupiec proportion of failure test, Christoffersen independence test and Conditional coverage test are used. A comparison was also made between the models by Lopez test. Findings showed that at %95 and %99 confidence levels, the conditional risk value model using the fireworks algorithm has a suitable and reliable validity for measuring market risk and optimizing the stock portfolio. Manuscript profile -
Open Access Article
13 - Presenting of nonlinear hybrid model based on Extreme Value Theory for forecasting the Conditional Value at Risk (CVaR)
Ehsan Mohammadian Amiri Ehan Atefi Seyed Babak EbrahimiThe political and economic instability in recent years and followed by rapid changes in the realm of financial markets, has increased the risk of most financial institutions. So that risk managers at these institutions are worried about the decline in their asset value MoreThe political and economic instability in recent years and followed by rapid changes in the realm of financial markets, has increased the risk of most financial institutions. So that risk managers at these institutions are worried about the decline in their asset value over the coming days. In recent studies, generally the Conditional Value at Risk is used to measure and forecast the risks existing in financial markets. Therefore, in this research, it has been attempted to introduce, calculate and implement a nonlinear hybrid model for forecasting the Conditional Value at Risk. For this purpose, the new hybrid model based on the Extreme Value Theory and the Holt-Winters exponential smoothing (HWES-EVT) that, in addition to dynamics, cluster characteristics and broad data sequence, also takes into account the forecast Conditional Value at Risk of the industry and Tehran Stock Exchange Indices. For evaluating the accuracy the performance of proposed hybrid model, this modek is compared with the GARCH-EVT model. The results of backtesting show that the proposed hybrid approach provides a more accurate answer to the forecasting of Conditional Value at Risk for these indicators Indices. Manuscript profile -
Open Access Article
14 - Analysis of financial risk in the cryptocurrency market: Evidence from predicting value at risk
Zahra Bozorgtabar Baei Reza Aghajan Nashtaei Mohammad Hasan GholizadehConsidering the extreme fluctuations of the cryptocurrency market and also the importance of predicting the value at risk in such conditions, the purpose of the present study is to predict the value at risk in the cryptocurrency market and also to compare different mode MoreConsidering the extreme fluctuations of the cryptocurrency market and also the importance of predicting the value at risk in such conditions, the purpose of the present study is to predict the value at risk in the cryptocurrency market and also to compare different models for predicting the value at risk. In addition, the impact of different distributions of model innovation terms has been investigated. In this research, we use different models to predict the value at risk of return of four well-known cryptocurrencies. The data used in the research covers the period from 1/1/2018 to 16/3/2022. This research uses CAViaR and DQR models that directly predict the return distribution quantiles as value at risk. In addition to the mentioned models, several types of common models have been used to predict value at risk. In order to check the performance of the used models, we have used the back-test method, which is one of the common methods for testing the performance of the models. The results show that the models that directly use the quantiles of the return distribution to predict value at risk (specifically CAViaR and DQR models) have a much better performance than other common models for predicting value at risk. Manuscript profile -
Open Access Article
15 - Portfolio optimization by using the Copula Approach and multivariate conditional value at risk in Tehran Stock Exchange
Mirfeiz Fallahshams Amir SadeghiOne of the main problems of shareholders in the stock market is the discovery, quantification and calculation of market risk. In many studies, one-way distributions are used to estimate risk metrics that usually do not give credible results to the investor. Because the MoreOne of the main problems of shareholders in the stock market is the discovery, quantification and calculation of market risk. In many studies, one-way distributions are used to estimate risk metrics that usually do not give credible results to the investor. Because the distribution of assets is generally a broad sequence, and the results of computations are not acceptable for the consideration of the univariate normal distribution and the use of parametric methods. In this paper, using the Coppola theory, we calculate risk-weighted value (VaR) and conditional value-at-risk (CVaR). After estimating the multivariate T- Copula and the normal distribution of multivariate, the Monte Carlo method is used to generate a scenario for calculating the variance of the portfolio as well as risk estimation. Also, the calculations performed using the loss function method are tested and the accuracy of the approximations is verified. Finally, the minimum value of the copula based on the variance of the portfolio as well as its CVaR value is considered as the function of the portfolio planning, and the optimal portfolio is obtained by considering the weight of each share index. In the calculation of the 1200 index, we consider a sample basket of different industries, by calculating VaR and CVaR with confidence levels of 95 and 99 percent. The results obtained from the efficiency and reliability of the Monte Carlo simulation by the Copula T-Student versus the normalized multivariate distribution. Manuscript profile -
Open Access Article
16 - Evaluation of multivariate GARCH models in estimating the Values at Risk (VaR) of currency, stock and gold markets
abdollah rajabi khanghah Hashem Nikoomaram Mehdi Taghavi Mirfeiz Fallah ShamsThe development of financial markets requires the introduction of new models, forecasting and risk management. One of the indicators that are considered in risk management and measurement is value at risk index. In this research, the multivariate GARCH model has been ev MoreThe development of financial markets requires the introduction of new models, forecasting and risk management. One of the indicators that are considered in risk management and measurement is value at risk index. In this research, the multivariate GARCH model has been evaluated to predict the value of exposed portfolio risk, including currency, stocks and gold, and the combined returns of gold price data, total stock exchange index and exchange rates from 2009 to 2016 were used. The results of VECH, BEKK, DCC, and VECH diagonal models have shown that the volatility of these variables in the estimation period is effective and this confirms the hypothesis of market independence in Iran, in order to evaluate the performance of these models in predicting VAR One-day prediction of conditional variance covariance matrix of models was used. The results of the post-test of the models using the coup and kristoferson tests showed the performance of all four models was appropriate and the comparison of the mean loss function of Lopez showed that the VECH model had better performance than other models. Despite the good performance of the VECH model, however, the estimation of this model is very time-consuming. due to the large number of parameters that are estimated in the estimation of VECH and BEKK models that lead to a reduction in the degree of freedom and, as a result, a reduction in the validity of the model, the use of these two models for portfolios with more than three assets is not recommended. Manuscript profile -
Open Access Article
17 - Calculating Tail Value at Risk Using a EGARCH-Extreme Learning Machine Model And The long-term forecast approach in the insurance industry
reza raei Azam Honardoust ezzatolah abbasianOne of the most important methods for market risk measurement is Value-at-risk (VaR) that financial institutions such as banks, insurers and investment funds use them extensively. VaR as a risk measure is heavily criticized for not being sub-additive, thus the researche MoreOne of the most important methods for market risk measurement is Value-at-risk (VaR) that financial institutions such as banks, insurers and investment funds use them extensively. VaR as a risk measure is heavily criticized for not being sub-additive, thus the researchers focuses on the assessment of the Tail value-at-risk (TVaR), and this measure is using on the Basel Committee on Banking and Solvency II of Europe and Swiss Solvency Test (SST). this paper focuses on TVaR to measure the risk of the stock market. Considering that the time horizon of the risks of an insurer unlike banks is annually. thus, to calculate the TVaR, we use of the two methods of the variance-covariance approach with the EGARCH-Extreme learning Machine model to volatility forecasting and use of square-root-of-time rule; and Filtered Historical simulation model. The results of using the daily returns of the Tehran Stock Exchange Index for 1388 to 1396 confirm that the EGARCH-Extreme learning Machine model with use of square-root-of-time rule performs better in TVaR calculation in terms of efficiency and accuracy. Manuscript profile -
Open Access Article
18 - Portfolio VaR Modelling using EVT-Pair-Copulas Approach
Ali Souri Saeed Falahpor Ali Foroush Bastani Ehsan AhmadiThe purpose of this research is to model Value-at-Risk (VaR) of portfolio with EVT-Pair-Copulas approach. In the financial literature, a significant amount of empirical studies have been done on the characteristics of financial assets returns and researchers have found MoreThe purpose of this research is to model Value-at-Risk (VaR) of portfolio with EVT-Pair-Copulas approach. In the financial literature, a significant amount of empirical studies have been done on the characteristics of financial assets returns and researchers have found a set of stylized facts about this subject. In this regard leptokurtic, left-skewed, weak autocorrelation, volatility clustering, and heteroscedasticity can be mentioned. Any estimation of risk without considering these characteristics or using unrealistic assumptions about financial assets returns increases the probability of failure in the risk management process. For this purpose, at first, the marginal distributions of returns are obtained using extreme value theory (EVT). Concerning characteristics of financial assets returns and also the primary filter to apply EVT, we use heteroscedasticity models for the marginal distributions of assets. Then the structure of the dependence between different stocks is estimated by using C-Vine, D-Vine, and R-Vine pair copula models. Afterward, the VaR of portfolio is estimated using the Monte Carlo simulation method. The final results show that the model with GARCH marginal distribution and R-Vine pair copula has been able to achieve the best performance among rival models at 95% confidence level. Manuscript profile -
Open Access Article
19 - Investment Portfolio Optimization of Insurance Companies with Copulas and Extreme Value Approach
arash goodarzi reza Tehrani Ali souriThis study determines the optimal investment portfolio of insurance companies by considering underwriting activities. investment decisions in insurance companies are affected by underwriting activities. In this paper, the investment optimization problem of insurers is m MoreThis study determines the optimal investment portfolio of insurance companies by considering underwriting activities. investment decisions in insurance companies are affected by underwriting activities. In this paper, the investment optimization problem of insurers is modeled using the copula-based conditional risk value, taking into account the results of insurance activities. Also, since the emphasis is on tails of distribution, the probability distribution of variables in tails is estimated using Pareto distribution and in other parts of the distribution using the Empirical probability distribution. Data collected on monthly basis covers two periods in-sample, between 2006 to 2015 and out-of-sample, between 2016 to 2019.The findings show that the optimum portfolio includes eighty percent of risky assets (stock and real estate) and only twenty percent of risk-free assets (bank deposits) and it is outside the legal constraints set by Central Insurance Therefore, legal constraints prevent insurance companies from the optimal selection of investment portfolio. Also, the comparison of out-of-sample performance with in-sample performance of portfolios shows that portfolios based on copula functions have better and more robust performance than traditional models. Manuscript profile -
Open Access Article
20 - Application of Copula and Simulated Returns in the Portfolio Optimization with Conditional Value-at-Risk (CVaR) in Tehran Stock Exchange (TSE)
Esmaeil Lalegani Mostafa ZehtabianSeveral studies have confirmed with using criteria appropriate to the structure and characteristics of the data, the performance of the models significantly improved. The Copula function is one of the models in determining the relationship between variables has attracte MoreSeveral studies have confirmed with using criteria appropriate to the structure and characteristics of the data, the performance of the models significantly improved. The Copula function is one of the models in determining the relationship between variables has attracted a lot of attention. In this study, we investigated the portfolio of TSE industry indexes optimized to minimize the Conditional Value at Risk, simulated data based on Copula function and generalized Pareto distribution as input. The statistical analyzes implies portfolio performance improves significantly. Since the Copula functions are diverse, Compare the impact of any one risk reduction is recommended. Manuscript profile -
Open Access Article
21 - An Investigation of methods to reduce transaction costs in Tehran Stock Exchange
Romina Atrchi Shahin RamtinniaAmong 37 methods to reduce transaction costs introduced by Cha (2007), we recursively choose the best method for next period's investment in each of three portfolio strategies: Mean-Variance Optimization, Mean-CVaR Optimization, and the equally-weighted market. We ident MoreAmong 37 methods to reduce transaction costs introduced by Cha (2007), we recursively choose the best method for next period's investment in each of three portfolio strategies: Mean-Variance Optimization, Mean-CVaR Optimization, and the equally-weighted market. We identify a few of the best methods and offer a framework by which additional methods can be considered. Within our framework, the best methods recapture a substantial amount of wealth and significantly improve risk-adjusted performance, both economically and statistically. We used prices and returns of the 10 most active firms of Tehran Stock Exchange market, from 1391 to 1394 on a monthly basis in this research. The transactions costs reduction methods will be applied on them and the best methods will be identified. Also, a framework will be offered for comparison and investigation of new methods. Manuscript profile -
Open Access Article
22 - Presentation of a model for the active optimization of stock portfolios using value at risk exposure; Application of Convergence Variance Difference Models Approach Based on Algorithm DE Approach
Saeid Fallahpour Reza Raei M. Esmaeil Fadaeinejad Reza MonajatiActive management is one of the issues that is important in terms of violating effectiveness of financial markets financial markets. Because inefficient market, there is a potential to generate abnormal returns through active portfolio management. In many studies in thi MoreActive management is one of the issues that is important in terms of violating effectiveness of financial markets financial markets. Because inefficient market, there is a potential to generate abnormal returns through active portfolio management. In many studies in this regard the reason for the surplus return compared to the baseline portfolio by minimizing the tracking error variance (TEV) in this regard, the risk of the entire portfolio is not taken into account. In this study, by using the differential evolution algorithm (DE) to optimize the active portfolio, with the goal of maximizing portfolio surplus returns compared to the standard portfolio, considering the risk of the entire portfolio from the calculated conditional risk value criterion (CVaR) based on the GARCH approach is used. The results of the portfolio consist of 14 stocks with a positive average yield from the beginning of 2011 to the end of June of 2017 from the top 50 stock exchanges on a monthly shows that subject to risk portfolio based on CVaR, causes better performance in the active optimization of the portfolio, based on backtesting method. Manuscript profile -
Open Access Article
23 - The Effect of Portfolio Diversification on Value at Risk in Tehran Stock Exchange (TSE)
Ali Rostami Narges NikniaThe concept of risk always attracted investors.Diversification is one of strategies that investors used it to against the risk. This research explores the risk associated with the stocks prices in the twenty-two companies that are listed in Tehran Stock Exchange (TSE) & MoreThe concept of risk always attracted investors.Diversification is one of strategies that investors used it to against the risk. This research explores the risk associated with the stocks prices in the twenty-two companies that are listed in Tehran Stock Exchange (TSE) as well as portflio of investment that are constructed from these twenty-two companies employed. In addition to national studies, the importance of international diversification by constructing a portfolio of investment from stock price indexes of emeging and developed countries would be examined.Correlation between stocks in national diversification porfolios shows the relationship between various domestic equities in investment portfolios, as well as correlation between indices, displays relationship between stock price indexes in international investment porfolio. Value at risk (VaR) is undertaken for studying the benefits associated with domestic as well as international diversification. The results show that domestic diversification reduces risk and more significient result is that international diversification significiently reduces the risk. Manuscript profile -
Open Access Article
24 - A novel Meta-Heuristic method for solving an extended Markowitz Mean–Variance portfolio selection model
Gholamreza Eslami Bidgoli Ehsan Tayebi SaniThis paper presents a novel Meta-Heuristic method for solving an extended Markowitz Mean–Variance portfolio selection model. The extended model considers Value-at-Risk (VaR) as risk measure instead of Variance. Depending on the method of VaR calculation its minimi MoreThis paper presents a novel Meta-Heuristic method for solving an extended Markowitz Mean–Variance portfolio selection model. The extended model considers Value-at-Risk (VaR) as risk measure instead of Variance. Depending on the method of VaR calculation its minimizing methodology differs. if we use Historical Simulation which is applied in this paper then the curve would be non-convex. On the other hand the Mean-VaR model here includes three sets of constraints: bounds on holdings, cardinality and minimum return which cause a Mixed Integer Quadratic Programming Problem. The first set of constraints guarantee that the amount invested (if any) in each asset is between its predetermined upper and lower bounds. The cardinality constraint ensures that the total number of assets selected in the portfolio’s equal to a predefined number. Because of above mentioned reasons, in this paper, we propose a new Meta-Heuristic approach based on combined Ant Colony Optimization (ACO) method and Genetic Algorithm (GA). The computational results show that the proposed Hybrid Algorithm has the ability to optimized Mean-VaR portfolio for small portfolio Manuscript profile -
Open Access Article
25 - Application of Extreme Value Theory in Value at Risk forecasting
Hosein Falahtalab Mohammadreza AziziQuantifying the uncertainty is one of the most important subject in financial issues, so nowadays in each financial and investment activity risk assessment and management is required. Value-at-risk (VaR) has become a popular risk measure since it was adopted by the Inte MoreQuantifying the uncertainty is one of the most important subject in financial issues, so nowadays in each financial and investment activity risk assessment and management is required. Value-at-risk (VaR) has become a popular risk measure since it was adopted by the International agencies in 1988. Precise prediction of VaR provides proper evaluation criteria in areas such as investment decision-making and risk management. Due to the fat-tailed distribution in most real financial time-series, extreme value theory (EVT) is a powerful tool in determining the VaR by concentrating on the shape of the fat-tailed probability distribution. In This study, Peak Over Threshold (POT) approach used for value at risk forecasting by Tehran Stock Exchange (TSE) data. The results show this approach is better than traditional approaches such as historical simulation and variance-covariance methods. Manuscript profile -
Open Access Article
26 - Multivariate GARCH models". Journal of business and economic statistic Value at Risk and Spillover effect estimate using MGARCH
Mohammadreza Rostami Sahar FarahmandIn this paper we examine the usefulness of multivariate GARCH models to estimate Value-at-Risk (VaR) and spillover effect using a portfolio of returns in the OPEC and WTI oil spot market. In this procedure first we estimate conditional covariance matrix using multivaria MoreIn this paper we examine the usefulness of multivariate GARCH models to estimate Value-at-Risk (VaR) and spillover effect using a portfolio of returns in the OPEC and WTI oil spot market. In this procedure first we estimate conditional covariance matrix using multivariate GARCH models, results show that in multivariate GARCH models, although CCC model estimate variance matrix well with utilize more complete information of correlation matrix. Also we detect extreme risk spillover effect between the two oil markets from existence covariance between variable. The tests showed the importance of time varying correlation in risk portfolio management. The estimated Value-at-Risk represents the superiority of CCC to other models. The distributional assumption has large impact on VaR estimation. These results are valuable for anyone who needs to evaluate and forecast the risk situation in international crude oil markets. Manuscript profile -
Open Access Article
27 - Expression and design a model to forecast the exchange rate shocks and stress testing of the currency in Iran
Abdollah Rajabi Khanghah Hashem Nikomaram Mehdi Taghavi Fereydoon Rahnamay Roodposhti Mirfiyaz Fallah ShamsThis paper attempts to Expression and design a model to forecast the exchange rate shocks and stress testing of the currency in Iran . In other words, what factors influence the currency shock and is there the shock predictability in the currency marke MoreThis paper attempts to Expression and design a model to forecast the exchange rate shocks and stress testing of the currency in Iran . In other words, what factors influence the currency shock and is there the shock predictability in the currency market. On the other hand, are there in critical condition (shock) the ability to predict currency risk through stress tests? The research method is descriptive-analytic and data collection library using econometric regression model using econometric software Eviews is carried out. The research is method in this study (time series modeling) . The results suggest that based on estimations made clear that the exchange rate shock predictable feature of the model is capable MGARCH. . In other words, using multivariate GARCH model and Conditional value at risk predictability of the exchange rate shock and influence the variable of Macroeconomic variables has been clarified. Finally, using the Back Testing the validity and effectiveness model was estimated and validation tests with stress tests to estimate the shock has been in critical condition. Manuscript profile -
Open Access Article
28 - تخمین سرمایه مورد نیاز در حوزه بانکداری به منظور پوشش زیانهای غیرانتظاری ناشی از نکول اعتباری به کمک آزمون استرس
مهسا قربانی جزین کامیار عسکری -
Open Access Article
29 - The Estimation of Systematic Risk in Iranian Financial Sectors (ΔCoVaR Approach)
samad hekmati farid Ali Rezazadeh ali malekAbstract The occurrence of last crisis has led to the consideration of systematic risk and it's transmission in theoretical and empirical point view. Hence, the main aim of this paper is to estimate and localize of systematic risk in financial sectors of Iran such as St MoreAbstract The occurrence of last crisis has led to the consideration of systematic risk and it's transmission in theoretical and empirical point view. Hence, the main aim of this paper is to estimate and localize of systematic risk in financial sectors of Iran such as Stock, Insurance and Bank sectors during the period of 1995-2015. The quintile regression econometric approach has been used for estimating the difference conditional value at risk in these sectors. The main empirical findings of post estimation indicated that there is significant difference between Stock, Insurance and Bank sectors as main financial sectors. Moreover, the results of Fridman test as a method for ordering of variable status showed that, the systematic risk of insurance is high and risk of bank is low during the period of study. So, there is significant difference between orders of financial sectors in Iran over the period of study. Manuscript profile -
Open Access Article
30 - Forecasting Future Trends of the Stock Market Using the Probit Regression Approach with Emphasis on Value at Risk
Seyed Ali Mousavi Loleti Emran Mohammadi Saeed ShavvalpourForecasting has always been recognized as an important issue in financial markets and is considered a unique factor in estimating future unknown values. The aim of this research is to identify and forecast the conditions of the Tehran Stock Exchange(TSE) and the factors MoreForecasting has always been recognized as an important issue in financial markets and is considered a unique factor in estimating future unknown values. The aim of this research is to identify and forecast the conditions of the Tehran Stock Exchange(TSE) and the factors affecting them, focusing on the correlation between market prosperity and value at risk. To achieve this, in the first step of this study, the time series of the value at risk index on the capital market TSE was estimated using daily data and the first-order GARCH method from spring 2010 to June 2023. Then, the factors influencing prosperity in TSE were evaluated based on seasonal data from spring 2010 to June 2023 using the probit regression approach. In addition, value at risk index was calculated seasonally and the relationship between the probability of market prosperity and the value at risk index was examined using correlation coefficients.The research results show that the probability of market prosperity in the Iranian capital market has a significant negative relationship with the bank interest rate, liquidity growth and the occurrence of sanctions. There is also a significant positive relationship with the inflation rate and the growth of the exchange rate. Furthermore, the correlation analysis shows that market prosperity is directly related to equity value at risk. Assuming stable conditions, the research suggests that the probability of a prosperity market in the next three seasons is significantly higher than the occurrence of a recession. Manuscript profile -
Open Access Article
31 - مدلسازی ریاضی مبتنی بر GAS جهت برآورد ارزش در معرض ریسک فاقد حافظه برای شاخص کل بورس اوراق بهادار تهران
محمدابراهیم سماوی هاشم نیکومرام مهدی معدنچی زاج احمد یعقوب نژاددر دههای اخیر، به صورت ویژه از سال 2000 میلادی روشهای پیشرفته ریاضی جهت مدلسازی مالی کاربرد فراوانی پیدا کرده است به طوری که با استفاده از این روشهای میتوان به بسیاری از چالشهای اساسی علوم مالی فائق آمد. اولین قدم در مدیریت ریسک در حوزه سرمایه گذاری، محاسبه متغیری Moreدر دههای اخیر، به صورت ویژه از سال 2000 میلادی روشهای پیشرفته ریاضی جهت مدلسازی مالی کاربرد فراوانی پیدا کرده است به طوری که با استفاده از این روشهای میتوان به بسیاری از چالشهای اساسی علوم مالی فائق آمد. اولین قدم در مدیریت ریسک در حوزه سرمایه گذاری، محاسبه متغیری است که ریسک را به طور دقیق توضیح می دهد. یکی از پرکاربردترین معیارها برای محاسبه ریسک، ارزش در معرض ریسک است که در سه دهه گذشته مورد توجه محققان مالی بوده است. هدف مطالعه حاضر مدلسازی پویا و زمان متغیر با استفاده از تکنیکی به نام امتیاز خودرگرسیون تعمیم یافته (GAS) برای تخمین ارزش در معرض ریسک شاخص کل با استفاده از داده های روزانه از سال 1390 الی 1399 و با فرض توزیع t-student است. نتایج آن با نتایج مدل های AR و GARCH شناخته شده مقایسه شده است. برای TSE تنها دو مدل GAS و GARCH برای تخمین ارزش در معرض ریسک مناسب هستند و مدل GAS ارجحیت دارد. همچنین، مدت زمان ریسک خطای ارزش در معرض ریسک برای هر سه مدل فاقد حافظه بلندمدت است که نشان دهنده اتکای آن در بحران های مالی است. Manuscript profile -
Open Access Article
32 - Designing and explaining the dynamic model of comprehensive risk transfer of cryptocurrency in the financial markets of the world
Reza Karimi Mirfeiz Falahshams Shadi Shahverdiani Gholamreza zomorodianThe purpose of this article was to provide a dynamic and dynamic model to explain how to transfer the pervasive risk of cryptocurrencies in the world markets. In this regard, the statistical information of the cryptocurrency market index and the data of the Nasdaq, New MoreThe purpose of this article was to provide a dynamic and dynamic model to explain how to transfer the pervasive risk of cryptocurrencies in the world markets. In this regard, the statistical information of the cryptocurrency market index and the data of the Nasdaq, New York, Toronto, London, Frankfort, Madrid, Shanghai, Hong Kong, Tokyo, and Mumbai stock market indices were used. In this research, the data related to the cryptocurrency market and financial markets from July 2012 to July 2022 have been used. In the first part of this study, using the information of the period 2012-2022, based on the frequency of monthly data for the financial markets, the comprehensive risk criterion has been calculated using the method of value at risk, conditional interval and expected loss. In the second part, using multivariate conditional heteroscedastic variance autocorrelation method (MGARCH), the external effects related to pervasive risk related to cryptocurrency were estimated on financial markets. The obtained results indicate that there are spillover effects between financial markets and an increase in pervasive risk in each of the financial markets leads to an increase in pervasive risk in other financial markets. In the second part, using multivariate conditional heteroscedastic variance autocorrelation method (MGARCH), the external effects related to pervasive risk related to cryptocurrency were estimated on financial markets. The obtained results indicate that there are spillover effects between financial markets and an increase in pervasive risk in each of the financial markets leads to an increase in pervasive risk in other financial Manuscript profile -
Open Access Article
33 - Wavelet based Filtered historical simulation value at risk model in different time horizons in Tehran Stock Exchange
وحید ویسی زاده جواد شکرخواه میثم امیریAbstract: Value at risk is applied as a downside risk measure to quantify risk and as a basis for calculating the regulatory purpose capital of financial institutions. The present study seeks to select the most accurate models for estimating value at risk, both simple a MoreAbstract: Value at risk is applied as a downside risk measure to quantify risk and as a basis for calculating the regulatory purpose capital of financial institutions. The present study seeks to select the most accurate models for estimating value at risk, both simple and advanced, and to present a new wavelet based model on Tehran Stock Exchange. Filtered historical simulation(FHS), Conditional extreme value theory model(CPOT) and a new hybrid semiparametric model called "Wavelet based Filtered historical simulation" in various forms using different volatility models and distribution assumptions were estimated and on the Tehran Stock Exchange. The backtest finding of research conducted in a period of about 11 years of the total index of Tehran Stock Exchange(TSE) from 2010/4/7 to 2020/4/1 (more than 2400 daily of index return data) indicate the higher accuracy of the filtered historical wavelet-based simulation (WFHS) VaR model in comparison to other models at all-time horizons and different confidence levels. Manuscript profile -
Open Access Article
34 - مقایسه ارزش در معرض ریسک سهام تهران با بازارهای سهام بین المللی با استفاده از نظریه ارزش فرین شرطی
شهرام بابا لویان هاشم نیکو مرام حمیدرضا وکیلی فرد فریدون رهنمای رود پشتی -
Open Access Article
35 - Value at Risk Assessment in Tehran Stock Exchange using Non-parametric and parametric Approaches
ebrahim ghanbari memeshi seyed ali nabavi chashmi erfan memarianThe purpose of this study is to evaluate the value at risk of stock indexes based on parametric and nonparametric approaches in Tehran Stock Exchange. In this regard, the Tehran Stock Exchange (TEPIX) index was used as a representative of market portfolios and daily dat MoreThe purpose of this study is to evaluate the value at risk of stock indexes based on parametric and nonparametric approaches in Tehran Stock Exchange. In this regard, the Tehran Stock Exchange (TEPIX) index was used as a representative of market portfolios and daily data for the period 13/10/2009-12/11/2019. In this study, first, the results of estimating the value at risk using two models of exponentially weighted Moving Average (EWMA) and Monte Carlo simulation (MC) are presented. The performance tests of these models are then compared with other models including GARCH and historical simulation models. The estimation results of these models were obtained using Eviews 10 and Matlab 2018 software. The results show that the exponential moving average (EWMA) model is more efficient and more accurate than other models. The results also show that based on violation ratio and Back Tests, non-parametric models such as Monte Carlo simulation have overestimated the value at risk . Manuscript profile -
Open Access Article
36 - مقایسه کارایی مدل میانگین- واریانس و نظریه ارزش فرین در بهینه سازی سبد سرمایه گذاری در بورس اوراق بهادار تهران
افسانه سینا میرفیض فلاح -
Open Access Article
37 - Assessing the Transparency of Selected Private Banks' Information Based on Risk Criteria (Value At Risk)
Hossein Abdo Tabrizi reza tehrani Ghodratolla Imam Verdi Saeed Fallahpour Ali BaghaniAbstractTransparency of financial information has always been one of the most important concerns of investors and depositors of the banking system. Therefore, the purpose of this study is to investigate the significant relationship between value at risk using book data MoreAbstractTransparency of financial information has always been one of the most important concerns of investors and depositors of the banking system. Therefore, the purpose of this study is to investigate the significant relationship between value at risk using book data and market data as a measure of information transparency. For this purpose, at first, the value at risk was calculated using the EGARCH model and then, to examine the significance of the relationship and ranking of banks in terms of information transparency, Pearson correlation coefficient between value at risk (VaR) calculated from market data and book data has been used. The results showed that in the simultaneous data dimension, there is a weak relationship between book and market VaR and only the correlation coefficient between book and market VaR of Pasargad and Sina banks are statistically significant at 95% confidence level. If we consider the issue of the speed of book value information spreading in the market with a time lag, the values of the correlation coefficient of book and market VaRs for Parsian, Pasargad and Eghtesad-e-novin banks are significant at 99% confidence level and this coefficient is significant for Sina and Saman banks at 95% confidence level. Manuscript profile -
Open Access Article
38 - مقایسه کارایی روش های GARCH و ARCH در پیش بینی ارزش در معرض ریسک جهت انتخاب پرتفولیوی بهینه
امیررضا کیقبادی محمد احمدی -
Open Access Article
39 - Multivariate Portfolio Optimization under Illiquid Market Prospects
Nastaran Sarvipour fatemeh samadiThe aim of the current research is to optimize the multivariate portfolio optimization algorithms under illiquid market (commodity and financial) perspective. In this regard, an optimization model for portfolio risk-return assessment with LVaR constraints is investigate MoreThe aim of the current research is to optimize the multivariate portfolio optimization algorithms under illiquid market (commodity and financial) perspective. In this regard, an optimization model for portfolio risk-return assessment with LVaR constraints is investigated using reasonable financial and operational scenarios. This approach is achieved by minimizing LVaR. The research method is descriptive and correlational. The statistical population is the companies admitted to the Tehran stock exchange, which were selected by systematic elimination sampling (screening) of 100 companies that were present in the stock exchange during the financial years of 1392-1399.The required information was extracted through the new Rah Avard software and the official website related to the Tehran Stock Exchange Organization. The unit root test of the variables was investigated using the method of Lin and Chui, and the basics of econometrics were discussed, and the variables were investigated using the vector auto-regression method (VAR) using Eviews and MATLAB statistical software. Based on the results, it can be said; Liquidity affects commodity and financial markets. Also, the effect of optimization algorithms and modeling techniques on portfolio management and risk assessment was confirmed Manuscript profile -
Open Access Article
40 - Presenting the combined algorithm of machine learning and the combination of risk metrics and fuzzy theory in choosing an investment portfolio
danial mohammadi Seyed jafar Sajadi Emran Mohammadi naeim shokriThe current research was conducted to find the optimal portfolio for investing in stock exchange stocks, and one of the methods that is currently very popular among analysts and researchers in this field is methods based on artificial intelligence, followed by methods a MoreThe current research was conducted to find the optimal portfolio for investing in stock exchange stocks, and one of the methods that is currently very popular among analysts and researchers in this field is methods based on artificial intelligence, followed by methods aimed at reducing risk metrics. The aim of the current research is to form a portfolio using machine learning methods, risk measurement and its combination with fuzzy theory, which has a better return than the average return of the market. The output of each method is entered into the random forest algorithm and prediction is made by this algorithm, and in the last step, the prediction output is entered into the value-at-risk and value-at-risk optimization model with the fuzzy theory approach to form the capital portfolio. Shares information is daily and its time period is from the beginning of 2014 to the middle of 2018. At the end of each of these methods and steps, it was compared with the real return of the market. the CVAR risk measure has a better ability than the VAR risk measure, and the random forest algorithm among the used machine learning algorithms has achieved better results in choosing the investment portfolio. Manuscript profile -
Open Access Article
41 - Value Risk Assessment of Stock Indexes Based on Parametric, Quasi-Parametric and Nonparametric Approaches (Tehran Stock Exchange Study)
ebrahim ghanbari memeshi seyyed ali nabavi chashmi erfan memarianThe purpose of the present study is to evaluate the value at risk of stock indexes based on parametric, quasi-parametric and non-parametric approaches in Tehran Stock Exchange on the basis of data collected during the period of 2009-2010. The purpose of this study is pr MoreThe purpose of the present study is to evaluate the value at risk of stock indexes based on parametric, quasi-parametric and non-parametric approaches in Tehran Stock Exchange on the basis of data collected during the period of 2009-2010. The purpose of this study is practical. On the other hand, the present study is empirically oriented epistemologically, its inductive reasoning system, and field-library study using causal-historical information (ie, past information). In this regard, the performance of each of the above approaches was evaluated and finally the accuracy of accuracy was evaluated by the Basel Committee test and Bin, POF and TUFF frequency tests. The results show that parametric, quasi-parametric and semi-parametric models have priority in terms of efficiency and accuracy, respectively. In addition, the results from another perspective show that non-parametric and semi-parametric models based on error ratio and post hoc tests have overestimated the value of risk exposure, although the contribution of nonparametric model is higher Manuscript profile -
Open Access Article
42 - The assessment of extreme value theory and Copula - Garch models in prediction of value at risk and the expected short fall in portfolio Investment Company in Tehran stock exchange.
ali alizadeh Mirfeiz FallahThe present study has endeavored to represent a more precise model to calculate the risk of banks in this study by ARIMA-GARCH-COPULA Model has been introduced.In obtaining the iid distributions and variance estimation the mean model and conditional variance have been d MoreThe present study has endeavored to represent a more precise model to calculate the risk of banks in this study by ARIMA-GARCH-COPULA Model has been introduced.In obtaining the iid distributions and variance estimation the mean model and conditional variance have been determined and estimated simultaneously.In so doing, the ARIMA methodology has been employed to model the average return on assets of the study, and for modeling the research conditional variance of GARCH have been applied. Also mean error criterion has been used to compare the different models of VAR estimation, and for the purpose of testing statistical results backtesting methods have been employed. Based on mean error criterion, the proposed model of the study at hand has demonstrated the most accuracy The GEV model derived from the EVT has been ranked second The output of the Dow ranking method, however, has been very similar to one another According to Dow ranking method, the GEV model has had the lowest loss function at 5% level of significance, and at 1% level of significance, the HS model has demonstrated the least loss function. ES calculations have also been carried out for the four models with ARIMA-GARCH-COPULA model showing the least loss. Manuscript profile -
Open Access Article
43 - Designing a Risk Assessment Model and determining an Optimal Currency Portfolio for banks by Value-at-risk (VaR) criterion and exponentially weighted moving average (EWMA)
Gholamreza Bayati Mohammad Ebrahim mohammadPourzarandiBanks as fund intermediaries in providing and allocating resources to the community, encounter market risk, liquidity risk and etc. In this study, the market risk, is taken into consideration in order to determine the optimal currency basket, one of the fundamental aspe MoreBanks as fund intermediaries in providing and allocating resources to the community, encounter market risk, liquidity risk and etc. In this study, the market risk, is taken into consideration in order to determine the optimal currency basket, one of the fundamental aspects of Foreign Currency Reserve Management in banks, which itself is also affected by fluctuating interest rates, exchange rates, stock prices and etc. The approach used in this paper is the value-at-risk criterion (VaR) the variance-covariance method, along with the exponentially weighted moving average (EWMA) technic. Value at risk actually summarizes the types of risks in a single digit, and it releases the senior management from bunches of risk calculations. The purpose is to design a model which provide an optimal combination for holding 6 currency reserves such as U.S. dollar, Dirham, Yen, Lira, Won, and Euro in Bank Mellat using the reference rates data of the aforementioned currencies in 2018. At the end, the model was solved using LINGO and Excel software. The results show that the maximum share of the US dollar and the dirhams in the currency basket of Bank Mellat are 33% and 67%, respectively. Accordingly, if the share of that currencies mentioned above exceed the obtained digits in the currency basket, then the maximum expected losses on the currency portfolio increase over the time and at the level of desired level of confidence. Also, other currencies are so risky, therefore Mellat Bank, to hold these currencies must plan more based on its trading needs. Manuscript profile -
Open Access Article
44 - Estimation value at risk (VAR) and conditional value at risk (CoVaR) at Tehran Stock Exchange by approach to using Fréchet distribution (FD)
Azadeh Meharani Ali Najafi moghadam Ali baghaniRisk estimation cannot deliver appropriate reliable predictions by focusing on one or two models and considering the irrelevant factors. This study aims to estimate the value at risk (VAR) and the conditional value at risk (CoVaR) in the Tehran Stock Exchange using Fr&e MoreRisk estimation cannot deliver appropriate reliable predictions by focusing on one or two models and considering the irrelevant factors. This study aims to estimate the value at risk (VAR) and the conditional value at risk (CoVaR) in the Tehran Stock Exchange using Fréchet distribution (FD). In doing so, generalized extreme value (GEV) is used with the help of Friche distribution approach. In this study, the return of 21-day and 63-day data of the time series of the total index, free-float-stock index, and index of 50 active companies of Tehran Stock Exchange during 01/01/2012 to 12/29/1398 have been used. The obtained results through the estimation of three parameters of GEV, including location, scale, and shape, have shown that the parameter of distribution shape within all 21 and 63-day periods of each indicator is positive, and the distribution for indexes studied follows FD as the second type of generalized distribution of GEV. By using the same pattern, the measurement of CoVaR and VaR has presented that it is possible to estimate CoVar and VaR through the use of FD and CoVaR is higher than VaR within the whole range of alpha. Manuscript profile -
Open Access Article
45 - Dynamic GAS Based Modeling for Predicting and Assessing the Value at Risk of Bitcoin and Gold
Mohammad Ebrahim Samavi Hashem Nikoomaram Mahdi Madanchi Zaj Ahmad YaghobnezhadThe first step in risk management in the field of investment is to calculate the variable that explains the risk accurately. One of the most widely used criteria for calculating risk is the value at risk, which has been the focus of financial researchers for the past th MoreThe first step in risk management in the field of investment is to calculate the variable that explains the risk accurately. One of the most widely used criteria for calculating risk is the value at risk, which has been the focus of financial researchers for the past three decades. Therefore, the aim of the present study is dynamic modeling and variable time using a technique called Generalized Autoregressive Score (GAS) to estimate value at risk in bitcoin and gold by using daily data since 2010 to 2020 and assuming the distribution of t-student. its results are compared with the results of known AR and GARCH models. The results showed that for gold models such as GAS, GARCH and AR were able to estimate the value at risk at 5% error level. Among them, the GAS model had the best performance. For Bitcoin only two models, GAS and GARCH, are suitable for estimating value at risk and GARCH model is preferable. Also, the duration of risk of value at risk errors for all three models for gold and bitcoin lacks long-term memory, indicating its reliance on financial turmoil. Manuscript profile -
Open Access Article
46 - Provide a multi-objective - multi-objective mathematical model for investing in a portfolio under a hybrid risk measure
ahmad dadashpour omrani syed ali nabavi chashmi erfan memarianWhat has been said so far in the financial calculations and in the field of stock portfolio selection is that it prioritizes the existing investments in terms of degree of risk and return, so that investors can, considering the financial possibilities and Their risk lev MoreWhat has been said so far in the financial calculations and in the field of stock portfolio selection is that it prioritizes the existing investments in terms of degree of risk and return, so that investors can, considering the financial possibilities and Their risk level to form their preferred stock portfolio. Therefore, in this research, to present a multi-objective mathematical model for measuring stock portfolio risk by combining return metrics with two risk metrics, namely half variance and conditional risk exposure value along with transaction cost limit for fifteen shares of the top fifty stocks. The period of twelve months ending in 1398 has been discussed in the context of the Iranian capital market. According to the tables and graphs obtained from solving this type of model with the help of dynamic planning in different investment times, we will see better results in the efficiency of investors' decisions by spending less time and money and consequently more profitability of the portfolio. Manuscript profile -
Open Access Article
47 - Multi-Asset Portfolio Optimization based on Conditional Value at Risk using Artificial Bee Colony Algorithm
Somayeh Mousavi Abbasali Jafari-Nodoushan Marzieh Kazemi-Rashnani Mahsa MohammadtaheriMulti-asset portfolio management and optimization have always been of interest to investors. Due to the inflation in Iran market, different performance of the asset classes in different market conditions and the ability to earn more profit along with less risk by divers MoreMulti-asset portfolio management and optimization have always been of interest to investors. Due to the inflation in Iran market, different performance of the asset classes in different market conditions and the ability to earn more profit along with less risk by diversifying the types of assets, it seems necessary to select a portfolio consisting of stocks, foreign currency and commodities. In this paper, assets of the above categories, including Emami coins, American dollar, and 11 sector indices, are considered in the portfolio composition. Due to the importance of the risk measure in multi-asset portfolio optimization, a model with conditional value at risk, the historical simulation approach has been extended and its efficiency has been compared with the mean-variance model. The models have been solved using the artificial bee colony and imperialist competitive algorithms. The daily asset prices in the period 2013 to 2020 have been used to evaluate the models in Iran market. Results show that the mean-conditional value at risk model performs better than the mean-variance in the training and testing periods. Furthermore, optimized portfolios with the artificial bee colony algorithm could outperform the imperialist competitive algorithm based on the Sharpe ratio, conditional Sharpe ratio, and return on risk. Manuscript profile -
Open Access Article
48 - 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 MehraraThe 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 MoreThe 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 -
Open Access Article
49 - Tail Risk Analysis Using realized measure and Dynamic Asymmetric Laplace Models in Tehran Stock Exchange
esmail mohammadi salari Mohammad Reza Rostami Reza Gholami Jamkarani Mojganm safaAbstractThe main objective of this study is to estimate and evaluate the performance of the dynamic realized conditioned autoregressive value at risk model (Realized-ES-CAViaR-Add-RV-SAV) in forecasting tail risk measures (VaR and ES). In this regard, daily as well as i MoreAbstractThe main objective of this study is to estimate and evaluate the performance of the dynamic realized conditioned autoregressive value at risk model (Realized-ES-CAViaR-Add-RV-SAV) in forecasting tail risk measures (VaR and ES). In this regard, daily as well as intraday (hourly) data of Tehran Stock Exchange Index in the period of 24/6/2014 – 2/2/2021are used. The results of the model are compared to the results of ES-CAViaR-SAV and ES-CAViaR-AS models to investigate the effect of incorporating the realized component to the model. Using backtesting tools such as Bin, POF, TUFF, CC, CCI, VRate tests, Lopez loss function (LL) (in VaR part) and McNeil and Frey test and ranking according to MCS method in The ES part, the efficiency of the models are examined. The results of this study indicate the efficiency of all three models in forecasting the tail risk measures. In addition, the results show that the use of realized criteria increases the tail risk forecasting efficiency. Manuscript profile -
Open Access Article
50 - Portfolio optimization based on parametric and nonparametric period value at risk
Mohamad ali tabibi sayyed mohammad reza davoodi abdolmajid abdolbaghy ataabadyValue at risk is one of the most widely used risk measurement criteria. Period value at risk extends the concept of value at risk for an investment with a set of maturity horizons, thus neutralizing the model's sensitivity to a point investment horizon. This reduces the MoreValue at risk is one of the most widely used risk measurement criteria. Period value at risk extends the concept of value at risk for an investment with a set of maturity horizons, thus neutralizing the model's sensitivity to a point investment horizon. This reduces the impact of liquidity risk and the investor has ample opportunity to sell and can make the right decision in an interval. In the present study, two stock portfolio models are designed based on the period value at risk, the first based on historical simulation and the second is parametric and based on the distribution of normal-Laplace mixture for proper fitting of tail data. The result of the experimental study of the models designed on a stock portfolio with eight indices of the Tehran Stock Exchange in the period 1390 to 1399 shows that the parametric approach in the test data in average return and Sharp ratio criteria has a better performance than the historical scenario. Also, the relative error between the period risk value predicted by the stock portfolio and its estimation in the test data in the parametric approach is less. Manuscript profile -
Open Access Article
51 - تخمین ذخیره سرمایه ریسک عملیاتی در صنعت بانکداری
هاشم نصرتی کامران پاکیزه -
Open Access Article
52 - VaR modeling and back testing of short and long positions according to in Sample and out of Sample: application of family models Fractionally Integrated GARCH
Mansour Kashi S. Hassan Hosseyni A. Sadat niyazkhani S. Amin AbdollahiIn this study, In addition to calculate the short and long trading positions, we examined In Sample and Out of Sample VaR to assess the quality forecast model is considered. To estimate VaR Result, family models Fractionally Integrated GARCH (long term memory) shows tha MoreIn this study, In addition to calculate the short and long trading positions, we examined In Sample and Out of Sample VaR to assess the quality forecast model is considered. To estimate VaR Result, family models Fractionally Integrated GARCH (long term memory) shows that the model HYGARCH (1, d, 1) with the distribution skewed Student-t similar to the result for FIGARCH (1, d, 1) with skewed Student-t distribution for fat-tail phenomenon exhibits. A comparison of the two models with different distribution model HYGARCH (1, d, 1) with skewed Student-t distribution based on AIC criteria and maximum log-likelihood model was superior. failure rates, , and duration-based tests where were prepared for back testing in Sample VaR, Indicates that the VaR model of the student-t HYGARCH (1, d, 1) acceptable performance than other distributed models HYGARCH (1, d, 1) and the FIGARCH (1, d, 1) will be . So to estimate Out of Sample VaR by student-t HYGARCH (1, d, 1) has been paid. Like the analysis of the in sample VaR, Out of Sample VaR was compared with the observed output and results were evaluated by and DQ tests. Ultimately resulting VaR-based loss function at all levels quintile (either long or short term trading positions) shows that the model that has the characteristics of long memory in the conditional variance, minimum losses and better performance in assessment Forecast offers. Manuscript profile -
Open Access Article
53 - برآورد و ارزیابی ارزش در معرض ریسک در بازار فارکس
ابراهیم عباسی -
Open Access Article
54 - امکان سنجی استفاده از مدل ارزش در معرض ریسک
غلامحسین گل ارضی عظیم الله زارعی لیلا دلاوری مرغزار -
Open Access Article
55 - کاربرد شبیه سازی مونت کارلو و فرایند قدم زدن تصادفی
رضا راعی حسین فلاح طلب -
Open Access Article
56 - برآورد وارزیابی ارزش در معرض ریسک در بازار فارکس
ابراهیم عباسی -
Open Access Article
57 - Investment portfolio optimization using value at risk under credibility theory with Z-numbers approach
Amirsina Jirofti Amirabbas NajafiZ-numbers theory was proposed in 2011 by Lotfy Zadeh. This theory describe the uncertainty of information where any z-number is displayed by a pair of fuzzy number. Because of the uncertainty in the financial markets, this theory can be used in the investment portfolio MoreZ-numbers theory was proposed in 2011 by Lotfy Zadeh. This theory describe the uncertainty of information where any z-number is displayed by a pair of fuzzy number. Because of the uncertainty in the financial markets, this theory can be used in the investment portfolio selection. As the first component of z-number is the fuzzy asset return and the second component is reliability of prediction of first component. We can use value at risk criterion for increasing efficiency of investment portfolio selection model. Due to consideration the uncertainty in asset returns and using value at risk, this model is an appropriate model for investment portfolio selection. The advantage of this method compared to the conventional fuzzy method is consideration uncertainty of expert knowledge and allocation reliability to their prediction of fuzzy parameter. Finally, we provide a numerical example from Tehran stock market. Manuscript profile -
Open Access Article
58 - برآورد ارزش در معرض ریسک با استفاده از تئوری مقدار حدی در بورس اوراق بهادارتهران
سعید فلاحپور مهدی یاراحمدی -
Open Access Article
59 - پیش بینی ریسک نامطلوب با استفاده از مدلVaRبارویکرد چگالی حداکثرسازی آنتروپی در بورس اوراق بهادار تهران
میرفیض فلاح شمس لیالستانی عباس صالح اردستانی فریده حق شناس کاشانی سمیه رادسر -
Open Access Article
60 - Forecasting Volatility & Risk Management in Tehran Stock Exchange through Long memory impacts
ehsan Taiebysani Madihe Changi AshtianiIn this paper we explored the relevance of asymmetry and long memory in modeling and forecasting the conditional volatility and market risk of equity market in Iran capital M MoreIn this paper we explored the relevance of asymmetry and long memory in modeling and forecasting the conditional volatility and market risk of equity market in Iran capital Market (Tehran Stock exchange(TSE) and Iran Fara Bourse(IFB)). A broad set of the most popular linear and nonlinear GARCH (generalized autoregressive conditional Heteroskedasticity)-type models is used to investigate this relevancy of asymmetry and long memory. Our in sample and out-of-sample results displayed that volatility of commodity returns can be better described by nonlinear volatility models accommodating the long memory and asymmetry features. In particular, the FIAPARCH (Fractionally Integrated Asymmetric Power ARCH) model is found to be the best suited for estimating the VaR forecasts for both short and long trading positions. This model given a risk exposure at the 99% confidence interval level have Several implications for equity market risks, policy regulations and hedging strategies can be drawn from the obtained results of this paper. Manuscript profile -
Open Access Article
61 - مدیریت ریسک سبد با استفاده از مدلهای تجدید نظر شده ارزش در معرض ریسک (VaR)
فریدون رهنمای رودپشتی مسعود ملائی -
Open Access Article
62 - Statistical ranking of different VaR and ES models by using Model Confidence Set approach for the banking industry: With an emphasis on Conditional Extreme Value Theory
Alireza Saranj marziyeh nourahmadiIn this paper, we deal with the ranking of different VaR and ES approaches using daily banking industry index data over the period 2008 to 2016, with an emphasis on Conditional Extreme Value approach. In the first stage, we use Bernoulli coverage and independence of vio MoreIn this paper, we deal with the ranking of different VaR and ES approaches using daily banking industry index data over the period 2008 to 2016, with an emphasis on Conditional Extreme Value approach. In the first stage, we use Bernoulli coverage and independence of violation tests for VaR models and McNeil & Frey’s backtest for ES models to examine the validity of these models. In the second stage, we import the loss functions of the valid models remained from the first stage into the MCS function and rank statistically them. The loss function used for VaR models is Dowd loss function and the one used for ES models is Olsen loss function. The results show that the in both VaR and ES models, the conditional EV with normal standardized residuals, the conditional EV with student's t standardized residuals and GARCH with student's t residuals models are respectively ranked first to third. Manuscript profile -
Open Access Article
63 - بررسی مقایسه ای کارایی مدل ریسک سنجی و مدل اقتصادسنجی GARCH در پیش بینی ریسک بازار در بورس اوراق بهادار تهران
میرفیض فلاح شمس -
Open Access Article
64 - بهینه سازی سبدسرمایه گذاری بر اساس ارزش در معرض ریسک
غلامرضا اسلامی بیدگلی احسان طیبی ثانی -
Open Access Article
65 - Optimizing Portfolio through Extreme Value Theory in Tehran Stock Exchange
Afsaneh Sina Mirfeiz FallahshamsCreating a balance between risk and return has always been the major criterion in investment decisions in stock exchange. All investors look for an optimized compromise for their investments so that the utility function of their investment is maximized. This study aims MoreCreating a balance between risk and return has always been the major criterion in investment decisions in stock exchange. All investors look for an optimized compromise for their investments so that the utility function of their investment is maximized. This study aims at arriving at a more efficient model for optimizing investment portfolio. This model is to consider uncertainty and investment risk on the way to create a bigger return for the investors. In this way, Extreme value theory for assessing investment risk, as one of the newest assessors of value at risk (VaR) was utilized. The time of this study covers the period from 2013 to 2018. The sample includes top 50 companies in Tehran Stock Exchange. Using GARCH method and maximizing likelihood function, the type of return distribution of top companies of Tehran Stock Exchange was determined at the first step. Next, efficiency frontier for investment risk in Tehran Exchange was compared to Markovitz model`s efficient frontier, using a quadric planning model through a Extreme value theory approach. The results of this study signify that forming an optimized investment portfolio through a Extreme value model would not make any significant difference with Morkovitz Variance-Mean model. Manuscript profile -
Open Access Article
66 - Proposition of a model For Forecasting Value at Risk in One Step Ahead
ehsan Mohammadian Amiri S. Babak Ebrahimi maryam Nezhad AfrasiabiRisk forecasting for future periods plays an important role in making the right decisions of managers and financial activists to invest in companies and institutions. On the other hand wrong decisions of commercial managers can have undesirable consequences for their or MoreRisk forecasting for future periods plays an important role in making the right decisions of managers and financial activists to invest in companies and institutions. On the other hand wrong decisions of commercial managers can have undesirable consequences for their organizations. Therefore the most important issues for investors is forecasting risk in future periods. The importance of this issue was caused us to forecast Value at Risk (VaR) in one step ahead by using the exponential smoothing family for two normal and t-student distributions with confidence levels of 95%, 97.5% and also 99% in this research. Previously the classic method is commonly used to forecast future periods of VaR, but in this research the family of exponential smoothing models is used, which process data by considering trend and doing so online monitoring. In order to validate the model, the proposed model has been compared with the classic method by using backtesting. The results confirms the more accurate forecasting of proposed method in normal distribution with confidence levels of 97.5%, and 99% and also in t-student distribution with confidence levels of 97.5%, 99%. Manuscript profile -
Open Access Article
67 - Foster-Hart Optimal Portfolio
sepehr asefi reza eivazlu reza tehraniThis 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 MoreThis 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 -
Open Access Article
68 - VAR and ES calculation based on the Extreme Value Theory (block maxima and GPD): Evidence from Tehran Stock Exchange (TSE)
Mansour Kashi S. Hassan Hoseini mohammad Mousa Ghaliliou saeed Golkarian Arani Current study, has explores the VAR and ES in the Tehran Stock Exchange (TSE) by using the Extreme Value Theory (block maxima and GPD). Earlier estimates of the preliminary findings of the analysis that uses statistics, Empirical Distribution Function, Mean More Current study, has explores the VAR and ES in the Tehran Stock Exchange (TSE) by using the Extreme Value Theory (block maxima and GPD). Earlier estimates of the preliminary findings of the analysis that uses statistics, Empirical Distribution Function, Mean Excess Function and QQ plot, Pareto and heavy-tailed behavior were found data. To estimate the optimal threshold value, we have Mean Excess Function and hill plot applied. To estimate the optimal threshold value, Mean Excess Function and Hill plot use the statistics mentioned for the positive and negative returns, the threshold value for GPD models are about ./75 And ./60 have provided. Comparing the estimated residual value model classic extreme (monthly, quarterly, six month and one year) and the GPD, concluded the optimal performance GPD calculated on the value of extreme block which is highly sensitive to the choice of the period. Finally, to estimate VAR and ES, we GPD model demonstrated that a better performance was applied. The results showed that VAR and ES should not be the dominant financial risk management. In other words, dependence on individual risk scale for ignoring the problem will create portfolio risk information. So to contain the missing information by VAR and ES, it is essential that the various aspects of the distribution of losses / profits look like heavy-tailed. Manuscript profile -
Open Access Article
69 - Measurement conditional value at risk based on FIGARCH-EVT method at Tehran stock Exchange
mohammadreza Lotfalipour Mahdiyeh Nosrati abolfazl Ghadiri Moghaddam Mahdi FilsaraeiAn important factor in risk management is optimized conditional value at risk (CVaR) of the portfolio. Choose a model which calculates time depended to variance rather than the model with constant variance lead to improve data modeling. Using an appropriated method for MoreAn important factor in risk management is optimized conditional value at risk (CVaR) of the portfolio. Choose a model which calculates time depended to variance rather than the model with constant variance lead to improve data modeling. Using an appropriated method for measuring risk in financial asset returns distribution has a great utility. The main purpose of this study is implementing a hybrid procedure to calculate CVaR which, models, volatility and dynamics in clusters, and calculates CVaR value based on fat tail feature. In this case, using Extreme value theory (EVT) leads to calculate CVaR more precisely. In addition to, using some ARCH (autoregressive conditional heteroskedasticity) family models result to dynamic feature in estimating CVaR. Data were used in this study related to TEDPIX during 2001-2015. Total 2781 data were derived from Rahavard Novinand & TseCline softwares as daily. For analysis this TEDPIX data, MATLAB software and EXCELL were used. This result represented, return data distribution has fat tail. The historical simulation (HS) at 95% confidence level isn’t accurate, while the accuracy Generalized Auto-Regressive Conditional Heteroskedasticity-EVT (GARCH-EVT) model at 95% is more suitable. Using (Fractionally integrated generalized autoregressive conditional heteroskedasticity -EVT) FIGARCH-EVT method leads accurate estimates of CVaR in comparison with HS procedure. Calculating CVaR by FIGARCH-EVT-CVaR was more accurate than the GARCH-EVT-CVaR. This model has considered to both GARCH-EVT features and long memory property. The FIGARCH-EVT-CVaR model had acceptable accuracy and its exceptions are independent. In General, models which considered heteroscedastic, had an acceptable accuracy in comparing HS Manuscript profile -
Open Access Article
70 - Estimation Value at Risk using by combining approach Exteme Value Theory and CIPRA at Tehran stock Exchange
Ehsan Atefi Meysam Rashidi RanjbarThe expansion of the capital market and the reduction of interest rates on commercial banks has made that investing in dominate shares as one of the most important opportunities for obtain gain on investment, which requires risk acceptance. In this paper, the goal is to MoreThe expansion of the capital market and the reduction of interest rates on commercial banks has made that investing in dominate shares as one of the most important opportunities for obtain gain on investment, which requires risk acceptance. In this paper, the goal is to extract the residual values of the logarithmic return of the Tehran stock exchange index using the CIPRA model. Then, using the extreme value theory, the extreme value model was obtained for these residual. Extreme value theory is a good approach to the estimation of high and low tails and measure such as Value Risk (VaR). In order to determine the performance of this method, another model was compared with this model using the two indexes include Tehran Stock Exchange and the Top 50 Industry Index at 99 and 99.5% for the estimated value of risk. The results of the backtesting show that the EVT-CIPRA approach works better. Manuscript profile -
Open Access Article
71 - Determine the optimal portfolio weights var-stock approach And compare it with the Markowitz model
sayyedmohammadmahdi ahmadi hasan lotfi vali rajabiEvery investor is always looking for the investment portfolio that will bring him the most profit with the least risk. The standard deviation of an asset return is the amount of risk of that asset. In this study, the value-at-risk approach has been used as a measure of MoreEvery investor is always looking for the investment portfolio that will bring him the most profit with the least risk. The standard deviation of an asset return is the amount of risk of that asset. In this study, the value-at-risk approach has been used as a measure of risk in the formation of the optimal stock portfolio. By selecting a statistical sample consisting of seven companies operating on the Tehran Stock Exchange, first the variance-covariance matrix is extracted by the moving average weighted method (EWMA) and then the Markowitz model is calculated with the aim of reducing portfolio risk against an expected return level. Portfolio performance has been achieved. Then the value-at-risk limit is added to the efficient frontier chart, and then by analyzing the sensitivity of the value-at-risk value for different values of the level of confidence and the maximum risk accepted by the investor, we show that with the risk-value approach in forming the optimal portfolio Stocks may not change the limit of the Markowitz model, or be limited, or become a point, or even disappear. Manuscript profile -
Open Access Article
72 - Dynamic GAS Based Modeling for Predicting and Assessing the Value at Risk of Tehran Stock Exchange Index and Bitcoin
Mohammad Ebrahim Samavi Hashem Nikoomaram Mahdi Madanchi Zaj Ahmad YaghoobnezhadPurpose: This research has been written with the aim of modeling a new criterion for measuring risk in order to eliminate the shortcomings of traditional models in the field of investment risk management.Methodology: In the present study, with a practical purpose, to es MorePurpose: This research has been written with the aim of modeling a new criterion for measuring risk in order to eliminate the shortcomings of traditional models in the field of investment risk management.Methodology: In the present study, with a practical purpose, to estimate the value at risk of daily bitcoin price data (2,707 views) in the years 2013 to 2020 and the data of the total stock exchange index (2,753 views) 2011 to 2020 has been used in two groups of education and test (500 views). In order to estimate the value at risk using the nonlinear method and the generalized variable self-fitting time (GAS) method, modeling was performed by learning from the data of the training group and the accuracy of the model was determined by the data of the experimental group.Findings: The results showed that for the total stock index, only two models, GAS and GARCH, are suitable risk estimators. On the other hand, for Bitcoin cryptocurrencies, only two models, GAS and GARCH, are suitable risk estimators, which GARCH model is more preferable.Originality / Value: Findings showed that the new GAS model is a preferential estimator for the total stock market index than other nonlinear models. This is due to the variable time feature as well as the dynamics of the GAS model, which is able to respond to market turbulence conditions unlike traditional models in the short run. These results also help investors and active financial institutions to manage risk in their trading systems. Manuscript profile -
Open Access Article
73 - The use of support vector machine and Naive Bayes algorithms and its combination with risk measure and fuzzy theory in the selection of stock portfolio
Danial Mohammadi Emran Mohammadi Naeim Shokri Nima HeidariPurpose: The purpose of the current research is to create an optimal portfolio using machine learning algorithms and fuzzy theory, which has a better return than the average return of the market (total index of the stock exchange).Research Methodology:In this article, t MorePurpose: The purpose of the current research is to create an optimal portfolio using machine learning algorithms and fuzzy theory, which has a better return than the average return of the market (total index of the stock exchange).Research Methodology:In this article, the stocks of the selected companies are classified in the first stage using the two introduced algorithms. In the next step, stocks that entered the positive class are predicted for the next trading day with the help of random forest algorithm. For each company, three predictions are made, which are the inputs of fuzzy method optimization. Optimization is done with the aim of minimizing the risk with risk measures of value at risk and value at conditional risk. Shares information is five years old (daily) and its time period is from the beginning of 2017 to the end of 2021.Findings: In the end, each of the algorithms and the risk measure used were measured and compared with the actual market return. Based on the obtained results, the CVAR risk measure has a better capability and result than the VAR risk measure, and the support vector machine algorithm has also achieved a better performance in choosing the investment portfolio.Originality/ value: This research is optimized in the form of a capital sample by integrating machine learning methods and risk measures. Adding VaR and CVaR risk metrics enhances the decision-making process regarding risk reduction. Forecasting with the help of random forest and using an approach based on fuzzy theory for risk and value analysis gives the research an innovative perspective in portfolio formation. The findings provide investors and researchers with valuable insights in their search for better investment strategies. Manuscript profile
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