Value at Risk

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 Valahzaghard

Financial 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 More

Financial 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 - Estimating Portfolio Market Risk Based on Value at Risk (VaR)
M. Khalili Araghi S. Hashemi

Considerating the day by day ever changing environment and economic systems factors, every day, differentrisks influence on finance structure of financial institutions. Incremental trend of globalization phenomenonin financial markets, internationalization of economy, f More

Considerating the day by day ever changing environment and economic systems factors, every day, differentrisks influence on finance structure of financial institutions. Incremental trend of globalization phenomenonin financial markets, internationalization of economy, financial innovations and create new financialinstruments, as well as the vast and fast derivative products development, understanding of the effect of themarket circumstances in firm’s situation is powerful more than ever.Therefore, market risk is the important point of view for market players. Market risk is kind of risk thatarises in market. It includes several kinds of risk such as: product and stock price risk, bull-bear market risk,exchange rate risk and etc.In this paper, we want to answer this question that “how market risk of portfolio can estimate whit value atrisk mode”. this research based on special manner of data gathering called correlation research. VaR is thestatistical measure of the risk that estimates the maximum loss that may be experienced on a portfolio with agiven level of confidence. In this article, at first, we considered the importance of risk management, and thenexplain the role of market risk in financial market of our country. In continue, we will presentation theefficient instrument for calculate portfolio market risk management. Finally, we will calculate amount ofportfolio VaR for an investment company as a case study. Research outcomes indicate that sevenpercentages from capital or value of portfolio tantamount to 11 millions Rials, exposure at market risk.Whereas this measure specify amount of company’s value at risk for financial managers, operate better thanpast models. Manuscript profile

Open Access Article

3 - Portfolio Optimization Based on Cross Efficiencies By Linear Model of Conditional Value at Risk Minimization
K. Yakideh M.H . Gholizadeh M. Kazmi

Markowitz model is the first modern formulation of portfolio optimization problem. Relyingon historical return of stocks as basic information and using variance as a risk measure aretow drawbacks of this model. Since Markowitz model has been presented, many effortshave More

Markowitz model is the first modern formulation of portfolio optimization problem. Relyingon historical return of stocks as basic information and using variance as a risk measure aretow drawbacks of this model. Since Markowitz model has been presented, many effortshave been done to remove theses drawbacks. On one hand several better risk measures havebeen introduced and proper models have been developed to detect optimized portfolio basedon them. On the other hand the idea of using generated data by data envelopment analysisinstead of historical return of stocks has been presented.In this paper, both improvements are collected by applying a conditional value at riskminimization linear model on cross efficiencies, generated by a proper model of dataenvelopment analysis model, called range adjusted model. Performance of proposedmethod, market portfolio as a benchmark and method of applying Markowitz model oncross efficiencies calculated according to sharp ratio using next year real return of eachportfolio during years of study. Results support proper performance of proposed method. Manuscript profile

Open Access Article

4 - Three steps method for portfolio optimization by using Conditional Value at Risk measure
S. Navidi sh. Banihashemi M. Sanei

Comprehensive methods must be used for portfolio optimization. For this purpose, financial data of stock companies, inputs and outputs variable, the risk measure and investor’s preferences must be considered. By considering these items, we propose a method for por More

Comprehensive methods must be used for portfolio optimization. For this purpose, financial data of stock companies, inputs and outputs variable, the risk measure and investor’s preferences must be considered. By considering these items, we propose a method for portfolio optimization. In this paper, we used financial data of companies for screening the stock companies. We used Conditional Value at Risk (CVaR) as a risk measure, because of its advantages. Data Envelopment Analysis (DEA) can be used to calculate the efficiency of stock companies. Conventional DEA models assume non-negative data. However, many of these data take the negative value, therefore we propose the MeanSharp- CVaR (MSh CV) model and the Multi Objective MeanSharp- CVaR (MOMSh CV) model base on Range Directional Measure (RDM) that can take positive and negative values. By using Multi Objective Decision Making (MODM) model, investors can allocate their capital to the stocks of portfolio as they like. Finally, a numerical example of the purposed method is applied to Iran’s financial market. Manuscript profile

Open Access Article

5 - Survey on the Fisibility of Substitution Catastrophe Securitization and Current Reinsurance in Iranian Insurance Industry
Kambiz Peykarjou hanieh davodi

After 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 More

After 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

6 - Estimating Conditional VaR Using Symmetric and Non-Symmetric Autoregressive Models in Old and Oil Markets
Saeid Fallahpour Fatemeh Rezvani Mohammadreza Rahimi

Price 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 More

Price 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

7 - A framework for measuring and predicting system risk with the conditional value at risk approach
Ja'far Baba Jani M. Taghi Taghavi Fard Amin Ghazali

In recent years with the increasing integration and innovation in financial markets, concerns about the overall stability of the financial system has increased and the concept of systemic risk has become more important. systemic risk is the risk imposed by interlinkages More

In recent years with the increasing integration and innovation in financial markets, concerns about the overall stability of the financial system has increased and the concept of systemic risk has become more important. systemic risk is the risk imposed by interlinkages and interdependencies in a system or market, where the failure of a single entity or cluster of entities can cause a crisis in the entire system or market. In this study, we presented a framework for measuring and predicting systemic risk in the capital market of Iran using conditional value at risk approach (CoVaR). On this basis, ΔCoVaR as a measure of systematic risk using quintile regression based on a set of state variables that indicates changes in the distribution of asset returns has been estimated. As well as to enhance the accuracy of the estimate, the research variables modeled after the conditional autoregressive value at risk model (CAViaR) has been developed and some Lagged firm specific characteristic has also been added. In order to test the validity of the model back testing methods have been used. On the other hand, The potential for systemic risk increases when volatility decreases (volatility paradox). In this study, we try to predict systemic risk by take advantage of the panel structure of the data and the relationship between ΔCoVaR and firm-specific variables that are available in certain sections. Manuscript profile

Open Access Article

8 - Estimating the Investment Risk in a Digital Currency Portfolio and Optimizing it Using Value at Risk
Ahmad Aghamohammadi Fereydoon Ohadi Mohsen Seighaly Bahman Banimahd

A digital currency is a complex form of electronic money.The process of transferring this system is quite direct, and compared to the traditional method, there is less cost and time for transactions to take place in different parts of the world. Digital currencies use a More

A digital currency is a complex form of electronic money.The process of transferring this system is quite direct, and compared to the traditional method, there is less cost and time for transactions to take place in different parts of the world. Digital currencies use a system called the Block chain,Anyone who understands the benefits of the Chinese block,It's empty in our country .Advantages such as the impossibility of manipulating information, intelligence and decentralizing processes, along with high transparency, are issues that optimistic about the future of this technology. In this research, we select a number of digital currencies with the highest transaction volume and liquidity to create portfolios. and calculated using the Value at Risk (VaR) approach and the return on the portfolio Finally, an optimal investment portfolio is offered. Manuscript profile

Open Access Article

9 - Fuzzy Mean-CVaR Portfolio Selection Based on Credibility Theory
S. Babak Ebrahimi Amirsina Jirofti Matin Abdi

This 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 More

This 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

10 - Risk Measurement in Value at Risk (VaR): Application of Levy GARCH models (Study of Chemical industries in Tehran Stock Exchange)
hossein amiri mahmood najafi nezhad mohammad sayadi

Given that investing in the stock market is associated with risk, measuring it is one of the most important issues for investors. The present study measures risk measurement by the measure of risk. In this study, the value at risk, using the GARCH, APARCH and GJR models More

Given that investing in the stock market is associated with risk, measuring it is one of the most important issues for investors. The present study measures risk measurement by the measure of risk. In this study, the value at risk, using the GARCH, APARCH and GJR models with normal distributions, T-stents, T-stents, strings and strings, including string distributions; the reverse distribution of normal GIG (NIG) and generalized hyperbolic distribution (GHyp) is estimated. In this study, to measure risk, the efficiency of Tehran Stock Exchange index in chemical industries and total index has been used. The time period in this study includes a seven-year period with a daily frequency during the period of 05/01/1392 to 28/12/1398. The results showed that the Garc models were more accurate with the Levy distribution, and among the Garc models, the GJR model was more accurate, considering the Lou distribution and the Skewed-t distribution used among the other models. Manuscript profile

Open Access Article

11 - Portfolio optimization with differential evolution and conditional value at risk approach
Shahin Ramtinnia Romina Atrchi

Portfolio 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 More

Portfolio 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

12 - The impact of structural dependence on the efficient frontier of portfolio changes and comparison with traditional methods in Tehran Stock Exchange (Copula functions)
Mehdi Salehi Samaneh Zamani Moghaddam

Markowitz optimization problem and to determine the efficient frontier of investment, when the number of assets and restrictions on investment in the market is low, the mathematical model is solved. But this mathematical approach can reply different provider that someti More

Markowitz optimization problem and to determine the efficient frontier of investment, when the number of assets and restrictions on investment in the market is low, the mathematical model is solved. But this mathematical approach can reply different provider that sometimes it is more accurate and more complete. In this paper, we examine the dependence structure between time series Tehran Stock Exchange market indices and exchange rate of the dollar and its impact on the efficient frontier portfolios have covered.The results show that the upper tail dependence indices is less than the lower tail dependence, this means that the decline in the dollar exchange rate indices are reduced, but with the rise in the dollar exchange rate accepted in Tehran stock Exchange index increase is lower. We also propose a new optimization program where the risk is worth the risk and return of joint function is estimated. The results show that the upper tail dependence indices is less than the lower tail dependence, Manuscript profile

Open Access Article

13 - Investigating different methods of estimating tail risk measures with generalized Pareto distribution in Tehran stock exchange
Eisa Mahmoudi Najme Dehqani Hojjatollah Sadeqi

The study of the probability of the occurrence of the extreme events (the events which occur with low probability of occurrence) is an important issue in the risk management. Extreme value theory calculates risk measures using extreme events for a financial basket, rega More

The study of the probability of the occurrence of the extreme events (the events which occur with low probability of occurrence) is an important issue in the risk management. Extreme value theory calculates risk measures using extreme events for a financial basket, regardless of the distribution function of the return of the financial assets. In this theory, the method of peaks over threshold is practically the most appropriate and applied method by the use of which separate modeling of the tail part of the dataset is possible by using the generalized Pareto distribution and the start of the appropriate threshold. For this reason, in this paper, the methods of maximum likelihood estimator, likelihood moment estimator, Zhang and the weighted nonlinear least squares under the POT framework have studied and compared to estimate the parameters of the generalized Pareto distribution in order to estimate the value at risk and the expected shortfall of indices of food other than sugar, banks, car, chemicals, pharmaceuticals, cement, agriculture, petroleum products, textiles, coal, financial , industrial, the price of 50 companies, free float and the second market of Tehran stock exchange from March 25, 2013 to May 18, 2016. The overall results show that the expected shortfall is a more coherent measure for risk calculation, and the nonlinear weighted least squares estimator under the POT framework provides better estimation for generalized Pareto distribution. Manuscript profile

Open Access Article

14 - Deviation from normal distribution and its impact on the differential value at risk
Hojatollah Sadeghi Samaneh Dehghan Menshadi

In the most of financial models it’s supposed that distribution of observations is normal and the Value at Risk (VaR) and other criteria of market risk are calculated upon this distribution. This is while observations follow abnormal distributions in reality. So t More

In the most of financial models it’s supposed that distribution of observations is normal and the Value at Risk (VaR) and other criteria of market risk are calculated upon this distribution. This is while observations follow abnormal distributions in reality. So this study calculates Incremental Value at Risk (IVaR) with the assumption of being normal initially and then with regard to real distribution of data and finally compares the results of these two situations. The scope of this study consists of 42 companies present in financial sector of Tehran Stock Exchange during 2009 to 2013.The result show that by using IVaR criterion we can analyze the impact of each stock on creating the risk of portfolio and we can selected the optimal stocks. Also the results confirm this point that analysis of an portfolio’s sensitivity using IVaR criterion and based on that portfolio’s real distribution achieves more accurate and reliable results rather than it’s normal distribution. Manuscript profile

Open Access Article

15 - Risk Analysis & Financial Evaluation in Power Plant BOT
Faramarz Nouri Parastoo Mohammadi Esmaeil Vassaf

The 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 More

The 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

16 - Using intelligent methods in Solving Constrained Portfolio in Tehran Stock Exchange
Esmat Jamshidi Eyni Hamid Khaloozadeh

The 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 More

The 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

17 - Using intelligent methods in Solving Constrained Portfolio in Tehran Stock Exchange
Esmat Jamshdi Eyni Hamid Khaloozadeh

The 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 More

The 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

18 - 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 Baghani

Selecting 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 More

Selecting 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

19 - Ranking of exchange-traded funds (ETF) And value at risk approach (EVT) based on value-generating theory (VaR) risk approach
Gholamreza Zomorodian Maryam Sohrabi

Given 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 More

Given 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

20 - Comparative Analysis of Stock Portfolio Optimization in Fireworks and Genetic Algorithms Using Conditional Value at Risk
Ali Asghar Shahriari saeed Daei-Karimzadeh Reza Behmanesh

10.30495/jfksa.2021.19255

Devaluation 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 More

Devaluation 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

21 - 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 Ebrahimi

The 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 More

The 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

22 - Assessing the Efficiency of the Value-at-Risk Index (VAR) using Extreme Value Theory in comparison with traditional risk assessment methods
Mehrdokht Mozaffari Hashem Nikoomaram

Generally, the greatest risk in the capital market or in the portfolio of investors occurs when large sudden changes occur in the unfavorable portfolio. These losses are in the distribution sequence, and for this purpose they are called "limitative values". In this rese More

Generally, the greatest risk in the capital market or in the portfolio of investors occurs when large sudden changes occur in the unfavorable portfolio. These losses are in the distribution sequence, and for this purpose they are called "limitative values". In this research, the logarithmic efficiency of the Tehran Stock Exchange Index based on the information received during the time interval between the day (due to the use of high frequency data) during the years 1392 to 1395, and the use of the maximum block approach in measuring the VaR value index is used. It turned out VaR index was calculated using historical simulation methods and variance-covariance method as the traditional risk assessment criteria and the results were compared. The results of data analysis in R software showed that the use of monthly information in calculating the risk-weighted value index has a higher predictive accuracy and the error rate (test error) in this case is lower than traditional risk assessment methods. Manuscript profile

Open Access Article

23 - Financial Risk Modeling with Markova Chain
Fraydoon Rahnamay Roodposhti Hamid Vaezi Ashtiani Bahman Esmaeili

Manuscript profile

Open Access Article

24 - A Evaluation Power of Value at Risk (VaR) model and Fama & French 3-Factor Estimation model Selecting Optimazed Portfolio of Stock in Stocks Market of Tehran in Year 2001-2008
دکتر قدرت اله طالب نیا فاطمه احمدی نظام آبادی

If investors inrest all their stocks in one special possesson, they may confront withmany risck and only gain major capital but also minor capital too. So, they select setof investories in their decisions , so that set is the best of possible set from investory ,until , More

If investors inrest all their stocks in one special possesson, they may confront withmany risck and only gain major capital but also minor capital too. So, they select setof investories in their decisions , so that set is the best of possible set from investory ,until , they can gain access to their optimum out put that is close to market out put.Aim of this search is that with use from ٢models such as 3 Fama & French factorsand Value at Risk model, in Power of estimation models for selection of bestportfolio, to designers is helped. Hypothesis of this search is based on this subject thatevery one has foresight ability estimation optimazed portfolio. Atlast, after to do testof hypothesis by regresion, this result is Fama & French 3-factor has power ofsuggestion in selection of optimazed portfolio and Value at Risk moel has power ofsuggestion in selection of optimazed portfolio. Manuscript profile

Open Access Article

25 - Robust Portfolio Optimization with risk measure CVAR under MGH distribution in DEA models
Morteza Robatjazi Shokoofeh Banihashemi Navideh Modarresi

Manuscript profile

Open Access Article

26 - Analysis of financial risk in the cryptocurrency market: Evidence from predicting value at risk
Zahra Bozorgtabar Baei Reza Aghajan Nashtaei Mohammad Hasan Gholizadeh

Considering 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 More

Considering 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

27 - 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 Shams

The 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 More

The 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

28 - Effect of asset-liability management on credit risk
hadi farnian Fraydoon Rahnamay Roodposhti taghi torabi

Banks as the biggest and most important active institutions in money market as well as having financial intermediary role including resource saving and financing play a significant role in the economy. Banks face with different challenges to play their role in the socie More

Banks as the biggest and most important active institutions in money market as well as having financial intermediary role including resource saving and financing play a significant role in the economy. Banks face with different challenges to play their role in the society. One of these challenges is the optimal asset-liability management along with evaluating the related risks including credit risk which derives from lending facilities. The present study aimed to implement asset-liability management model for managing the credit risk of the banks. The ratio of lending facilities to asset and the ratio of delayed debts to facilities and capital adequacy were the variables of the study to assess the credit risk. In addition, the value at risk was calculated. In this study, data were collected from all 14 banks listed on the Tehran Stock Exchange from 2009 to 2016. The results indicated that it is essential to implement asset-liability management model for effective management and reducing the credit risk for the banks. Manuscript profile

Open Access Article

29 - Model for Calculating the Deposit Guarantee Fund’s Special Membership Fee Based on Risk
mehran aarabi ghasem aarabi ali saghafi jafar babajani

ارجحیت و اوزان 22 شاخص با استفاده از اعداد فازی ذوزنقه‌ای با روش تحلیل سلسله مراتب فازی تعیین و پس از انجام محاسبات میانگین هندسی و نرمالایز کردن آنها، ضرایب شاخص‌های موصوف بدست آمده است. با استفاده از داده‌های واقعی سال 1395، شاخص‌های 31 بانک و موسسه اعتباری در سه بعد More

ارجحیت و اوزان 22 شاخص با استفاده از اعداد فازی ذوزنقه‌ای با روش تحلیل سلسله مراتب فازی تعیین و پس از انجام محاسبات میانگین هندسی و نرمالایز کردن آنها، ضرایب شاخص‌های موصوف بدست آمده است. با استفاده از داده‌های واقعی سال 1395، شاخص‌های 31 بانک و موسسه اعتباری در سه بعد مالی، نظارتی و سرمایه‌ای محاسبه و مقدار ریسک جامع بانک‌ها تعیین شده است. پس از تعیین ریسک جامع هر بانک از تاثیر ریسک جامع بر مبلغ تضمین، ارزش در معرض خطر5 هر بانک محاسبه شده است. در نهایت از طریق تعیین سهم از کل ارزش در معرض خطر، مبلغ حق عضویت خاص محاسبه شده است. Manuscript profile

Open Access Article

30 - Performance Assessment of a Mutual Fund Using Fractional Modeling and the Concept of Value at Risk
Mahmoudreza Khajehnasiri Hamidreza Vakilifard

During the last few years, the extraordinary explosion experienced by fundraising organizations or investment companies purchasing other companies's stocks has led the responsible organizations for controlling these investments to apply some risk-based management guidel More

During the last few years, the extraordinary explosion experienced by fundraising organizations or investment companies purchasing other companies's stocks has led the responsible organizations for controlling these investments to apply some risk-based management guidelines. But the flexibility of this issue raises a lot of questions regarding the selection of the most accurate and most appropriate estimation model. The aim of this paper is to calculate the value at risk of mutual funds in Iran using fractional modeling. In this study, using the parametric method, we compute value at risk. Firstly, the variance is considered to be a constant value and then conditional ones (Arch and Garch models), finally, using the fractional modeling, we calculate and take into account it in the parametric method to find the best way to predict possible losses of the investment fund files. Consequently, according to the nonparametric, Kupiec, Christopherson and Hendricks tests, value at risk method is applicable for evaluating the performance of investment funds. On the other hand, the Garch and Figarch methods are capable of receiving %97.5 and %99 confidence levels and their results are acceptable in terms of statistics. Therefore, as a general result: the two methods stated to calculate value at risk of investment funds can be used for predicting the risk of these funds. Manuscript profile

Open Access Article

31 - Systemic risk assessment models: a better approach in Iranian financial institutions
majid noroozi Hamid Reza Kordlouei Reza gholamijamkarani hossein Jahangirnia

ریسک سیستمیک به خطر شکست سیستم مالی یا شکست کل بازار اطلاق می‌شود. این ریسک می‌تواند از بی‌ثباتی یا بحران در مؤسسات مالی نشأت بگیرد و در اثر سرایت به کل نظام مالی انتقال یابد. به‌عبارتی ریسک سیستمیک به میزان به‌ هم‌پیوستگی در یک سیستم مالی اشاره دارد جایی‌که شکست در یک More

ریسک سیستمیک به خطر شکست سیستم مالی یا شکست کل بازار اطلاق می‌شود. این ریسک می‌تواند از بی‌ثباتی یا بحران در مؤسسات مالی نشأت بگیرد و در اثر سرایت به کل نظام مالی انتقال یابد. به‌عبارتی ریسک سیستمیک به میزان به‌ هم‌پیوستگی در یک سیستم مالی اشاره دارد جایی‌که شکست در یک نهاد مالی می‌تواند به بحران کل سیستم منجر شود. این تحقیق با توجه به رویکردهای مختلف جهت اندازه&rlm;گیری ریسک سیستمیک به دنبال انتخاب رویکرد بهتر برای اندازه&rlm;گیری ریسک سیستمیک است. انتخاب رویکرد بهتر با توجه به خطای پیش&rlm;بینی ارائه شده توسط هریک از مدل&rlm;ها است. مدل‌های به کار گرفته شده اعم از مدل&rlm;های گارچی چند متغیره، مدل ارائه شده توسط برانلس و انگل به نام VCT، مدل&rlm;های عاملی&rlm;، مدل&rlm;های آماری دومتغیره است. نتایج تحقیق نشان می&rlm;دهد که مدل پیشنهادی برانلس و انگل (VCT) خطای کمتری را نسبت به سایر مدل&rlm;ها از خود نشان داده است. Manuscript profile

Open Access Article

32 - Relationship between risk and risk - aversion utility Based on Multi-Period prospect theory
RAZIEH Ahmadi Adel Azar gholam reza zomorodianS

The purpose of this study is to investigate the effect of loss-aversion behavior on multi-period investment decisions. For this purpose, two models of portfolio optimization have been designed. Instead of a single-period portfolio model, a three-period model has been us More

The purpose of this study is to investigate the effect of loss-aversion behavior on multi-period investment decisions. For this purpose, two models of portfolio optimization have been designed. Instead of a single-period portfolio model, a three-period model has been used. In order to bring the optimization models closer to the real world, in addition to the CVaR as one of the main constraints, the transaction cost and the lower bound and upper bound investment in each asset are also considered. two models of loss aversion and mean-CVaR optimization were solved using PSO algorithm. Also, some important criteria such as initial loss aversion coefficient and reference point are used to test the robustness of model. The results based on the optimal wealth and Sharp ratio showed that loss-averse investors tend to concentrate most of their wealth and have a better performance than rational investors. The impact of CVaR on investment performance was identified. When the market is falling, investors with higher risk aversion avoid extreme losses and obtain more gains. Manuscript profile

Open Access Article

33 - Structural Equations Approach in Analyzing the Relationship Between Corporate Governance and Value at Risk with Emphasizing on the Role of Risk Management and Intellectual Capital
mohammad zamani Yadollah Noorifard Ghodratollah Emamverdi mohsen hamidian Seyede Mahboobeh Jafari

Value at risk, which is a way of measuring the risk of reducing the price of portfolios or financial portfolios, is one of the most important market risk measures, which is widely used to manage financial risk by the Financial Regulatory Authority and portfolio managers More

Value at risk, which is a way of measuring the risk of reducing the price of portfolios or financial portfolios, is one of the most important market risk measures, which is widely used to manage financial risk by the Financial Regulatory Authority and portfolio managers.the effect of monitoring criteria on value at risk is considered as the risk criterion considering the role of intellectual capital and risk management with regard to the importance of value at risk as the main purpose of the research.for this purpose, financial information of 138 companies active between 1390 and 1397 was used as statistical society.to test the hypotheses of the research, using structural equation modeling and statistical analysis tests, the t - statistic was used. the results of the research show the effect of Corporate Governance system on value at risk, as well as the moderating role of risk management on value at risk. in this study, it has been shown that intellectual capital is not related to the impact of the criteria of Corporate Governance and value at risk of the information content. Manuscript profile

Open Access Article

34 - Portfolio VaR Modelling using EVT-Pair-Copulas Approach
Ali Souri Saeed Falahpor Ali Foroush Bastani Ehsan Ahmadi

The 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 More

The 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

35 - Investment Portfolio Optimization of Insurance Companies with Copulas and Extreme Value Approach
arash goodarzi reza Tehrani Ali souri

This 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 More

This 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

36 - Application of Copula and Simulated Returns in the Portfolio Optimization with Conditional Value-at-Risk (CVaR) in Tehran Stock Exchange (TSE)
Esmaeil Lalegani Mostafa Zehtabian

Several 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 More

Several 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

37 - Investigating the relationship between personality phases of mutual fund managers and fund risk measures: considering the moderating effect of personality types
Hosein Didehkhani Amir reza Mehralizadeh

Present research was accomplished to survey the relationship between Severity of personality phases of mutual fund managers and the risk measure of mutual funds. The research hypothesizes are that the intensity of individual phases of managers and their portfolio risk a More

Present research was accomplished to survey the relationship between Severity of personality phases of mutual fund managers and the risk measure of mutual funds. The research hypothesizes are that the intensity of individual phases of managers and their portfolio risk are related. And also the personality types (A & B) can have a moderating effect on the relationship. The sample size in this study consisted of 98 Person of investment fund managers. The methodology of this study was to evaluate the correlation between structural modeling with using the smart PLS software. The results indicated that there are significant relations between 5 personality Phases (Depression, Hypomania, Psychopathic Deviate, Psychasthenia, Paranoia) and fund risk measures including Value at Risk & Semi Variance. Also it was shown that personality type of investment fund managers is moderating effect on these relations.     Manuscript profile

Open Access Article

38 - An Investigation of methods to reduce transaction costs in Tehran Stock Exchange
Romina Atrchi Shahin Ramtinnia

Among 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 More

Among 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

39 - Algorithmic Trading System for future contract of gold coin based on intra-day data
Mohammad Ali Rastegar Amin Sedaghatipour

Today, with the prevalence of online trading and algorithmic trading, it is required that the trading data of financial markets be analyzed faster and become profitable decision. The purpose of this paper is to develop an automated and algorithmic trading system on gold More

Today, with the prevalence of online trading and algorithmic trading, it is required that the trading data of financial markets be analyzed faster and become profitable decision. The purpose of this paper is to develop an automated and algorithmic trading system on gold coin future contracts in Iran Mercantile Exchange. According to the suitableness of technical analysis for two-sided markets (long and short position), 8 technical tool signals has been used for trading system. In order to develop the trading system, MOPSO algorithm is used with the aim of optimizing the efficiency function and Conditional Value at Risk (CVaR). Besides for completing the risk management system, optimized take profit and stop loss has been specified for future contract. The results show that the designed trading system has a more favorable ratio of return to risk than other competitor strategies such as buy & hold and sell & hold. Also the time frame of 30 minutes seems appropriate for designing a trading system based on gold futures contract.   Manuscript profile

Open Access Article

40 - Dependence structure between Iranian financial system’s sub sectors: a vine copula approach
Soheil Khalili Reza Tehrani

In this paper, we apply R-Vine copula -ARMA-APGARCH approach to investigate the dynamic relationship between banking, insurance and pension, investment and other financials sub-indexes in Tehran stock exchange. Using a sample of more than 8 years of daily return ob More

In this paper, we apply R-Vine copula -ARMA-APGARCH approach to investigate the dynamic relationship between banking, insurance and pension, investment and other financials sub-indexes in Tehran stock exchange. Using a sample of more than 8 years of daily return observations of the financial sub-indexes, we find evidence of significant and symmetric relationship between these variables. Finally, there is evidence to suggest that the application of the vine copula model improves the accuracy of VaR estimates, compared to traditional approaches. This paper results show that vine copula VaR is accurate at 1% and 5% significance levels. This paper’s findings suggest the flexibility and capacity of vine copula structures in financial dependency modeling and risk management     Manuscript profile

Open Access Article

41 - Financial risk assessment based on Extreme Value Theory and instantaneous data of Tehran Stock Exchange Index
Mehrdokht Mozaffari Hashem Nikoomaram

Value at Risk is one of the most important criteria in financial markets for risk assessment. Various methods have been proposed for measuring this index. Extreme Value Theory is one of the new methods for calculating the value at risk that focuses on Distribution seque More

Value at Risk is one of the most important criteria in financial markets for risk assessment. Various methods have been proposed for measuring this index. Extreme Value Theory is one of the new methods for calculating the value at risk that focuses on Distribution sequence of series, and instead of taking all data into account without considering the limiting assumptions such as the assumption of normalization. In this research, the logarithmic return of Tehran Stock Exchange index based on the data received during the time intervals of the day (due to the use of high frequency data) during the years 1392 to 1395 was summed up and the Block Maxima Approach was used in VaR measurement. Given the correlation between the variance and the time series of the data, the problem was first solved using the E-GARCH model. Then VaR index was calculated in three blocking conditions based on hourly, daily and monthly data. The results showed that the use of monthly data in calculating this index has a higher predictive accuracy. Manuscript profile

Open Access Article

42 - Examining and Comparing Security of Investment in the Stock, Gold, Exchange and Housing Market of Iran using Value at Risk (VaR) Criteria
Gholam Reza Zomorodian Mahdi Shabanzadeh. Valiollah . Faryadras

Investment in each country is subject to a set of variables that Security of Investment is one of the most them.Official statistics show that in the recent decades, on average, only about 12‌% of the country's real GDP has been allocated to investment in the manufacturi More

Investment in each country is subject to a set of variables that Security of Investment is one of the most them.Official statistics show that in the recent decades, on average, only about 12‌% of the country's real GDP has been allocated to investment in the manufacturing sector, including the production of goods and services and a considerable portion of it has been absorbed into unproductive speculative activities.Accordingly, this study with purpose to examining and comparing security of investing in different markets has evaluated the risk of investing in four market including stocks, gold, currency and Iran's housing using the Value at Risk (VaR) Criteria. Also in this study to providing a more accurate analysis of the security investment based on investors' attitudes TOPSIS method has been used.All information required for the study was collected on a monthly basis for during 2002 - 2013.The result of this study showed based on VaR Criterion, the security of investment in the stock market is much lower than other markets, so investors in this market face higher risk of investments relative to other markets.Also, the result of this study showed based on TOPSIS method (according to risk and return critrias) risk averse and risk neutral Investors have the Similar behavior, So that the two groups prefer The investment in the housing market and then investment in the gold market on the parallel markets including exchange and stock. However, unlike the aforementioned groups, risk-taking investors prefered investing in the stock market and then investing in the housing market on the investment in the gold and currency markets. Manuscript profile

Open Access Article

43 - Selection of optimal portfolio by using improved Non-Dominated Sorting Genetic Algorithm and Evolutionary Algorithm Strength Pareto By taking risk on the basis of conditional value at risk
Mojtaba Moradi Maryam Ghavidel

Portfolio selection problem is one of the most important economic issues. The right combination of stock or other asset portfolio is that an investor pays to buy it. Selection of an optimal portfolio is based on the principle that the investor decides to accept one or s More

Portfolio selection problem is one of the most important economic issues. The right combination of stock or other asset portfolio is that an investor pays to buy it. Selection of an optimal portfolio is based on the principle that the investor decides to accept one or several investments among different investment depending on the tolerance of risk and expected a reasonable amount of stock returns. In this study, improved Non-Dominated Sorting multi-objective genetic algorithms and Evolutionary Algorithm Strength Pareto are used to create an optimum portfolio. These algorithms are improved version of their previous versions and have a better solution than its previous versions. The value of the portfolio and its risk, as optimization purposes and conditional value at risk as the basis risk, have been used. Two applied conditions consider to Portfolio and shown that the Evolutionary Algorithm Strength Pareto‌ has better results than the Non-Dominated Sorting Genetic Algorithm II.       Manuscript profile

Open Access Article

44 - Rating parametric and nonparametric methods for estimating the expected shortfall and value at risk
Mohammadreza Rostami Alireza Saranj Zoha Savari

Financial market developments make it more important to measure market risks correctly. In this paper we investigatethe forecasting accuracy of different historical simulation models in relation to the risk measure expected shortfall and in comparison to established par More

Financial market developments make it more important to measure market risks correctly. In this paper we investigatethe forecasting accuracy of different historical simulation models in relation to the risk measure expected shortfall and in comparison to established parametric models.we used historical simulation, mirrored historical simulatin,volatility weighted historical simulation,filtered historical simulation and GARCH(1,1) models.The data that we used consists of Tehran stock exchange market index from 2010 to 2014.Christofferson backtest used for value at risk and mc neil & frey backtest used for expected shortfall. According to unconditional coverage backtesting ,mirrored historical simulation model was rejected and others were accepted and  according to independence backtesting all models were accepted thus the christoferson backtest will omit the mirrored historical simulation model and According to mc neil and frey backtest all models were accepted and finally the model confidence set procedure showed that semi parametric models are best models to forecast expected shortfall. Manuscript profile

Open Access Article

45 - Estimation of Value at Risk by using Extreme Value Theory
Rasoul Sajjad Shohreh Hedayati Sharareh Hedayati

Value at Risk (VaR) measures risk exposure at a given probability level and is very important for risk management. In this paper, mainly EVT models are compared to other well-known models such as GARCH, Historical Simulation and Filtered Historical Simulation. Then eval More

Value at Risk (VaR) measures risk exposure at a given probability level and is very important for risk management. In this paper, mainly EVT models are compared to other well-known models such as GARCH, Historical Simulation and Filtered Historical Simulation. Then evaluation their models with different back testing such as Kupiec test, Christoffersen test and Lopez Loss function. Our results indicate that using conditional methods and Extreme Value Theory to forecast Value at Risk, is better than other models. And we should examine different methods for forecast Value at Risk, then select the best method for any tails of distributions. Manuscript profile

Open Access Article

46 - The Revised Sharp Method Examination Based on Value at Risk for Evaluation of Tehran Stock Exchange Companies
S. Reza Mirghaffari

Initially in this research we introduce a new method for evaluating the performance of company in Tehran Stock Exchange that called Revised-Sharp ratio and then examine this index was compared with sharp ratio. In Revised- Sharp ration we used of Value at Risk (Var) con More

Initially in this research we introduce a new method for evaluating the performance of company in Tehran Stock Exchange that called Revised-Sharp ratio and then examine this index was compared with sharp ratio. In Revised- Sharp ration we used of Value at Risk (Var) concept. Due to the unique properties and its application in the international financial institutions, VaR was applied as a financial innovation in Revised Sharp index. In this study, evaluating the performance by Revised-Sharp and Sharp was done in Investment and Metal Producer Company for period of study (2007-2011). The results show that there is no difference between ranking of Revised-Sharp and Sharp index in Investment companies (Portfolio). Although in Metal companies there were some differences between ranking of Revised Sharp and Sharp apparently, but also this hypothesis was not approved by nonparametric statistical examination. Manuscript profile

Open Access Article

47 - Application of Extreme Value Theory in Value at Risk forecasting
Hosein Falahtalab Mohammadreza Azizi

Quantifying 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 More

Quantifying 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

48 - Estimating Conditional Value at Risk (CVaR) with consideration the robust of the measure based on robust Cipra method
Ehsan Mohammadian Amiri Ehsan Mohammadian Amiri Seyed Babak Ebrahimi

Since the atmosphere of financial markets is uncertain and ambiguous, Conditional Value at Risk measurement has been of great importance in recent years for financial companies and micro and macro investors. In this paper, we estimate the CVaR of the Tehran Stock Exchan More

Since the atmosphere of financial markets is uncertain and ambiguous, Conditional Value at Risk measurement has been of great importance in recent years for financial companies and micro and macro investors. In this paper, we estimate the CVaR of the Tehran Stock Exchange Index for distribution of the Trial Student at confidence levels of 95%  and 99%  based on the Cipra method, which is proposed as a new approach for the estimation of the CVaR. In order to evaluate the performance of this approach, the comparison between the said approach and the conventional methods of GARCH, EGARCH and TGARCH was performed using four backtesting of unconditional coverage  test, conditional coverage  test, joint test and Lopez loss function test. The results show that robust Cipra method has a better and more reliable performance than the other methods in estimating the CVaR.   Manuscript profile

Open Access Article

49 - The ranking of Exchange-Trade Funds (ETFs); Applying the parametric value at risk approach
Gholamreza Zomorodian Fraydoon Rahnamay Roodposhti Maryam Borzabadi Farahani

Studying and ranking the Exchange-Traded Funds have been vital issues, since these asset funds have been amongst the most popular financial means, which their significant emergence and growth may confirm undeniable success in the global market. On the other hand, the mo More

Studying and ranking the Exchange-Traded Funds have been vital issues, since these asset funds have been amongst the most popular financial means, which their significant emergence and growth may confirm undeniable success in the global market. On the other hand, the most part of studying and ranking these funds can be categorized based on the efficiency criteria. Accordingly, applying a new perspective, this paper would consider the funds ranking based on value at risk approach. In doing so, the funds have been considered who had been active in the period of the 2014-September to 2017- September. Findings of the research show the appropriate value at risk models based on GARCH approach. In addition, the ranking based on the loss function illustrates that Almas, Atlas and Asam Exchange-Traded Funds have had the lowest risk in this study.     Manuscript profile

Open Access Article

50 - Investigation of capabilities of econometrist models in determination of value at risk in investment companies for determination of optimized portfolio in capital market of Iran
Hashem Nikoomaram Gholamreza Zomorodian

In today’s complicated world, we are witness many elements that affect on the profit level of companies. Each of these changes can promote group of companies to the top while destroy other group . So investment decision for actual and legal companies are severely More

In today’s complicated world, we are witness many elements that affect on the profit level of companies. Each of these changes can promote group of companies to the top while destroy other group . So investment decision for actual and legal companies are severely depended on these changes. For decreasing the risk of these sudden changes a desirable portfolio should be determined to avoid least damages from changes. Dealers uses different models to determine the risk value of their portfolio in the capital market. Each of these models uses specific assumptions to determine value under the risk of portfolio. this paper  intend to survey risk value of 21 investment companies by using the econometrist models. Then to compare the prediction power of each models, and introduce the superior model.   Manuscript profile

Open Access Article

51 - Comparing Between Multivariate Volatility Models in Estimation of Exchange Rate and Stock Index Relationship
Hosein Abbasinejad Shapour Mohammadi Sajad Ebrahimi

Financial variables volatility as basic factor of financial assets pricing, has been observed by many studies. In addition to GARCH model as common model for volatility estimation, stochastic volatility (SV) model is another approach that rarely is applied in research. More

Financial variables volatility as basic factor of financial assets pricing, has been observed by many studies. In addition to GARCH model as common model for volatility estimation, stochastic volatility (SV) model is another approach that rarely is applied in research. In this paper base of daily data from 1381 until 1392 exchange rate and Tehran stock index volatilities are estimated by applying bivariate stochastic volatility (SV). In order to evaluating the result, a loss function is formed based on value at risk(VaR) and then volatility models result(including stochastic volatility(SV) and GARCH) compare to each other. According to Loss function comparing result, BEKK-GARCH with t student distribution has more accurate estimation of exchange rate and stock market index volatilities. In addition, the results of the best model show that increasing exchange rate growth leads to stock index growth, but stock market changes have not significant effect on exchange rate growth. Also rising in volatility of a market causes increasing in volatility in another one. Manuscript profile

Open Access Article

52 - Multivariate GARCH models". Journal of business and economic statistic Value at Risk and Spillover effect estimate using MGARCH
Mohammadreza Rostami Sahar Farahmand

In 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 More

In 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

53 - 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 Shams

This 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 More

This 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

54 - تاثیر شاخص متا مالمکوئیست روی بهینه سازی سبد دارایی
زهره طائب شکوفه بنی هاشمی

10.30495/ijim.2022.61818.1532

از آنجائیکه تغییر ارزش در معرض خطر شرطی (CVaR) در سطوح مختلف اطمینان برای بهینه سازی سبد بسیار موثر است، شاخص متا مالمکوئیست (MMI) دراین پژوهش استفاده شده است. برای این هدف، مدلهای میانگین- ارزش در معرض خطر شرطی با شاخص متا مالمکوئیست در حضور داده منفی معرفی گردیده است. More

از آنجائیکه تغییر ارزش در معرض خطر شرطی (CVaR) در سطوح مختلف اطمینان برای بهینه سازی سبد بسیار موثر است، شاخص متا مالمکوئیست (MMI) دراین پژوهش استفاده شده است. برای این هدف، مدلهای میانگین- ارزش در معرض خطر شرطی با شاخص متا مالمکوئیست در حضور داده منفی معرفی گردیده است. مشابه تئوری مارکوویتزدر چارچوب میانگین- واریانس، ارزش در معرض خطر شرطی به عنوان سنجه ریسک بکار رفته و مدلها بدون در نظر گرفتن چولگی و کشیدگی بازده مطرح شده است. در این مطالعه تعدادی داده منفی وجود دارد، بنابراین مدلهای برمبنای مدل اندازه جهت دار مبنایی (RDM) است که مقادیر مثبت و منفی را می پذیرد. در این مقاله، کارائیها در همه سطوح اطمینان در مدل های میانگین- ارزش در معرض خطر شرطی و شاخص متا مالمکوئیست روی سطوح اطمینان به عنوان دوره ها در حضور داده منفی محاسبه شده است. این روش به سرمایه گذاران کمک می کند که سبدهای سودآورشان را با شاخص متا مالمکوئیست بسازند. همچنین یک مطالعه عملی روی بازار بورس ایران انجام گرفته است. Manuscript profile

Open Access Article

55 - Estimation of portfolio efficient frontier by different measures of risk via ‎DEA
M. Sanei S. &lrm;Banihashemi&lrm; M. &lrm;Kaveh&lrm;

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Open Access Article

56 - Using MODEA and MODM with Different Risk Measures for Portfolio Optimization
Sarah Navidi Mohsen Rostamy-Malkhalifeh Shokoofeh Banihashemi

10.22034/amfa.2019.1864620.1200

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Open Access Article

57 - Portfolio Optimization Based on Semi Variance and Another Perspective of Value at Risk Using NSGA II, MOACO, and MOABC Algorithms
Reza Aghamohammadi Reza Tehrani Abbas Raad

10.22034/amfa.2020.1907264.1479

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Open Access Article

58 - Forecasting Daily Volatility and Value at Risk with High Frequency Data
Amir Mohammad Zadeh Sahar Masoud Zadegan

One of the key aspects in the financial markets and its development is fluctuation. Fluctuation plays a key role in option pricing, portfolio management and the market sentiment. In general, financial institutions are faced with four various kinds of risk, which are cre More

One of the key aspects in the financial markets and its development is fluctuation. Fluctuation plays a key role in option pricing, portfolio management and the market sentiment. In general, financial institutions are faced with four various kinds of risk, which are credit risk, liquidity risk, operational risk, and market risk. The most appropriate method to measure the market risk is by using the VaR (value at risk). Value at Risk is statistical technique used to measure and quantify the level of financial risk within the investment portfolio over a specific time frame. It is always expressed by the monetary amount that is at risk as well as the probability of loss. This research is to predict the VaR for a one-day period in six different industries in which three companies are monitored in each industry. The time periods of the study are 30-minute intervals between 91/11/1 to 92/4/1,  in which the GARCH model is used for predicting the variance. The research then checks to see whether the data fits the normal or t-distributions models. Thus, six models are used for six different industries. All six chosen models are deemed proper to predict the coefficients, how fit the coefficients are, and Watson statistic camera. The estimation of the variance and the Var for all models is done at a %95 confidence interval. The research concludes that the companies involved in the basic metals group are more prone to risk and have higher VaR in comparison to other industries. Manuscript profile

Open Access Article

59 - The impact of diversification on risk reduction: using a mix of Merton model and random matrix approach to take into account non-stationary
Zahra Eskandari Mirfeiz Fallah Shams Gholamreza Zomorodian

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Open Access Article

60 - The Estimation of Systematic Risk in Iranian Financial Sectors (ΔCoVaR Approach)
samad hekmati farid Ali Rezazadeh ali malek

Abstract 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 More

Abstract 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

61 - 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 Shavvalpour

Forecasting 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 More

Forecasting 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

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62 - Fuzzy Portfolio Optimization Using Credibility Theory: Multi-Objective Evolutionary Optimization Algorithms
MariehAlsadat MirAboalhassani Farzad Movahedi Sobhani Emran Mohammadi

10.30495/fomj.2022.1949727.1054

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63 - 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 نژاد

در 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 More

در 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

64 - 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 zomorodian

10.30495/ecomag.2023.1979337.1057

The 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 More

The 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

65 - Analyzing and measuring the systemic risk between cryptocurrencies and real currencies using the value-at-risk and the marginal expected shortfall
Zohre Rahimi Gholamreza Zomorodian Azita Jahanshad Mehdi Madanchizaj

The purpose of this paper is to analyze and measure the systemic risk between the cryptocurrency and real currencies using the conditional risk exposure value approach and the expected marginal loss. In this study, statistical data of real and virtual currencies during More

The purpose of this paper is to analyze and measure the systemic risk between the cryptocurrency and real currencies using the conditional risk exposure value approach and the expected marginal loss. In this study, statistical data of real and virtual currencies during the years 2015-2021 have been used. For this purpose, systemic risk indices have been calculated using CoVaR and MES indices and then the correlation between systemic risk of currencies has been evaluated. In this study, the statistical data of the currencies of the exchange rate of the pound to the dollar, the exchange rate of the yuan to the dollar, the exchange rate of the lira to the dollar, the exchange rate of the euro to the dollar, bitcoin, atrium, ripple, litcoin and atrium based on daily price returns Currencies and real currencies were used. The results showed that there was a correlation between systemic risk indicators for the studied currencies and virtual currencies had a lower systemic risk index than real currencies. The purpose of this paper is to analyze and measure the systemic risk between the cryptocurrency and real currencies using the conditional risk exposure value approach and the expected marginal loss. In this study, statistical data of real and virtual currencies during the years 2015-2021 have been used. For this purpose, systemic risk indices have been calculated using CoVaR and MES indices and then the correlation between systemic risk of currencies has been evaluated. Manuscript profile

Open Access Article

66 - Examining the Efficiency Models, Genetic Algorithm under MSV Risk and Particle Swarm Optimization Algorithm under CVAR Risk Criterion in Selection Optimal Portfolio Shares Listed Firms on Stock Exchange
Dariush Adinevand Ebrahim Ali Razini Mahmoud Khodam Fereydoun Ohadi Elham Elsadat Hashemizadeh

10.30495/fed.2023.707996

Abstract Choosing the optimal stock portfolio is one of the main goals of capital management. Today, There are several tools and techniques for measuring portfolio risk and selecting the optimal stock portfolio. In this article, using data of 15 shares selected by purp More

Abstract Choosing the optimal stock portfolio is one of the main goals of capital management. Today, There are several tools and techniques for measuring portfolio risk and selecting the optimal stock portfolio. In this article, using data of 15 shares selected by purposeful sampling method from the top companies of Tehran Stock Exchange Organization including; PKOD, ZMYD, BPAS, FOLD, MKBT, GOLG, MSMI, PTAP, SSEP, AZAB, FKAS, NBEH, PFAN, GMRO and GSBE, the First return of these stocks are calculated daily in the period of 31/3/1394 -31/3/1399 for 5 years for 1183 days and then using MATLAB software models The Metaheuristic Optimization of the Genetic Algorithm under the MSV Risk Criterion and the Particle Swarm Algorithm under the CVaR risk Criterion are Compared. The results show that the genetic algorithm model under MSV risk criterion is more efficient and less risky, therefore the genetic algorithm model under MSV risk criterion is more efficient than the particle swarm algorithm model under CVaR risk criterion. Manuscript profile

Open Access Article

67 - Value at Risk Assessment in Tehran Stock Exchange using Non-parametric and parametric Approaches
ebrahim ghanbari memeshi seyed ali nabavi chashmi erfan memarian

The 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 More

The 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

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68 - 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 Baghani

10.30495/faar.2022.697084

AbstractTransparency 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 More

AbstractTransparency 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

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69 - Stock portfolio optimization using Imperialist Competitive Algorithm (ICA) and Particle Swarm Optimization (PSO) under Conditional Value at Risk (CVaR)
Arezou Karimi sara goodarzi dahrizi

The choice of stock portfolio is a special issue in the field of investment. Given the wide range of options in the stock market, one of the major concerns of investment groups is the optimal allocation of assets. Therefore, most of these collections use portfolio selec More

The choice of stock portfolio is a special issue in the field of investment. Given the wide range of options in the stock market, one of the major concerns of investment groups is the optimal allocation of assets. Therefore, most of these collections use portfolio selection models. The conditional value at Risk, which is one of the models of portfolio selection, follows the Quadratic Programming. Given that Quadratic Programming requires extensive computations, the use of metaheuristic algorithms in solving these problems increases the speed and accuracy of computations. The aim of this study is to minimize the Conditional Value at Risk by using two algorithms of Imperialist Competitive Algorithm and Particle Swarm Optimization. Therefore, using 800 days of data from 12 companies listed on the Tehran Stock Exchange in the period of 2/5/92 to 1/28/98, portfolio has been formed, and the weight of each stock in the optimal portfolio and the risk and return of the portfolio has been calculated using MATLAB2018 software. Then, using SPSS software, the average difference between risk and return of the two algorithms was tested.The results showed that the risk and return of the two algorithms were not statistically significant,. Manuscript profile

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70 - Multivariate Portfolio Optimization under Illiquid Market Prospects
Nastaran Sarvipour fatemeh samadi

The 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 More

The 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

71 - Dependence structure and portfolio risk in Iran exchange market by using GARCH-EVT-Copula method
Farhad Ghaffari sahar fathi

Abstract In this research, the GARCH-EVT-COPULA method is investigated to determine the dependency structure and portfolio risk estimation on the foreign exchange market data in Iran. GARCH-EVT models are used to mariginal distribution of each of four currency returns s More

Abstract In this research, the GARCH-EVT-COPULA method is investigated to determine the dependency structure and portfolio risk estimation on the foreign exchange market data in Iran. GARCH-EVT models are used to mariginal distribution of each of four currency returns series. For the joint model, we choose five copuls with different dependence structure such as Frank, Clayton, Gumble, Normal and t-Student copulas. In this research portfolio risk is measured using VaR and CVaR.The statistical sample of this study is the daily exchange rate of USD,EURO, Pound and AED for the free market with 5 working days from September to the end of 1396.Based on the results of the research, using the Akaike information criterion values, the t-student function is the best fitted copula model for investigating the dependency structure.Exchange rates have the same upper and lower tail dependencies. Accordingly, in the markets for boom (severe positive) and stagnation (severe negative), the dependence between the two exchange rates is the same. Manuscript profile

Open Access Article

72 - 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 memarian

The 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 More

The 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

73 - Stock Portfolio Optimization with MAD and CVaR Criteria by Comparing Classical and Metaheuristic Methods
Mohammad reza Haddadi Younes Nademi Fateme Tafi

Choosing the optimal stock portfolio is one of the main goals of capital management. There are several criteria for choosing the optimal portfolio. In this paper, using data of 10 stocks which randomly selected from the Tehran Stock Exchange including Vanovin, Vakharazm More

Choosing the optimal stock portfolio is one of the main goals of capital management. There are several criteria for choosing the optimal portfolio. In this paper, using data of 10 stocks which randomly selected from the Tehran Stock Exchange including Vanovin, Vakharazm, Seghrab, Shepna, Vapetro, Dana, Khasapa, Shekarbon, Shadous and Khahen, first the returns of these stocks are calculated and their portfolio risk is calculated using the models of absolute deviation risk and risk value, and these two criteria are compared by the classical solution method. The portfolio optimization output with each of these risks represents a different weight per share. In the optimization with the risk criterion of absolute deviation, the Dana has the highest weight and in the optimization with the value at risk criterion, the stocks of Segharb, Shepna and Shekarbon have the most weight. In the following, the deviation-absolute risk model and value at risk model of metaheuristic method are compared. The results show that the NSGA2 model of metaheuristic method compared to the classical method in solving portfolio optimization problem showed more risk in both MAD and CVaR criteria and therefore it is a better method to solve such portfolio optimization problems. Manuscript profile

Open Access Article

74 - Structural Equation Model Approach in Analyzing the Relationship Between Company Financial status and Value at Risk with Emphasis on The Role of Risk Management
Mohammad zamani Ghodratollah Emamverdi Yadollah Noorifard mohsen hamidian Seyedeh Mahboubeh Jafari

The purpose of this study is analyzing the relationship between firm financial status and value at risk by emphasizing the role of risk management. Therefore, from value at risk information with the bootstrap simulation between the period of 2012 and 2019 and informatio More

The purpose of this study is analyzing the relationship between firm financial status and value at risk by emphasizing the role of risk management. Therefore, from value at risk information with the bootstrap simulation between the period of 2012 and 2019 and information of 138 companies in Tehran stock exchange (TSE) for statistical sample companies and the company's financial status criteria (performance measures and firm risk) and management criteria, as a moderating variable firms were used. In this study, the method of structure analysis which tests a specific model of relation between variables is used because this model is a comprehensive approach to test assumptions about the relationships of the observed and latent variables. The results of the hypotheses and model fitting showed that the firm's financial status on the value at risk is significantly effective and the risk management of this connection can be properly adjusted, however, performance measures were higher power in explaining the company's status as well as the value at risk. Manuscript profile

Open Access Article

75 - 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 Fallah

The 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 More

The 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

76 - 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 mohammadPourzarandi

Banks 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 More

Banks 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

77 - Stock portfolio optimization using multi-objective genetic algorithm (NSGA II) and maximum Sharp ratio
Arezou Karimi

One of the most important issues in finance is how to choose an investment portfolio. Activists in this field are seeking to select a portfolio that controls risk with high return. Due to the increasing limitations of the capital market, the efficiency of classical meth More

One of the most important issues in finance is how to choose an investment portfolio. Activists in this field are seeking to select a portfolio that controls risk with high return. Due to the increasing limitations of the capital market, the efficiency of classical methods has been discussed. Hence, researchers have turned their attention to metaheuristic algorithms. The aim of this study is to determine the optimal portfolio of pharmaceutical companies accepted in the Tehran Stock Exchange by two methods of multi-objective genetic algorithm (NSGA-II) and maximum Sharp ratio. In this study, the multi-objective genetic algorithm (NSGA-II) is under Conditional Value at Risk criterion. Also, the data of 13 companies in the period of 90-97 were used to form the portfolio. The results show that in the multi-objective genetic algorithm (NSGA-II) method, the stock with the lowest Value at Risk gains the most weight in the optimal portfolio. Also, the optimized portfolio by multi-objective genetic algorithm is more return and at the same time less risky. Manuscript profile

Open Access Article

78 - 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 baghani

Risk 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 More

Risk 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

79 - The pervasive risk of the financial crisis in the Iranian banking system with the ARFIMA-FIGARCH-Delta CoVaR approach and the expected marginal Shortfall
leila barati mirfeiz falahshams farhad ghafari Alireza Heidarzadehhanzaee

Systemic risk refers to the risk of failure of the financial system or failure of the entire market. This risk can arise from instability or crisis in financial institutions and can be transmitted to the entire financial system as a result of transmission. The purpose o More

Systemic risk refers to the risk of failure of the financial system or failure of the entire market. This risk can arise from instability or crisis in financial institutions and can be transmitted to the entire financial system as a result of transmission. The purpose of this paper was to assess the pervasive risk of a financial crisis in the Iranian banking system. In this study, statistical information of banks during the years 1392-1397 has been used. In the first part, the comprehensive risk indicators of the financial crisis are calculated using the Delta CoVaR index, then the risk susceptibility is assessed using the ARFIMA-FIGARCH method. In the first step, the unit root test indicates the existence of a deficit root in the bank stock price index. Comprehensive risk indicators are then calculated and systemic risk transmission modeling is discussed. The results of the model indicated that the systemic risk situation in the country's banking system was abnormal, which was due to the leverage situation of the country's banks. Using the results of this study, it can also be stated that different financial sectors are required to consider sufficient capital for systemic Manuscript profile

Open Access Article

80 - 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 Yaghobnezhad

The 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 More

The 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

81 - Examining the Efficiency Models, Conditional Value at Risk and Mean Absolute Deviation and Particle Swarm Optimization Algorithm under CVAR and MAD risk criterion in Selection Optimal Portfolio Shares Listed Firms on Stock Exchange
dariuosh adinehvand Ebrahim ali Razini Rahmani Mahmod khoddam Fereydon Ohadi alhamsadat hashemizadeh

Choosing the optimal stock portfolio is one of the main goals of capital management. There are several techniques and tools to solve problem the optimal portfolio. In this research, using data of 15 stocks which randomly selected from the Tehran Stock Exchange including More

Choosing the optimal stock portfolio is one of the main goals of capital management. There are several techniques and tools to solve problem the optimal portfolio. In this research, using data of 15 stocks which randomly selected from the Tehran Stock Exchange including; PKOD, ZMYD, BPAS, FOLD, MKBT, GOLG, MSMI, PTAP, SSEP, AZAB, FKAS, NBEH, PFAN, GMRO and GSBE, the First return of these stocks are calculated daily in the period of 31/3/1394 -31/3/1399 for 5 years for 1183 days. Then and their portfolio risk is calculated using the models of absolute deviation risk and conditional value at risk, and these two criteria are compared by the classical solution method. The portfolio optimization output with each of these risks represents a different weight per share. In the following, the deviation - absolute risk model and conditional value at risk model of metaheuristic method using MATLAB (R2019) software are compared. The results show that the PSO model of metaheuristic method compared to the classical method in solving portfolio optimization problem showed more return in PSO-MAD criteria and therefore it is a better method to solve such portfolio optimization problems. Manuscript profile

Open Access Article

82 - Multi-Asset Portfolio Optimization based on Conditional Value at Risk using Artificial Bee Colony Algorithm
Somayeh Mousavi Abbasali Jafari-Nodoushan Marzieh Kazemi-Rashnani Mahsa Mohammadtaheri

Multi-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 More

Multi-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

83 - Long Memory usage in Portfolio Optimization using the Copula‌ Functions: Empirical evidence of Iran and Turkey Stock Markets
Hasti Chitsazan Motahareh Moghadasi Reza Tehrani Mohsen Mehrara

The main objective of this paper is to optimize and manage the portfolio by using copula functions. Copula function has been using as a powerful and flexible tool for the determination of dependency structure. Research data include the Iran stock market index and the Tu More

The main objective of this paper is to optimize and manage the portfolio by using copula functions. Copula function has been using as a powerful and flexible tool for the determination of dependency structure. Research data include the Iran stock market index and the Turkey stock market index. The present study seeks to find the effect of long memory on the structure of dependence between returns and optimal portfolio structure. In the first step, we compare the dependence structure between the net returns and the filter generated from the ARFIMA-GARCH process returns to investigate the impact of long memory on them. In the second step, the influence of the dependence structure between net returns and filtered returns on portfolio optimization has been investigated. The results indicated that the model can be fitted to the return of time series and the best pattern is the frank pattern. The results also indicated the existence of long memory in the mean and variance of stock return on the Iran stock market and the existence of long memory in the variance of the Turkey stock market. All models allocate more percentage of capital to Iran stock market and lower percent to Turkey stock market. Manuscript profile

Open Access Article

84 - 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 safa

AbstractThe 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 More

AbstractThe 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

85 - Portfolio optimization based on parametric and nonparametric period value at risk
Mohamad ali tabibi sayyed mohammad reza davoodi abdolmajid abdolbaghy ataabady

Value 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 More

Value 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

86 - Introducing new risk measure Glue VaR and its estimation using composite quantile regression model
Ali Aghamohammadi Mahdi Sojoudi Meysam Sojoudi mohammad Javad Tavoosi

Value-at-Risk and Average Value-at-Risk are two important risk measures that used to measure the market's risk with quantity structure. However, both of these risk measures have defects in measuring risk. For this reason, the new risk measure GlueVaR has been introduced More

Value-at-Risk and Average Value-at-Risk are two important risk measures that used to measure the market's risk with quantity structure. However, both of these risk measures have defects in measuring risk. For this reason, the new risk measure GlueVaR has been introduced in 2014. In this paper the new measure is describe and the advantaes of this mesure are explained. A method for estimating the new mesure is provided using the composite quantile regression model. Finally, the efficiency of GlueVaR will be compared with two other mentioned risk measures for log-return data from the American’s stock market and Iran’s stock market. Manuscript profile

Open Access Article

87 - 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 Abdollahi

In 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 More

In 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

88 - Measuring portfolio Value at Risk: The application of copula approach
Esmaeil Pishbahar sahar abedi

Due to the fact that traditional univariate approach in portfolio value at risk measurements ignore the time varying correlation between its components, these models underestimate or overestimate value at risk. In addition, complex financial markets make it necessary to More

Due to the fact that traditional univariate approach in portfolio value at risk measurements ignore the time varying correlation between its components, these models underestimate or overestimate value at risk. In addition, complex financial markets make it necessary to use effective approaches, such as multivariate risk measurement. Therefore, in this present study, we tried to evaluate four multivariate value at risk measurement approaches for two portfolios in food industry exchange. The result of Christoffersen, quadratic probability score and root mean squared error tests showed copula-based Monte Carlo approach has more reliable result in comparison with others. Hence, we applied this approach to investigate dependence structure and measure risk, and its result showed the maximum expected loss of dairy portfolio value over a week is 2.01 percent, while for sugar portfolio is 1.09 percent.   Manuscript profile

Open Access Article

89 - Investment portfolio optimization using value at risk under credibility theory with Z-numbers approach
Amirsina Jirofti Amirabbas Najafi

Z-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 More

Z-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

90 - Forecasting Volatility & Risk Management in Tehran Stock Exchange through Long memory impacts
ehsan Taiebysani Madihe Changi Ashtiani

In  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 More

In  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

91 - 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 nourahmadi

In 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 More

In 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

92 - Developing a Fuzzy Multibjective Model for Multiperiod Portfolio Optimazation Considering Average Value at Risk
Amir Shiri Ghehi Hosein Didehkhani kaveh Khalili Damghani parviz Saeedi

The purpose of the present research is to provide a multi-period portfolio optimization model in a fuzzy credibility environment, aimed for end-of-period wealth maximization and risk minimization. The investor’s risk was measured using the Average Value at Risk (A More

The purpose of the present research is to provide a multi-period portfolio optimization model in a fuzzy credibility environment, aimed for end-of-period wealth maximization and risk minimization. The investor’s risk was measured using the Average Value at Risk (AVaR) as a coherent risk measure. The model is designed in such a way that, in addition to considering transaction costs, the investor will have the opportunity to allocate part of his wealth to a risk-free asset. In designing the model, in addition to the cardinality constraints, constraints such as the minimum “proportion entropy” (as the portfolio of diversification degree) and the expected returns of the portfolio in each period are considered. The results of the model running by MOPSO algorithm indicated that the model objectives in the optimum portfolios were better suited than those when the model was run with random weights. The results also indicated that an increase in the portfolio diversification degree reduced the amount of the final wealth. Manuscript profile

Open Access Article

93 - Optimizing Portfolio through Extreme Value Theory in Tehran Stock Exchange
Afsaneh Sina Mirfeiz Fallahshams

Creating 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 More

Creating 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

94 - Investigating the Value at Risk of Gold Coin Future Market through Wavelet Analysis Approach
Mohammad Hamed Khan Mohammadi mehrnoosh ebrahimi

The most common criterion used to measure market risk is the value at risk method. The value at risk is the maximum loss which may occur over a specified time period and considering a specified degree of confidence in a portfolio of assets. In the current research, data More

The most common criterion used to measure market risk is the value at risk method. The value at risk is the maximum loss which may occur over a specified time period and considering a specified degree of confidence in a portfolio of assets. In the current research, data related to coin future market price indicator have been considered. The daily data used were gathered over a time period from 2008 to 2017. According to the results obtained from this study, coin future price data did not have a normal distribution; accordingly, the value at risk in this market was estimated using TGARCH method.  Time series was analyzed using wavelet analysis over 7 time periods of 2-128 days. In short time periods the normal distribution outperformed other distributions, but in longer time periods, the skewed-t distribution outperformed other distributions. In the sales situation, this threshold behavior is observed over a longer time period. The hope of increased future price by investors can somewhat justify these behavior changes over time. Manuscript profile

Open Access Article

95 - Proposition of a model For Forecasting Value at Risk in One Step Ahead
ehsan Mohammadian Amiri S. Babak Ebrahimi maryam Nezhad Afrasiabi

Risk 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 More

Risk 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

96 - Futures Contracts Margin Setting by CVaR Approach Based on Extreme Value Theory
mirFeyz Fallahshams ali Saghafi alireza naserpoor

this study, using gold coins spot price returns, in the period from 2008 to 2016, estimates IME gold coin futures contracts Initial margin, by Value at Risk and ConditionalValue at Risk (CVAR) approaches. It use variance- covariance modeles, based on normal and T-studen More

this study, using gold coins spot price returns, in the period from 2008 to 2016, estimates IME gold coin futures contracts Initial margin, by Value at Risk and ConditionalValue at Risk (CVAR) approaches. It use variance- covariance modeles, based on normal and T-student distributions,  general pareto distribution and adaptive GPD models fore estimating initial margin requerment for futures contracts open positions. Fore VaR moles backtesting, it applies Christoffersen conditonal coverage liklihood ratio(LRcc) test and lopez and Blanco-Ihle loss functions. MAE and RMSE loss functions have been used for Conditional Value at Risk (CVAR) models Evalution. The paper finds that all models have been underperforming in low confidence level and Variance - covariance models based on T-student Distribution and adaptive GPD has outperformed the other models that support the fat tailed nature of gold coin spot price data historical distribution. Manuscript profile

Open Access Article

97 - Selection of the optimal method in calculating the value at risk of investment fund
Ali Najafi moghadam

During the past several years experience extraordinary explosion of collective investment organisms or of investment companies (who buys the shares of other companies), led to the agencies responsible for controlling and monitoring these investments are a The series is More

During the past several years experience extraordinary explosion of collective investment organisms or of investment companies (who buys the shares of other companies), led to the agencies responsible for controlling and monitoring these investments are a The series is based on Value at Risk management guidelines apply. But the flexibility that many questions regarding the accurate and appropriate estimation model provokes. The purpose of this article Choose from three parametric method, historical simulation and Monte Carlo Simulation is the best way to predict the possible losses if the investment fund files open Tunisians find. For this purpose, different methods of estimating VaR propose. The descriptive statistical characteristics of 14 cases we analyzed combined investment fund. Then we present the results of experimental studies, so we can take advantage of Monte Carlo simulation method to predict the potential value of the company's chief of investor Tunisian specify. Manuscript profile

Open Access Article

98 - The evaluation of Systemic Risk in the Iran Banking System by Delta Conditional Value at Risk ( CoVaR) Criterion
asadollah farzinvash naser elahi javad gilanipour Ghadir Mahdavi

The Banking Crisis is previous decades caused the discussion of Systemic Risk in the financial market, including the Banks, has been taken into Consideration by Policy- makers. Based on this in this research using Delta Conditional Value at Risk (CoVaR), the Systemic ri More

The Banking Crisis is previous decades caused the discussion of Systemic Risk in the financial market, including the Banks, has been taken into Consideration by Policy- makers. Based on this in this research using Delta Conditional Value at Risk (CoVaR), the Systemic risk in Iran Banking Section has been evaluated. For this reason, seventeen banks out of all ones which have been listed in Tehran Stock Exchange and the equity of their Owners from 1389 to 1395 was available, have been chosen. The results Show that CoVaR for Khavarmianeh Bank Was the most (15.61) and for Sarmayeh Bank was the least (0.32). These results indicate that the crisis or disturbance in Khavarmianeh Bank more than the other Banks, affects the Financial System and Sarmayeh Bank has the least effect. In other words, any crisis in khavarmianeh Bank will give a rise of about 15.61 Percent to the Financial System risk, while the corresponded value for the Sarmayeh Bank is only 0.32 percent. Manuscript profile

Open Access Article

99 - 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

100 - Measurement conditional value at risk based on FIGARCH-EVT method at Tehran stock Exchange
mohammadreza Lotfalipour Mahdiyeh Nosrati abolfazl Ghadiri Moghaddam Mahdi Filsaraei

An 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 More

An 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

101 - Estimation of Value at Risk with Extreme Value Theory approach and using Stochastic Differential Equation
Amir Shafiee reza raei Hossein Abdoh Tabrizi saeed falahpor

The occurrence of financial crises in recent decades has caused a lot of damage to the economy as well as economic enterprises in many countries. The Extreme Value Approach is a new approach to the phenomenon of financial crisis, which has been able to analyze the event More

The occurrence of financial crises in recent decades has caused a lot of damage to the economy as well as economic enterprises in many countries. The Extreme Value Approach is a new approach to the phenomenon of financial crisis, which has been able to analyze the events that are less likely to occur but the damage caused by them is significant. In this study, we use the Extreme Value theory and Stochastic differential equations to find a new method for estimating the more precisely the value at risk. For this purpose, after estimating the parameters of the Stochastic differential equations, which includes the geometric Brownian motion, the geometric Brownian motion with the jump, the nonlinear GARCH model, and the Heston model, simulate the Monte Carlo simulations of future paths and then use peak over threshold approach, to estimate the value We at risk. The results of the simultaneous use of Stochastic differential equations and Extreme value theory are compared with historical simulations and variance-covariance approaches for value at risk. The results of Back-test techniques on value at risk indicate the superiority of the Heston model in estimation of value at risk. Manuscript profile

Open Access Article

102 - Estimation Value at Risk using by combining approach Exteme Value Theory and CIPRA at Tehran stock Exchange
Ehsan Atefi Meysam Rashidi Ranjbar

The 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 More

The 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

103 - Determine the optimal portfolio weights var-stock approach And compare it with the Markowitz model
sayyedmohammadmahdi ahmadi hasan lotfi vali rajabi

Every 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 More

Every 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

104 - 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 Yaghoobnezhad

10.30495/afi.2022.1956046.1119

Purpose: 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 More

Purpose: 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

105 - Examining the efficiency of optimization models of multi objective genetic algorithm and particle swarm algorithm under the risk criteria of conditional value at risk and mean smai variance in determining the optimal stock portfolio
Dariush Adinehvand Ebrahim Ali Razini Rahmani Mahmoud Khoddam Fereydoun Ohadi Elham Sadat Hashemizadeh

10.30495/afi.2023.1988982.1233

Objective: The goal is to select an optimal portfolio of stocks by allocating capital among various investment opportunities in the stock market to achieve maximum return at a specified level of risk. This constitutes an efficient portfolio.Research Methodology: Attaini More

Objective: The goal is to select an optimal portfolio of stocks by allocating capital among various investment opportunities in the stock market to achieve maximum return at a specified level of risk. This constitutes an efficient portfolio.Research Methodology: Attaining an efficient portfolio involves solving an optimization problem. There are numerous techniques and tools available to solve this issue. In this study, 15 stocks from companies listed on the Tehran Stock Exchange, including symbols such as Khapars, Khazamiya, Vepasar, Foulad, Akhabar, Kegel, Femli, Tapiko, Sepaha, Fazer, Fakhas, Shohbaran, Shefan, Qamro and Qathabat, were selected using cluster sampling. First, the daily returns of these stocks were calculated over a 5-year period from 2015 to 2020 (1183 days). The risk of the optimal investment portfolio was then calculated using the Mean-Semi Variance and Conditional Value at Risk models. These two criteria were compared using a classic solution method. Subsequently, the output data obtained from these calculations were compared using MATLAB software, employing the Particle Swarm Optimization algorithm under the Mean-Semi Variance risk criterion and the Genetic Algorithm under the Conditional Value at Risk criterion.Findings: The results of this study indicate that the meta-heuristic Particle Swarm Optimization method yields a higher portfolio return ratio compared to the Genetic Algorithm in the Mean-Semi Variance risk criterion.Originality / Value: This research utilizes multi-objective genetic algorithms and Particle Swarm Optimization, which are intelligent and novel algorithms, to minimize the objective function value using Conditional Value at Risk and Mean-Semi Variance criteria. These algorithms optimize the return and risk ratios of the stocks in the investment portfolio with the highest possible accuracy. Additionally, the efficiency comparison of these models using MATLAB software contributes an innovative aspect to this study. Manuscript profile

Open Access Article

106 - 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 Heidari

10.30495/afi.2023.1995691.1257

Purpose: 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 More

Purpose: 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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