List of Articles value-at-risk

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  1 - Forecasting value-at-risk and expected shortfall using high frequency data modeling
  S. Babak Ebrahimi Negin Mohebbi
  The present study compares the performance of the long memory FIGARCH model, with that of the short memory GARCH specification, in the forecasting of multi-period value-at-risk and expected shortfall across 3 industry indices in Tehran Stock Exchange such as chemical, v More

  The present study compares the performance of the long memory FIGARCH model, with that of the short memory GARCH specification, in the forecasting of multi-period value-at-risk and expected shortfall across 3 industry indices in Tehran Stock Exchange such as chemical, vehicle and metals. The dataset is composed of daily data covering the period from May, 2011 to May, 2015. According to the result of this research accounting for fractional integration in the conditional variance model does not appear to improve the accuracy of the VaR forecasts for the 1-day-ahead, 10-day-ahead and 20-day-ahead forecasting horizons relative to the short memory GARCH specification. Furthermore, the GARCH model has a lower quadratic loss between actual returns and ES forecasts, for the majority of the indices considered in 1-day, 10-day and 20-day forecasting horizons. Therefore, a long memory volatility model compared to a short memory GARCH model does not appear to improve the VaR and ES forecasting accuracy, even for longer forecasting horizons. Manuscript profile
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  2 - Modeling the Liquidity Risk Spillover Between Banks Accepted in the Tehran Stock Exchange Market
  abas banisharif mir feyz fallahshams zad fathi
  The analysis and examination of the spillover of risks among markets has been emphasized in practice for some decades by the theorists and scholars from different fields. The complex atmosphere of the financial markets and the close relationship between these markets an More

  The analysis and examination of the spillover of risks among markets has been emphasized in practice for some decades by the theorists and scholars from different fields. The complex atmosphere of the financial markets and the close relationship between these markets and also the necessity of predicting the future economic changes prompted the financial researchers to take an effective step to attain the goals of the financial and economic system by discovering and analyzing the relationships between those markets. Identifying the financial risks in banking industry and the way they are transferred among different banks is one of the main financial issues that has a significant role in realizing the risk management of the financial institutes and banks. The present research was conducted to examine the spillover of one of the financial risks (liquidity risk) among the banks listed on Tehran Stock Exchange. The liquidity adjusted Value-at-Risk (LaVaR) has been used to evaluate the liquidity risk and the required data has been gathered from 8 banks listed on Tehran Stock Exchange on daily basis from 2011 to Sep. 2020. The method of spillover of the risks to each other has been modeled based on GARCH-DCC model. All obtained coefficients had a significant difference with zero in the estimated model and at 95% confidence level, and the estimated variance equation indicate the existence of spillover of liquidity risk as mutual among the banks Manuscript profile
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  3 - A New Approach to Evaluate the Performance of Value-at-risk Estimators, Using Genetic Algorithms
  Seyed Ali Nabavi Chashmi Hamze Pourbabagol Ahmad Dadashpoor Omrani
  Value at Risk (VaR) is the maximum loss which could be incurred within a given time horizon, except for a small percentage, that its application has sharply increased after the 90s. Parallel to the increase in usage of value-at-risk in risk management are More

  Value at Risk (VaR) is the maximum loss which could be incurred within a given time horizon, except for a small percentage, that its application has sharply increased after the 90s. Parallel to the increase in usage of value-at-risk in risk management areas, validation of VaR measures has gain great importance. In prevalent back testing approaches, returns which are yielded from VaR estimators are not regarded as a criterion. It's may not be desirable for the investors who emphasize on return more than the risk. What distinguishes this study from other researches in the field of back testing VaR estimation models is the simultaneous consideration of actual return and loss(CVaR) which were yielded from VaR estimators  as criteria of risk and return that are the primary basis for financial studies. On the other hand, due to relativeness of risk and return in terms of investors, we considered the weight of these two indexes as fuzzy. In this paper, we constitute and optimize our risky portfolio with safety-first investor's rule. We need to estimate quantile of risky portfolio's return in objective function of safety-first investor's rule to optimize the portfolio. VaR estimators were used to calculate it. On the other hand, given the non- convexity of VaR function and also other reasons, we applied one of the most popular meta-heuristic models namely genetic algorithms for optimization. Our findings show that GEV and HS models are more conservative than parametric models (t-student and normal) and also have better performance in portfolio optimization. The empirical findings also indicate that safety-first investor will choose significantly different amounts of borrowing. Thus, the scale of the risky portfolio and the amount borrowed is diverse across methods. There is another interesting finding. Despite the computational simplicity of historical simulation method, it has shown the best performance of all.    Manuscript profile
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  4 - The Effect of Portfolio Diversification on Value at Risk in Tehran Stock Exchange (TSE)
  Ali Rostami Narges Niknia
  The concept of risk always attracted investors.Diversification is one of strategies that investors used it to against the risk. This research explores the risk associated with the stocks prices in the twenty-two companies that are listed in Tehran Stock Exchange (TSE) & More

  The concept of risk always attracted investors.Diversification is one of strategies that investors used it to against the risk. This research explores the risk associated with the stocks prices in the twenty-two companies that are listed in Tehran Stock Exchange (TSE)  as well as portflio of investment that are constructed from these twenty-two companies employed. In addition to national studies, the importance of international diversification by constructing a portfolio of investment from stock price indexes of emeging and developed countries would be examined.Correlation between stocks in national diversification porfolios shows the relationship between various domestic equities in investment portfolios, as well as correlation between indices, displays relationship between stock price indexes in international investment porfolio. Value at risk (VaR) is undertaken for studying the benefits associated with domestic as well as international diversification. The results show that domestic diversification reduces risk and more significient result is that international diversification significiently reduces the risk. Manuscript profile
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  5 - Portfolio optimization considering cardinality constraints and based on various risk factors using the differential evolution algorithm
  Behnaz Ghadimi Mehrzad Minooei Gholamreza Zomorodian Mirfeiz Fallahshams
  10.22034/amfa.2022.1950768.1688
  As the main achievement of the modern portfolio theory, portfolio diversifica-tion based on risk and return has attracted the attention of many researchers. The Markowitz mean-variance problem is a convex quadratic problem turned into a mixed-integer quadratic programmi More

  As the main achievement of the modern portfolio theory, portfolio diversifica-tion based on risk and return has attracted the attention of many researchers. The Markowitz mean-variance problem is a convex quadratic problem turned into a mixed-integer quadratic programming problem when incorporating car-dinality constraints. Due to the high number of stocks in a market, this problem becomes an NP-hard problem. In this paper, a metaheuristic approach is pro-posed to solve the portfolio optimization problem with cardinality constraints using the differential evolution algorithm, while it is also intended to improve the solutions generated by the algorithm developed. In addition, variance, val-ue-at-risk, and conditional value-at-risk are assessed as risk measures. Candi-date models are solved for 50 top stocks introduced by the Tehran Stock Ex-change by considering the cardinality constraints of not more than five stocks within the portfolio and 24 trading periods. Finally, the obtained results are compared with the results of genetic algorithm. The results show that the pro-posed method has reached the optimal solution in a shorter time. Manuscript profile
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  6 - Foster-Hart Optimal Portfolio
  sepehr asefi reza eivazlu reza tehrani
  This essay is going to optimize the portfolio of stocks similar to the Markowitz approach. Nonetheless, the way in which the risk is measured is Foster-Hart risk. This measure was proposed by Foster and Hart in 2009. It takes into account the extreme events of losses. T More

  This essay is going to optimize the portfolio of stocks similar to the Markowitz approach. Nonetheless, the way in which the risk is measured is Foster-Hart risk. This measure was proposed by Foster and Hart in 2009. It takes into account the extreme events of losses. The theoretical definition could be as a minimum wealth that an investor should have in order not to face with bankruptcy. Our sample consists of adjusted daily data from thirty-four companies chosen from Tehran Stock Exchange’s Top 50 Index in the period between 1391/07/01 and 1396/06/31. Data has been collected from Rahavard Novin software which is widely used in finance studies in Iran. Different optimal portfolios has been achieved in this essay. Each of which uses a different method of risk like Cvar and Semi-Variance besides Foster-Hart. Results of this essay show that Foster-Hart optimal portfolio could have higher sharp ratio in comparison with the others. Manuscript profile