This paper aims to investigate the portfolio optimization under various market risk conditions using copula dependence and extreme value approaches. According to the modern portfolio theory, diversifying investments in assets that are less correlated with one another al More
This paper aims to investigate the portfolio optimization under various market risk conditions using copula dependence and extreme value approaches. According to the modern portfolio theory, diversifying investments in assets that are less correlated with one another allows investors to assume less risk. In many models, asset returns are assumed to follow a normal distribution. Consequently, the linear correlation coefficient explains the dependence between financial assets, and the Markowitz mean-variance optimization model is used to calculate efficient asset portfolios. In this regard, monthly data-driven information on the top 30 companies from 2011 to 2021 was the subject to consideration. In addition, extreme value theory was utilized to model the asset return distribution. Using Gumbel’s copula model, the dependence structure of returns has been analyzed. Distribution tails were modeled utilizing extreme value theory. If the weights of the investment portfolio are allocated according to Gumbel’s copula model, a risk of 2.8% should be considered to obtain a return of 3.2%, according to the obtained results.
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The purpose of this article was to investigate the replacement of traditional money with virtual currencies and its effects on macroeconomic variables with the approach of Dynamic Stochastic General Equilibrium (DSGE) models. For this purpose, the data of the period 201 More
The purpose of this article was to investigate the replacement of traditional money with virtual currencies and its effects on macroeconomic variables with the approach of Dynamic Stochastic General Equilibrium (DSGE) models. For this purpose, the data of the period 2018-2019 with seasonal frequency have been used. In the model designed in this article, it is assumed that due to the use of virtual money, a substitution between virtual money and traditional money will happen in people's asset portfolio. In this study, the shock caused by the price and volume of Bitcoin transactions is considered as an indicator for the demand for virtual currency. The results show that the shock from virtual currencies has led to a decrease in the demand for traditional money, in other words, there has been a substitution between holding traditional money and virtual money. In addition, the results indicated that due to the shock of virtual currencies, the amount of consumption in the economy has increased, and on the other hand, the amount of government income from royalties and money printing has decreased. Also, the results showed that the government's tax revenues have also decreased due to the trend of financial resources in the economy towards the demand of virtual currencies.
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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.
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