جستجوی مقالات مرتبط با کلیدواژه « diversification » در نشریات گروه « اقتصاد »

Markowitz model of asset portfolio optimization has some deficits, one of the most important of which is the normality assumption of stock market returns. Normality of returns has been rejected in numerous studies and has been shown that mean is not a good maximization objective anymore. Mean of returns is quite sensitive to outliers. There are three different ways of facing this problem in the literature. The first approach is generally to abandon the modern portfolio theory and turn to using meta-heuristic algorithms in portfolio optimization. The second approach still considers the modern portfolio theory important and valuable and uses it with adjustments. Some studies under the ultra-modern portfolio theory have focused on the inappropriateness of variance and use other measures of risk. Some others studies focus on drastic changes in the optimal portfolio as a result of changes in input values and use robust statistics. The third approach, on the other hand, tries to avoid the mentioned problems simply by using different parameters in optimization instead of average and variance. This paper based on the third approach seeks to use the median instead of the mean in stock portfolio optimization. The purpose is to compare the performance of mean and median in optimization. Moreover, the variance is not enough to control the risk because of heavy tails of return distribution and, thus, this paper incorporates various risk measures into models to test which one performs better beside median as an alternative to mean-variance models. 

Five median maximization models are presented with different risk measures of mean absolute deviations (MAD), value at risk (VaR), average value at risk (CVaR), and maximum loss (ML). Models are solved using GAMS software package and daily real data of twenty stocks from Tehran Stock Exchange from the beginning of 2016 to the end of 2019. For this purpose, the models are first employed for portfolio optimization in a certain period of 50 days. After computation, then the optimal weights are used for the next period of 50 days. This procedure is then repeated for the next 100 days to the end of 2019. Finally, the average and the distribution of returns of the optimal portfolio obtained from different models are compared with three other models: the mean optimization method without any control for risk, the mean optimization method subject to value at risk (VaR) constraint, and the portfolio with equal weights (EqW).

Findings show that the median has a better performance in portfolio optimization. The model of median maximization gains higher returns in seventy percent of cases and a higher return on average. This means that a higher value of portfolio would be obtained using median in optimization. As a second conclusion, it was also shown that the median optimization method results in a portfolio with higher degree of diversification. The result remains true adding various risk measures to the model showing that median optimization instead of mean obtains a more diversified portfolio. In comparison among different median optimization models, it was also shown that CVaR and MAD risk measures controls the risk better than VaR and Maximum loss and obtains even further diversification.

The results generally show that portfolio optimization models based on the mean instead of the median and subject to risk measures of the average value at risk (VaR) and the mean absolute deviations (MAD) have a better performance in return maximization, control of risk and portfolio diversification.

One of the most important problems in modern finance is finding efficient ways to summarize and visualize stock market data. Modeling the filtering of complex networks in the stock market allows this to be achieved by reducing the market size, obtaining reliable information with less disturbance. Since stock price changes are not independent of each other, the study of the correlation between stock price changes provides a better understanding of market performance for investors. Stock market analysis based on complex networks allows studying the correlation of stock prices. In this paper, using the stock market data in the Tehran Stock Exchange, the Iranian stock market network is created by the threshold method, and then the network filtering is based on MST. The results show that the filtration modeling of Iran's stock market network based on the MST can form a subset of the stock market that follows the performance of the entire market with a significant reduction in size and has a similar degree of diversification with the entire market. These analyzes provide a more in-depth insight into the structure of the stock market while reducing the size.

In this study, using portfolio theory and the risk content of exports models and risk- weighted comparative advantage (RiskCA), the risk and diversification of Iran's non-oil export portfolio are analyzed. In fact, each of the export commodity sectors is considered as an asset and its variation in the export structure are calculated as the content risk of exports. In this regard, using export data during the period 1988-2019, the diversification index of Iran's non-oil exports has been measured based on the overall difference measures. Also, the risk- weighted comparative advantage is calculated and its relationship with the risk content of exports and export diversification index using nonparametric estimation and semi-parametric and analyzed by Matlab programming. According to the results of this research, the relationship between the degree of export diversification and the risk of the risk- weighted comparative advantage (RiskCA) is U-shaped. This means that if there is a comparative advantage in the safe export sectors of the country, it will choose fully specialized. Exports will specialize in high-risk sectors if the comparative advantage is strong enough. However, in intermediate values of comparative advantage, the export will diversify between risky and risk-free sectors and an optimal combination solution is selected.

The increasing dependence of European Union member countries on imported oil and gas has led to concerns about energy supply and security.  At the same time the share of clean energy in Europe’s energy consumption basket is increasing due to environmental issues. About a quarter of all energy consumption in the EU is natural gas, and most EU member states import almost all of their energy resources, especially oil and gas. The increase of European energy imports, including gas from Russia, increases their energy dependence.  We use literature review to study the question of what the most important energy security problems for European countries are and what strategies they can adopt to increase their energy security. The results of this study show that European energy security is compromised by high dependence on oil and gas imports from Russia and inability to source energy from countries like Iran and Venezuela due to sanctions. The most important strategies of countries are to strengthen international institutions such as oil exchanges, use of alternative sources of fossil fuels, diversification of oil and gas import portfolios, joint investment with a basket of oil producers and new pipelines to transport gas. Iran can be a good option for Europe to increase its energy security, given the country’s oil and gas resources and strategic position.

Recently, the role of industrial structure on regional employment has attracted much attention. One of the branches of these studies, focusing on Jacobs (1960), suggests that more diversity of industrial structure leads to employment and protects the areas against the adverse effects of external shocks. Jacobs's hypothesis has been validated experimentally in many studies. These studies provide a positive relationship between regional economic diversification and employment growth. Following the increasing trend of studies related to economic diversity on employment growth, regional employment models have also been focused on considering spatial dependency. In terms of industry structure, the more diverse areas can be benefited from their externalities, while more diversity within a region improves technical innovations and their impacts. According to Iran's provinces' employment rate, we found a significant regional dispersion between different regions. Although regional employment growth has received more attention from scholars and policymakers than ever before, few empirical studies have been conducted on the relationship between R&D specialization and diversification and regional employment growth. Therefore, this paper aimed to investigate the spatial effects of R&D specialization and diversification on employment growth in the Iranian provinces from 2005 to 2015.

For this study, R&D specialization and diversification in Iran's provinces were first measured, and then the spatial effects of each of these variables on the employment growth of Iranian provinces were estimated using an econometric model. According to Chen& et al. (2015), the Gini index has been used to measure the degree of R&D specialization. Following Ocaner et al. (2018), total diversity is measured by total entropy and related and unrelated diversification.

Given that this study's spatial unit of choice is based on administrative boundaries rather than economic regions, it might be expected that spillovers would exist from the neighboring region. So a full Spatial Durbin Model (SDM) specified, which takes the form of the following: (1)The SDM allows for the observed value of neighboring region employment growth () and other regional characteristics of neighboring regions' employment () to impact a regions’ employment growth rate. The coefficient  shows the impact of employment growth in neighboring regions on the employment growth rate of a particular region or, in other words, the spatially lagged dependent variable. (Ocaner et al., 2018)According to Table 1, the results of the estimation of equation1 showed that employees in the sector of services and relevant or irrelevant specialization and diversification had a significant positive effect on employment growth so that the effect of specialization was more than that of irrelevant diversification and the effect of irrelevant diversification was greater than that of the relevant diversification.

 Conclusions and Suggestions:

The findings of this study supported the Jacobs hypothesis for the Iranian provinces. Also, there was a reverse U-shaped relation between economic specialization and employment growth, indicating that as R&D specialization increased, provincial employment growth increased, but the specialization led to a decrease in employment growth at higher levels. Therefore, as R&D specialization increased, productivity increased, and it was replaced by employment growth. So, the Marshall hypothesis was supported by a range of specialization. For more precise analysis, direct, indirect, and total effects have been calculated. The indirect effect measures the effect of changes in the region j on the dependent variable in region i, which i≠j. The direct effect measures a particular explanatory variable in region i on the dependent variable in region i. The calculation of direct and indirect effects showed that increasing R&D specialization in one region could affect employment growth of the same region; however, it had no significant effect on the adjacent regions' employment growth. Increasing the irrelevant diversification in each region also led to employment growth in the same region, but increasing the relevant diversification in the adjacent regions resulted in a decrease in the host region's employment growth.Increasing the average income of the adjacent regions decreases the host region's growth rate and leads to the host region's employment growth. Thus, the limited influence of entropy related to the growth of provincial employment indicates evidence of transmission mechanisms between regions. Indirect results indicate a significant spatial spillover, and the evidence from estimating direct effect indicates that geography is essential in terms of neighborhood zones. Therefore, in developing programs and policies of increasing employment, it is necessary to pay attention to the potentials of the region and the influence of neighboring areas. It is suggested to deploy industries with more diversity in provinces with lower employment rates. So, creating industrial clusters as a unit for all of the provinces is not a suitable policy. Also, increasing the specialization index by increasing R&D expenditures in areas with a high unemployment rate can increase employment. From this perspective, granting specific and increasing tax credits to the firms in exchange for R&D can be helpful in increasing the employment rate of the province.

The relation between export growth and economic growth has been controversial among economist and policy makers during several last decades. In this study, we introduce a model to test export diversification and economic growth, in Iran after revolution (1980-2005). The findings show that non-oil export has increased and diversified during the three last decades. The export diversification index for some goods has lead to higher export growth. So export diversification especially in non-oil good's has contributed to economic growth.