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
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Portfolio optimization is one of more important problems in financial area. The classic model consider that stocks is random variable with symmetric probability density function. But in real world, forecasting stock condition always faced with uncertainty and we need in More
Portfolio optimization is one of more important problems in financial area. The classic model consider that stocks is random variable with symmetric probability density function. But in real world, forecasting stock condition always faced with uncertainty and we need insert human factors in our forecasting. Fuzzy logic is one of methods that we can use this to model this condition. On other hand, experimental studies show that assets return isn’t normal and symmetric, so we should use down risk measure such as semi variance and semi absolute deviation. In this research we consider two point in portfolio selection problem. Then we use two intelligent method based genetic and deferential evolutionary algorithm for solving the models. Making use of Tehran Stock Exchange data, it is concluded that considering semi absolute deviation has higher efficiency than semi variance model and intelligent method based deferential evolutionary algorithm has higher efficiency from intelligent method based genetic algorithm.
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Realism has different and perhaps conflicting meanings in discussions of legal theory and philosophy of law. The general meaning of realism refers to an image of the world in which external reality plays a stronger and more effective role than ideal aspects. Accordingly More
Realism has different and perhaps conflicting meanings in discussions of legal theory and philosophy of law. The general meaning of realism refers to an image of the world in which external reality plays a stronger and more effective role than ideal aspects. Accordingly, the American realist movement seeks to exclude artificial and mysterious layers in the realm of law. Realism in this sense is somehow testing of legal theories considering the reality that takes place in the outside world. Legal reality, then, is anything that the courts actually do when decision-making. In this regard, descriptive-analytical method is used in problem processing and the purpose of this article is to examine the American school of legal realism and the issues raised by experts in this field. Finally, the findings show that realists, against their will, have succeeded in developing a strong and coherent theoretical perspective on law and judgment.
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Since Allameh Tabatabai designed firstly the theory of derivation purposing to protect the rational identity of a part of human knowledge confirming that human knowledge is not at all the result of his livelihood. Therefore this theory quickly showed its impact on the r More
Since Allameh Tabatabai designed firstly the theory of derivation purposing to protect the rational identity of a part of human knowledge confirming that human knowledge is not at all the result of his livelihood. Therefore this theory quickly showed its impact on the realm of moral philosophy. Recently, there are some attempts to establish philosophy of culture on the basis of this theory. This article addresses the theory of abstraction and its application in the political philosophy and global peace. Finally, it suggests that the theory provides an important basis to establish a kind of political philosophy and global peace by regarding ethics, religion, culture and language as derivative affairs. It will be able to reduce the strength and intensity of conflict on ethnic and cultural affairs and facilitate peace and stability and ethnic coexistence. All of these cannot be achieved except by a profound consideration of the epistemological nature of religion, culture and morality.
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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.
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