One of the latest security threats in cyberspace to steal personal and financial information is created by phisher. Due to there Are various methods to detect phishing and also there is not an up-date comprehensive study on the issue, the authors Motivated to review and More
One of the latest security threats in cyberspace to steal personal and financial information is created by phisher. Due to there Are various methods to detect phishing and also there is not an up-date comprehensive study on the issue, the authors Motivated to review and analysis the proposed phishing detection methods in five categories such as: anti-phishing tools Based, data mining based, heuristic based, meta-heuristic based and machine learning based methods. The advantages and Disadvantages of each method are extracted from the current review and comparison. The outlines of this study can be suitable to identify the probability gaps in phishing detection problems for feature researches.
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In order to evaluate the performance and desirability of the activities of its units each organization needs an evaluation system to assess this desirability and it is more important for financial institutions, including information technology-based companies. Data enve More
In order to evaluate the performance and desirability of the activities of its units each organization needs an evaluation system to assess this desirability and it is more important for financial institutions, including information technology-based companies. Data envelopment analysis (DEA) is a non-parametric method to measure the effectiveness and efficiency of decision-making units (DMUs). On the other hand, data mining technique allows DMUs to explore and discover meaningful information, which had previously been hidden in large databases. . This paper presents a general framework for combining DEA and regression tree for evaluating the effectiveness and efficiency of the DMUs. Resulting hybrid model is a set of rules that can be used by policy makers to discover reasons behind efficient and inefficient DMUs. Using the proposed method for examining factors related to productivity, a sample of 18 branches of Iran insurance in Tehran was elected as a case study. After modeling based on advanced model the input oriented LVM model with weak disposability in data envelopment analysis was calculated using undesirable output, and by use of decision tree technique deals with extracting and discovering the rules for the cause of increased productivity and reduced productivity.
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Risk parity is one of the stock portfolio selection models that has received much attention after the American financial crisis in 2008. The philosophy of this model is to allocate the risk of the portfolio to the same extent among its constituent assets. Conditional va More
Risk parity is one of the stock portfolio selection models that has received much attention after the American financial crisis in 2008. The philosophy of this model is to allocate the risk of the portfolio to the same extent among its constituent assets. Conditional value at risk is one of the popular and common measures of risk measurement in finance, which measures the mathematical expectation of loss of a stock portfolio for values beyond a threshold value and at a known confidence level and time horizon. The aim of the current research is to design and optimize the performance of the risk parity stock portfolio model with the criterion of conditional risk value. There are different approaches in modeling optimal portfolio selection that use different criteria and methods to calculate and estimate returns and risks. Various criteria have been proposed to measure risk in finance, each of which has its own advantages and disadvantages. One of the criteria that has been introduced with the aim of reducing the disadvantages of the common and popular measure of value at risk is the conditional value at risk or expected drop, which is used as a measure of risk in the present study. Conditional value at risk measures the average loss of the portfolio for cases where the amount of loss exceeds value at risk
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