محمدرضا میری لواسانی

محمدرضا میری لواسانی

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فیلتر های جستجو: فیلتری انتخاب نشده است.
نمایش ۱ تا ۲ مورد از کل ۲ مورد.
۱.

Introduction of New Risk Metric using Kernel Density Estimation Via Linear Diffusion(مقاله علمی وزارت علوم)

کلید واژه ها: Risk measurement Generalized Co-Lower Partial Moment Portfolio optimization Nonparametric estimation Stock Market

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تعداد بازدید : 628 تعداد دانلود : 897
Any investor in stock markets around the world has a deep concern about the shortfalls of allocation wealth to any stock without accurate estimation of related risks. As we review the literature of risk management methods, one of the main pillars for the risk management framework in defining risk measurement approach using historical data is the estimation of the probability distribution function. In this paper, we propose a new measure by using kernel density estimation via diffusion as a nonparametric approach in probability distribution estimation to enhance the accuracy of estimation and consider some distribution characteristics, investor risk aversion and target return which will make it more accurate, compre-hensive and consistent with stock historical performance and investor concerns.
۲.

Forming Efficient Frontier in Stock Portfolios by Utility Function, Risk Aversion, and Target Return(مقاله علمی وزارت علوم)

کلید واژه ها: Risk Aversion Generalized Co-Lower Partial Moment Target Rate of Return Portfolio optimization Reference Dependent Utility Function

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تعداد بازدید : 837 تعداد دانلود : 671
Asset allocation has always been a challenging issue / for individuals and businesses to survive in our competitive world. One of the famous businesses, which has an enormous impact on people's lives worldwide, is the pension industry. Pension funds- as Defined Benefit, Defined Contribution, or others- accept reserves from contributors and try to invest them in a way to keep up with their obligations in the future or even pay more than that. The equity market has been one of the good choices for investment as pension funds try to reach a particular rate of return to maximize their wealth while considering not crossing red lines in taking risks. This paper will detail the new mathematical model for finding optimal stock portfolios using Generalized Co-Lower Partial Moment as a risk measure to minimize portfolio optimization. On the other hand, it introduces new tailored Expected Utility as a performance metric to maximize in this model. The proposed model's issue against previous studies is considering risk aversion and target rate of investment return as two significant investor characteristics. This is based on price returns' simulation of candidate stocks in TSE while using accurate and nonparametric Probability Density Function in historical data analysis.

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