Introduction of New Risk Metric using Kernel Density Estimation Via Linear Diffusion
Publish Year: 1401
نوع سند: مقاله ژورنالی
زبان: English
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شناسه ملی سند علمی:
JR_AMFA-7-2_013
تاریخ نمایه سازی: 21 اردیبهشت 1401
Abstract:
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.
Keywords:
Risk measurement , Generalized Co-Lower Partial Moment , Portfolio optimization , Nonparametric estimation , Stock market
Authors
Ahmad Darestani Farahani
Department of Finance, Science and Research Branch, Islamic Azad University, Tehran, Iran
Mohammadreza Miri Lavasani
Department of HSE, Science and Research Branch, Islamic Azad University, Tehran, Iran
Hamidreza Kordlouie
Department of Financial Management, Eslamshahr Branch, Islamic Azad University, Tehran, Iran
Ghodratallah Talebnia
Department of Accounting, Science and Research Branch, Islamic Azad University, Tehran, Iran.
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