Mean-Variance, Mean-VaR, Mean-CVaR Models for Portfolio Selection With Background Risk - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Mean-Variance, Mean-VaR, Mean-CVaR Models for Portfolio Selection With Background Risk write by Xu Guo. This book was released on 2018. Mean-Variance, Mean-VaR, Mean-CVaR Models for Portfolio Selection With Background Risk available in PDF, EPUB and Kindle. This paper extends Jiang, et al. (2010), Guo, et al. (2017), and others by investigating the impact of background risk on an investor's portfolio choice in the mean-VaR, mean-CVaR and mean-variance framework, and analyzes the characterizations of the mean-variance boundary and mean-VaR efficient frontier in the presence of background risk. We also consider the case with a risk-free security. Finally, we extend our work to the non-normality situation and examine the economic implications of the mean-VaR/CVaR model.
A Comparison of VAR and Cvar Constraints on Portfolio Selection with the Mean-Variance Model
A Comparison of VAR and Cvar Constraints on Portfolio Selection with the Mean-Variance Model - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook A Comparison of VAR and Cvar Constraints on Portfolio Selection with the Mean-Variance Model write by Gordon J. Alexander. This book was released on 2006. A Comparison of VAR and Cvar Constraints on Portfolio Selection with the Mean-Variance Model available in PDF, EPUB and Kindle. In this paper, we analyze the portfolio selection implications arising from imposing a value-at-risk (VaR) constraint on the mean-variance model, and compare them with those arising from the imposition of a conditional value-at-risk (CVaR) constraint. We show that for a given confidence level, a CVaR constraint is tighter than a VaR constraint if the CVaR and VaR bounds coincide. Consequently, a CVaR constraint is more effective than a VaR constraint as a tool to control slightly risk-averse agents, but in the absence of a risk-free security, has a perverse effect in that it is more likely to force highly risk-averse agents to select portfolios with larger standard deviations. However, when the CVaR bound is appropriately larger than the VaR bound or when a risk-free security is present, a CVaR constraint "dominates" a VaR constraint as a risk management tool.
Mean-Variance Portfolio Selection With 'At-Risk' Constraints and Discrete Distributions
Mean-Variance Portfolio Selection With 'At-Risk' Constraints and Discrete Distributions - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Mean-Variance Portfolio Selection With 'At-Risk' Constraints and Discrete Distributions write by Gordon J. Alexander. This book was released on 2008. Mean-Variance Portfolio Selection With 'At-Risk' Constraints and Discrete Distributions available in PDF, EPUB and Kindle. We examine the impact of adding either a VaR or a CVaR constraint to the mean-variance model when security returns are assumed to have a discrete distribution with finitely many jump points. Three main results are obtained. First, portfolios on the VaR-constrained boundary exhibit (K 2)-fund separation, where K is the number of states for which the portfolios suffer losses equal to the VaR bound. Second, portfolios on the CVaR-constrained boundary exhibit (K 3)-fund separation, where K is the number of states for which the portfolios suffer losses equal to their VaRs. Third, an example illustrates that while the VaR of the CVaR-constrained optimal portfolio is close to that of the VaR-constrained optimal portfolio, the CVaR of the former is notably smaller than that of the latter. This result suggests that a CVaR constraint is more effective than a VaR constraint to curtail large losses in the mean-variance model.
Economic Implications of Using a Mean-VaR Model for Portfolio Selection
Economic Implications of Using a Mean-VaR Model for Portfolio Selection - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Economic Implications of Using a Mean-VaR Model for Portfolio Selection write by Gordon J. Alexander. This book was released on 2007. Economic Implications of Using a Mean-VaR Model for Portfolio Selection available in PDF, EPUB and Kindle. We relate Value at Risk (VaR) to mean-variance analysis and examine the economic implications of using a mean-VaR model for portfolio selection. When comparing two mean-variance efficient portfolios, the higher variance portfolio might have less VaR. Consequently, an efficient portfolio that globally minimizes VaR may not exist. Surprisingly, we show that it is plausible for certain risk-averse agents to end up selecting portfolios with larger standard deviations if they switch from using variance to VaR as a measure of risk. Therefore, regulators should be aware that VaR is not an unqualified improvement over variance as a measure of risk.
Mean-Variance Optimal Portfolio Selection with a Value-At-Risk Constraint
Mean-Variance Optimal Portfolio Selection with a Value-At-Risk Constraint - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Mean-Variance Optimal Portfolio Selection with a Value-At-Risk Constraint write by Hui Deng. This book was released on 2017-01-27. Mean-Variance Optimal Portfolio Selection with a Value-At-Risk Constraint available in PDF, EPUB and Kindle. This dissertation, "Mean-variance Optimal Portfolio Selection With a Value-at-risk Constraint" by Hui, Deng, 鄧惠, was obtained from The University of Hong Kong (Pokfulam, Hong Kong) and is being sold pursuant to Creative Commons: Attribution 3.0 Hong Kong License. The content of this dissertation has not been altered in any way. We have altered the formatting in order to facilitate the ease of printing and reading of the dissertation. All rights not granted by the above license are retained by the author. DOI: 10.5353/th_b4189721 Subjects: Risk Portfolio management - Mathematical models
