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Author Jianjun Gao ♦ Yan Xiong
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©2013
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science ♦ Technology ♦ Engineering & allied operations
Subject Keyword Portfolios ♦ Equations ♦ Investment ♦ Random variables ♦ Optimization ♦ Reactive power ♦ Computational modeling
Abstract The conditional value-at-risk(CVaR) is defined as the expected value of the tail distribution exceeding Value-at-Risk(VaR). As a kind of risk measure, CVaR recently receives much attention from both academic field and financial industry. However, due to the tractability, most of the studies on mean-CVaR portfolio optimization are restricted to the static portfolio analysis, where only buy-and-hold portfolio policy is computed numerically. In this paper, we study the dynamic portfolio policy of the mean-CVaR portfolio model, in which the investor is allowed to adjust the investment policy dynamically to minimize the CVaR of the portfolio as well as keep certain level of the expected return. On recognizing the ill-posed nature of such a problem in continuous-time model, we modify the model by imposing the limited funding level as the upper bound of the wealth. By using the martingale approach, we develop the explicit portfolio policy and mean-CVaR efficient frontier for such a problem.
Description Author affiliation: Dept. of Autom., Shanghai Jiao Tong Univ., Shanghai, China (Jianjun Gao; Yan Xiong)
ISBN 9781467347075
ISSN 19483449
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research ♦ Reading
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2013-06-12
Publisher Place China
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
e-ISBN 9781467347082
Size (in Bytes) 156.70 kB
Page Count 6
Starting Page 1550
Ending Page 1555

Source: IEEE Xplore Digital Library