Portfolio Selection with Uncertain Exit Time: A Robust CVaR Approach

Portfolio Selection with Uncertain Exit Time: A Robust CVaR Approach

In this paper we explore the portfolio selection problem involving an uncertain time of eventual exit. To deal with this uncertainty, the worst-case CVaR methodology is adopted in the case where no or only partial information on the exit time is available, and the corresponding problems are integrat...

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Main Authors: Dashan HUANG, ZHU, Shushang, FABOZZI, Frank, FUKUSHIMA, Masao
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2008
Subjects:
Robust CVaR; Robust portfolio selection; Uncertain exit time
Finance and Financial Management
Portfolio and Security Analysis
Online Access:https://ink.library.smu.edu.sg/lkcsb_research/4779
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Institution: Singapore Management University
Language: English
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spelling sg-smu-ink.lkcsb_research-57782016-01-08T10:00:06Z Portfolio Selection with Uncertain Exit Time: A Robust CVaR Approach Dashan HUANG, ZHU, Shushang FABOZZI, Frank FUKUSHIMA, Masao In this paper we explore the portfolio selection problem involving an uncertain time of eventual exit. To deal with this uncertainty, the worst-case CVaR methodology is adopted in the case where no or only partial information on the exit time is available, and the corresponding problems are integrated into linear programs which can be efficiently solved. Moreover, we present a method for specifying the uncertain information on the distribution of the exit time associated with exogenous and endogenous incentives. Numerical experiments with real market data and Monte Carlo simulation show the usefulness of the proposed model. 2008-02-01T08:00:00Z text https://ink.library.smu.edu.sg/lkcsb_research/4779 info:doi/10.1016/j.jedc.2007.03.003 Research Collection Lee Kong Chian School Of Business eng Institutional Knowledge at Singapore Management University Robust CVaR; Robust portfolio selection; Uncertain exit time Finance and Financial Management Portfolio and Security Analysis
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Robust CVaR; Robust portfolio selection; Uncertain exit time
Finance and Financial Management
Portfolio and Security Analysis
spellingShingle Robust CVaR; Robust portfolio selection; Uncertain exit time
Finance and Financial Management
Portfolio and Security Analysis
Dashan HUANG,
ZHU, Shushang
FABOZZI, Frank
FUKUSHIMA, Masao
Portfolio Selection with Uncertain Exit Time: A Robust CVaR Approach
description In this paper we explore the portfolio selection problem involving an uncertain time of eventual exit. To deal with this uncertainty, the worst-case CVaR methodology is adopted in the case where no or only partial information on the exit time is available, and the corresponding problems are integrated into linear programs which can be efficiently solved. Moreover, we present a method for specifying the uncertain information on the distribution of the exit time associated with exogenous and endogenous incentives. Numerical experiments with real market data and Monte Carlo simulation show the usefulness of the proposed model.
format text
author Dashan HUANG,
ZHU, Shushang
FABOZZI, Frank
FUKUSHIMA, Masao
author_facet Dashan HUANG,
ZHU, Shushang
FABOZZI, Frank
FUKUSHIMA, Masao
author_sort Dashan HUANG,
title Portfolio Selection with Uncertain Exit Time: A Robust CVaR Approach
title_short Portfolio Selection with Uncertain Exit Time: A Robust CVaR Approach
title_full Portfolio Selection with Uncertain Exit Time: A Robust CVaR Approach
title_fullStr Portfolio Selection with Uncertain Exit Time: A Robust CVaR Approach
title_full_unstemmed Portfolio Selection with Uncertain Exit Time: A Robust CVaR Approach
title_sort portfolio selection with uncertain exit time: a robust cvar approach
publisher Institutional Knowledge at Singapore Management University
publishDate 2008
url https://ink.library.smu.edu.sg/lkcsb_research/4779
_version_ 1770572690891997184

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