Comparing Mean-Variance and CVaR optimal portfolios, assuming bivariate skew-t distributed returns
(2005)Department of Economics
- Abstract
- In this paper we are building portfolios consisting of the
S&P 500 index and a T-bond index. The portfolio weights are
chosen in such a way that the risk for the portfolio is minimized.
To be able to minimize the risk for a portfolio, we first have to
specify how to measure the portfolios risk. There are several ways
of measuring the risk for a portfolio. In this paper we are
investigating how the portfolio weights differ whether we measure
the portfolios risk by the variance or by the Conditional
Value-at-Risk (CVaR). To measure the risk for the portfolios we
first estimated a two-dimensional density function for the returns
of the assets, using a skew student-t distribution. The time horizon
for each portfolio was one week. The result... (More) - In this paper we are building portfolios consisting of the
S&P 500 index and a T-bond index. The portfolio weights are
chosen in such a way that the risk for the portfolio is minimized.
To be able to minimize the risk for a portfolio, we first have to
specify how to measure the portfolios risk. There are several ways
of measuring the risk for a portfolio. In this paper we are
investigating how the portfolio weights differ whether we measure
the portfolios risk by the variance or by the Conditional
Value-at-Risk (CVaR). To measure the risk for the portfolios we
first estimated a two-dimensional density function for the returns
of the assets, using a skew student-t distribution. The time horizon
for each portfolio was one week. The result shows that the weights
in the S&P 500 index always were lower for the portfolios
constructed by minimizing CVaR. The reason for this is that the
distribution for the returns of the S&P 500 index exhibits a
negative skewness and has fatter tails than the returns of the
T-bond index. This fact isn't taken care of when choosing weights
according to the variance criteria, which leads to an
underestimation of the risk associated with the S&P 500 index.
The underestimation of the risk leads to an overestimation of the
optimal weights in the S&P 500 index. (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/1335470
- author
- Wohlfart, Peter and Nossman, Marcus
- supervisor
- organization
- year
- 2005
- type
- H1 - Master's Degree (One Year)
- subject
- keywords
- mean-variance, CVaR, portfolios, skew-t, Economics, econometrics, economic theory, economic systems, economic policy, Nationalekonomi, ekonometri, ekonomisk teori, ekonomiska system, ekonomisk politik
- language
- English
- id
- 1335470
- date added to LUP
- 2005-09-21 00:00:00
- date last changed
- 2010-08-03 10:53:12
@misc{1335470,
abstract = {{In this paper we are building portfolios consisting of the
S&P 500 index and a T-bond index. The portfolio weights are
chosen in such a way that the risk for the portfolio is minimized.
To be able to minimize the risk for a portfolio, we first have to
specify how to measure the portfolios risk. There are several ways
of measuring the risk for a portfolio. In this paper we are
investigating how the portfolio weights differ whether we measure
the portfolios risk by the variance or by the Conditional
Value-at-Risk (CVaR). To measure the risk for the portfolios we
first estimated a two-dimensional density function for the returns
of the assets, using a skew student-t distribution. The time horizon
for each portfolio was one week. The result shows that the weights
in the S&P 500 index always were lower for the portfolios
constructed by minimizing CVaR. The reason for this is that the
distribution for the returns of the S&P 500 index exhibits a
negative skewness and has fatter tails than the returns of the
T-bond index. This fact isn't taken care of when choosing weights
according to the variance criteria, which leads to an
underestimation of the risk associated with the S&P 500 index.
The underestimation of the risk leads to an overestimation of the
optimal weights in the S&P 500 index.}},
author = {{Wohlfart, Peter and Nossman, Marcus}},
language = {{eng}},
note = {{Student Paper}},
title = {{Comparing Mean-Variance and CVaR optimal portfolios, assuming bivariate skew-t distributed returns}},
year = {{2005}},
}