A new approach to optimizing a portfolio of financial instruments to reduce risk of high losses is considered and tested on application. It focuses on minimizing Conditional value-at-risk (CVaR). CVaR is frequently used risk measure in current risk management practice. For continuous distribution, CVaR is defined as the conditional expected loss under the condition that it exceeds Value-at-risk (VaR). We consider optimization portfolios for minimizing CVaR. In this work, this approach to the optimization problems with CVaR constraints. In particular, the approach can be used for maximizing expected returns under CVaR constraints. \\
Two main difficult tasks for an investor are (1) to find the optimal portfolio with the smallest amount of risk given a required expected return and (2) to determine buying or selling prices of the exotic options that suitable for optimal portfolio.
In this work, we apply this approach to option markets. We consider standard put and call options which are written on S\&P 500 Mini Index. The quotes come with bid and ask prices as well as sizes. We first determine the optimal portfolio, the portfolio with the smallest CVaR given a required return. We also investigate the changes in optimized portfolios subject to various modeling parameters. The index is modeled by a variance gamma process which is a geometric Brownian motion with gamma-distributed random time implements.
A new
approach
to optimizing a portfolio of financial instruments to
reduce
risk
of high losses
is considered
and
tested
on application. It focuses on minimizing Conditional value-at-
risk
(
CVaR
).
CVaR
is
frequently
used
risk
measure in
current
risk
management practice. For continuous distribution,
CVaR
is defined
as the conditional
expected
loss under the condition that it exceeds Value-at-
risk
(
VaR
). We consider optimization portfolios for minimizing
CVaR
. In this work, this
approach
to the optimization problems with
CVaR
constraints.
In particular
, the
approach
can be
used
for maximizing
expected
returns under
CVaR
constraints. \\
Two main difficult tasks for an investor are (1) to find the optimal portfolio with the smallest amount of
risk
given
a required
expected
return and (2) to determine buying or selling prices of the exotic options that suitable for optimal portfolio.
In this work, we apply this
approach
to option markets. We consider standard put and call options which
are written
on S\
&P
500 Mini Index. The quotes
come
with bid and ask prices
as well
as sizes. We
first
determine the optimal portfolio, the portfolio with the smallest
CVaR
given
a required return. We
also
investigate the
changes
in optimized portfolios subject to various modeling parameters. The index
is modeled
by a variance gamma process which is a geometric Brownian motion with gamma-distributed random time implements.