  In this paper, we consider the chance constrained based uncertain portfolio
optimization problem in which the uncertain parameters are stochastic in
nature. The primary goal of the work is to formulate the uncertain problem into
a deterministic model to study its robust counterpart, which will be helpful
for solving such types of uncertain problems. In the present study, we assume
that the uncertainty occurs in the expected asset returns, accordingly we
derive the corresponding robust counterparts for the cases when the
perturbations follow normal and exponential distributions. The obtained robust
counterparts are computationally tractable. So our study can be used to find
out the deterministic robust counterparts of any quadratic programming problems
with uncertain constraints. In the end, we solve an Indian stock market problem
for the nominal case as well as the cases for normally and exponentially
distributed perturbations, and the results are analyzed.
