This paper considers the mean variance portfolio management problem. We examine portfolios which contain both primary and derivative securities. The challenge in this context is the well posedness of the optimization problem . We find examples in which this problem is well posed. Numerical experiments provide the efficient frontier . The methodology developed in this paper can be also applied to pricing and hedging in incomplete markets.
This paper considers the mean variance portfolio management problem. We examine portfolios which contain both primary and derivative securities. The challenge in this context is due to portfolio's nonlinearities. The delta-gamma approximation is employed to overcome it. Thus, the optimization problem is reduced to a well posed quadratic program . The methodology developed in this paper can be also applied to pricing and hedging in incomplete markets.
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the well posedness of the optimization problem . We find examples in which this problem is well posed. Numerical experiments provide the efficient frontier
due to portfolio's nonlinearities. The delta-gamma approximation is employed to overcome it. Thus, the optimization problem is reduced to a well posed quadratic program