Chebyshev Inequality based Approach to Chance Constrained Portfolio Optimization
نویسنده
چکیده
A new approach to solve Chance constrained Portfolio Optimization Problems (CPOPs) without using the Monte Carlo simulation is proposed. Specifically, according to Chebyshev inequality, the prediction interval of a stochastic function value included in CPOP is estimated from a set of samples. By using the prediction interval, CPOP is transformed into Lower-bound Portfolio Optimization Problem (LPOP). It is proved that the feasible solution of LPOP is also feasible for CPOP. Furthermore, in order to solve LPOP, Differential Evolution (DE) is used. Finally, through a numerical experiment, the usefulness of the proposed approach is demonstrated. Key–Words: Portfolio Optimization, Risk Management, Chance Constraint, Chebyshev Inequality
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