The Admissible M-V Portfolio Optimization Based on Bayesian Theory
The traditional M-V model based on historical data has uncertainty in the estimation of expected return and variance.The shortcomings of the model in parameter estimation can be reduced by Bayes theory.Considering the realistic constraints such as admissible deviation,investor's subjective emotional preference,transaction cost and borrowing constraints,the admissible mean variance portfolio model based on Bayesian theory is constructed in this paper,and Bayesian theory is used to adjust the parameters of the model.These models are convex programming problems,which can be solved by se-quential quadratic programming and inequality rotation algorithm.In the sample,the effective frontier of the optimal portfolio under different optimistic indexs are calculated and analyzed in this paper.Outside the sample,this paper uses the method of"rolling sample"to compare the Sharpe ratio of the models with the equal proportion portfolio model,and verifies the investment effect of the models.
the admissible M-V portfolio modelBayes theoryoptimism indexconjugate prior distri-butiondiffusion prior distribution
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