On Sensitivity for Portfolio Optimisation Based on a High-dimensional Jump-diffusion Merton Model

The problem of singularity the variance-covariance matrix and its impact on sensitivity Markowitz portfolio optimization has been extensively studied in literature when underlying model does not include jump terms. In this paper, we first use a jump-diffusion multivariate Merton to evaluate apply principal component analysis (PCA) for dimensionality reduction as solution matrix. Finally, provide numerical study based adjusted daily closing price $S\&{P}\, 500$ stocks explore dimension reduced space terms optimization. Empirical experiments confirm that models without terms, may reflect correct assessment