A Linearization of the Portfolio Optimization Problem with General Risk Measures Under Multivariate Conditional Heteroskedastic Models1. (13th June 2018) - Huang, Shih‐Feng; Lin, Tze‐Yun
Abstract: This study presents an example of the linearization of a complex mean‐risk investment problem. The spectral risk measure is employed as a measure of risk and assets are assumed to have autocorrelation and conditionally heteroskedastic volatilities. Simulation results indicate that the proposed method saves a great deal of computational time. Empirical studies show that this strategy, implemented with certain trading frequency constraints, outperforms the equal‐weighted portfolio, the classical mean‐variance method, and the corresponding market index in Taiwan, the US, and Japan when considering transaction costs and different economic conditions.