This paper constructs a robust optimization framework of the uncertain worst-case return. The model defines an adjustable discrete uncertainty set which controls the conservatism of the optimal asset allocation. Without prior assumptions on the data generating process, the model also develops an...

Portfolio optimization results are strongly dependent on the model parameters. To circumvent this shortcoming, this paper proposes a new modeling approach to address data uncertainty. The model offers full control over the degree of conservatism and underlines its interaction with robustness for...

This paper constructs a robust optimization framework of the uncertain worst-case return. The model defines an adjustable discrete uncertainty set which controls the conservatism of the optimal asset allocation. Without prior assumptions on the data generating process, the model also develops an...

Volatility plays an important role when managing risks, composing portfolios, and pricing financial instruments. However it is not directly observable, being usually estimated through parametric models such as those in the GARCH family. A more natural empirical measure of daily returns...