We propose using the well-known conditional value at risk (CVaR) risk measure as a new methodology for incorporating robustness into portfolio optimization. Robustness in portfolio optimization can address the poor out-of-sample performance of the classical mean-variance optimization problems....

In this paper we entertain a method of finding the most robust moving average weighting scheme to use for the purpose of timing the market. Robustness of a weighting scheme is defined its ability to generate sustainable performance under all possible market scenarios regardless of the size of...

The purpose of this article is to assess whether correct application of robust estimators in construction of minimum variance portfolios' (MVP) allows to achieve better investment results in comparison with portfolios defined using classical MLE estimators. Theoretical robust portfolios...

In the last few years, the financial advisory industry has been impacted by the emergence of digitalization and robo-advisors. This phenomenon affects major financial services, including wealth management, employee savings plans, asset managers, private banks, pension funds, banking services,...

The purpose of this paper is to introduce the Gerber statistic, a robust co-movement measure for covariance matrix estimation for the purpose of portfolio construction. The Gerber statistic extends Kendall's Tau by counting the proportion of simultaneous co-movements in series when their...

We study issues of robustness in the context of Quantitative Risk Management and Optimization. We develop a general methodology for determining whether a given risk measurement related optimization problem is robust, which we call "robustness against optimization". The new notion is studied for...

We present a method for computing a normalized measure of model risk. The method is based on the definition of a "distance" between models, measured by the conditional entropy of a perturbed model with respect to a reference model. The method is illustrated by numerical examples

We determine the optimal investment strategy for an ambiguity averse investor in a setting with stochastic interest rates. The investor is assumed to be ambiguous about the expected rate of return of both bonds and stocks, and may have different levels of ambiguity aversion about the two types...