The twin objectives of risk diversification and expected return maximization are essential to portfolio efficiency. However, what constitutes an appropriate measure of risk and its reliable estimation remains elusive. Furthermore, the integrated risk management of a set of portfolios, even when individually efficient, presents challenges as well. This issue of The Journal of Risk contains papers that contribute to the better understanding of each of these topics.
In the first paper in this issue, "The alpha alignment factor: a solution to the underestimation of risk for optimized active portfolios", Anureet Saxena and Robert A. Stubbs develop a factor model framework that captures the interaction between alpha and risk model predictions in order to address the risk underestimation problem of optimized portfolios. As well as being robust and practical, their approach is integral to the determination of the optimal portfolio allocation.
In the paper by Saxena and Stubbs, risk is measured through volatility. In contrast, in the issue's second paper, "Asset allocation with conditional value-at-risk budgets", Kris Boudt, Peter Carl and Brian G. Peterson use a tail-focused measure. In their paper, the authors use ex ante methods both to evaluate the contribution of component risk and to construct risk budgets. Their empirical results suggest that their approach will achieve a good balance between low overall risk, good upside return, high diversification and low turnover in portfolio selection.
This second risk measure is considered more generally in the third paper in the issue: "Dynamic option-based strategies under downside loss aversion" by Amine Jalal. Therein, the author incorporates derivatives in order to complete markets in the presence of jumps and stochastic volatility. Though the number of assets involved is not as large as in the first two papers, the resulting closed-form expressions for the smaller set enable an analysis that distills the role played by the relevant derivatives.
The fourth and final paper in this issue, "On the reliability of integrated risk measurement in practice" by Peter Grundke, addresses the integration of various and often independently controlled risk measurements within a single institution. However, the associated losses are typically dependent and the author conducts a simulation study to evaluate the reliability and sensitivity of integrated risk management. The results in this paper highlight explicitly the impact of bottom-up and top-down approaches.