We investigate a discrete-time mean-risk portfolio selection problem, where risk is measured by the conditional value-at-risk (CVaR). By embedding this time-inconsistent problem into a family of expected utility maximization problems with a piecewise linear utility function, we solve the problem...

This paper deals with risk measurement and portfolio optimization under risk constraints. Firstly we give an overview of risk assessment from the viewpoint of risk theory, focusing on moment-based, distortion and spectral risk measures. We subsequently apply these ideas to an asset management...

In this paper, we propose a method for hedge fund replication using a factor-based model supplemented with a series of risk and return constraints that implicitly target all the moments of the hedge fund return distribution. We use the approach to replicate the monthly returns of ten broad hedge...

The Firm-Value Risk Model combines the technology of actuarial optimal dividends models with insights regarding financial frictions from financial economics, especially as they apply to risk transfer in (re)insurance firms. This paper illustrates, by numerical solution of a set of case studies,...

Financial institutions now face the important challenge of having to do multiple portfolio revaluations for their risk computation. The list is almost endless: from XVAs to FRTB, stress testing programs, etc. These computations require from several hundred up to a few million revaluations. The...

Measuring risk is at the center of modern financial risk management. As the world economy is becoming more complex and standard modeling assumptions are violated, the advanced artificial intelligence solutions may provide the right tools to analyze the global market. In this paper, we provide a...

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...

A decomposition of a sub-class of spectral risk measures is introduced in terms of L-moments accounting for geometric characteristics of the return distribution similar to the ones described by the ordinary moments. The decomposition characterizes completely the spectral risk measures with...

We propose a method for optimal portfolio selection built on the Black and Litterman model and with two major contributions. We introduce in the investors' objective function a risk measure named expected tail loss, which is useful in portfolio selection context as it supports the benefi ts of...