Pareto optimal allocations and optimal risk sharing for coherent or convex risk measures as well as for insurance … applying inf-convolution of risk measures and convex analysis.In the recent literature, an increasing interest has been devoted … to quasiconvex risk measures, that is risk measures where convexity is replaced by quasiconvexity and cash-additivity is …

The mean-variance portfolio optimization theory of Markowitz assumes that stock returns are distributed according to … inherently more risky than stocks with normal pdfs. This paper examines portfolio optimization using the kurtosis as a risk … fluctuations from the mean which is counter-intuitive and contrary to normal practice. It is argued that risk is multidimensional …

requirement of rich expertise in financial risk. Compared with other black-box algorithms, the explainable CBR system allows a … predicting financial risk, which is essential for both financial companies and their customers. In addition, results show that …

investment periods is the conditional risk mapping approach. The idea is to develop a model in which information from the … optimization problem with rebalancing in a more time-efficient way when coherent risk measures are used. Artzner et al. (1999 …) outlined a set of mathematical properties for a risk measure that reflect the interests of risk-averse investors. Furthermore …

assets only, the constrained one, and the presence of a risk-free asset. The use of a generalized form for the budget … - and infer the price of pure risk. Some properties of the several solutions are highlighted. The rationale for a linear …

The purpose of this article is to evaluate optimal expected utility risk measures (OEU) in a risk- constrained … constraint to a portfolio selection model using value at risk as constraint. The former is a coherent risk measure for utility … functions with constant relative risk aversion and allows individual specifications to the investor's risk attitude and time …

benchmark for all decreasing absolute risk-averse investors, using Quadratic Programming. The method is applied to standard data … the performance of Mean-Variance optimization by tens to hundreds of basis points per annum, for low to medium risk levels …. The improvements critically depend on imposing the complex condition of Decreasing Absolute Risk Aversion in addition to …

"Examines the multidisciplinary applications, problems, and case histories in risk modeling, assessment, and management … This book examines risk analysis, focusing on quantifying risk and constructing probability in conjunction with real … material (extreme events and the partitioned multi-objective risk method; multi-objective decision-tree analysis; multi …