Decision-makers who usually face model/parameter risk may prefer to act prudently by identifying optimal contracts that … solved. Numerical experiments are run for various risk preference choices and it is found that for relatively large sample … the modeler puts on the tail risk when defining its objective function. These findings suggest that one should be very …

This paper originally proposes two unique closed-form solutions, respectively to risky assets only and a risk …, this curve intersects the mean-skewness plane of the portfolio return wtih zero-variance (zero-risk) at a line. Calculating … performance of the risk-adjusted returns of market portfolio. The ratio is similar to the Sharpe ratio, moreover, under the more …

Value-at-risk (VaR) and conditional value-at-risk (CVaR) are popular risk measures from academic, industrial and … investor is faced with a Markowitz type of risk reward problem at the final horizon, where variance as a measure of risk is …

We implement a long-horizon static and dynamic portfolio allocation involving a risk-free and a risky asset. This model …

divided for an improvement in the worst-case objective value. Based on this theory, we propose several splitting heuristics …

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 …

In this paper, we focus on the portfolio optimization problem associated to a quasiconvex risk measure (satisfying some … additional assumptions). For coherent/convex risk measures, the portfolio optimization problem has been already studied by … characterize optimal solutions of the portfolio problem associated to quasiconvex risk measures. The shape of the efficient …