Translation-invariant and positive-homogeneous risk measures and optimal portfolio management
研究了在椭圆分布假设下，使用平移不变且正齐次的风险度量（如VaR和TCE）进行投资组合优化的问题，给出了显式闭式解及其存在条件，并用纳斯达克10只股票数据进行了验证。
The problem of risk portfolio optimization with translation-invariant and positive-homogeneous risk measures, which includes value-at-risk (VaR) and tail conditional expectation (TCE), leads to the problem of minimizing a combination of a linear functional and a square root of a quadratic functional for the case of elliptical multivariate underlying distributions. In this paper, we provide an explicit closed-form solution of this minimization problem, and the condition under which this solution exists. The results are illustrated using the data of 10 stocks from NASDAQ/Computers. The distance between the VaR and TCE optimal portfolios has been investigated.