在供需不确定环境下,企业难以精准地预测供应链上游的供给能力和下游市场的实际需求。在解决如何决策供应商组合和订单分配这一基本问题外,企业还需评估潜在风险并在风险和成本之间寻求平衡点。因此,文中对供需不确定下的供应商选择与...在供需不确定环境下,企业难以精准地预测供应链上游的供给能力和下游市场的实际需求。在解决如何决策供应商组合和订单分配这一基本问题外,企业还需评估潜在风险并在风险和成本之间寻求平衡点。因此,文中对供需不确定下的供应商选择与订单分配问题进行研究,利用均值-条件风险价值(Mean-Conditional Value at Risk,M-CVaR)构建了风险规避的决策模型。数值分析表明:选择合适的供应商数量可以有效降低来自供需两端不确定性的影响;成本随风险规避水平的增加而增加。当风险规避水平较低时,置信水平的变化对决策的影响较小,且增加成本可以显著降低风险。展开更多
Non-normality in asset returns is now a common feature of financial markets. However, many practitioners as well as investors do still refer to classic risk adjusted performance measures to assess their investment. Fo...Non-normality in asset returns is now a common feature of financial markets. However, many practitioners as well as investors do still refer to classic risk adjusted performance measures to assess their investment. For example, Sharpe and Treynor ratios are designed for a Gaussian world. Then, employing them for a performance assessment prospect relative to the risk borne is a biased approach. If we look for consistency in risk assessment and in asset performance valuation, we need to look for robust methods or tools. Moreover, the well-known mathematical consistency and numerical tractability concerns drive our preference for simple methods. Under this setting, we propose to account in a simple way and to some extent for the skewness and kurtosis patterns describing the deviations from normality. We adjust therefore the classic Sharpe and Treynor ratios to asymmetries in the downside and upside deviations from the mean values of asset returns. Specifically, the adjusted Sharpe and Treynor ratios are weighted by the upside and downside deviation risks. Accounting for skewness and kurtosis changes generally the ranking of hedge fund performance. Moreover, the obtained adjusted performance measures capture well the skewness and/or kurtosis patterns in hedge fund returns depending on the targeted investment strategy展开更多
文摘在供需不确定环境下,企业难以精准地预测供应链上游的供给能力和下游市场的实际需求。在解决如何决策供应商组合和订单分配这一基本问题外,企业还需评估潜在风险并在风险和成本之间寻求平衡点。因此,文中对供需不确定下的供应商选择与订单分配问题进行研究,利用均值-条件风险价值(Mean-Conditional Value at Risk,M-CVaR)构建了风险规避的决策模型。数值分析表明:选择合适的供应商数量可以有效降低来自供需两端不确定性的影响;成本随风险规避水平的增加而增加。当风险规避水平较低时,置信水平的变化对决策的影响较小,且增加成本可以显著降低风险。
文摘Non-normality in asset returns is now a common feature of financial markets. However, many practitioners as well as investors do still refer to classic risk adjusted performance measures to assess their investment. For example, Sharpe and Treynor ratios are designed for a Gaussian world. Then, employing them for a performance assessment prospect relative to the risk borne is a biased approach. If we look for consistency in risk assessment and in asset performance valuation, we need to look for robust methods or tools. Moreover, the well-known mathematical consistency and numerical tractability concerns drive our preference for simple methods. Under this setting, we propose to account in a simple way and to some extent for the skewness and kurtosis patterns describing the deviations from normality. We adjust therefore the classic Sharpe and Treynor ratios to asymmetries in the downside and upside deviations from the mean values of asset returns. Specifically, the adjusted Sharpe and Treynor ratios are weighted by the upside and downside deviation risks. Accounting for skewness and kurtosis changes generally the ranking of hedge fund performance. Moreover, the obtained adjusted performance measures capture well the skewness and/or kurtosis patterns in hedge fund returns depending on the targeted investment strategy
