英文标题：
《Simulation-based Value-at-Risk for Nonlinear Portfolios》
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作者：
Junyao Chen, Tony Sit and Hoi Ying Wong
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最新提交年份：
2019
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英文摘要：
Value-at-risk (VaR) has been playing the role of a standard risk measure since its introduction. In practice, the delta-normal approach is usually adopted to approximate the VaR of portfolios with option positions. Its effectiveness, however, substantially diminishes when the portfolios concerned involve a high dimension of derivative positions with nonlinear payoffs; lack of closed form pricing solution for these potentially highly correlated, American-style derivatives further complicates the problem. This paper proposes a generic simulation-based algorithm for VaR estimation that can be easily applied to any existing procedures. Our proposal leverages cross-sectional information and applies variable selection techniques to simplify the existing simulation framework. Asymptotic properties of the new approach demonstrate faster convergence due to the additional model selection component introduced. We have also performed sets of numerical results that verify the effectiveness of our approach in comparison with some existing strategies.
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中文摘要：
自引入风险价值（VaR）以来，它一直扮演着标准风险度量的角色。在实践中，通常采用delta-normal方法来近似具有期权头寸的投资组合的VaR。然而，当相关投资组合涉及具有非线性回报的高维衍生品头寸时，其有效性大幅降低；这些潜在高度相关的美式衍生品缺乏封闭式定价解决方案，这进一步使问题复杂化。本文提出了一种基于仿真的VaR估计通用算法，该算法可以方便地应用于任何现有的过程。我们的建议利用横截面信息，并应用变量选择技术来简化现有的模拟框架。由于引入了额外的模型选择组件，新方法的渐近性质证明了更快的收敛速度。我们还进行了一系列数值计算，与一些现有策略相比，验证了我们方法的有效性。
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分类信息：

一级分类：Statistics 统计学
二级分类：Methodology 方法论
分类描述：Design, Surveys, Model Selection, Multiple Testing, Multivariate Methods, Signal and Image Processing, Time Series, Smoothing, Spatial Statistics, Survival Analysis, Nonparametric and Semiparametric Methods
设计，调查，模型选择，多重检验，多元方法，信号和图像处理，时间序列，平滑，空间统计，生存分析，非参数和半参数方法
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一级分类：Quantitative Finance 数量金融学
二级分类：Risk Management 风险管理
分类描述：Measurement and management of financial risks in trading, banking, insurance, corporate and other applications
衡量和管理贸易、银行、保险、企业和其他应用中的金融风险
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