论文标题
瓦斯尔斯坦·巴里卡特（Wasserstein Barycenter）下的风险度量估计
Risk Measures Estimation Under Wasserstein Barycenter
论文作者
论文摘要
金融市场的随机性需要现代和强大的风险度量模型。本文提出了一种新的方法，用于建模在瓦斯尔斯坦（Wasserstein Barycenters）下的多元风险度量，该概率措施对位置丝网家族的支持。将风险模型的简单和先进的多元价值与派生技术进行了比较。该模型的性能还会在COVID-19引起的金融危机产生的美国市场指数中检查。引入的模型在资产价格的共同时期和动荡时期都令人满意，在这个社会疏远时代提供了现实的VAR预测。
Randomness in financial markets requires modern and robust multivariate models of risk measures. This paper proposes a new approach for modeling multivariate risk measures under Wasserstein barycenters of probability measures supported on location-scatter families. Simple and advanced copulas multivariate Value at Risk models are compared with the derived technique. The performance of the model is also checked in market indices of United States generated by the financial crisis due to COVID-19. The introduced model behaves satisfactory in both common and volatile periods of asset prices, providing realistic VaR forecast in this era of social distancing.
