Using Bidirectional Generative Adversarial Networks to estimate Value-at-Risk for Market Risk Management

我们将探讨双向生成对抗网络（BiGAN）在市场风险管理中的应用：风险价值（VaR）等投资组合风险度量的估计。生成对抗网络（Generative atteriral Networks，GAN）允许我们将潜在复杂分布的可能性最大化。在许多其他金融服务用例中，处理来自复杂分布的高维数据是市场风险管理的一个关键方面。GAN，特别是BiGAN，将允许我们处理潜在的复杂金融服务数据，这样我们就不必明确指定一种分布，如多维高斯分布。

We will explore the use of Bidirectional Generative Adversarial Networks (BiGAN) for market risk management: Estimation of portfolio risk measures such as Value-at-Risk (VaR). Generative Adversarial Networks (GAN) allow us to implicitly maximize the likelihood of a potentially complex distribution. Dealing with high dimensional data potentially coming from a complex distribution is a key aspect to market risk management among many other financial services use cases. GAN, specifically BiGAN, will allow us to deal with potentially complex financial services data such that we do not have to explicitly specify a distribution such as a multidimensional Gaussian distribution.

完整资料领取