论文标题
其合成生成的隐含波动率表面的新编码
A new encoding of implied volatility surfaces for their synthetic generation
论文作者
论文摘要
从财务上讲，隐含的波动表面可以通过其术语结构，偏度和整体波动率水平来描述。我们使用PCA变量自动编码器模型将这些描述符完美地表示为三个维度的潜在空间。我们的新编码为合成表面产生带来了重大好处，因为（i）场景产生更容易解释； （ii）挥发性外推获得更好的准确性； （iii）我们提出了一种解决方案，以从索引中推断出股票的隐含波动率表面，该索引直接通过对其在编码的潜在空间进行建模来直接属于其属于其属性。只要数据稀缺，所有这些应用程序，尤其是后者，都有可能改善金融衍生产品的风险管理。
In financial terms, an implied volatility surface can be described by its term structure, its skewness and its overall volatility level. We use a PCA variational auto-encoder model to perfectly represent these descriptors into a latent space of three dimensions. Our new encoding brings significant benefits for synthetic surface generation, in that (i) scenario generation is more interpretable; (ii) volatility extrapolation achieve better accuracy; and, (iii) we propose a solution to infer implied volatility surfaces of a stock from an index to which it belongs directly by modelling their relationship on the latent space of the encoding. All these applications, and the latter in particular, have the potential to improve risk management of financial derivatives whenever data is scarce.
