论文标题
时间序列使用D-Vines和V-Transforms的模型
Time series copula models using d-vines and v-transforms
论文作者
论文摘要
提出了一种使用固定的D-vine Copula工艺与Lebesgue-Measure-Measure-Measure-Measure-Measure-Measion-presserving转换（称为V-Transforms）结合使用的挥发性财务回报系列的方法。通过开发一种随机反相V变换的方法，可以构建模型，可以描述价格运动幅度的随机波动性，又可以描述其方向上的串行相关性。结合参数边际分布，表明这些模型可以与扩展的Garch家族中的模型竞争，有时甚至超过了众所周知的模型。
An approach to modelling volatile financial return series using stationary d-vine copula processes combined with Lebesgue-measure-preserving transformations known as v-transforms is proposed. By developing a method of stochastically inverting v-transforms, models are constructed that can describe both stochastic volatility in the magnitude of price movements and serial correlation in their directions. In combination with parametric marginal distributions it is shown that these models can rival and sometimes outperform well-known models in the extended GARCH family.
