Estimation and Testing in Models Containing Both Jumps and Conditional Heteroscedasticity
提出一种检验离散时间序列是否由扩散过程生成的检验方法，基于方差与峰度参数的过度识别关系，并估计同时包含跳跃和条件异方差的模型，发现美元汇率中存在跳跃。
In this article we develop a test for the hypothesis that a series (observed in discrete time) is generated by a diffusion process. This test is based on an overidentifying relation between variance and kurtosis parameters that holds for generalized autoregressive conditional heteroscedastic diffusions. The proposed test is not specific to a particular data frequency and clearly indicates the presence of jumps in dollar exchange rates. To assess the size and intensity of the jumps, we estimate a model containing both jumps and conditional heteroscedasticity.