Simulation-Based Density Estimation for Time Series Using Covariate Data
利用协变量数据的时间序列模拟型密度估计
This article proposes a simulation-based density estimation technique for time series that exploits information found in covariate data. The method can be paired with a large range of parametric models used in time series estimation. We derive asymptotic properties of the estimator and illustrate attractive finite sample properties for a range of well-known econometric and financial applications.