Automated Model Selection in Finance: General‐to‐Specific Modelling of the Mean and Volatility Specifications*
提出并研究了一种自动化方法，用于金融时间序列的从一般到特殊（GETS）建模，能同时简化均值和波动率设定，适用于包含自回归项、解释变量及多种波动率成分的复杂模型。
Abstract General‐to‐Specific (GETS) modelling has witnessed major advances thanks to the automation of multi‐path GETS specification search. However, the estimation complexity associated with financial models constitutes an obstacle to automated multi‐path GETS modelling in finance. Making use of a recent result we provide and study simple but general and flexible methods that automate financial multi‐path GETS modelling. Starting from a general model where the mean specification can contain autoregressive terms and explanatory variables, and where the exponential volatility specification can include log‐ARCH terms, asymmetry terms, volatility proxies and other explanatory variables, the algorithm we propose returns parsimonious mean and volatility specifications.