Stochastic tail index model for high frequency financial data with Bayesian analysis
高频金融数据的随机尾指数模型与贝叶斯分析
This paper proposes a new dynamic model called Stochastic Tail Index (STI) model to analyze time-varying tail index for financial asset using high frequency return data. Bayesian tools are developed to estimate the model, make related inferences, and perform model selection. To construct efficient posterior sampler for the STI model by an approximation approach, a new algorithm called ALSO (Auxiliary Least Squares Optimization) is introduced, which can quickly make…