Mathematical and Quantitative Methods: Dynamic Models for Volatility and Heavy Tails: With Applications to Financial and Economic Time Series
该书提出了一类非线性时间序列模型的理论，处理动态分布，特别关注观测值条件分布可能厚尾且位置或尺度随时间变化的情况，适合金融和经济时间序列研究者。
Timo Terasvirta of Aarhus University reviews, “Dynamic Models for Volatility and Heavy Tails: With Applications to Financial and Economic Time Series” by Andrew C. Harvey. The Econlit abstract of this book begins: “Presents a theory for a class of nonlinear time series models that can deal with dynamic distributions, with an emphasis on models in which the conditional distribution of an observation may be heavy-tailed and the location and/or scale changes over time. Discusses statistical distributions and asymptotic theory; location; scale; location/scale models for nonnegative variables; dynamic kernel density estimation and time-varying quantiles; multivariate models, correlation, and association; and further directions in dynamic models. Harvey is Professor of Econometrics at the University of Cambridge and Fellow of Corpus Christi College, the Econometric Society, and the British Academy.”