Modelling and Prediction of Financial Time Series

被引：4
|
作者：
Bingham, N. H. [1 ]
机构：
[1] Univ London Imperial Coll Sci Technol & Med, Dept Math, London SW7 2AZ, England
来源：
COMMUNICATIONS IN STATISTICS-THEORY AND METHODS | 2014年 / 43卷 / 07期
关键词：
Elliptic distribution; Ergodic diffusion; Levy process; Ornstein-Uhlenbeck process; Prediction; Semi-parametric model; Stationary; Time series; 62M10; 62M20; 62H99; AFFINE EQUIVARIANT ESTIMATORS; MULTIVARIATE LOCATION; APPROXIMATION; THEOREM; JUMPS;
D O I：
10.1080/03610926.2012.754467
中图分类号：
O21 [概率论与数理统计]; C8 [统计学];
学科分类号：
020208 ; 070103 ; 0714 ;
摘要：
We consider statistical aspects of the modelling and prediction theory of time series in one and many dimensions. We discuss Levy-based and general models, and the stationary and non-stationary cases. Our starting point is the recent pair of surveys, Szeg'o's theorem and its probabilistic descendants and Multivariate prediction and matrix Szeg'o theory, by this author.
引用
收藏
页码：1351 / 1361
页数：11
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