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【书名】Modelling Financial Time Series with S-PLUS
【作者】Eric Zivot and Jiahui Wang
【版本】Second Edition
【语言】English
【出版日期】April 13, 2005
【文件格式】PDF
【文件大小】10.7M
【页数】996页
【资料类别】统计学&软件
【扫描版还是影印版】扫描简洁版
【是否缺页】完整
【关键词】统计建模 S-PLUS
【内容简介】
This book is a guide to analyzing and modeling financial time series using S-PLUS and S+FinMetrics. It is a unique blend of econometric theory, financial models, data analysis, and statistical programming. It serves as a user’s guide for Insightful’s S+FinMetrics module of statistical functions for financial time series analysis and financial onometrics as well as a general reference for models used in applied financial econometrics. The ormat of the chapters in the book is to give a reasonably complete description of a statistical model and how it works followed by illustrations of how to analyze the model using S-PLUS and the functions in S+FinMetrics. In this way, the book stands alone as an introduction to financial time series analysis as well as a user’s guide for S+FinMetrics. It also highlights the general analysis of time series data using the new time series objects introduced in S-PLUS 6.
【目录】
Preface v
1 S and S-PLUS 1
2 Time Series Specification, Manipulation, and Visualization in S-PLUS 15
3 Time Series Concepts 57
4 UnitRootTests 111
5 Modeling Extreme Values 141
6 Time Series Regression Modeling 181
7 Univariate GARCH Modeling 223
8 Long Memory Time Series Modeling 271
9 Rolling Analysis of Time Series 313
10 Systems of Regression Equations 361
11 Vector Autoregressive Models for Multivariate Time Series 383
12 Cointegration 429
13 Multivariate GARCH Modeling 479
14 State Space Models 517
15 Factor Models for Asset Returns 567
16 Term Structure of Interest Rates 615
17 Robust Change Detection 633
18 Nonlinear Time Series Models 651
19 Copulas 711
20 Continuous-Time Models for Financial Time Series 757
21 Generalized Method of Moments 783
22.Semi-Nonparametric Conditional Density Models 845
23 Efficient Method of Moments 921
Index 989

【整理书评】
This book is written for a wide audience of individuals who work, do research or study in the areas of empirical finance and financial econometrics. The field of financial econometrics has exploded over the last decade, and this book represents an integration of theory, methods and examples using the S-PLUS modeling language to facilitate the practice of financial econometrics. This audience includes researchers and practitioners in the finance industry, academic researchers in economics and finance, and advanced MBA and graduate students in economics and finance. Researchers and practitioners in the finance industry who already use S-PLUS and desire more functionality for analyzing and modeling financial data will find this text useful. It is also appropriate for financial analysts who may not be familiar with S-PLUS but who desire an integrated and open statistical modeling and programming environment for the analysis of financial data. This guide is useful for academic researchers interested in empirical finance and financial econometrics. Finally, this book may be used as a textbook or a textbook companion for advanced MBA and graduate level courses in time series analysis, empirical finance and financial econometrics. It is assumed that the reader has a basic familiarity with S-PLUS and a background in mathematical statistics ， is comfortable with linear algebra and linear regression, and has been exposed to basic time series concepts .Most importantly, the book assumes that the reader is interested in modeling and analyzing financial time series.

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