| Vorliegende Sprache |
eng |
| Hinweise auf parallele Ausgaben |
370542266 Buchausg. u.d.T.: ‡Kirchgässner, Gebhard, 1948 - 2017: Introduction to modern time series analysis |
| ISBN |
978-3-642-33435-1 |
| Name |
Kirchgässner, Gebhard |
| Wolters, Jürgen |
| ANZEIGE DER KETTE |
Wolters, Jürgen |
| Name |
Hassler, Uwe |
| T I T E L |
Introduction to Modern Time Series Analysis |
| Auflage |
2nd ed. 2013 |
| Verlagsort |
Berlin ; Heidelberg |
| Verlag |
Springer |
| Erscheinungsjahr |
2013 |
| 2013 |
| Umfang |
Online-Ressource (XII, 319 p. 42 illus, digital) |
| Reihe |
Springer Texts in Business and Economics |
| Notiz / Fußnoten |
Description based upon print version of record |
| Weiterer Inhalt |
""Introduction to Modern Time Series Analysis ""; ""Preface to the Second Edition""; ""Preface to the First Edition""; ""Contents""; ""1 Introduction and Basics""; ""1.1 The Historical Development of Time Series Analysis""; ""1.2 Graphical Representations of Economic Time Series""; ""1.3 The Lag Operator""; ""1.4 Ergodicity and Stationarity""; ""Example 1.1""; ""Example 1.2""; ""Example 1.3""; ""1.5 The Wold Decomposition""; ""References""; ""2 Univariate Stationary Processes""; ""2.1 Autoregressive Processes""; ""2.1.1 First Order Autoregressive Processes"". ""Derivation of Wold�s Representation""""The Lag Operator""; ""Calculation of Moments""; ""An Alternative Method for the Calculation of Moments""; ""The Autocorrelogram""; ""Example 2.1""; ""Example 2.2""; ""Stability Conditions""; ""Example 2.3""; ""2.1.2 Second Order Autoregressive Processes""; ""Example 2.4""; ""Example 2.5""; ""Example 2.6""; ""2.1.3 Higher Order Autoregressive Processes""; ""Example 2.7""; ""2.1.4 The Partial Autocorrelation Function""; ""Example 2.8""; ""2.1.5 Estimating Autoregressive Processes""; ""Example 2.9""; ""2.2 Moving Average Processes"". ""2.2.1 First Order Moving Average Processes""""Example 2.10""; ""2.2.2 MA(1) and Temporal Aggregation""; ""Example 2.11""; ""Example 2.12""; ""2.2.3 Higher Order Moving Average Processes""; ""Example 2.13""; ""2.3 Mixed Processes""; ""2.3.1 ARMA(1,1) Processes""; ""2.3.2 ARMA(p,q) Processes""; ""Example 2.15""; ""2.4 Forecasting""; ""2.4.1 Forecasts with Minimal Mean Squared Errors""; ""2.4.2 Forecasts of ARMA(p,q) Processes""; ""Forecasts with a Stationary AR(1) Process""; ""Forecasts with Stationary AR(p) Processes""; ""Forecasts with an Invertible MA(1) Process"". ""Forecasts with ARMA(p,q) Processes""""2.4.3 Evaluation of Forecasts""; ""Example 2.16""; ""2.5 The Relation between Econometric Models and ARMA Processes""; ""References""; ""3 Granger Causality""; ""3.1 The Definition of Granger Causality""; ""3.2 Characterisation of Causal Relations in Bivariate Models""; ""3.2.1 Characterisation of Causal Relations Using the Autoregressive and Moving Average Representations""; ""3.2.2 Characterisation of Causal Relations Using the Residuals of the Univariate Processes""; ""3.3 Causality Tests""; ""3.3.1 The Direct Granger Procedure""; ""Example 3.1"". ""3.3.2 The Haugh-Pierce Test""""Example 3.2""; ""3.3.3 The Hsiao Procedure""; ""Example 3.3""; ""3.4 Applying Causality Tests in a Multivariate Setting""; ""3.4.1 The Direct Granger Procedure with More Than Two Variables""; ""Example 3.4""; ""Example 3.5""; ""3.4.2 Interpreting the Results of Bivariate Tests in Systems With More Than Two Variables""; ""3.5 Concluding Remarks""; ""References""; ""4 Vector Autoregressive Processes""; ""4.1 Representation of the System""; ""Example 4.1""; ""Example 4.2""; ""Example 4.3""; ""Example 4.4""; ""4.2 Granger Causality""; ""Example 4.5"". ""4.3 Impulse Response Analysis"" |
| Titelhinweis |
Buchausg. u.d.T.: ‡Kirchgässner, Gebhard, 1948 - 2017: Introduction to modern time series analysis |
| ISBN |
ISBN 978-3-642-33436-8 |
| Klassifikation |
KCH |
| BUS021000 |
| *91-01 |
| 62-01 |
| 91B84 |
| 62M10 |
| 62M20 |
| 62P20 |
| 330.015195 |
| 330.0151955 |
| HB139-141 |
| QH 237 |
| SK 845 |
| Kurzbeschreibung |
Introduction and Basics -- Univariate Stationary Processes -- Granger Causality -- Vector Autoregressive Processes -- Nonstationary Processes -- Cointegration -- Nonstationary Panel Data -- Autoregressive Conditional Heteroscedasticity |
| 2. Kurzbeschreibung |
This book presents modern developments in time series econometrics that are applied to macroeconomic and financial time series, bridging the gap between methods and realistic applications. It presents the most important approaches to the analysis of time series, which may be stationary or nonstationary. Modelling and forecasting univariate time series is the starting point. For multiple stationary time series, Granger causality tests and vector autogressive models are presented. As the modelling of nonstationary uni- or multivariate time series is most important for real applied work, unit root and cointegration analysis as well as vector error correction models are a central topic. Tools for analysing nonstationary data are then transferred to the panel framework. Modelling the (multivariate) volatility of financial time series with autogressive conditional heteroskedastic models is also treated. |
| 1. Schlagwortkette |
Ökonometrie |
| Zeitreihenanalyse |
| 1. Schlagwortkette ANZEIGE DER KETTE |
Ökonometrie -- Zeitreihenanalyse |
| 2. Schlagwortkette |
Ökonometrie |
| Zeitreihenanalyse |
| ANZEIGE DER KETTE |
Ökonometrie -- Zeitreihenanalyse |
| SWB-Titel-Idn |
375373667 |
| Signatur |
Springer E-Book |
| Bemerkungen |
Elektronischer Volltext - Campuslizenz |
| Elektronische Adresse |
$uhttp://dx.doi.org/10.1007/978-3-642-33436-8 |
| Internetseite / Link |
Volltext |
| Siehe auch |
Inhaltsverzeichnis |
| Siehe auch |
Inhaltstext |
| Siehe auch |
Volltext |
| Siehe auch |
Cover |
| Siehe auch |
Inhaltstext |
