國立高雄大學圖資館 |

語系: 繁體中文

說明(常見問題)

圖資館首頁

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Time series econometrics

Neusser, Klaus.

Time series econometrics

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Time series econometricsby Klaus Neusser.
作者:	Neusser, Klaus.
出版者:	Cham :Springer International Publishing :2016.
面頁冊數:	xxiv, 409 p. :ill., digital ;26 cm.
Contained By:	Springer eBooks
標題:	Econometric models.
電子資源:	http://dx.doi.org/10.1007/978-3-319-32862-1
ISBN:	9783319328621$q(electronic bk.)

Time series econometrics
Neusser, Klaus.

Time series econometrics[electronic resource] /by Klaus Neusser. - Cham :Springer International Publishing :2016. - xxiv, 409 p. :ill., digital ;26 cm. - Springer texts in business and economics,2192-4333. - Springer texts in business and economics..

1. Introduction -- 2. ARMA models -- 3. Forecasting stationary processes -- 4. Estimation of Mean and Autocovariance Function -- 5.Estimation of ARMA Models -- 6. Spectral Analysis and Linear Filters -- 7. Integrated Processes -- 8. Models of Volatility -- 9. Multivariate Time series -- 10. Estimation of Covariance Function -- 11. VARMA Processes -- 12. Estimation of VAR Models -- 13. Forecasting with VAR Models -- 14. Interpretation of VAR Models -- 15. Co-integration -- 16. The Kalman Filter -- 17. Appendices.

This text presents modern developments in time series analysis and focuses on their application to economic problems. The book first introduces the fundamental concept of a stationary time series and the basic properties of covariance, investigating the structure and estimation of autoregressive-moving average (ARMA) models and their relations to the covariance structure. The book then moves on to non-stationary time series, highlighting its consequences for modeling and forecasting and presenting standard statistical tests and regressions. Next, the text discusses volatility models and their applications in the analysis of financial market data, focusing on generalized autoregressive conditional heteroskedastic (GARCH) models. The second part of the text devoted to multivariate processes, such as vector autoregressive (VAR) models and structural vector autoregressive (SVAR) models, which have become the main tools in empirical macroeconomics. The text concludes with a discussion of co-integrated models and the Kalman Filter, which is being used with increasing frequency. Mathematically rigorous, yet application-oriented, this self-contained text will help students develop a deeper understanding of theory and better command of the models that are vital to the field. Assuming a basic knowledge of statistics and/or econometrics, this text is best suited for advanced undergraduate and beginning graduate students.

ISBN: 9783319328621$q(electronic bk.)

Standard No.: 10.1007/978-3-319-32862-1doiSubjects--Topical Terms:

183244
Econometric models.

LC Class. No.: HB141 / .N48 2016

Dewey Class. No.: 330.015

Time series econometrics
LDR:02927nmm a2200325 a 4500 001 490477
003 DE-He213
005 20161122140935.0
006 m d
007 cr nn 008maaau
008 170118s2016 gw s 0 eng d
020 $a 9783319328621$q(electronic bk.)
020 $a 9783319328614$q(paper)
024 7 $a 10.1007/978-3-319-32862-1 $2 doi
035 $a 978-3-319-32862-1
040 $a GP $c GP
041 0 $a eng
050 4 $a HB141 $b .N48 2016
072 7 $a KCH $2 bicssc
072 7 $a BUS021000 $2 bisacsh
082 0 4 $a 330.015 $2 23
090 $a HB141 $b .N496 2016
100 1 $a Neusser, Klaus. $3 749890
245 1 0 $a Time series econometrics $h [electronic resource] / $c by Klaus Neusser.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2016.
300 $a xxiv, 409 p. : $b ill., digital ; $c 26 cm.
490 1 $a Springer texts in business and economics, $x 2192-4333
505 0 $a 1. Introduction -- 2. ARMA models -- 3. Forecasting stationary processes -- 4. Estimation of Mean and Autocovariance Function -- 5.Estimation of ARMA Models -- 6. Spectral Analysis and Linear Filters -- 7. Integrated Processes -- 8. Models of Volatility -- 9. Multivariate Time series -- 10. Estimation of Covariance Function -- 11. VARMA Processes -- 12. Estimation of VAR Models -- 13. Forecasting with VAR Models -- 14. Interpretation of VAR Models -- 15. Co-integration -- 16. The Kalman Filter -- 17. Appendices.
520 $a This text presents modern developments in time series analysis and focuses on their application to economic problems. The book first introduces the fundamental concept of a stationary time series and the basic properties of covariance, investigating the structure and estimation of autoregressive-moving average (ARMA) models and their relations to the covariance structure. The book then moves on to non-stationary time series, highlighting its consequences for modeling and forecasting and presenting standard statistical tests and regressions. Next, the text discusses volatility models and their applications in the analysis of financial market data, focusing on generalized autoregressive conditional heteroskedastic (GARCH) models. The second part of the text devoted to multivariate processes, such as vector autoregressive (VAR) models and structural vector autoregressive (SVAR) models, which have become the main tools in empirical macroeconomics. The text concludes with a discussion of co-integrated models and the Kalman Filter, which is being used with increasing frequency. Mathematically rigorous, yet application-oriented, this self-contained text will help students develop a deeper understanding of theory and better command of the models that are vital to the field. Assuming a basic knowledge of statistics and/or econometrics, this text is best suited for advanced undergraduate and beginning graduate students.
650 0 $a Econometric models. $3 183244
650 1 4 $a Economics. $3 175999
650 2 4 $a Econometrics. $3 182271
650 2 4 $a Macroeconomics/Monetary Economics/Financial Economics. $3 737439
650 2 4 $a Statistics for Business/Economics/Mathematical Finance/Insurance. $3 274062
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer eBooks
830 0 $a Springer texts in business and economics. $3 557968
856 4 0 $u http://dx.doi.org/10.1007/978-3-319-32862-1
950 $a Economics and Finance (Springer-41170)