Items related to Forecasting Economic Time Series using Locally Stationary...
Forecasting Economic Time Series using Locally Stationary Processes: A New Approach with Applications: 19 (Volkswirtschaftliche Analysen) - Hardcover
Synopsis
Stationarity has always played an important part in forecasting theory. However, some economic time series show time-varying autocovariances. The question arises whether forecasts can be improved using models that capture such a time-varying second-order structure. One possibility is given by autoregressive models with time-varying parameters. The author focuses on the development of a forecasting procedure for these processes and compares this approach to classical forecasting methods by means of Monte Carlo simulations. An evaluation of the proposed procedure is given by its application to futures prices and the Dow Jones index. The approach turns out to be superior to the classical methods if the sample sizes are large and the forecasting horizons do not range too far into the future.
"synopsis" may belong to another edition of this title.
About the Author
Tina Loll holds a Diploma in Civil Engineering from the University of Duisburg-Essen and a Diploma in Business Administration and Engineering from the University of Bochum. From 2007 to 2011 she worked as a research assistant at the Institute of Statistics and Econometrics of the University of Hamburg and received a Doctor of Economics.
"About this title" may belong to another edition of this title.
Search results for Forecasting Economic Time Series using Locally Stationary...
Seller Image
Forecasting economic time series using locally stationary processes : a new approach with applications. Volkswirtschaftliche Analysen ; Bd. 19.
Published by
Frankfurt, M. u.a. : Lang, 2012
ISBN 10: 3631621876
ISBN 13: 9783631621875
Used
Hardcover
Seller: Fundus-Online GbR Borkert Schwarz Zerfaß, Berlin, Germany
Seller rating 5 out of 5 stars
Originalhardcover. Condition: Sehr gut. 138 S. : graph. Darst. Ein tadelloses Exemplar. - Stationarity has always played an important part in forecasting theory. However, some economic time series show time-varying autocovariances. The question arises whether forecasts can be improved using models that capture such a time-varying second-order structure. One possibility is given by autoregressive models with time-varying parameters. The author focuses on the development of a forecasting procedure for these processes and compares this approach to classical forecasting methods by means of Monte Carlo simulations. An evaluation of the proposed procedure is given by its application to futures prices and the Dow Jones index. The approach turns out to be superior to the classical methods if the sample sizes are large and the forecasting horizons do not range too far into the future. ISBN 9783631621875 Sprache: Englisch Gewicht in Gramm: 288. Seller Inventory # 1083716
Quantity: 1 available
Seller Image
Forecasting Economic Time Series using Locally Stationary Processes
Print on DemandSeller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Stationarity has always played an important part in forecasting theory. However, some economic time series show time-varying autocovariances. The question arises whether forecasts can be improved using models that capture such a time-varying second-order structure. One possibility is given by autoregressive models with time-varying parameters. The author focuses on the development of a forecasting procedure for these processes and compares this approach to classical forecasting methods by means of Monte Carlo simulations. An evaluation of the proposed procedure is given by its application to futures prices and the Dow Jones index. The approach turns out to be superior to the classical methods if the sample sizes are large and the forecasting horizons do not range too far into the future. 140 pp. Englisch. Seller Inventory # 9783631621875
Quantity: 2 available
Seller Image
Forecasting Economic Time Series using Locally Stationary Processes
Print on DemandSeller: moluna, Greven, Germany
Seller rating 4 out of 5 stars
Gebunden. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Forecasting Economic Time Series using Locally Stationary ProcessesStationarity has always played an important part in forecasting theory. However, some economic time series show time-varying autocovariances. The question arises whether forecasts can be. Seller Inventory # 117177300
Quantity: Over 20 available
Seller Image
Forecasting Economic Time Series using Locally Stationary Processes
Published by
Peter Lang, Peter Lang Jan 2012, 2012
ISBN 10: 3631621876
ISBN 13: 9783631621875
New
Hardcover
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
Buch. Condition: Neu. Neuware -Stationarity has always played an important part in forecasting theory. However, some economic time series show time-varying autocovariances. The question arises whether forecasts can be improved using models that capture such a time-varying second-order structure. One possibility is given by autoregressive models with time-varying parameters. The author focuses on the development of a forecasting procedure for these processes and compares this approach to classical forecasting methods by means of Monte Carlo simulations. An evaluation of the proposed procedure is given by its application to futures prices and the Dow Jones index. The approach turns out to be superior to the classical methods if the sample sizes are large and the forecasting horizons do not range too far into the future. 140 pp. Englisch. Seller Inventory # 9783631621875
Quantity: 2 available
Seller Image
Forecasting Economic Time Series using Locally Stationary Processes : A New Approach with Applications
Seller: AHA-BUCH GmbH, Einbeck, Germany
Seller rating 5 out of 5 stars
Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Stationarity has always played an important part in forecasting theory. However, some economic time series show time-varying autocovariances. The question arises whether forecasts can be improved using models that capture such a time-varying second-order structure. One possibility is given by autoregressive models with time-varying parameters. The author focuses on the development of a forecasting procedure for these processes and compares this approach to classical forecasting methods by means of Monte Carlo simulations. An evaluation of the proposed procedure is given by its application to futures prices and the Dow Jones index. The approach turns out to be superior to the classical methods if the sample sizes are large and the forecasting horizons do not range too far into the future. Seller Inventory # 9783631621875
Quantity: 1 available
Seller Image
Forecasting Economic Time Series using Locally Stationary Processes | A New Approach with Applications
Print on DemandSeller: preigu, Osnabrück, Germany
Seller rating 5 out of 5 stars
Buch. Condition: Neu. Forecasting Economic Time Series using Locally Stationary Processes | A New Approach with Applications | Tina Loll | Buch | Englisch | 2012 | Peter Lang | EAN 9783631621875 | Verantwortliche Person für die EU: Lang, Peter GmbH, Gontardstr. 11, 10178 Berlin, r[dot]boehm-korff[at]peterlang[dot]com | Anbieter: preigu Print on Demand. Seller Inventory # 106625593
Quantity: 5 available
Stock Image
Forecasting Economic Time Series using Locally Stationary Processes: A New Approach with Applications (Volkswirtschaftliche Analysen)
Published by
Peter Lang GmbH, Internationaler Verlag der Wissen, 2012
ISBN 10: 3631621876
ISBN 13: 9783631621875
Used
Hardcover
Seller: Mispah books, Redhill, SURRE, United Kingdom
Seller rating 4 out of 5 stars
Hardcover. Condition: Very Good. Very Good. book. Seller Inventory # ERICA82936316218766
Quantity: 1 available