Forecasting Economic Time Series using Locally Stationary Processes

Language: English

Published by Peter Lang Jan 2012, 2012

3631621876 / 9783631621875

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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

Title
Forecasting Economic Time Series using Locally Stationary Processes
Author
Tina Loll
Publisher
Peter Lang Jan 2012
Publication year
2012
Condition
Neu
Binding
Buch
Language
English
ISBN 10
3631621876
ISBN 13
9783631621875
Item weight
303 grams
Dimensions
216x153x11 mm

BuchWeltWeit Ludwig Meier e.K.

Bergisch Gladbach, Germany

5-star seller

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