Forecasting Economic Time Series using Locally Stationary Processes : A New Approach with Applications
New
by
Tina Loll
Book Details
Format
Hardback or Cased Book
Book Series
Volkswirtschaftliche Analysen
ISBN-10
3631621876
ISBN-13
9783631621875
Edition
New
Publisher
Peter Lang AG
Imprint
Peter Lang AG
Country of Manufacture
DE
Country of Publication
GB
Publication Date
Jan 19th, 2012
Print length
138 Pages
Weight
282 grams
Dimensions
15.30 x 21.50 x 1.20 cms
Product Classification:
Data analysis: generalEconomic theory & philosophyBusiness mathematics & systems
Ksh 5,900.00
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Forecasting Economic Time Series using Locally Stationary Processes
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.
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