Time-Series Forecasting

From the author of the bestselling "Analysis of Time Series, Fifth Edition," this important book provides a comprehensive, up-to-date review of forecasting methods, ranging from ad-hoc to multivariate methods. The more important methods are compared in terms of their theoretical inter-relationships and their practical merits including empirical accuracy. The book also considers two other general forecasting topics that have been rather neglected hitherto: the computation of prediction intervals and the effect of model uncertainty on forecast accuracy.

From the author of the bestselling "Analysis of Time Series," Time-Series Forecasting offers a comprehensive, up-to-date review of forecasting methods. It provides a summary of time-series modelling procedures, followed by a brief catalogue of many different time-series forecasting methods, ranging from ad-hoc methods through ARIMA and state-space modelling to multivariate methods and including recent arrivals, such as GARCH models, neural networks, and cointegrated models. The author compares the more important methods in terms of their theoretical inter-relationships and their practical merits. He also considers two other general forecasting topics that have been somewhat neglected in the literature: the computation of prediction intervals and the effect of model uncertainty on forecast accuracy.Although the search for a "best" method continues, it is now well established that no single method will outperform all other methods in all situations-the context is crucial. Time-Series Forecasting provides an outstanding reference source for the more generally applicable methods particularly useful to researchers and practitioners in forecasting in the areas of economics, government, industry, and commerce.

INTRODUCTIONTypes of Forecasting MethodsSome Preliminary QuestionsThe Dangers of ExtrapolationAre Forecasts Genuinely Out-of-Sample?Brief Overview of Relevant LiteratureBASICS OF TIME-SERIES ANALYSISDifferent Types of Time SeriesObjectives of Time-Series AnalysisSimple Descriptive TechniquesStationary Stochastic ProcessesSome Classes of Univariate Time-Series ModelsThe CorrelogramUNIVARIATE TIME-SEIES MODELLINGARIMA Models and Related TopicsState Space ModelsGrowth Curve ModelsNonlinear ModelsTime-Series Model BuildingUNIVARIATE FORECASTING METHODSThe Prediction ProblemModel-Based ForecastingAd Hoc Forecasting MethodsSome Interrelationships and CombinationsMULTIVARIATE FORECASTING METHODSIntroductionSingle-Equation ModelsVector AR and ARMA ModelsCointegrationEconometric modelsOther ApproachesSome Relationships Between ModelsA COMPARATIVE ASSESSMENT OF FORECASTING METHODSIntroductionCriteria for Choosing a Forecasting MethodMeasuring Forecast AccuracyForecasting Competitions and Case StudiesChoosing an Appropriate Forecasting MethodSummaryCALCULATING INTERVAL FORECASTSIntroductionNotationThe Need for Different ApproachesExpected Mean Square Prediction ErrorProcedures for Calculating P.I.sA Comparative AssessmentWhy are P.I.s too Narrow?An ExampleSummary and RecommendationsMODEL UNCERTAINTY AND FORECAST ACCURACYIntroduction to Model UncertaintyModel Building and Data DredgingExamplesInference after Model Selection: Some FindingsCoping with Model UncertaintySummary and DiscussionREFERENCES