Time series models for business and economic forecasting - Franses, Philip Hans, 1963-; Dijk, H. A. L. van; Opschoor, Anne (New York : Cambridge University Press, 2014)
"With a new author team contributing decades of practical experience, this fully updated and thoroughly classroom-tested second edition textbook prepares students and practitioners to create effective forecasting models and master the techniques of time series analysis. Taking a practical and example-driven approach, this textbook summarises the most critical decisions, techniques and steps involved in creating forecasting models for business and economics. Students are led through the process with an entirely new set of carefully developed theoretical and practical exercises. Chapters examine the key features of economic time series, univariate time series analysis, trends, seasonality, aberrant observations, conditional heteroskedasticity and ARCH models, non-linearity and multivariate time series, making this a complete practical guide. A companion website with downloadable datasets, exercises and lecture slides rounds out the full learning package"--
"The econometric analysis of economic and business time series is a major field of research and application. The last few decades have witnessed an increasing interest in both theoretical and empirical developments in constructing time series models and in their important application in forecasting. This book aims at reviewing several important developments within the context of forecasting business and economic time series"--
Machine generated contents note: Preface; 1. Introduction and overview; 2. Key features of economic time series; 3. Useful concepts in univariate time series analysis; 4. Trends; 5. Seasonality; 6. Aberrant observations; 7. Conditional heteroskedasticity; 8. Non-linearity; 9. Multivariate time series; Index.
economic&political bookfair2015
Includes bibliographical references and index.
Keywords: Time-series analysis; Social sciences -- Statistical methods; Business forecasting; Economic forecasting; BUSINESS & ECONOMICS / Econometrics