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Time Series Models for Business and Economic Forecasting

Author : Philip Hans Franses

Publisher : Cambridge University Press

Page : 421 pages

File Size : 39,19 MB

Release : 2014-04-24

Category : Business & Economics

ISBN : 1139952129

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Book Description

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. Downloadable datasets are available online.



Applied Economic Forecasting Using Time Series Methods

Author : Eric Ghysels

Publisher : Oxford University Press

Page : 617 pages

File Size : 49,38 MB

Release : 2018

Category : Business & Economics

ISBN : 0190622016

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Book Description

Economic forecasting is a key ingredient of decision making in the public and private sectors. This book provides the necessary tools to solve real-world forecasting problems using time-series methods. It targets undergraduate and graduate students as well as researchers in public and private institutions interested in applied economic forecasting.



Applied Economic Forecasting using Time Series Methods

Author : Eric Ghysels

Publisher : Oxford University Press

Page : 617 pages

File Size : 19,82 MB

Release : 2018-03-23

Category : Business & Economics

ISBN : 0190622032

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Book Description

Economic forecasting is a key ingredient of decision making both in the public and in the private sector. Because economic outcomes are the result of a vast, complex, dynamic and stochastic system, forecasting is very difficult and forecast errors are unavoidable. Because forecast precision and reliability can be enhanced by the use of proper econometric models and methods, this innovative book provides an overview of both theory and applications. Undergraduate and graduate students learning basic and advanced forecasting techniques will be able to build from strong foundations, and researchers in public and private institutions will have access to the most recent tools and insights. Readers will gain from the frequent examples that enhance understanding of how to apply techniques, first by using stylized settings and then by real data applications--focusing on macroeconomic and financial topics. This is first and foremost a book aimed at applying time series methods to solve real-world forecasting problems. Applied Economic Forecasting using Time Series Methods starts with a brief review of basic regression analysis with a focus on specific regression topics relevant for forecasting, such as model specification errors, dynamic models and their predictive properties as well as forecast evaluation and combination. Several chapters cover univariate time series models, vector autoregressive models, cointegration and error correction models, and Bayesian methods for estimating vector autoregressive models. A collection of special topics chapters study Threshold and Smooth Transition Autoregressive (TAR and STAR) models, Markov switching regime models, state space models and the Kalman filter, mixed frequency data models, nowcasting, forecasting using large datasets and, finally, volatility models. There are plenty of practical applications in the book and both EViews and R code are available online at authors' website.



Forecasting: principles and practice

Author : Rob J Hyndman

Publisher : OTexts

Page : 380 pages

File Size : 23,92 MB

Release : 2018-05-08

Category : Business & Economics

ISBN : 0987507117

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Book Description

Forecasting is required in many situations. Stocking an inventory may require forecasts of demand months in advance. Telecommunication routing requires traffic forecasts a few minutes ahead. Whatever the circumstances or time horizons involved, forecasting is an important aid in effective and efficient planning. This textbook provides a comprehensive introduction to forecasting methods and presents enough information about each method for readers to use them sensibly.



Long-Run Growth Forecasting

Author : Stefan Bergheim

Publisher : Springer Science & Business Media

Page : 194 pages

File Size : 33,87 MB

Release : 2008-03-29

Category : Business & Economics

ISBN : 354077680X

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Book Description

This book explores how to set up an empirical model that helps with forecasting long-term economic growth. GDP forecasts for the years 2006 to 2020 for 40 countries are derived in a transparent way. Offering a systematic approach to models of potential GDP that can also be used for forecasts of more than a decade it fills the wide gap between the high demand for such models by banks, international organizations, and governments on the one hand and the limited supply on the other hand. Frequent forecast failures in the past (e.g. Japan 1990, Asia 1997) and the heavy economic losses they produced motivated the work. The book assesses the large number of theories of economic growth, the drivers of economic growth, the available datasets and the empirical methods on offer. A preference is shown for evolutionary models and an augmented Kaldor model. The book uses non-stationary panel techniques to find pair-wise cointegration among GDP per capita and its main correlates.



Business Forecasting

Author : Michael Gilliland

Publisher : John Wiley & Sons

Page : 435 pages

File Size : 25,61 MB

Release : 2021-05-11

Category : Business & Economics

ISBN : 1119782473

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Book Description

Discover the role of machine learning and artificial intelligence in business forecasting from some of the brightest minds in the field In Business Forecasting: The Emerging Role of Artificial Intelligence and Machine Learning accomplished authors Michael Gilliland, Len Tashman, and Udo Sglavo deliver relevant and timely insights from some of the most important and influential authors in the field of forecasting. You'll learn about the role played by machine learning and AI in the forecasting process and discover brand-new research, case studies, and thoughtful discussions covering an array of practical topics. The book offers multiple perspectives on issues like monitoring forecast performance, forecasting process, communication and accountability for forecasts, and the use of big data in forecasting. You will find: Discussions on deep learning in forecasting, including current trends and challenges Explorations of neural network-based forecasting strategies A treatment of the future of artificial intelligence in business forecasting Analyses of forecasting methods, including modeling, selection, and monitoring In addition to the Foreword by renowned researchers Spyros Makridakis and Fotios Petropoulos, the book also includes 16 "opinion/editorial" Afterwords by a diverse range of top academics, consultants, vendors, and industry practitioners, each providing their own unique vision of the issues, current state, and future direction of business forecasting. Perfect for financial controllers, chief financial officers, business analysts, forecast analysts, and demand planners, Business Forecasting will also earn a place in the libraries of other executives and managers who seek a one-stop resource to help them critically assess and improve their own organization's forecasting efforts.



Advanced Time Series Data Analysis

Author : I. Gusti Ngurah Agung

Publisher : John Wiley & Sons

Page : 538 pages

File Size : 37,5 MB

Release : 2019-03-18

Category : Mathematics

ISBN : 1119504716

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Book Description

Introduces the latest developments in forecasting in advanced quantitative data analysis This book presents advanced univariate multiple regressions, which can directly be used to forecast their dependent variables, evaluate their in-sample forecast values, and compute forecast values beyond the sample period. Various alternative multiple regressions models are presented based on a single time series, bivariate, and triple time-series, which are developed by taking into account specific growth patterns of each dependent variables, starting with the simplest model up to the most advanced model. Graphs of the observed scores and the forecast evaluation of each of the models are offered to show the worst and the best forecast models among each set of the models of a specific independent variable. Advanced Time Series Data Analysis: Forecasting Using EViews provides readers with a number of modern, advanced forecast models not featured in any other book. They include various interaction models, models with alternative trends (including the models with heterogeneous trends), and complete heterogeneous models for monthly time series, quarterly time series, and annually time series. Each of the models can be applied by all quantitative researchers. Presents models that are all classroom tested Contains real-life data samples Contains over 350 equation specifications of various time series models Contains over 200 illustrative examples with special notes and comments Applicable for time series data of all quantitative studies Advanced Time Series Data Analysis: Forecasting Using EViews will appeal to researchers and practitioners in forecasting models, as well as those studying quantitative data analysis. It is suitable for those wishing to obtain a better knowledge and understanding on forecasting, specifically the uncertainty of forecast values.



Introductory Time Series with R

Author : Paul S.P. Cowpertwait

Publisher : Springer Science & Business Media

Page : 262 pages

File Size : 24,97 MB

Release : 2009-05-28

Category : Mathematics

ISBN : 0387886982

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Book Description

This book gives you a step-by-step introduction to analysing time series using the open source software R. Each time series model is motivated with practical applications, and is defined in mathematical notation. Once the model has been introduced it is used to generate synthetic data, using R code, and these generated data are then used to estimate its parameters. This sequence enhances understanding of both the time series model and the R function used to fit the model to data. Finally, the model is used to analyse observed data taken from a practical application. By using R, the whole procedure can be reproduced by the reader. All the data sets used in the book are available on the website http://staff.elena.aut.ac.nz/Paul-Cowpertwait/ts/. The book is written for undergraduate students of mathematics, economics, business and finance, geography, engineering and related disciplines, and postgraduate students who may need to analyse time series as part of their taught programme or their research.



Applied Econometrics with R

Author : Christian Kleiber

Publisher : Springer Science & Business Media

Page : 229 pages

File Size : 43,11 MB

Release : 2008-12-10

Category : Business & Economics

ISBN : 0387773185

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Book Description

R is a language and environment for data analysis and graphics. It may be considered an implementation of S, an award-winning language initially - veloped at Bell Laboratories since the late 1970s. The R project was initiated by Robert Gentleman and Ross Ihaka at the University of Auckland, New Zealand, in the early 1990s, and has been developed by an international team since mid-1997. Historically, econometricians have favored other computing environments, some of which have fallen by the wayside, and also a variety of packages with canned routines. We believe that R has great potential in econometrics, both for research and for teaching. There are at least three reasons for this: (1) R is mostly platform independent and runs on Microsoft Windows, the Mac family of operating systems, and various ?avors of Unix/Linux, and also on some more exotic platforms. (2) R is free software that can be downloaded and installed at no cost from a family of mirror sites around the globe, the Comprehensive R Archive Network (CRAN); hence students can easily install it on their own machines. (3) R is open-source software, so that the full source code is available and can be inspected to understand what it really does, learn from it, and modify and extend it. We also like to think that platform independence and the open-source philosophy make R an ideal environment for reproducible econometric research.



The Art of Forecasting Economic Growth

Author : Barrett Williams

Publisher : Barrett Williams

Page : 163 pages

File Size : 35,49 MB

Release : 2024-08-24

Category : Business & Economics

ISBN :

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Book Description

Unlock the Power of Predicting Tomorrow with "The Art of Forecasting Economic Growth"! Are you ready to delve into the intricate world of economic forecasting? Discover the strategies, methods, and tools that shape the way experts predict future economic trends. "The Art of Forecasting Economic Growth" is your comprehensive guide to mastering economic predictions and leveraging them for smarter decision-making. Start your journey with an essential introduction to economic forecasting, exploring its significance, history, and the key players that have set the stage. As you progress, get acquainted with the fundamentals of data analysis in economics – uncover the types of data, collection methods, and basic concepts in economic modeling. Dive deeper into statistical techniques with chapters dedicated to descriptive and inferential statistics, and regression analysis. Grasp the intricacies of time series analysis and learn how to utilize economic indicators for accurate predictions. Build your full understanding of constructing and validating predictive economic models. Venture into advanced econometric techniques and discover the cutting-edge role of machine learning in economic forecasting. Understand the impact of big data, and the nuanced field of behavioral economics, to enhance your forecasting accuracy even further. Explore the significance of economic policy analysis, scenario planning, and stress testing. Enhance your insight on forecasting financial markets and evaluate the accuracy of your predictions with clear, actionable metrics. Learn the best practices for communicating your forecasts, ensuring clarity and impact. Ethics play a critical role in economic forecasting. This eBook provides a mindful exploration of ethical considerations, dilemmas, and solutions, backed by real-world case studies. Utilize forecasts to shape business strategies and align them with market realities. As you reach the final chapters, look ahead to the future of economic forecasting, exploring emerging trends, the transformative influence of AI, and the dynamics of a globalized economy. "The Art of Forecasting Economic Growth" is a must-have for anyone seeking to understand and apply economic forecasting techniques. Equip yourself with the knowledge to predict, plan, and prosper in an ever-changing economic landscape. Your journey into the future of economics starts here!