Forecast Evaluation Methods
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Forecast Evaluation Methods
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Author : Frank Undorf
language : en
Publisher:
Release Date : 2018-09-11
Forecast Evaluation Methods written by Frank Undorf and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-11 with categories.
Seminar paper from the year 2016 in the subject Economics - Statistics and Methods, grade: 1,0, University of Cologne (Institut für Ökonometrie und Statistik), course: Seminar "Statistics and Econometrics," language: English, abstract: This seminar paper aims to briefly introduce selected modelfree methods which can be used both to evaluate specific forecast series and to compare pairwise competing series of forecasts. Problems arising from parameter estimation uncertainty and nested forecast generating models are illuminated curtly. The model-free methods will be applied to three series of annual german economic forecasts from 1970 - 2015 provided by the joint forecast and the Council of Economic Advisors. It turns out that the forecast accuracy matches the chronology of the forecasts within the annual forecast semester. Moreover, a simple Monte Carlo study aims to illustrate graphically empirical size and empirical power of the tests for pairwise comparison depending on certain properties of the underlying forecast error sequences.
Forecast Evaluation Methods A Monte Carlo Investigation And An Application To The Predictability Of Interest Rates
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Author : Frank Undorf
language : en
Publisher: GRIN Verlag
Release Date : 2018-09-07
Forecast Evaluation Methods A Monte Carlo Investigation And An Application To The Predictability Of Interest Rates written by Frank Undorf and has been published by GRIN Verlag this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-07 with Business & Economics categories.
Master's Thesis from the year 2017 in the subject Economics - Statistics and Methods, grade: 1,0, University of Cologne (Institut für Ökonometrie und Statistik), language: English, abstract: Abstract: This thesis overviews selected forecast evaluation tests and attempts to link the concept of testing equal mean squared error and forecast encompassing within a common simple regression framework. A Monte Carlo analysis provides size and power properties for both a model-free and model-based environment. In particular, the encompassing regression based test assessing the null hypothesis of equal mean squared error offers beneficial size and power properties compared to the Diebold-Mariano test, at least in a conditional homoskedastic small sample framework without autocorrelation. A simple application of several tests is provided by comparing different interest rate prediction models like a time series model, a linear model with macroeconomic indicators and a dynamic yield curve model. It turns out that simple time series specifications are hard to outperform for most of the comparisons. However, indicators like the German stock market index or the ifo expectation indicator provide useful information for future German government bond yields. Contents: 1 Introduction 2 Forecast evaluation methods 2.1 Selected tests in a model-free environment 2.1.1 Forecast encompassing 2.1.2 Equal mean squared error 2.2 Selected tests in a model-based environment 2.2.1 Exemplary forecasting framework 2.2.2 Non-nested model structure 2.2.3 Nested model structure 2.2.4 Inference à la Giacomini and White (2006) 3 Monte Carlo evidence 3.1 Model-free framework 3.1.1 Size properties 3.1.2 Power properties 3.2 Model-based framework 3.2.1 Non-nested models 3.2.1.1 Size investigation 3.2.1.2 Power investigation 3.2.2 Nested models 3.2.2.1 Size investigation 3.2.2.2 Power investigation 4 Application: Predicting interest rates 4.1 Competing prediction models 4.1.1 Macro-indicator model 4.1.2 Pure time series model 4.1.3 Dynamic Svensson (1994) model 4.2 Results of pairwise comparison 4.3 Out-of-sample Granger causality 5 Conclusion
Statistical Methods For Forecasting
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Author : Bovas Abraham
language : en
Publisher: John Wiley & Sons
Release Date : 2009-09-25
Statistical Methods For Forecasting written by Bovas Abraham and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-09-25 with Mathematics categories.
The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. "This book, it must be said, lives up to the words on its advertising cover: 'Bridging the gap between introductory, descriptive approaches and highly advanced theoretical treatises, it provides a practical, intermediate level discussion of a variety of forecasting tools, and explains how they relate to one another, both in theory and practice.' It does just that!" -Journal of the Royal Statistical Society "A well-written work that deals with statistical methods and models that can be used to produce short-term forecasts, this book has wide-ranging applications. It could be used in the context of a study of regression, forecasting, and time series analysis by PhD students; or to support a concentration in quantitative methods for MBA students; or as a work in applied statistics for advanced undergraduates." -Choice Statistical Methods for Forecasting is a comprehensive, readable treatment of statistical methods and models used to produce short-term forecasts. The interconnections between the forecasting models and methods are thoroughly explained, and the gap between theory and practice is successfully bridged. Special topics are discussed, such as transfer function modeling; Kalman filtering; state space models; Bayesian forecasting; and methods for forecast evaluation, comparison, and control. The book provides time series, autocorrelation, and partial autocorrelation plots, as well as examples and exercises using real data. Statistical Methods for Forecasting serves as an outstanding textbook for advanced undergraduate and graduate courses in statistics, business, engineering, and the social sciences, as well as a working reference for professionals in business, industry, and government.
An Evaluation Of Forecasting Methods And Forecast Combination Methods In Goods Management Systems
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Author : Carsten Schneider
language : en
Publisher:
Release Date : 1999
An Evaluation Of Forecasting Methods And Forecast Combination Methods In Goods Management Systems written by Carsten Schneider and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999 with categories.
Applied Economic Forecasting Using Time Series Methods
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Author : Eric Ghysels
language : en
Publisher: Oxford University Press
Release Date : 2018-03-23
Applied Economic Forecasting Using Time Series Methods written by Eric Ghysels and has been published by Oxford University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-03-23 with Business & Economics categories.
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.
Handbook Of Economic Forecasting
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Author : Graham Elliott
language : en
Publisher: Elsevier
Release Date : 2013-08-23
Handbook Of Economic Forecasting written by Graham Elliott and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-08-23 with Business & Economics categories.
The highly prized ability to make financial plans with some certainty about the future comes from the core fields of economics. In recent years the availability of more data, analytical tools of greater precision, and ex post studies of business decisions have increased demand for information about economic forecasting. Volumes 2A and 2B, which follows Nobel laureate Clive Granger's Volume 1 (2006), concentrate on two major subjects. Volume 2A covers innovations in methodologies, specifically macroforecasting and forecasting financial variables. Volume 2B investigates commercial applications, with sections on forecasters' objectives and methodologies. Experts provide surveys of a large range of literature scattered across applied and theoretical statistics journals as well as econometrics and empirical economics journals. The Handbook of Economic Forecasting Volumes 2A and 2B provide a unique compilation of chapters giving a coherent overview of forecasting theory and applications in one place and with up-to-date accounts of all major conceptual issues. Focuses on innovation in economic forecasting via industry applications Presents coherent summaries of subjects in economic forecasting that stretch from methodologies to applications Makes details about economic forecasting accessible to scholars in fields outside economics
Economic Forecasting
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Author : Graham Elliott
language : en
Publisher: Princeton University Press
Release Date : 2016-04-05
Economic Forecasting written by Graham Elliott and has been published by Princeton University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-04-05 with Business & Economics categories.
A comprehensive and integrated approach to economic forecasting problems Economic forecasting involves choosing simple yet robust models to best approximate highly complex and evolving data-generating processes. This poses unique challenges for researchers in a host of practical forecasting situations, from forecasting budget deficits and assessing financial risk to predicting inflation and stock market returns. Economic Forecasting presents a comprehensive, unified approach to assessing the costs and benefits of different methods currently available to forecasters. This text approaches forecasting problems from the perspective of decision theory and estimation, and demonstrates the profound implications of this approach for how we understand variable selection, estimation, and combination methods for forecasting models, and how we evaluate the resulting forecasts. Both Bayesian and non-Bayesian methods are covered in depth, as are a range of cutting-edge techniques for producing point, interval, and density forecasts. The book features detailed presentations and empirical examples of a range of forecasting methods and shows how to generate forecasts in the presence of large-dimensional sets of predictor variables. The authors pay special attention to how estimation error, model uncertainty, and model instability affect forecasting performance. Presents a comprehensive and integrated approach to assessing the strengths and weaknesses of different forecasting methods Approaches forecasting from a decision theoretic and estimation perspective Covers Bayesian modeling, including methods for generating density forecasts Discusses model selection methods as well as forecast combinations Covers a large range of nonlinear prediction models, including regime switching models, threshold autoregressions, and models with time-varying volatility Features numerous empirical examples Examines the latest advances in forecast evaluation Essential for practitioners and students alike
Business Forecasting
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Author : Michael Gilliland
language : en
Publisher: John Wiley & Sons
Release Date : 2016-01-05
Business Forecasting written by Michael Gilliland and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-01-05 with Business & Economics categories.
A comprehensive collection of the field's most provocative, influential new work Business Forecasting compiles some of the field's important and influential literature into a single, comprehensive reference for forecast modeling and process improvement. It is packed with provocative ideas from forecasting researchers and practitioners, on topics including accuracy metrics, benchmarking, modeling of problem data, and overcoming dysfunctional behaviors. Its coverage includes often-overlooked issues at the forefront of research, such as uncertainty, randomness, and forecastability, as well as emerging areas like data mining for forecasting. The articles present critical analysis of current practices and consideration of new ideas. With a mix of formal, rigorous pieces and brief introductory chapters, the book provides practitioners with a comprehensive examination of the current state of the business forecasting field. Forecasting performance is ultimately limited by the 'forecastability' of the data. Yet failing to recognize this, many organizations continue to squander resources pursuing unachievable levels of accuracy. This book provides a wealth of ideas for improving all aspects of the process, including the avoidance of wasted efforts that fail to improve (or even harm) forecast accuracy. Analyzes the most prominent issues in business forecasting Investigates emerging approaches and new methods of analysis Combines forecasts to improve accuracy Utilizes Forecast Value Added to identify process inefficiency The business environment is evolving, and forecasting methods must evolve alongside it. This compilation delivers an array of new tools and research that can enable more efficient processes and more accurate results. Business Forecasting provides an expert's-eye view of the field's latest developments to help you achieve your desired business outcomes.
Forecasting With Artificial Intelligence
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Author : Mohsen Hamoudia
language : en
Publisher: Springer Nature
Release Date : 2023-10-22
Forecasting With Artificial Intelligence written by Mohsen Hamoudia and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-22 with Business & Economics categories.
This book is a comprehensive guide that explores the intersection of artificial intelligence and forecasting, providing the latest insights and trends in this rapidly evolving field. The book contains fourteen chapters covering a wide range of topics, including the concept of AI, its impact on economic decision-making, traditional and machine learning-based forecasting methods, challenges in demand forecasting, global forecasting models, meta-learning and feature-based forecasting, ensembling, deep learning, scalability in industrial and optimization applications, and forecasting performance evaluation. With key illustrations, state-of-the-art implementations, best practices, and notable advances, this book offers practical insights into the theory and practice of AI-based forecasting. This book is a valuable resource for anyone involved in forecasting, including forecasters, statisticians, data scientists, business analysts, or decision-makers.
The Evaluation Of Forecast Accuracy Of A Non Statistical Method Of Forecasting
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Author : Chee Choong Foong
language : en
Publisher:
Release Date : 1991
The Evaluation Of Forecast Accuracy Of A Non Statistical Method Of Forecasting written by Chee Choong Foong and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1991 with Business forecasting categories.