Forecasting: theory and practice

TL;DR

This paper provides a comprehensive review of forecasting theories, methods, and applications, highlighting their practical use across various fields and offering insights for future developments in forecasting.

Contribution

It offers an extensive, non-systematic overview of forecasting models, principles, and applications, serving as a reference for both theory and practice in the field.

Findings

Diverse forecasting methods are applied in real-world contexts.

Theoretical concepts are linked to practical applications.

Open-source tools support forecasting practices.

Abstract

Forecasting has always been at the forefront of decision making and planning. The uncertainty that surrounds the future is both exciting and challenging, with individuals and organisations seeking to minimise risks and maximise utilities. The large number of forecasting applications calls for a diverse set of forecasting methods to tackle real-life challenges. This article provides a non-systematic review of the theory and the practice of forecasting. We provide an overview of a wide range of theoretical, state-of-the-art models, methods, principles, and approaches to prepare, produce, organise, and evaluate forecasts. We then demonstrate how such theoretical concepts are applied in a variety of real-life contexts. We do not claim that this review is an exhaustive list of methods and applications. However, we wish that our encyclopedic presentation will offer a point of reference for the rich work that has been undertaken over the last decades, with some key insights for the future of forecasting theory and practice. Given its encyclopedic nature, the intended mode of reading is non-linear. We offer cross-references to allow the readers to navigate through the various topics. We complement the theoretical concepts and applications covered by large lists of free or open-source software implementations and publicly-available databases.