Entropy Application for Forecasting

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Tác giả: Ana Jesus Lopez-Menendez, Rigoberto Pérez-Suárez

Ngôn ngữ: eng

ISBN-13: 978-3039364879

Ký hiệu phân loại:

Thông tin xuất bản: Basel, Switzerland : MDPI - Multidisciplinary Digital Publishing Institute, 2020

Mô tả vật lý: 1 electronic resource (200 p.)

Bộ sưu tập: Tài liệu truy cập mở

ID: 225229

This book shows the potential of entropy and information theory in forecasting, including both theoretical developments and empirical applications. The contents cover a great diversity of topics, such as the aggregation and combination of individual forecasts, the comparison of forecasting performance, and the debate concerning the tradeoff between complexity and accuracy. Analyses of forecasting uncertainty, robustness, and inconsistency are also included, as are proposals for new forecasting approaches. The proposed methods encompass a variety of time series techniques (e.g., ARIMA, VAR, state space models) as well as econometric methods and machine learning algorithms. The empirical contents include both simulated experiments and real-world applications focusing on GDP, M4-Competition series, confidence and industrial trend surveys, and stock exchange composite indices, among others. In summary, this collection provides an engaging insight into entropy applications for forecasting, offering an interesting overview of the current situation and suggesting possibilities for further research in this field.
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