Forecasting and Foresight in Business and Economics in the Turbulent and Uncertain New Normal

A special issue of Forecasting (ISSN 2571-9394). This special issue belongs to the section "Forecasting in Economics and Management".

Deadline for manuscript submissions: 31 December 2024 | Viewed by 1103

Special Issue Editors


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Guest Editor
Business Information Systems & Analytics, Durham University, Durham DH1 3LE, UK
Interests: forecasting; business analytics; information systems; operations; economics

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Guest Editor
Institute of Hazard, Risk and Resilience Forecasting Lab, University of Notre Dame, London SW1Y 4HG, UK
Interests: social investments; labour markets; judgmental forecasting

Special Issue Information

Dear Colleagues,

We live in the aftermath of a very turbulent period—the COVID-19 pandemic—and during severe geopolitical tensions, which create a very uncertain environment. As such, we are in need of accurate and robust forecasting models for near-, short-, and mid-term periods as well as foresight models for the longer term. This is true for both business applications as well as applications in finance and economics. Valuable research can range from technical results and contributions on models and methods up to methodological contributions and case studies of the successful application of such models during and after the pandemic.

The Special Issue aims to gather a series of state-of-the-art contributions on forecasting and foresight in business and economics under turbulent and uncertain conditions; given the overall aim of the journal (to advance forecasting studies), this is an extremely relevant and timely Special Issue.

  • Forecasting studies in business in uncertain and turbulent environments;
  • Foresight studies in business in uncertain and turbulent environments;
  • Forecasting studies in finance in uncertain and turbulent environments;
  • Forecasting studies in economics in uncertain and turbulent environments;
  • Foresight studies in economics in uncertain and turbulent environments;
  • Forecasting methodological contributions;
  • Empirical studies;
  • Forecasting studies in regional contexts – especially in BRICS, The Gulf, and South East Asia;
  • Comparative international studies of performance of forecasting models.

Prof. Dr. Konstantinos Nikolopoulos
Dr. Vasileios Bougioukos
Guest Editors

Manuscript Submission Information

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Keywords

  • forecasting
  • foresight
  • business
  • economics
  • turbulence
  • disruptions
  • uncertainty

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Published Papers (1 paper)

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Review

35 pages, 1703 KiB  
Review
Cryptocurrency Price Prediction Algorithms: A Survey and Future Directions
by David L. John, Sebastian Binnewies and Bela Stantic
Forecasting 2024, 6(3), 637-671; https://doi.org/10.3390/forecast6030034 - 15 Aug 2024
Viewed by 745
Abstract
In recent years, cryptocurrencies have received substantial attention from investors, researchers and the media due to their volatile behaviour and potential for high returns. This interest has led to an expanding body of research aimed at predicting cryptocurrency prices, which are notably influenced [...] Read more.
In recent years, cryptocurrencies have received substantial attention from investors, researchers and the media due to their volatile behaviour and potential for high returns. This interest has led to an expanding body of research aimed at predicting cryptocurrency prices, which are notably influenced by a wide array of technical, sentimental, and legal factors. This paper reviews scholarly content from 2014 to 2024, employing a systematic approach to explore advanced quantitative methods for cryptocurrency price prediction. It encompasses a broad spectrum of predictive models, from early statistical analyses to sophisticated machine and deep learning algorithms. Notably, this review identifies and discusses the integration of emerging technologies such as Transformers and hybrid deep learning models, which offer new avenues for enhancing prediction accuracy and practical applicability in real-world scenarios. By thoroughly investigating various methodologies and parameters influencing cryptocurrency price predictions, including market sentiment, technical indicators, and blockchain features, this review highlights the field’s complexity and rapid evolution. The analysis identifies significant research gaps and under-explored areas, providing a foundational guideline for future studies. These guidelines aim to connect theoretical advancements with practical, profit-driven applications in cryptocurrency trading, ensuring that future research is both innovative and applicable. Full article
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