Special Issue "New Challenges in Energy and Finance Forecasting in the Era of Big Data"

A special issue of Forecasting (ISSN 2571-9394).

Deadline for manuscript submissions: 31 December 2021.

Special Issue Editors

Dr. Luigi Grossi
E-Mail Website
Guest Editor
Department of Statistical Sciences, University of Padova, Via Cesare Battisti, 241, 35121 Padova, Italy
Interests: electricity markets; electricity demand; price forecasting; CO2 emissions; time series analysis; robust forecasting; energy efficiency; energy storage
Dr. Mariangela Guidolin
E-Mail Website
Guest Editor
Department of Statistical Sciences, University of Padova, Via Cesare Battisti, 241, 35121 Padova, Italy
Interests: energy transition modelling; decarbonization; innovation diffusion models; competition and cooperation dynamics; nonlinear modelling

Special Issue Information

Dear Colleagues,

Big data are becoming increasingly available in many areas. Energy and finance are two of the main research fields where the production of a massive amount of data gives rise to many issues and challenges requiring the development of new tools and models. Smart meters’ data, sensor networks, customer payments, credit history, satellite imagery, Internet of Things devices, and high-frequency trading are just a few examples of big data generators creating new research challenges. Private and public energy and finance companies are aiming to take advantage of big data analytics to optimize their performances and improve service delivery. Big data analytics play a crucial role in reducing energy consumption and improving energy efficiency in the energy sector and in supporting investment decisions in the financial industry. Proper treatment of data flows generated almost in real time and reliable short- and medium-term predictions give strong support to decision makers operating on energy and financial markets. This Special Issue aims at collecting original contributions containing new theoretical and/or empirical results in the context of energy and finance forecasting using big data. Mathematical, statistical, and econometric models are common tools adopted in forecasting procedures; however, effective alternative approaches are also welcome.

Dr. Luigi Grossi
Dr. Mariangela Guidolin
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Forecasting is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • energy forecasting
  • energy prices
  • energy demand
  • big data
  • energy storage
  • greenhouse gasses
  • CO2 emissions
  • financial price
  • high-frequency data
  • financial econometrics

Published Papers

This special issue is now open for submission.
Back to TopTop