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

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

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