Time Series and Forecasting with Applications in Economics, Finance and Beyond

Dear Colleagues, 

Forecasting has long been at the heart of empirical and theoretical research in economics and finance. From early applications to the more recent surge in high-dimensional, nonlinear and both machine learning- and AI-based approaches, the field has witnessed tremendous progress over the past decades. Despite this progress, important challenges remain. For instance, different evaluation metrics may lead to conflicting conclusions about the same forecast, raising questions about what “predictability” truly means in practice. As a matter of fact, recent research has shown that forecasts may contain valuable information even when traditional accuracy measures suggest otherwise, illustrating the need for a broader perspective on how to evaluate predictive ability.

In addition, social, economic and financial time series often display structural breaks, volatility clustering and complex dependence structures across variables and markets. These features call for new tools to assess predictability and dependence; they also call for methodological innovations that can provide a deeper understanding of forecasting performance. 

This Special Issue aims to bring together contributions that push the frontier of forecasting and time-series econometrics with applications not only in economics and finance but also in related fields where prediction plays a central role. We welcome both theoretical and empirical papers, including, but not limited to, the following topics: 

• New ideas to clarify and understand the relationships between different forecasting metrics.
• Novel metrics to evaluate predictability.
• Advances in forecast combinations, time-varying parameter models and efficiency adjustments.
• Applications of machine learning, Bayesian methods and high-dimensional econometrics.
• Aplications of AI to forecasting.
• General improvements in time-series econometrics that provide useful insights for scholars, practitioners and policymakers. 

We particularly encourage contributions that challenge the conventional wisdom in forecast evaluation and propose novel perspectives. All submissions will be peer-reviewed and accepted articles will be published open access.

Dr. Pablo Pincheira
Guest Editor

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 submissions that pass pre-check are 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. Mathematics is an international peer-reviewed open access semimonthly 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 2600 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.