Modern Challenges and Innovations in Financial Econometrics

Dear Colleagues,

Financial econometrics lies at the crossroads of statistics, economics, and finance, providing an essential tool for understanding increasingly complex and data-rich markets. The growing availability of high-frequency and alternative data, combined with advances in computation and artificial intelligence, has transformed this field—while simultaneously introducing new challenges. This Topic aims to explore recent methodological and empirical developments that address issues such as model instability, nonstationarity, high dimensionality, and structural breaks. We invite the submission of contributions that propose innovative econometric frameworks; integrate machine learning techniques; and enhance forecasting, risk modeling, and decision-making in financial contexts. Both theoretical papers and applied studies that demonstrate the practical relevance of new methods are welcome. By fostering dialog between researchers and practitioners, this Topic seeks to advance robust, scalable, and interpretable approaches that can meet the demands of modern financial analysis.

Dr. Agnieszka Szmelter-Jarosz
Dr. Hamed Nozari
Topic Editors