Call for Papers: Special Issue on ‘AI and machine learning in finance’

There is growing interest in applying artificial intelligence (AI) and machine learning to solve different financial problems, especially considering the significant amount of historical information, structured and unstructured, available for most financial instruments. This task requires a systematic and analytical approach to find financial patterns that could be used for investment and trading decisions. Time series analysis and machine learning algorithms facilitate this process of understanding, modeling, and forecasting the behavior of financial assets.

This special issue brings together papers that have developed new theoretical or applied models employing AI and machine learning in a variety of financial problems. We encourage papers that explore new research perspectives such as the strategic behavior and interpretability of machine learning models, and applications to financial topics including, but not restricted to, forecasting, financial networks, investment, trading, risk management, portfolio optimization, insurance, digital currencies and asset pricing. This special issue will investigate the accuracy, computational efficiency, and risk-adjusted return of various methods that can be employed in the analysis of these problems.

A blind copy of the full paper and a separate title page should be submitted to the special issue editorial board via fsc.stevens.edu/AIF. Please do not submit papers through ScholarOne. All submissions should be in PDF. For papers which are finally accepted for the QF special issue, the normal journal requirements for publication will apply.