Dear Colleagues,
This Special Issue of Data Science in Science invites both original and survey manuscripts that bring together novel data science, machine learning, and AI methodology and applications in modern finance. We evaluate submissions on the basis of scientific rigor, technical depth, and ethical standards, regardless of perceived novelty. We also value high-quality papers with interesting and relevant research hypotheses and/or new datasets from previously untapped data sources (digital economy, blockchain ledgers, etc). We welcome original, unpublished, and innovative submissions including, but not limited to the following areas of research:
- Advances in financial time series, including derivative pricing, risk management, portfolio optimization, algorithmic trading, game theory, and insurance.
- Novel and emerging financial markets, e.g., climate/ESG investment, cryptocurrency, NFTs, etc.
- Applications of deep learning, AI, natural language processing, and generative models in finance and financial economics.
- Data mining and knowledge discovery for FinTech, e-commerce, electronic auctions, etc.
- Risk, volatility, and uncertainty quantification for time series analysis and/or forecasting.
- Graphs, networks, and interconnectedness of financial institutions.
- Measures of systemic risk for understanding and predicting financial crises.
- Mathematical foundations for financial data science, including advances in optimization and Bayesian methodology.
- Real-time measurement of key financial and macroeconomic indicators through public sources, e.g., social media, blockchain.
- Causal inference and observational studies in capital markets.
- Novel applications of methodology stemming from financial literature to other domains, including but not limited to economics, healthcare, and social sciences.
Sincerely yours,
Mila Getmansky Sherman (UMass), Ruey S. Tsay (UChicago), Rong Chen (Rutgers), Markus Pelger (Stanford), Sumanta Basu (Cornell), Daniel R. Kowal (Rice), Rebecca Killick (Lancaster), Shawn Mankad (Cornell), Ines Wilms (Maastricht), Abolfazl Safikhani (UFlorida), Linden McBride (US Census), David S. Matteson (Cornell)
