Abstract: I describe distinguishing features of financial data and discuss tailoring machine learning and AI models for financial applications. I then focus on the specific example based on "Asset Pricing with Panel Trees under Global Split Criteria." In this study, we introduce a class of interpretable tree-based models (P-Trees) for analyzing panel data, with iterative and global (instead of recursive and local) splitting criteria to avoid overfitting and improve model performance. We apply P-Tree to generate a stochastic discount factor model and test assets for cross-sectional asset pricing. Unlike other tree algorithms, P-Trees accommodate imbalanced panels of asset returns and grow under the no-arbitrage condition. P-Trees also graphically capture nonlinearity and interaction effects and accommodate regime-switching and interactions between macroeconomic states and firm characteristics. For example, P-Tree identifies inflation as the most important macro predictor with regime-switching in U.S. equity data. Based on multiple pricing, prediction, and investment metrics, we find that (boosted or time-series) P-Trees outperform standard factor models and PCA latent factor models. An equal-weighted portfolio for five factors generated by P-Trees delivers an excess alpha of 1.09% against the Fama-French 3-factor benchmark, producing an annualized Sharpe ratio of 1.98 out of sample. Data-driven cutpoints in P-Trees reveal that long-run reversal, volume volatility, and industry-adjusted market equity drive cross-sectional return variations, consistent with variable importance analysis using random forests.

Please find the related papers provided below. The primary one is

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3949463

and two supplementary ones are

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3554486

and

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3646170

Bio: Lin William Cong is the Rudd Family Professor of Management and Associate Professor of Finance at the Johnson Graduate School of Management at Cornell University SC Johnson College of Business. He is also the founding faculty director for the FinTech Initiative at Cornell. Prior to joining Cornell, he was an assistant professor of Finance and Ph.D. advisor at the University of Chicago Booth School of Business and faculty member at the Center for East Asian Studies. He is a Kauffman Junior Faculty Fellow, a Poets & Quants World Best Business School Professor, a former doctoral fellow at the Stanford Institute for Innovation in Developing Economies, and a former George Shultz Scholar at the Stanford Institute for Economic Policy Research. Cong serves as associate editor for Management Science, Journal of Financial Intermediation, Journal of Corporate Finance, and the Journal of Banking and Finance, has advised FinTech organizations such as Wall Street Blockchain Alliance and ChainLink, was consulted for regulators' lawsuits against KIN/Kik and Telegram's TON regarding their ICOs, as well as for the incubation of Dfinity and its initial research. Cong is a member of multiple professional organizations such as the American Economic Association, European Finance Association, and the Econometric Society.

Cong researches on financial economics, information economics, FinTech and Economic Data Science, Entrepreneurship, and China. His academic interests include financial innovation, mechanism and information design, blockchains, cryptocurrencies, digital economy, real options, financial policy and markets in China, machine learning, AI, and alternative data. His recent work has focused on the intersection of technology, data science, and finance. His research has been featured in top academic journals and media such as Bloomberg, CNN, VOX, and Washington Post, and has been recognized with a number of accolades such as the AAM-CAMRI-CFA Institute Prize in Asset Management, Asseth--Kaiko Prize for Research in Cryptoeconomics, the CME Best paper Award, Crypto and Blockchain Economics Research Conference Best Paper Prize, Shmuel Kandel Award in Financial Economics, and Finance Theory Group Paper Award. He has also been invited to speak and teach at hundreds of world-renowned universities, venture funds, technology firms, investment and trading shops, and government agencies such as IMF, Asset Management Association of China, Ant Financial, SEC, and federal reserve banks.

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