Mizzou Joint Reading Group on ML in Financial Economics
(Computers deliver the best browsing experience for this page. This sheet is updated on Feb., 18, 2021.)

The joint reading group on machine learning in financial economics focuses on discussions of leading academic research that bridges the cutting edge techniques of machine learning and financial economics.

The joint reading group welcomes Ph.D. researchers (and faculties) who have strong research interests in applying ML methods to and tailoring ML methods for the research in financial economics.

All members of the joint reading group are REQUIRED to present IN TURNS and discuss top journal (*) quality working papers and recent top journal (*) publications on topics of applying ML techniques to the fields of

1. Asset return predictability,
2. Cross-sectional return explanation,
3. Analysts, institutional investors and their performance,
4. Corporate finance and governance,
5. Macroeconomics/macro-finance/household finance,
6. FinTech and cryptocurrencies, and
7. Broader economic applications of ML methods.

You can find example papers on a recent conference held by University of Miami:

We hope to start the weekly meetings as soon as possible. We tentatively set the meeting time in the Friday afternoon for every week. We may adjust the meeting frequencies as needed. Ideally, we will have 1-2 paper(s) every week just to keep the workload manageable. We expect that each meeting will last for less than 1.5 hours.

We also encourage the formation of research teams on the projects related to machine learning and financial economics targeting at the top journals (*). Hopefully, some members of the reading group can end up with some working papers together.

You can proceed to the sign-up from following the "next" button below. Admitted members will be included in the email list for weekly meetings.
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