I’m an Associate Researcher at Humboldt-University of Berlin and Data Editor at the Review of Financial Studies.
I co-created the open-source projects Tidy Finance and EconDataverse to foster reproducible research in finance and economics.
I’m also an independent consultant specializing in reproducible and auditable workflows, operating under the Tidy Intelligence brand.
Research
Peer-Reviewed
Chaderina, M., Muermann, A., & Scheuch, C. (2026). The dark side of liquid bonds in fire sales. Management Science, Forthcoming. doi.org/10.1287/mnsc.2023.03670
Hautsch, N., Scheuch, C., & Voigt, S. (2024). Building trust takes time: Limits to arbitrage for blockchain-based assets. Review of Finance, 28 (4), 1345–1381. doi.org/10.1093/rof/rfae004
Books
Scheuch, C., Voigt, S., Weiss, P., & Frey, C. (2024). Tidy Finance with Python. Chapman and Hall/CRC. doi.org/10.1201/9781032684307
Scheuch, C., Voigt, S., & Weiss, P. (2023). Tidy Finance with R. Chapman and Hall/CRC. doi.org/10.1201/b23237
Working Papers
Coqueret, G., Llull, J., Oswald, F., Pérignon, C., Scheuch, C., & Vilhuber, L. (2026). Randomness in large language models: What researchers need to know (and report). Working Paper. doi.org/10.2139/ssrn.7191580
D’Acunto, F., Rauter, T., Scheuch, C., & Weber, M. (2020). Perceived precautionary savings motives: Evidence from FinTech. NBER Working Paper No. 26817, National Bureau of Economic Research. doi.org/10.3386/w26817
Teaching
Foundations for Reproducible Research at Barcelona School of Economics: An annual summer school on reproducible empirical finance research, with hands-on coding in Python.
Empirical Research in Finance at Humboldt University of Berlin: A regular seminar on applying core financial theory to real-world data using generative AI tools, designed to prepare students for their bachelor thesis.
Reproducible Research Workflows at Vienna Graduate School of Finance: An annual workshop on reproducibility techniques and efficient collaboration for empirical research.