Learning to Detect Symbolic Failure: Machine Learning and the Limits of Black-Scholes
- DOI
- 10.48550/arxiv.2609.27764
- Published
- 2026
- Container
- Not recorded
- Publisher
- arXiv
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.48550/arxiv.2609.27764,
title = {Learning to Detect Symbolic Failure: Machine Learning and the Limits of Black-Scholes},
author = {Huang, Juli and Cheng, Jake and Lu, Rupert},
year = {2026},
doi = {10.48550/arxiv.2609.27764},
url = {https://doi.org/10.48550/arxiv.2609.27764}
}RIS
TY - JOUR TI - Learning to Detect Symbolic Failure: Machine Learning and the Limits of Black-Scholes AU - Huang, Juli AU - Cheng, Jake AU - Lu, Rupert PY - 2026 DO - 10.48550/arxiv.2609.27764 UR - https://doi.org/10.48550/arxiv.2609.27764 ER -
APA
Juli, H., Jake, C., & Rupert, L. (2026). Learning to Detect Symbolic Failure: Machine Learning and the Limits of Black-Scholes. https://doi.org/10.48550/arxiv.2609.27764
Source records
- datacite · retrieved 2026-09-26T00:17:52.786Z