Interpretability in deep learning for finance: A case study for the Heston model
Deep learning is a powerful tool whose applications in quantitative finance are growing every day. Yet, artificial neural networks behave as black boxes, and this introduces risks, hindering validation and accountability processes. Being able to interpret the inner functioning and the input–output r...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
KeAi Communications Co., Ltd.
2026-01-01
|
| Series: | Risk Sciences |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2950629825000207 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|