Value-at-risk student prescription trees for price personalization
Abstract Value-at-risk (VaR) models use statistical techniques to estimate potential losses in financial portfolios over a specified time period. In contrast, student prescription trees (SPTs) are interpretable policy optimizers that estimate individual consumer demand and utilize decision trees to...
Saved in:
| Main Authors: | Maria R. Lentini, Umashanger Thayasivam |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2025-03-01
|
| Series: | Journal of Big Data |
| Online Access: | https://doi.org/10.1186/s40537-024-01036-y |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Prescriptive Pricing and Stabilisation Clauses in Investment Agreements
by: Irene Musselli, et al.
Published: (2024-05-01) -
Machine learning driven diabetes care using predictive-prescriptive analytics for personalized medication prescription
by: Manaf Zargoush, et al.
Published: (2025-07-01) -
Pricing Options Based on Trinomial Markov Tree
by: Hu Xiaoping, et al.
Published: (2014-01-01) -
Binary Tree Pricing to Convertible Bonds with Credit Risk under Stochastic Interest Rates
by: Jianbo Huang, et al.
Published: (2013-01-01) -
Home-value insurance and idiosyncratic risks of residential property prices
by: Alfred Larm Teye
Published: (2018-12-01)