---
title: Multi-View Locally Weighted Regression for LGD Forecasting
url: https://www.ml-quant.com/papers/repec/eee-intfor-v-41-y-2025-i-1-p-290-306/
site: ML-Quant (https://www.ml-quant.com)
updated: 2026-09-26
license: Summaries CC BY 4.0; links go to the original sources
index: https://www.ml-quant.com/llms.txt
identifier: RePEc:eee:intfor:v:41:y:2025:i:1:p:290-306
source_url: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fwww.sciencedirect.com%2Fscience%2Farticle%2Fpii%2FS0169207024000451%3Bh%3Drepec%3Aeee%3Aintfor%3Av%3A41%3Ay%3A2025%3Ai%3A1%3Ap%3A290-306
featured: 2025-01-01
citations: unknown
topic: Econometrics & Forecasting
---


# Multi-View Locally Weighted Regression for LGD Forecasting

The paper presents a new method for forecasting loss given default (LGD) by dividing features into groups, building individual models, and combining the results.

- Source: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fwww.sciencedirect.com%2Fscience%2Farticle%2Fpii%2FS0169207024000451%3Bh%3Drepec%3Aeee%3Aintfor%3Av%3A41%3Ay%3A2025%3Ai%3A1%3Ap%3A290-306
- Identifier: RePEc:eee:intfor:v:41:y:2025:i:1:p:290-306
- Released: 2025-01-01
- First featured: Quant Letter No. 80 (2025-01-01): https://www.ml-quant.com/issues/2025-01-01/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: Econometrics & Forecasting

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