---
title: Mixed-frequency ML for weekly claims
url: https://www.ml-quant.com/papers/repec/eee-intfor-v-39-y-2023-i-3-p-1122-1144/
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:39:y:2023:i:3:p:1122-1144
source_url: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fwww.sciencedirect.com%2Fscience%2Farticle%2Fpii%2FS0169207022000656%3Bh%3Drepec%3Aeee%3Aintfor%3Av%3A39%3Ay%3A2023%3Ai%3A3%3Ap%3A1122-1144
featured: 2023-07-12
citations: unknown
topic: Risk, Credit & Banking
---


# Mixed-frequency ML for weekly claims

A new method combining mixed-data sampling and machine learning, using Google Trends data, enhances the accuracy of predicting weekly unemployment insurance claims, especially during the COVID-19 crisis.

- Source: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fwww.sciencedirect.com%2Fscience%2Farticle%2Fpii%2FS0169207022000656%3Bh%3Drepec%3Aeee%3Aintfor%3Av%3A39%3Ay%3A2023%3Ai%3A3%3Ap%3A1122-1144
- Identifier: RePEc:eee:intfor:v:39:y:2023:i:3:p:1122-1144
- Released: 2023-07-12
- First featured: Quant Letter No. 7 (2023-07-12): https://www.ml-quant.com/issues/2023-07-12/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: Risk, Credit & Banking

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