---
title: Forecasting Covariance Matrices
url: https://www.ml-quant.com/papers/repec/oup-jfinec-v-22-y-2024-i-3-p-696-742/
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:oup:jfinec:v:22:y:2024:i:3:p:696-742.
source_url: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fhdl.handle.net%2F10.1093%2Fjjfinec%2Fnbad013%3Bh%3Drepec%3Aoup%3Ajfinec%3Av%3A22%3Ay%3A2024%3Ai%3A3%3Ap%3A696-742.
featured: 2024-07-24
citations: unknown
topic: Econometrics & Forecasting
---


# Forecasting Covariance Matrices

A new model enhances the prediction accuracy of large realized covariance matrices of returns by breaking down the return covariance matrix using standard firm-level factors and sectoral restrictions.

- Source: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fhdl.handle.net%2F10.1093%2Fjjfinec%2Fnbad013%3Bh%3Drepec%3Aoup%3Ajfinec%3Av%3A22%3Ay%3A2024%3Ai%3A3%3Ap%3A696-742.
- Identifier: RePEc:oup:jfinec:v:22:y:2024:i:3:p:696-742.
- Released: 2024-07-24
- First featured: Quant Letter No. 58 (2024-07-24): https://www.ml-quant.com/issues/2024-07-24/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: Econometrics & Forecasting

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