---
title: Adaptive LASSO-MGARCH for Multivariate Volatility Forecasting
url: https://www.ml-quant.com/papers/repec/cdf-wpaper-2026-4/
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:cdf:wpaper:2026/4
source_url: https://econpapers.repec.org/RePEc:cdf:wpaper:2026/4
featured: 2026-09-25
citations: unknown
topic: Derivatives & Volatility
---


# Adaptive LASSO-MGARCH for Multivariate Volatility Forecasting

Introducing coefficient-specific penalization into multivariate GARCH equations reduces complexity and improves out-of-sample covariance forecasts across bonds, equities, and commodities.

- Source: https://econpapers.repec.org/RePEc:cdf:wpaper:2026/4
- Identifier: RePEc:cdf:wpaper:2026/4
- Released: 2026-09-16
- First featured: Quant Letter No. 132 (2026-09-25): https://www.ml-quant.com/issues/2026-09-25/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: Derivatives & Volatility
- Authors: Xu, Yongdeng, Lyu, Juyi, Lu, Wenna

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