---
title: Diagnosing and Stabilizing Dynamic Correlations in Multivariate Stochastic Volatility Models
url: https://www.ml-quant.com/papers/repec/cte-wsrepe-50561/
site: ML-Quant (https://www.ml-quant.com)
updated: 2026-10-02
license: Summaries CC BY 4.0; links go to the original sources
index: https://www.ml-quant.com/llms.txt
identifier: RePEc:cte:wsrepe:50561
source_url: https://econpapers.repec.org/RePEc:cte:wsrepe:50561
featured: 2026-10-02
citations: unknown
topic: Derivatives & Volatility
---


# Diagnosing and Stabilizing Dynamic Correlations in Multivariate Stochastic Volatility Models

Decomposing forecasting losses into correlation versus scale components, the paper shows how to diagnose and stabilize dynamic-correlation volatility models using realized-volatility inputs.

- Source: https://econpapers.repec.org/RePEc:cte:wsrepe:50561
- Identifier: RePEc:cte:wsrepe:50561
- Released: 2026-09-23
- First featured: Quant Letter No. 133 (2026-10-02): https://www.ml-quant.com/issues/2026-10-02/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: Derivatives & Volatility
- Authors: Guo, Hongfei, Marín Díazaraque, Juan Miguel, Veiga, Helena

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