On the correlations in linearized multivariate stochastic volatility models

Karim Moussa

In the analysis of multivariate stochastic volatility models, many estimation procedures begin by transforming the data, taking the logarithm of the squared returns to obtain a linear state space model. A well-known series representation links the correlations between elements of the observation error in the actual and linearized forms of the model. This note derives a closed-form expression for the series and discusses its statistical implications. Additionally, it offers a new interpretation of the correlations in the linearized model.

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Year of publication:	[2025]
Authors:	Moussa, Karim
Publisher:	Amsterdam, The Netherlands : Tinbergen Institute
Subject:	Multivariate volatility models \| Quasi-maximum likelihood \| Cross-correlation \| Volatilität \| Volatility \| ARCH-Modell \| ARCH model \| Korrelation \| Correlation \| Multivariate Analyse \| Multivariate analysis \| Stochastischer Prozess \| Stochastic process \| Wechselkurs \| Exchange rate \| Schätzung \| Estimation \| Zeitreihenanalyse \| Time series analysis \| Schätztheorie \| Estimation theory