Representation over Rents: Stochastic Volatility Models with Stable Disturbances: Estimation via Linearization

Fernando Roders, Siem Jan Koopman and Karim Moussa
Additional contact information
Fernando Roders: a.s.r. Asset Management
Siem Jan Koopman: Vrije Universiteit Amsterdam
Karim Moussa: Vrije Universiteit Amsterdam

No 26-082/II, Tinbergen Institute Discussion Papers from Tinbergen Institute

Abstract: In this study, we propose to estimate the parameters of stochastic volatility models with stable disturbances using methods based on linearization. Specifically, we obtain a linear state space form of the model by taking the logarithm of the squared financial returns, which, together with analytical expressions for logarithmic and fractional lower order moments of the stable distribution, forms the basis of the proposed quasi-maximum likelihood and generalized method of moments estimators. The methods are straightforward to implement and do not require simulation. We provide details of the implementation and study the finite-sample performance of the two estimation methods in a Monte Carlo study. The empirical relevance is illustrated by studying model-implied volatility estimates from time series of daily returns from stock indices, exchange rates, and cryptocurrencies.

JEL-codes: C32 C58 G15 (search for similar items in EconPapers)
Date: 2026-10-05
New Economics Papers: this item is included in nep-ets
References: Add references at CitEc
Citations:

Downloads: (external link)
https://papers.tinbergen.nl/26082.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:tin:wpaper:20260082

Access Statistics for this paper

More papers in Tinbergen Institute Discussion Papers from Tinbergen Institute Contact information at EDIRC.
Bibliographic data for series maintained by Tinbergen Office +31 (0)10-4088900 ().