00000cam 2200000zi 4500 9.961568 CaOODSP 20260401081945 m o d f cr cn||||||||| 260401e20260306oncd obs f000 0 eng d CaOODSP eng rda CaOODSP eng eng fre FB3-5/2026-8E-PDF Rodriguez Rondon, Gabriel, author. Estimation and inference for stochastic volatility models with heavy-tailed distributions / Gabriel Rodriguez Rondon, Jean-Marie Dufour, Md. Nazmul Ahsan. [Ottawa] : Bank of Canada = Banque du Canada, March 6, 2026. ©2026 1 online resource (47 pages) : graphs. text txt rdacontent computer c rdamedia online resource cr rdacarrier Staff working paper = Document de travail du personnel, 1701-9397 ; 2026-8 Cover title. Includes bibliographical references (pages 34-36). "Statistical inference-both estimation and testing-for stochastic volatility (SV) models is known to be challenging and computationally demanding. We propose simple and efficient estimators for SV models with conditionally heavy-tailed error distributions, particularly the Student's t and Generalized Exponential Distributions (GED). The estimators rely on a small set of moment conditions derived from ARMA-type representations of SV models, with an option to apply "winsorization" to improve stability and finite-sample performance. Except for the degrees-of-freedom parameter, closed-form expressions are available for all other parameters-extending-thus eliminating the need for numerical optimization or initial values. We derive the estimators' asymptotic distribution and show that, due to their analytical tractability, they support reliable-and even exact-simulation based inference via Monte Carlo bootstrap methods. We assess their performance through extensive simulations and demonstrate their practical relevance in financial return data, which strongly reject the normality assumption in favor of heavy-tailed models"--Abstract. Includes abstracts in English and French. Moments method (Statistics) Monte Carlo method. Stochastic analysis. Asymptotic distribution (Probability theory) Méthodes des moments (Statistique) Méthode de Monte-Carlo. Analyse stochastique. Distribution asymptotique (Théorie des probabilités) Statistics lcgft Statistiques rvmgf Bank of Canada, issuing body. Staff working paper (Bank of Canada) 1701-9397 ; 2026-8. (CaOODSP)9.806221 PDF 967 KB https://publications.gc.ca/collections/collection_2026/banque-bank-canada/FB3-5-2026-8-eng.pdf