Modele stochastycznej zmienności: estymacja metodą quasi-największej wiarygodności

• Autorzy: Anna Pajor
• Języki publikacji: PL

Abstrakty

Celem pracy jest zebranie podstawowych wiadomości o modelach stochastycznej zmienności oraz prezentacja jednego ze sposobów ich estymacji. Przedstawiona została estymacja metodą Quasi-Największej Wiarygodności, która nie wymaga zaawansowanych metod numerycznych i jednocześnie łatwo uogólnia się na przypadek wielowymiarowy. W celu ilustracji, omówiona technika została zastosowana do sztucznie wygenerowanej ścieżki procesu SV o znanych parametrach.

EN

The paper discusses the basic properties and estimation methods of Stochastic Volatility Models used in financial time series analysis. The author presented the Quasi-maximum Likelihood (QML) estimation, which uses the Kaiman filter to construct the quasi-likelihood function. This method is proposed for SV models with Gaussian errors for simulated data. Moreover, the author illustrated the QML estimation method by fitting SV models to the returns of the Warsaw Stock Exchange Index (WIG) for the period from 16 April 1991 to 31 March 1999 - 1 536 observations. Finally, the article considers a SV model with t-Student errors with unknown degrees of freedom as well as models where the conditional variance logarithm follows a random course. (original abstract)

Słowa kluczowe

PL

Modele stochastyczne; Procesy stochastyczne; Estymacja

EN

Stochastic models; Stochastic processes; Estimation

• Czasopismo: Przegląd Statystyczny
• Rocznik: 2001
• Tom: 48
• Numer: z. 1-2
• Strony: 203--224

Twórcy

autor

Anna Pajor

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