The present work focuses on the inference in stochastic volatility models. More precisely, estimation of suitable functions of the mean vector of the increment stock price is performed without estimating in advance the parameters of the model. A moving block bootstrap (MBB) approach is then suggested in order to estimate the variance of those functions and properties of the involved estimators are discussed. Simulations on the model are also performed

Estimating smooth functions of sample mean in diffusion processes: a MBB approach

ALBANO, GIUSEPPINA;GIORDANO, Francesco;PERNA, Cira
2010-01-01

Abstract

The present work focuses on the inference in stochastic volatility models. More precisely, estimation of suitable functions of the mean vector of the increment stock price is performed without estimating in advance the parameters of the model. A moving block bootstrap (MBB) approach is then suggested in order to estimate the variance of those functions and properties of the involved estimators are discussed. Simulations on the model are also performed
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11386/3037115
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