Influence diagnostics in stochastic volatility models / Diagnostico de influencia em modelos de volatilidade estocastica

AUTOR(ES)

Simoni Fernanda Martim

DATA DE PUBLICAÇÃO

2009

RESUMO

Model diagnostics is a key step to assess the quality of fitted models. In this sense, one of the most important tools is the analysis of influence. Peña (2005) introduced a way of assessing influence in linear regression models, which evaluates how each point is influenced by the others in the sample. This diagnostic strategy was adapted by Hotta and Motta (2007) on the influence analysis of univariate stochastic volatility models. In this dissertation, it is performed a study of influence diagnostics of asymmetric univariate stochastic volatility models as well as multivariate stochastic volatility models. The proposed methodologies are illustrated through the analysis of simulated data and financial time series returns.

ASSUNTO(S)

diagnostico observações influentes finanças - estatistica diagnostics finance influential observations series temporais time-series outliers (statistics) valores estranhos (estatistica)

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