Submitted by Maurício da Silva Medeiros Júnior (mauriciojr.df@gmail.com) on 2016-04-06T21:06:49Z No. of bitstreams: 1 Dissertação - Maurício Medeiros Jr. - FGV-EPGE.pdf: 2837403 bytes, checksum: dc338c6b56e600b8b9194b1c27abb080 (MD5) / Approved for entry into archive by BRUNA BARROS (bruna.barros@fgv.br) on 2016-04-19T18:34:15Z (GMT) No. of bitstreams: 1 Dissertação - Maurício Medeiros Jr. - FGV-EPGE.pdf: 2837403 bytes, checksum: dc338c6b56e600b8b9194b1c27abb080 (MD5) / Approved for entry into archive by Marcia Bacha (marcia.bacha@fgv.br) on 2016-04-27T18:16:31Z (GMT) No. of bitstreams: 1 Dissertação - Maurício Medeiros Jr. - FGV-EPGE.pdf: 2837403 bytes, checksum: dc338c6b56e600b8b9194b1c27abb080 (MD5) / Made available in DSpace on 2016-04-27T18:21:05Z (GMT). No. of bitstreams: 1 Dissertação - Maurício Medeiros Jr. - FGV-EPGE.pdf: 2837403 bytes, checksum: dc338c6b56e600b8b9194b1c27abb080 (MD5) Previous issue date: 2016-03-22 / We aim to provide a review of the stochastic discount factor bounds usually applied to diagnose asset pricing models. In particular, we mainly discuss the bounds used to analyze the disaster model of Barro (2006). Our attention is focused in this disaster model since the stochastic discount factor bounds that are applied to study the performance of disaster models usually consider the approach of Barro (2006). We first present the entropy bounds that provide a diagnosis of the analyzed disaster model which are the methods of Almeida and Garcia (2012, 2016); Ghosh et al. (2016). Then, we discuss how their results according to the disaster model are related to each other and also present the findings of other methodologies that are similar to these bounds but provide different evidence about the performance of the framework developed by Barro (2006).

Submitted by Diego Brandão (digusmao@hotmail.com) on 2017-01-06T20:29:33Z No. of bitstreams: 1 Tese - Versao final - Diego Brandao.pdf: 1402061 bytes, checksum: 2a9d03af25fdeae9cb4300343d707aa2 (MD5) / Approved for entry into archive by GILSON ROCHA MIRANDA (gilson.miranda@fgv.br) on 2017-02-20T13:39:19Z (GMT) No. of bitstreams: 1 Tese - Versao final - Diego Brandao.pdf: 1402061 bytes, checksum: 2a9d03af25fdeae9cb4300343d707aa2 (MD5) / Made available in DSpace on 2017-03-03T12:50:29Z (GMT). No. of bitstreams: 1 Tese - Versao final - Diego Brandao.pdf: 1402061 bytes, checksum: 2a9d03af25fdeae9cb4300343d707aa2 (MD5) Previous issue date: 2016-09-23 / The thesis consists in three articles about the estimation of asset pricing models. The first paper analyses small sample properties of Generalized Empirical Likelihood estimators for the risk aversion parameter in CRRA preferences when the economy is characterized by rare disasters. In the second article, we develop and test a methodology to assess misspeci fied asset pricing models by taking into account the smallest probability distortion necessary to assign correct prices. In the final paper, we estimate an approximate long run risks model using Brazilian data. / Esta tese consiste em três artigos sobre a estimação de modelos de apreçamento de ativos. No primeiro artigo, analisamos as propriedades de amostra pequena dos estimadores da classe Generalized Empirical Likelihood para o coeficiente de aversão ao risco de preferências CRRA quando a economia é suscetível a desastres. No segundo artigo, apresentamos e testamos uma metodologia de avaliação de modelos de apreçamento mal especificados que leva em conta a menor distorção de probabilidade necessária sobre a medida real para que modelo aprece corretamente ativos. No terceiro artigo, estimamos uma versão aproximada do modelo de riscos de longo prazo utilizando dados brasileiros.