SAMPAIO, Glaylson Rodrigues. Modelagem do comportamento forward-looking dos índices setoriais no Brasil. 2015. 41f. Dissertaçaõ (mestrado profissional) - Universidade Federal do Ceará, Programa de Pós Graduação em Economia, CAEN, Fortaleza - Ce, 2015. / Submitted by Mônica Correia Aquino (monicacorreiaaquino@gmail.com) on 2016-03-10T19:04:50Z No. of bitstreams: 1 2015_dissert_grsampaio.pdf: 798105 bytes, checksum: 7f1144b858543563b49c608a2d8a976c (MD5) / Approved for entry into archive by Mônica Correia Aquino(monicacorreiaaquino@gmail.com) on 2016-03-10T20:18:08Z (GMT) No. of bitstreams: 1 2015_dissert_grsampaio.pdf: 798105 bytes, checksum: 7f1144b858543563b49c608a2d8a976c (MD5) / Made available in DSpace on 2016-03-10T20:18:08Z (GMT). No. of bitstreams: 1 2015_dissert_grsampaio.pdf: 798105 bytes, checksum: 7f1144b858543563b49c608a2d8a976c (MD5) Previous issue date: 2015 / The co-movements among asset prices suggest the action of exogenous influences, however, there is no consensus in the literature about which economic factors are responsible. This study investigates the sensitivity of the sector indexes BM&FBOVESPA to changes in expectations of market participants to the constant economic variables Focus Report. Make up the sample the seven sectoral indexes with complete series for the period January 2009 to June 2014, comprising 286 weekly observations. The approach used for the average modeling of indexes of series is based on multifactor pricing theory, using the forward-looking variables accompanied this report as candidates for factors. Given the presence of conditional heteroskedasticity in the sector indexes return series, it is proposed to GARCH framework for modeling the volatility. The results suggest that some expectations variables are significant for explanation of variations in Brazilian industry indices and the proposed multifactor models of returns can generate prediction gains evidenced by reduced of mean squared error of the return predictions. / Os comovimentos entre os preços de ativos sugerem a atuação de influências exógenas. No entanto, não há consenso na literatura sobre quais fatores econômicos são determinantes. Neste estudo, investiga-se a sensibilidade dos índices setoriais BM&FBOVESPA a mudanças nas expectativas dos participantes do mercado para as variáveis econômicas constantes do Relatório Focus. Compõem a amostra os sete índices setoriais com série completa para o período de janeiro de 2009 a junho de 2014, compreendendo 286 observações semanais. A abordagem utilizada para a modelagem da média das séries dos índices fundamenta-se na teoria de precificação multifatorial, utilizando-se as variáveis forward-looking acompanhadas nesse relatório como candidatas a fatores. Dada a presença de heterocedasticidade condicional nas séries de retornos dos índices setoriais, propõe-se o arcabouço GARCH para modelagem da volatilidade. Os resultados sugerem que algumas variáveis de expectativas são significativas para explicação das variações dos índices setoriais brasileiros e que os modelos multifatoriais propostos podem gerar ganhos de previsão, evidenciados pela redução do erro quadrático médio das projeções de retorno.

Submitted by Fernando Luiz Cordeiro (fernandolpcordeiro@gmail.com) on 2018-06-22T20:12:54Z No. of bitstreams: 1 SDFDecomposition_finalv.pdf: 845158 bytes, checksum: 5ceb09364caa557c2198d20e41ee5522 (MD5) / Approved for entry into archive by GILSON ROCHA MIRANDA (gilson.miranda@fgv.br) on 2018-06-29T19:55:51Z (GMT) No. of bitstreams: 1 SDFDecomposition_finalv.pdf: 845158 bytes, checksum: 5ceb09364caa557c2198d20e41ee5522 (MD5) / Made available in DSpace on 2018-07-02T18:21:34Z (GMT). No. of bitstreams: 1 SDFDecomposition_finalv.pdf: 845158 bytes, checksum: 5ceb09364caa557c2198d20e41ee5522 (MD5) Previous issue date: 2018 / In this work, we use the framework developed by Christensen (2017) and Hansen and Scheinkman (2009) to study the long-term interest rates in the US and Brazil. In our first set of results, we assess Christensen (2017) estimator using Monte Carlo simulations in order to evaluate the estimator performance in the rare disasters and habit formation asset pricing models. Generally, the estimation quality is not uniform and, in some cases, requires a large sample size to attain reasonable results. Next, we apply the nonparametric estimation to US and Brazilian data and estimate how the yield of a long-term zero-coupon bond responds to the initial state of the economy. Using a flexible specification for the state process leads to an interesting non-linear response of the yield to changes in the initial state. We find that the Brazilian long-term interest rate is about 5.3% per year.