Financialization of the commodity future markets: a SVAR model approach

Submitted by Tommaso Momoli (tommaso.momoli@gmail.com) on 2017-03-29T04:51:52Z No. of bitstreams: 1 Tommaso.Momoli Thesis FGV.pdf: 2459609 bytes, checksum: 56072be31042eb761414eba91a983961 (MD5) === Approved for entry into archive by Josineide da Silva Santos Locatelli (josineide.locatelli@fgv.br)...

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Bibliographic Details
Main Author: Momoli, Tommaso
Other Authors: Boons, Martijn
Language:English
Published: 2017
Subjects:
Online Access:http://hdl.handle.net/10438/18105
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Summary:Submitted by Tommaso Momoli (tommaso.momoli@gmail.com) on 2017-03-29T04:51:52Z No. of bitstreams: 1 Tommaso.Momoli Thesis FGV.pdf: 2459609 bytes, checksum: 56072be31042eb761414eba91a983961 (MD5) === Approved for entry into archive by Josineide da Silva Santos Locatelli (josineide.locatelli@fgv.br) on 2017-03-29T11:04:04Z (GMT) No. of bitstreams: 1 Tommaso.Momoli Thesis FGV.pdf: 2459609 bytes, checksum: 56072be31042eb761414eba91a983961 (MD5) === Made available in DSpace on 2017-03-29T12:16:39Z (GMT). No. of bitstreams: 1 Tommaso.Momoli Thesis FGV.pdf: 2459609 bytes, checksum: 56072be31042eb761414eba91a983961 (MD5) Previous issue date: 2017-01-25 === This is a study regarding the impact of the index investments in the Commodity Future Market. The models applied, focus on the Causal Analysis and the Impulse Response Function through an orthogonalisation of the Vector of Auto Regression (SVAR), this allow to extract lead/lag correlation between the Index and First nearby Return for different Futures Sectors and in addition response to shocks in different equation. The study is divided in three different period, to reflect before and after the Financialization and then after the introduction in the market of the new generation of commodity Indexes. The results show a different behaviors of the parameters throughout time with a particular emphasis for the most traded Commodities to lead the others. === Trata-se de um estudo sobre o impacto dos investimentos em índices no mercado futuro de commodities. Os modelos aplicados, enfocam a Análise Causal e a Função de Resposta ao Impulso através de uma ortogonalização do Vetor de Auto Regressão (SVAR), permitindo extrair a correlação lead / lag entre o Índice e o Primeiro Retorno próximo para diferentes Setores Futuros e, A choques em diferentes equações. O estudo é dividido em três períodos diferentes, para refletir antes e depois da Financialização e, em seguida, após a introdução no mercado da nova geração de índices de commodities. Os resultados mostram um comportamento diferente dos parâmetros ao longo do tempo com uma ênfase particular para os Commodities mais negociados para liderar os outros.