Família de índice para o Mercado de Renda Fixa: uma proposta metodológica - Carvalho, Robson Góes de (2021)
Since 2015 it’s been possible to identify an increase in the debentures emission and negotiation from brasilian companies. These transactions can be arising from implementation of the restrict efforts instruction 476/09, the 12.431 law of infrastructure debentures emission improvement, the debentures price and pricing monitoring, from the REUNE, and the change related to the BNDES fundings and the SELIC rate decreasing. This way, verified only the ANBIMA debenture index and the Board Quantum existence, it was proposed, in this work, a new index family for the fixed income market. Therefore, it is suggested a methodology to the building of general debentures negotiation index (IDGng) and the B3 debenture index (IDB3). Being the IDGng theoretical portfolio composed of stocks independent from their ratings and the IDB3 portfolio only with debentures issued from companies traded on B3. It also added to the two indexes the non-inclusion of stocks with expiration less than a month and the need to be up to date with the payment of events. On the other hand, the stock’s theoretical quantity was obtained by the market quantity weighting with the negotiation factor. Being the index calculated using the summation of the sum of the product of proportional theoretical quantity with the unitary price in a specific date with the product of proportional theoretical quantity with the asset event. For this reason, it was used fixed income market datas, available on the site ANBIMA Data, between 2018 and 2020. Thus, the IDGng’s portfolio was composed of 32 debentures and the IDB3’s of 30. Therefore, after the series calculus, could be verified an increase in the IDGng from 2018 until June 2019, when it starts to show a tendency of decrement. While the IDB3 shows the highest score in mid 2020. Being with that verified, in the sequence, the persistence influence and the asymmetry on its return series volatility. Fact indicates that the proposed indexes present long memory characteristics, based on the results of the low order models implantation, GARCH (1,1), EGARCH(1,1) and TGARCH (1,1).