Inflation and Stock Returns at B3

ID: 52290

Authors: Carlos Chaves, André C. Silva.

Source: Revista Brasileira de Finanças, v. 16, n. 4, p. 521-544, October-December, 2018. 24 page(s).

Keyword: B3 , Focus survey , Ibovespa , inflation , inflation forecasts , Stock returns

Document type: Article (English) Show Abstract

We examine the impact of expected inflation on stock returns. We use inflation forecasts from the Focus survey and real returns of Ibovespa (the index of B3, the Brazilian stock exchange). In our main specification, an increaseof1percentagepointinexpectedinflationforthenext12monthsis associated with a decline of 0.57 percentage points in stock returns. Stock returns react negatively to the 5-year CDS volatility and the VIX index. A simulated portfolio with a strategy based on changes in inflation expectations from 2003 to 2016 has cumulated real returns of 135 percent while cumulatedrealIbovespareturnsare48percent. Thestrategyimplieshigher cumulated real returns compared with Ibovespa in 69 percent of the period.

A Statistical Factor Asset Pricing Model Versus the 4-Factor Model

ID: 52291

Authors: Verônica de Fátima Santana, Alex Augusto Timm Rathke.

Source: Revista Brasileira de Finanças, v. 16, n. 4, p. 545-572, October-December, 2018. 28 page(s).

Keyword: 4-Factor Model , Abnormal Returns , Principal Component Analysis , Risk Factors

Document type: Article (English) Show Abstract

This research aims to compare the performance of a statistical factor asset pricing model with the Fama-French-Carhart 4-factor model. We perform a Principal Component Analysis (PCA) to extract latent risk factors using dataofstockslistedonB3from2001to2015. Wetesttheabilitiesofthetwo models to explain assets’ returns both in the time-series and in the crosssection dimension. We found that the statistical factor models generates statistically significant abnormal returns in the time-series analysis while the 4-factor model does not. In the cross section dimension, neither model generatessignificantabnormalreturnsbuttheyalsoarenotabletogenerate positiveriskpremia. Similarresultsarefoundifweconsiderdifferentsetsof time and assets. Therefore, although the 4-factor model performs slightly better in the set of tests, neither of the models can be considered fully adequatetoexplainexpectedreturnsofassetsintheBrazilianstockmarket.

A GARCH-VaR Investigation on the Brazilian Sectoral Stock Indices

ID: 52292

Authors: Wilton Bernardino, Leonardo Brito, Raydonal Ospina, Silvio Melo.

Source: Revista Brasileira de Finanças, v. 16, n. 4, p. 573-610, October-December, 2018. 38 page(s).

Keyword: Brazilian stock market , GARCH models , Time Series , Valueat-Risk , Volatility

Document type: Article (English) Show Abstract

Inthispaper, weexploredmarketriskinBrazilbyconsideringdifferentsectoral indices of the Brazilian stock market and the GARCH Value-at-Risk (GARCH-VaR) estimation approach. We have carried a statistical evaluation of eight Brazilian sectoral stock indices during different time ranges so that GARCH-VaR methodologies could be chosen according to the data. We analyzed the sectoral indices in a Value-at-Risk point of view using recentdata. TheresultsofthestudyrevealthatVaRmaybeaneffectivetool onminimizingriskexposureandpotentiallytoavoidlosseswhentradingon the Brazilian stock market. Furthermore, we showed that different sectors of the Brazilian economy have significantly different risk behavior. In particular, the consumption and industrial sectoral indices presented the best riskperformance. Inthissense,wehighlightthatthistypeofanalysiswould be useful to small investors in evaluating the attractiveness of investing on the Brazilian stock market.

Evidences of Dividend Month Premium in the Brazilian Stock Market

ID: 52293

Authors: Camila Cardoso Pereira, Regis A. Ely, Claudio Djissey Shikida.

Source: Revista Brasileira de Finanças, v. 16, n. 4, p. 611-634, October-December, 2018. 24 page(s).

Keyword: Dividend month premium; Abnormal return , Portfolio selection

Document type: Article (Portuguese) Show Abstract

We test the presence of the dividend month premium in the Brazilian stock market. This premium consists in the existence of abnormal returns when companies are predicted to issue a dividend. We build portfolios based on predicted dividends and estimate asset pricing multifactor models to check for the existence of returns not associated with risks. We present evidences ofapositivemonthlypremiumofabout1%,butresultsarelessrobustwhen we exclude low liquidity assets from the sample. Also, the effect is larger for small caps and assets with higher dividend yields.

An Empirical Study of the Dynamic Correlation of Brazilian Stock Returns

ID: 52294

Authors: Hudson Chaves Costa, Sabino da Silva Porto Junior, Gabrielito Menezes.

Source: Revista Brasileira de Finanças, v. 16, n. 4, p. 635-667, October-December, 2018. 33 page(s).

Keyword: Conditional correlation , Eigenvalue , Idiosyncratic risk , Market risk , Multivariate garch

Document type: Article (Portuguese) Show Abstract

This article examines empirically the behavior of the correlation between the return of shares listed on the BMF& BOVESPA over the period from 2000 to 2015. To this end, we use multivariate GARCH models introduced by Bollerslev (1990) to remove the temporal series of arrays of conditional correlation of returns of stocks. With the temporal series of the largest eigenvalues of matrices of c or relation estimated conditional, we apply statistical tests (unit root, structural breaks and trend) to verify the existence of stochastic trend or deterministic to the intensity of the correlation between the returns of the shares represented by eigenvalues. Our results confirm that both in times of crises at national and international turbulence, there is greater correlation between the actions. However, we did not find any long-term trend in time series of the largest eigenvalues of matrices of correlation conditional.

List of Reviewers - Brazilian Review of Finance - RBFin 2018

ID: 52295

Authors: Revista Brasileira de Finanças - RBFin.

Source: Revista Brasileira de Finanças, v. 16, n. 4, p. 669-669, October-December, 2018. 1 page(s).

Document type: Other (English)