Gustavo Silva Araújo

Do central bank foreign exchange interventions affect market expectations

ABSTRACT The aim of this article is to study the impact of the Brazilian central bank swap interventions on the FX market from 2006 to 2013. In this period, these nontraditional interventions were the main FX instrument of the Brazilian Government. Since the central bank operates through a sequence of daily interventions in most of the period, we employ the event study method, which is appropriate to investigate cumulative impact of intervention episodes. We analyse the effects on the risk neutral distribution of BRL-USD exchange rate, which incorporates economic valuation besides the likelihoods. We investigate both changes in level and in the dynamics of the moments. Our tests indicate that interventions have little effects on the exchange rate distribution. We only find evidences of some impact on the dynamics of the mean, volatility and skewness over long horizons when the central bank takes short positions on the exchange rate.

Is Petrobras Options Market Efficient? A Study Using the Delta-Gamma Neutral Strategy

ABSTRACT This study aims to verify if the Petrobras options market is efficient in its weak form. For this purpose, this work tries to make profits on a systematic basis through delta-gamma neutral strategies using the firm’s stocks and options. In order to simulate the strategy as it would be used in the real world, we built order books every five minutes considering all buy and sell orders sent for both the underlying asset and its options. We apply the strategy when we observe distortions between implied volatilities extracted from the options. The results show evidence that the Petrobras options market is not efficient, since in 371 day-trade transactions (with an average investment of R

É possível bater o Ibovespa com operações de análise técnica no mercado futuro

81,000 and an average holding time of one hour and thirteen minutes), 85% of the options strategies were profitable and the average return was 0.49%, which corresponds to more than 1600% of the highest interbank interest rate for the period.

Avaliação de métodos de exigência de capital para risco de ações no Brasil

The asset selection decision has been one of the main challenges faced by financial market analysts. The theory of Charles Dow formulated in 1884 attempts to shed some light on this issue by forecasting stock market prices based on patterns. However the efficient market hypothesis has developed the hypothesis that this idea as useless. The aim of this work is to verify whether it is possible to profit from patterns in stock prices using the Ibovespa futures mini-contracts. Using the years 2006 and 2007 to calibrate the strategy and the period ranging from January 2008 to February 2010 to apply it, we obtained results higher than those of Ibovespa, even in terms of risk-return. The results suggest the weak form efficiency is not confirmed for the period under analysis.

Avaliação de Métodos de Cálculo de Exigência de Capital para Risco Cambial

This paper analyses four methods of calculating capital requirements for coverage of market risk due to exposure in stocks and their derivatives, except options. For simulation purposes, two theoretical portfolios are created with assets that participate in the composition of Ibovespa. The methods evaluated follow the directives of the Basel Committee. The first is based on the standardized approach and the others, on the internal models approach based on the Value-at-Risk (VaR) concept. The VaR methods evaluated are historical, Diagonal and the RiskmetricsTM approach. The backtesting of the methods follows the methodology suggested by the Committee. Additionally, for the methods based on VaR, it is applied the Kupiec test for proportion of failures. The relevance of the difference between the capital required and the verified losses is also considered. Although the historical method presents the best VaR performance, the best results with respect to the capital requirements belong to the RiskmetricsTM approach.