We forecast daily realized volatilities with linear and nonlinear models and evaluate the benefits of bootstrap aggregation (bagging) in producing more precise forecasts. We consider the linear autoregressive (AR) model, the Heterogeneous Autoregressive model (HAR), and a non-linear HAR model...

We study the simultaneous occurrence of long memory and nonlinear effects, such as structural breaks and thresholds, in autoregressive moving average (ARMA) time series models and apply our modeling framework to series of daily realized volatility. Asymptotic theory for the quasi-maximum...

The literature on excess return prediction has considered a wide array of estimation schemes, among them unrestricted and restricted regression coefficients. We consider bootstrap aggregation (bagging) to smooth parameter restrictions. Two types of restrictions are considered: positivity of the...

Brazilian Foreign Exchange (FX) markets have a unique structure: most trades are conducted in the derivatives (futures) market. We study price discovery in the FX markets in Brazil and indicate which market (spot or futures) adjusts more quickly to the arrival of new information. We find that...

The estimation of the impact of macroeconomic announcements in the Brazilian futuresmarkets is used to uncover the relationship between macroeconomic fundamentals andasset prices. Using intraday data from October 2008 to January 2011, we find thatexternal macroeconomic announcements dominate...

A model of realized variance-covariance is proposed using a portfolio with the most liquid stockassets of Ibovespa. The purpose is to evaluate the economic gains associated with following avolatility timing strategy based on the model’s conditional forecasts. Comparing with...