The macroeconomic effects of shocks in models of nominal rigidity depend crucially on the degree of strategic complementarity among price setters. However, the empirical evidence on its magnitude is indirect and ambiguous: the one based on macroeconomic data suggest strong strategic...

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...

Este estudo tem como objetivo analisar a descoberta de preços no mercado cambial brasileiro e indicar qual dos mercados (à vista ou futuro) se ajusta mais rapidamente à chegada de novas informações. Utilizando-se dados em alta frequência entre janeiro de 2008 e junho de 2013, estimaram-se...

This study aims to analyze price discovery in the foreign exchange market in Brazil and indicate which market (spot or futures) adjusts more quickly to the arrival of new information. Using high frequency data from January/2008 to June/2013, we estimate the following price discovery metrics:...

In this paper we consider a nonlinear model based on neural networks as well as linear models to forecast the daily volatility of the S&P 500 and FTSE 100 indexes. As a proxy for daily volatility, we consider a consistent and unbiased estimator of the integrated volatility that is computed from...

In this paper, we introduce a linearity test for fuzzy rule-based models in the framework of time series modeling. To do so, we explore a family of statistical models, the regime switching autoregressive models, and the relations that link them to the fuzzy rule-based models. From these...

In this paper we introduce a linear programming estimator (LPE) for the slope parameter in a constrained linear regression model with a single regressor. The LPE is interesting because it can be superconsistent in the presence of an endogenous regressor and, hence, preferable to the ordinary...

We consider a new method to estimate causal effects when a treated unit suffers a shock or an intervention, such as a policy change, but there is not a readily available control group or counterfactual. We propose a two-step approach where in the first stage an artificial counterfactual is...