In this paper we test the ability of three of the most popular methods to forecast the South African currency crisis of June 2006. In particular we are interested in the out-ofsample performance of these methods. Thus, we choose the latest crisis to conduct an out-of-sample experiment. In sum,...

This paper studies the performance of nonparametric quantile regression as a tool to predict Value at Risk (VaR). The approach is flexible as it requires no assumptions on the form of return distributions. A monotonized double kernel local linear estimator is applied to estimate moderate (1%)...

This paper surveys the techniques of wavelets analysis and the associated methods of denoising. The Discrete Wavelet Transform and its undecimated version, the Maximum Overlapping Discrete Wavelet Transform, are described. The methods of wavelets analysis can be used to show how the frequency...

This paper studies the performance of nonparametric quantile regression as a tool to predict Value at Risk (VaR). The approach is flexible as it requires no assumptions on the form of return distributions. A monotonized double kernel local linear estimator is applied to estimate moderate (1%)...

In this paper we test the ability of three of the most popular methods to forecast the South African currency crisis of June 2006. In particular we are interested in the out-ofsample performance of these methods. Thus, we choose the latest crisis to conduct an out-of-sample experiment. In sum,...

In this paper, we explore machine learning (ML) methods to improve inflation forecasting in Brazil. An extensive out-of-sample forecasting exercise is designed with multiple horizons, a large database of 501 series, and 50 forecasting methods, including new ML techniques proposed here,...

Consider forecasting the economic variable Y_{t h} with predictors X_{t}, where h is the forecast horizon. This paper introduces a semiparametric method that generates forecast intervals of Y_{t h}|X_{t} from point forecast models. First, the point forecast model is estimated, thereby taking...

We investigate price duration variance estimators that have long been neglected in the literature. We show i) how price duration estimators can be used for the estimation and forecasting of the integrated variance of an underlying semi-martingale price process and ii) how they are affected by a)...