This paper develops a method to improve the estimation of jump variation using high frequency data with the existence of market microstructure noises. Accurate estimation of jump variation is in high demand, as it is an important component of volatility in finance for portfolio allocation,...

We consider noisy non-synchronous discrete observations of a continuous semimartingale. Functional stable central limit theorems are established under high-frequency asymptotics in three setups: onedimensional for the spectral estimator of integrated volatility, from two-dimensional asynchronous...

The present paper offers a careful description of empirical identification of possible multiple changes in regime. We apply recently developed tools designed to select between regime-switching models among a broad class of linear and nonlinear regression models and provide a discussion of the...

We propose a flexible GARCH-type model for the prediction of volatility in financial time series. The approach relies on the idea of using multivariate B-splines of lagged observations and volatilities. Estimation of such a B-spline basis expansion is constructed within the likelihood framework...

In recent years, numerous volatility-based derivative products have been engineered. This has led to interest in constructing conditional predictive densities and confidence intervals for integrated volatility. In this paper, we propose nonparametric kernel estimators of the aforementioned...

In this paper I propose a novel optimal linear filter for smoothing, trend and signal extraction for time series with a unit root. The filter is based on the Singular Spectrum Analysis (SSA) methodology, takes the form of a particular moving average and is different from other linear filters...

Spanish Abstract: La relación existente entre el riego y la rentabilidad de un activo financiero es una preocupación constante del inversionista a la hora de conformar su portafolio de inversión. La principal meta en la construcción del portafolio consiste en distribuir óptimamente la...

We propose a simple but flexible parametric method for estimating multiple conditional quantiles. By construction, the estimated quantiles will satisfy the monotonicity requirement which must hold for any distribution, so, in contrast to many benchmark methods, they are not susceptible to the...

We propose a general class of Markov-switching-ARFIMA processes in order to combine strands of long memory and Markov-switching literature. Although the coverage of this class of models is broad, we show that these models can be easily estimated with the DLV algorithm proposed. This algorithm...