In this paper, we consider daily financial data of a collection of different stock market indices, exchange rates, and interest rates, and we analyze their multi-scaling properties by estimating a simple specification of the Markov- switching multifractal model (MSM). In order to see how well...

We introduce a multistep-ahead forecasting methodology that combines empirical mode decomposition (EMD) and support vector regression (SVR). This methodology is based on the idea that the forecasting task is simplified by using as input for SVR the time series decomposed with EMD. The outcomes...

In this paper, we consider daily financial data from various sources (stock market indices, foreign exchange rates and bonds) and analyze their multiscaling properties by estimating the parameters of a Markov-switching multifractal (MSM) model with Lognormal volatility components. In order to...

We perform a careful spectral analysis of the correlation structures observed in real and financial returns for a large pool of long-lived US corporations, and find that financial returns are characterized by strong collective fluctuations that are absent from real returns. Once the excessive...

The main contribution of this work consist on studying sales behaviour and their relationship with local market conditions like labor market indicators through a time series principal component analysis. We study the correlation structure of a large database on prices and found that all product...