Approximation theory suggests that series expansions and projections represent standard tools for random process applications from both numerical and statistical standpoints. Such instruments emphasize the role of both sparsity and smoothness for compression purposes, the decorrelation power...

We consider an approach for modeling non-stationary and non-Gaussian curves which has a natural impact on financial time series analysis due to the characteristic features of volatility processes. Provided that one can approximate the signal of interest, in this case stock index returns, with a...

We aim to investigate the potential usefulness of wavelets for representing and decomposing financial volatility processes. Our strategy relies on the empirical analysis of high-frequency intradaily stock index returns by using adaptive signal-processing techniques which exploit the...