This paper introduces a new hybrid approach for learning systems that builds on the theory of nonextensive statistical mechanics. The proposed learning scheme uses only the sign of the gradient, and combines adaptive stepsize local searches with global search steps that make use of an annealing...

This investigation integrates a novel hybrid asymmetric volatility approach into an Artificial Neural Networks option-pricing model to upgrade the forecasting ability of the price of derivative securities. The use of the new hybrid asymmetric volatility method can simultaneously decrease the...

Artificial neural networks (ANNs) have been successfully used for solving variety of problems. One major disadvantage of ANNs is that there is no formal systematic model building approach. This paper presents the application of the Taguchi method in the optimization of the design parameters of...

The detrended fluctuation analysis (DFA) is used to sort out temporal correlations in financial data. Its usefulness for the investigations of long-range power-law correlations in economic sequences is shown. Our findings of persistent and antipersistent sequences are suprisingly similar to...

We study the multifractal temporal scaling properties of river discharge and precipitation records. We compare the results for the multifractal detrended fluctuation analysis method with the results for the wavelet-transform modulus maxima technique and obtain agreement within the error margins....

By means of factorial moments (FM), the fractal structures embedded in gait time series are investigated. Intermittency is found in records for healthy objects. And this kind of intermittency is much sensitive to disease or outside influences. It is found that FM is an effective tool to deal...

Factor analysis is a well known statistical method to describe the variability among observed variables in terms of a smaller number of unobserved latent variables called factors. While dealing with multivariate time series, the temporal correlation structure of data may be modeled by including...

The characterization of the erythrocytes’ viscoelastic properties is studied from the perspective of bounded correlated random walk (Brownian motion), based on the assumption that diffractometric data involves both deterministic and stochastic components. The photometric readings are obtained...

A stochastic-optimization technique based on time series cluster analysis is described for index tracking and enhanced index tracking problems. Our methodology solves the problem in two steps, i.e., by first selecting a subset of stocks and then setting the weight of each stock as a result of an...

Recurrence plot is a quite easy tool to be used in time-series analysis, in particular for measuring unstable periodic orbits embedded in a chaotic dynamical system. Recurrence quantified analysis (RQA) is an advanced tool that allows the study of intrinsic complexity of a dynamical system with...