Financial time series analysis based on information categorization method

Financial Time Series Analysis Based On Normalized Mutual Information Functions

A method of predictability analysis of future values of financial time series is described. The method is based on normalized mutual information functions. In the analysis, the use of these functions allowed to refuse any restrictions on the distributions of the parameters and on the correlations between parameters. A comparative analysis of the predictability of financial time series of Tel Av...

Frequency-based Analysis of Financial Time Series

Discrimination of time series based on kernel method

Classical methods in discrimination such as linear and quadratic do not have good efficiency in the case of nongaussian or nonlinear time series data. In nonparametric kernel discrimination in which the kernel estimators of likelihood functions are used instead of their real values has been shown to have good performance. The misclassification rate of kernel discrimination is usually less than ...

Interpolating time series based on fuzzy cluster analysis problem

This study proposes the model for interpolating time series to use them  to forecast effectively for future. This model is established based on the improved fuzzy clustering analysis problem, which is implemented by the Matlab procedure. The proposed model is illustrated by a data set and tested for many other datasets, especially for 3003 series in  M3-Competition data. Comparing  to the exist...

Analysis of Satellite Image Time Series Based on Information Bottleneck

Derived from Information Theory, the Information Bottleneck principle enables to quantify and qualify the information contained in a signal. This paper presents an algorithm based on the Information Bottleneck principle to analyze Satellite Image Time Series (SITS). The method is composed of a parameter estimation and a model selection. This method has been previously applied to textural and ra...