Time series analysis and computational finance.

Routines for the analysis of nonlinear time series. This
        work is largely inspired by the TISEAN project, by Rainer
        Hegger, Holger Kantz and Thomas Schreiber:
        <http://www.mpipks-dresden.mpg.de/~tisean/>.

Implements an Entropy measure of dependence based on the Bhattacharya-Hellinger-Matusita distance. Can be used as a (nonlinear) autocorrelation/crosscorrelation function for continuous and categorical time series. The package includes tests for serial and cross dependence and nonlinearity based on it. Some routines have a parallel version that can be used in a multicore/cluster environment. The package makes use of S4 classes.

Multiscale multifractal analysis (MMA) (Gierałtowski et al.,
    2012)<DOI:10.1103/PhysRevE.85.021915> is a time series analysis method,
    designed to describe scaling properties of fluctuations within the signal
    analyzed. The main result of this procedure is the so called Hurst surface
    h(q,s) , which is a dependence of the local Hurst exponent h (fluctuation
    scaling exponent) on the multifractal parameter q and the scale of observation s
    (data window width).

Routines for nonlinear time series analysis based on Threshold Autoregressive Moving Average (TARMA) models. It provides functions and methods for: TARMA model fitting and forecasting, including robust estimators, see Goracci et al. JBES (2025) <doi:10.1080/07350015.2024.2412011>; tests for threshold effects, see Giannerini et al. JoE (2024) <doi:10.1016/j.jeconom.2023.01.004>, Goracci et al. Statistica Sinica (2023) <doi:10.5705/ss.202021.0120>, Angelini et al. (2024) <doi:10.48550/arXiv.2308.00444>;  unit-root tests based on TARMA models, see Chan et al. Statistica Sinica (2024) <doi:10.5705/ss.202022.0125>.

A set of tools designed to perform descriptive data analysis on assets, manage asset portfolios and capital allocation, and download, organize, and maintain data from the "Tehran Stock Exchange" and "NOBITEX" platforms.