Fractional Brownian motion time-changed by gamma and inverse gamma process
A. Kumar, A. Wy{\l}oma\'nska, R. Po{\l}ocza\'nski, S. Sundar

TL;DR
This paper introduces two new long-range dependent processes constructed as superpositions of fractional Brownian motion with gamma and inverse gamma processes, analyzing their properties, simulation, and parameter estimation methods.
Contribution
It presents novel long-range dependent models based on fractional Brownian motion with gamma and inverse gamma time changes, including their properties and estimation techniques.
Findings
Both processes exhibit long-range dependence.
The proposed estimation method is effective for rounded data.
Simulation results validate the estimation procedures.
Abstract
Many real time-series exhibit behavior adequate to long range dependent data. Additionally very often these time-series have constant time periods and also have characteristics similar to Gaussian processes although they are not Gaussian. Therefore there is need to consider new classes of systems to model these kind of empirical behavior. Motivated by this fact in this paper we analyze two processes which exhibit long range dependence property and have additional interesting characteristics which may be observed in real phenomena. Both of them are constructed as the superposition of fractional Brownian motion (FBM) and other process. In the first case the internal process, which plays role of the time, is the gamma process while in the second case the internal process is its inverse. We present in detail their main properties paying main attention to the long range dependence property.…
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