The recent literature on high frequency financial data includes models that use the difference of two Poisson processes, and incorporate a Skellam distribution for forward prices. The exponential distribution of inter-arrival times in these models is not always supported by data. Fractional generalization of Poisson process, or fractional Poisson process, overcomes this limitation and has Mittag-Leffler distribution of inter-arrival times. This paper defines fractional Skellam processes via the time changes in Poisson and Skellam processes by an inverse of a standard stable subordinator. An application to high frequency financial data set is provided to illustrate the advantages of models based on fractional Skellam processes
The fractional Poisson process (FPP) is a counting process with independent and identically distribu...
We introduce a non-homogeneous fractional Poisson process by replacing the time variable in the frac...
The Poisson process suitably models the time of successive events and thus has numerous applications...
The recent literature on high frequency financial data includes models that use the difference of tw...
In this article, we introduce the Skellam process of order k and its running average. We also discus...
The space-fractional and the time-fractional Poisson processes are two well-known models of fraction...
We study here different fractional versions of the compound Poisson process. The fractionality is in...
We study here different fractional versions of the compound Poisson process. The fractionality is in...
Motivated by features of low latency data in finance we study in detail discrete-valued Levy process...
Motivated by features of low latency data in finance we study in detail discrete-valued Levy process...
Fractional Lévy process is a relatively new term from stochastic calculus. Its main use is in physic...
We consider a fractional counting process with jumps of amplitude $1,2,\ldots,k$, with $k\in \math...
We consider two fractional versions of a family of nonnegative integer-valued processes. We prove th...
We present some correlated fractional counting processes on a finite time interval. This will be don...
In this study we consider the fractional Ornstein-Uhlenbeck processes driven by α-stable Levy motion...
The fractional Poisson process (FPP) is a counting process with independent and identically distribu...
We introduce a non-homogeneous fractional Poisson process by replacing the time variable in the frac...
The Poisson process suitably models the time of successive events and thus has numerous applications...
The recent literature on high frequency financial data includes models that use the difference of tw...
In this article, we introduce the Skellam process of order k and its running average. We also discus...
The space-fractional and the time-fractional Poisson processes are two well-known models of fraction...
We study here different fractional versions of the compound Poisson process. The fractionality is in...
We study here different fractional versions of the compound Poisson process. The fractionality is in...
Motivated by features of low latency data in finance we study in detail discrete-valued Levy process...
Motivated by features of low latency data in finance we study in detail discrete-valued Levy process...
Fractional Lévy process is a relatively new term from stochastic calculus. Its main use is in physic...
We consider a fractional counting process with jumps of amplitude $1,2,\ldots,k$, with $k\in \math...
We consider two fractional versions of a family of nonnegative integer-valued processes. We prove th...
We present some correlated fractional counting processes on a finite time interval. This will be don...
In this study we consider the fractional Ornstein-Uhlenbeck processes driven by α-stable Levy motion...
The fractional Poisson process (FPP) is a counting process with independent and identically distribu...
We introduce a non-homogeneous fractional Poisson process by replacing the time variable in the frac...
The Poisson process suitably models the time of successive events and thus has numerous applications...