Sample Path Bounds for Long Memory FBM Traffic

Author(s):  
Amr Rizk ◽  
Markus Fidler
Keyword(s):  
2021 ◽  
Vol 9 (1) ◽  
pp. 141-155
Author(s):  
Jeonghwa Lee

Abstract A generalized Bernoulli process (GBP) is a stationary process consisting of binary variables that can capture long-memory property. In this paper, we propose a simulation method for a sample path of GBP and an estimation method for the parameters in GBP. Method of moments estimation and maximum likelihood estimation are compared through empirical results from simulation. Application of GBP in earthquake data during the years of 1800-2020 in the region of conterminous U.S. is provided.


Risks ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 2
Author(s):  
Donatien Hainaut

This article proposes an interest rate model ruled by mean reverting Lévy processes with a sub-exponential memory of their sample path. This feature is achieved by considering an Ornstein–Uhlenbeck process in which the exponential decaying kernel is replaced by a Mittag–Leffler function. Based on a representation in term of an infinite dimensional Markov processes, we present the main characteristics of bonds and short-term rates in this setting. Their dynamics under risk neutral and forward measures are studied. Finally, bond options are valued with a discretization scheme and a discrete Fourier’s transform.


1984 ◽  
Vol 29 (7) ◽  
pp. 576-577
Author(s):  
Leonard D. Stern
Keyword(s):  

Bernoulli ◽  
2020 ◽  
Vol 26 (2) ◽  
pp. 1473-1503 ◽  
Author(s):  
Shuyang Bai ◽  
Murad S. Taqqu

2005 ◽  
Vol 7 (4) ◽  
pp. 21-45 ◽  
Author(s):  
Andrea Beltratti ◽  
Claudio Morana
Keyword(s):  
At Risk ◽  

2008 ◽  
Author(s):  
Gianluca Moretti ◽  
Giulio Nicoletti
Keyword(s):  

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