scholarly journals Analytic approximation of the transition density function under a multi-scale volatility model

2017 ◽  
Vol 48 (4) ◽  
Author(s):  
Yong-Ki Ma
2017 ◽  
Vol 2017 ◽  
pp. 1-7
Author(s):  
Yong-Ki Ma

The transition density function plays an important role in understanding and explaining the dynamics of the stochastic process. In this paper, we incorporate an ergodic process displaying fast moving fluctuation into constant volatility models to express volatility clustering over time. We obtain an analytic approximation of the transition density function under our stochastic process model. Using perturbation theory based on Lie–Trotter operator splitting method, we compute the leading-order term and the first-order correction term and then present the left and right skew scenarios through numerical study.


2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Carlo Cattani ◽  
Armando Ciancio

In this paper, the hybrid kinetic models of tumor-immune system competition are studied under the assumption of pure competition. The solution of the coupled hybrid system depends on the symmetry of the state transition density which characterizes the probability of successful occurrences. Thus by defining a proper transition density function, the solutions of the hybrid system are explicitly computed and applied to a classical (realistic) model of competing populations.


2021 ◽  
Vol 2 (1) ◽  
pp. 01-11
Author(s):  
Ahmed Nafidi ◽  
Oussama Rida ◽  
Boujemaa Achchab

A new stochastic diffusion process based on Generalized Brody curve is proposed. Such a process can be considered as an extension of the nonhomogeneous lognormal diffusion process. From the corresponding Itô’s stochastic differential equation (SDE), firstly we establish the probabilistic characteristics of the studied process, such as the solution to the SDE, the probability transition density function and their distribution, the moments function, in particular the conditional and non-conditional trend functions. Secondly, we treat the parameters estimation problem by using the maximum likelihood method in basis of the discrete sampling, thus we obtain nonlinear equations that can be solved by metaheuristic optimization algorithms such as simulated annealing and variable search neighborhood. Finally, we perform a simulation studies and we apply the model to the data of life expectancy at birth in Morocco.


A stochastic model is proposed for the propagation of a fatigue crack. It is shown that fatigue crack growth can be described by a transition density function, and that the probability of a fatigue crack reaching a critical size can be determined by solving the diffusion equation. The commonly used rate of crack growth, d a /d N , appears in the diffusion model as the drift parameter.


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