This paper deals with the problem of estimating the parameters of mixed Brownian–fractional Brownian motions with the combination of maximum likelihood approach and Powell's method. The maximum likelihood estimators are obtained based on the approximation by random walks of the driving noise....

Abstract In this paper, we develop a stochastic model to analyze how financial contagion may affect economic activity. In the deterministic case, we show that, according to specific parameter values, the economy may converge either to a stress-free equilibrium or to a stressed equilibrium: in...

We consider an investor who has available a bank account (risk free asset) and a stock (risky asset). It is assumed that the interest rate for the risk free asset is zero and the stock price is modeled by a diffusion process. The wealth can be transferred between the two assets under a...

We study the continuous-time limit of a class of Markov chains coming from the evolution of classical open systems undergoing repeated interactions. This repeated interaction model has been initially developed for dissipative quantum systems in Attal and Pautrat (2006) and was recently set up...

A systematic Bayesian framework is developed for physics constrained parameter inference of stochastic differential equations (SDE) from partial observations. Physical constraints are derived for stochastic climate models but are applicable for many fluid systems. A condition is derived for...

We describe a method of approximation of strong solutions to Stratonovich differential equations, that depends only on the Brownian motion defining the equation. h being the step size, it is known that the order of convergence of such approximations is h in the general case, and of h in some...

We propose a method for the simultaneous estimation of the drift and diffusion coefficients of stochastic differential equations (SDE) from panel data. The method involves matching the distribution of the experimental/field data with a panel of simulated data generated by a Monte Carlo...