Mohamed Anis Ben Lasmar | ESPRIT (original) (raw)
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Papers by Mohamed Anis Ben Lasmar
arXiv (Cornell University), Feb 2, 2013
This paper investigates a numerical probabilistic method for the solution of some semilinear stoc... more This paper investigates a numerical probabilistic method for the solution of some semilinear stochastic partial differential equations (SPDEs in short). The numerical scheme is based on discrete time approximation for solutions of systems of decoupled forward-backward doubly stochastic differential equations. Under standard assumptions on the parameters, the convergence and the rate of convergence of the numerical scheme is proven. The proof is based on a generalization of the result on the path regularity of the backward equation.
SSRN Electronic Journal, 2021
Financial data, related to companies listed on the Tunisian Stock Exchange, were collected and an... more Financial data, related to companies listed on the Tunisian Stock Exchange, were collected and analyzed according to the methodology applied in machine learning on over two different time periods. A particular interest was focused on the periods before and during the Covid-19 crisis. The results obtained in this paper show, on the one hand, that an empirical diversification based on unsupervised learning algorithms is possible and on the other hand, a good coherence with the corporates financial state in Tunisia. This paper shows, for instance, that the k-means algorithm makes it possible to segment companies according to several criteria and to discover the aberrant behavior of certain companies with an abnormal financial situation. These results were confirmed by other outlier detection algorithms.
Stochastics and Partial Differential Equations: Analysis and Computations, 2016
This paper investigates a numerical probabilistic method for the solution of some semilinear stoc... more This paper investigates a numerical probabilistic method for the solution of some semilinear stochastic partial differential equations (SPDEs in short). The numerical scheme is based on discrete time approximation for solutions of systems of decoupled forward-backward doubly stochastic differential equations. Under standard assumptions on the parameters, the convergence and the rate of convergence of the numerical scheme is proven. The proof is based on a generalization of the result on the path regularity of the backward equation.
arXiv (Cornell University), Feb 2, 2013
This paper investigates a numerical probabilistic method for the solution of some semilinear stoc... more This paper investigates a numerical probabilistic method for the solution of some semilinear stochastic partial differential equations (SPDEs in short). The numerical scheme is based on discrete time approximation for solutions of systems of decoupled forward-backward doubly stochastic differential equations. Under standard assumptions on the parameters, the convergence and the rate of convergence of the numerical scheme is proven. The proof is based on a generalization of the result on the path regularity of the backward equation.
SSRN Electronic Journal, 2021
Financial data, related to companies listed on the Tunisian Stock Exchange, were collected and an... more Financial data, related to companies listed on the Tunisian Stock Exchange, were collected and analyzed according to the methodology applied in machine learning on over two different time periods. A particular interest was focused on the periods before and during the Covid-19 crisis. The results obtained in this paper show, on the one hand, that an empirical diversification based on unsupervised learning algorithms is possible and on the other hand, a good coherence with the corporates financial state in Tunisia. This paper shows, for instance, that the k-means algorithm makes it possible to segment companies according to several criteria and to discover the aberrant behavior of certain companies with an abnormal financial situation. These results were confirmed by other outlier detection algorithms.
Stochastics and Partial Differential Equations: Analysis and Computations, 2016
This paper investigates a numerical probabilistic method for the solution of some semilinear stoc... more This paper investigates a numerical probabilistic method for the solution of some semilinear stochastic partial differential equations (SPDEs in short). The numerical scheme is based on discrete time approximation for solutions of systems of decoupled forward-backward doubly stochastic differential equations. Under standard assumptions on the parameters, the convergence and the rate of convergence of the numerical scheme is proven. The proof is based on a generalization of the result on the path regularity of the backward equation.