Add to ORKGWe propose a method of function approximation by radial basis function networks. We will demonstrate that this approximation method can be improved by a pre-treatment of data based on a linear model. This approximation method will be applied to option pricing. This choice justifies itself through the known nonlinear nature of the behavior of options price and through the effective contribution of the pre-treatment proposed for the implementation of radial basis function networks in this field
The aim of this paper is to show how option prices in the Jump-diffusion model can be computed using...
We propose a local mesh-free method for the Bates-Scott option pricing model, a 2D partial integro-d...
We use Radial Basis Function (RBF) interpolation to price options in exponential Lévy models by nume...
We propose a method of function approximation by radial basis function networks. We will demonstrate...
The general scheme of approximation supposes the existence of a relationship between several variabl...
AbstractIn this paper, we have derived a radial basis function (RBF) based method for the pricing of...
Radial basis function (RBF) approximation, is a new extremely powerful tool that is promising for hi...
In this thesis, we have developed meshless adaptive radial basis functions (RBFs) method for the pri...
In order to determine prices of pricing financial derivatives such as options, numerical methods mus...
In this article we focus on option Greeks computation by means of Radial Basis Functions (RBF) with ...
This thesis discusses the valuation of embedded options in insurance liabilities using radial basis ...
This paper will demonstrate how European and American option prices can be computed under the jump-d...
The price of an option can under some assumptions be determined by the solution of the Black–Scholes...
The aim of this paper is to show that option prices in jump-diffusion models can be computed using m...
In this thesis we price several financial derivatives by means of radial basis functions. Our main c...
The aim of this paper is to show how option prices in the Jump-diffusion model can be computed using...
We propose a local mesh-free method for the Bates-Scott option pricing model, a 2D partial integro-d...
We use Radial Basis Function (RBF) interpolation to price options in exponential Lévy models by nume...
We propose a method of function approximation by radial basis function networks. We will demonstrate...
The general scheme of approximation supposes the existence of a relationship between several variabl...
AbstractIn this paper, we have derived a radial basis function (RBF) based method for the pricing of...
Radial basis function (RBF) approximation, is a new extremely powerful tool that is promising for hi...
In this thesis, we have developed meshless adaptive radial basis functions (RBFs) method for the pri...
In order to determine prices of pricing financial derivatives such as options, numerical methods mus...
In this article we focus on option Greeks computation by means of Radial Basis Functions (RBF) with ...
This thesis discusses the valuation of embedded options in insurance liabilities using radial basis ...
This paper will demonstrate how European and American option prices can be computed under the jump-d...
The price of an option can under some assumptions be determined by the solution of the Black–Scholes...
The aim of this paper is to show that option prices in jump-diffusion models can be computed using m...
In this thesis we price several financial derivatives by means of radial basis functions. Our main c...
The aim of this paper is to show how option prices in the Jump-diffusion model can be computed using...
We propose a local mesh-free method for the Bates-Scott option pricing model, a 2D partial integro-d...
We use Radial Basis Function (RBF) interpolation to price options in exponential Lévy models by nume...