Given time series market observations for a price process, the parameters in an assumed underlying model can be determined through maximum likelihood estimation. Transition probability densities need to be estimated between each pair of data points. We show that Gaussian radial basis function approximation of the Fokker-Planck equations for the densities leads to a convenient mathematical representation. We present numerical results for one and two factor interest rate models
In order to determine prices of pricing financial derivatives such as options, numerical methods mus...
In this article we present a new model of the spot interest rate and a new method of estimation of n...
Closed-form explicit formulas for implied Black–Scholes volatilities provide a rapid evaluation meth...
We consider an n-dimensional square root process and we obtain a formula involving series expansions...
Nonlinear multivariate statistical techniques on fast computers offer the potential to capture mor...
We propose a method of function approximation by radial basis function networks. We will demonstrate...
We propose a method of function approximation by radial basis function networks. We will demonstrate...
We consider the problem of computing the survival (first-passage) probability density function of ju...
This paper overviews maximum likelihood and Gaussian methods of estimating contin-uous time models u...
This paper will demonstrate how European and American option prices can be computed under the jump-d...
<p>This dissertations presents the estimation methods of financial models for which the density func...
This paper develops a new econometric method to estimate continuous time processes from discretely s...
The general scheme of approximation supposes the existence of a relationship between several variabl...
This paper estimates stochastic differential equation models for the interest rate dynamics of the U...
This paper overviews maximum likelihood and Gaussian methods of estimating continuous time models us...
In order to determine prices of pricing financial derivatives such as options, numerical methods mus...
In this article we present a new model of the spot interest rate and a new method of estimation of n...
Closed-form explicit formulas for implied Black–Scholes volatilities provide a rapid evaluation meth...
We consider an n-dimensional square root process and we obtain a formula involving series expansions...
Nonlinear multivariate statistical techniques on fast computers offer the potential to capture mor...
We propose a method of function approximation by radial basis function networks. We will demonstrate...
We propose a method of function approximation by radial basis function networks. We will demonstrate...
We consider the problem of computing the survival (first-passage) probability density function of ju...
This paper overviews maximum likelihood and Gaussian methods of estimating contin-uous time models u...
This paper will demonstrate how European and American option prices can be computed under the jump-d...
<p>This dissertations presents the estimation methods of financial models for which the density func...
This paper develops a new econometric method to estimate continuous time processes from discretely s...
The general scheme of approximation supposes the existence of a relationship between several variabl...
This paper estimates stochastic differential equation models for the interest rate dynamics of the U...
This paper overviews maximum likelihood and Gaussian methods of estimating continuous time models us...
In order to determine prices of pricing financial derivatives such as options, numerical methods mus...
In this article we present a new model of the spot interest rate and a new method of estimation of n...
Closed-form explicit formulas for implied Black–Scholes volatilities provide a rapid evaluation meth...
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