This paper discusses two classes of distributions, and stochastic processes derived from them: modified stable (MS) laws and normal modified stable (NMS) laws. This extends corresponding results for the generalised inverse Gaussian (GIG) and generalised hyperbolic (GH) or normal generalised inverse Gaussian (NGIG) laws. The wider framework thus established provides, in particular, for added flexibility in the modelling of the dynamics of financial time series, of importance especially as regards OU based stochastic volatility models for equities. In the special case of the tempered stable OU process an exact option pricing formula can be found, extending previous results based on the inverse Gaussian and gamma distributions
and the Deutschen Forschungsgemeinschaft. †Michele Leonardo Bianchi’s research was supported by a Ph...
In this paper, we introduce a new time series model having a stochastic exponential tail. This model...
The focus of this paper is the use of stable distributions for GARCH models. Such models are applied...
This paper discusses two classes of distributions, and stochastic processes derived from them: modif...
In this contribution, a basic theoretical approach to stable laws is described. There are mentioned ...
The normal inverse Gaussian (NIG) process is a Lévy process with no Brownian component and NIG-distr...
The normal inverse Gaussian (NIG) process is a Lévy process with no Brownian component and NIG-distr...
The normal inverse Gaussian (NIG) process is a Lévy process with no Brownian component and NIG-distr...
Abstract. We introduce a new variant of the tempered stable distribu-tion, named the modified temper...
1 In this paper, we will discuss a parametric approach to risk-neutral density extraction from optio...
We discuss the Normal inverse Gaussian (NIG) distribution in modeling volatility in the financial ma...
This brief is concerned with tempered stable distributions and their associated Levy processes. It i...
Normal inverse Gaussian (NIG) distribution is quite a new distribution introduced in 1997. This is d...
In this paper, we introduce a new time series model having a stochastic exponential tail. This model...
In this paper, we introduce a new time series model having a stochastic exponential tail. This model...
and the Deutschen Forschungsgemeinschaft. †Michele Leonardo Bianchi’s research was supported by a Ph...
In this paper, we introduce a new time series model having a stochastic exponential tail. This model...
The focus of this paper is the use of stable distributions for GARCH models. Such models are applied...
This paper discusses two classes of distributions, and stochastic processes derived from them: modif...
In this contribution, a basic theoretical approach to stable laws is described. There are mentioned ...
The normal inverse Gaussian (NIG) process is a Lévy process with no Brownian component and NIG-distr...
The normal inverse Gaussian (NIG) process is a Lévy process with no Brownian component and NIG-distr...
The normal inverse Gaussian (NIG) process is a Lévy process with no Brownian component and NIG-distr...
Abstract. We introduce a new variant of the tempered stable distribu-tion, named the modified temper...
1 In this paper, we will discuss a parametric approach to risk-neutral density extraction from optio...
We discuss the Normal inverse Gaussian (NIG) distribution in modeling volatility in the financial ma...
This brief is concerned with tempered stable distributions and their associated Levy processes. It i...
Normal inverse Gaussian (NIG) distribution is quite a new distribution introduced in 1997. This is d...
In this paper, we introduce a new time series model having a stochastic exponential tail. This model...
In this paper, we introduce a new time series model having a stochastic exponential tail. This model...
and the Deutschen Forschungsgemeinschaft. †Michele Leonardo Bianchi’s research was supported by a Ph...
In this paper, we introduce a new time series model having a stochastic exponential tail. This model...
The focus of this paper is the use of stable distributions for GARCH models. Such models are applied...