We show the existence of a broad class of affine Markov processes on the cone of positive self-adjoint Hilbert–Schmidt operators. Such processes are well-suited as infinite-dimensional stochastic covariance models. The class of processes we consider is an infinite-dimensional analogue of the affine processes on the cone of positive semi-definite and symmetric matrices studied in Cuchiero et al. (2011). As in the finite-dimensional case, the processes we construct allow for a drift depending affine linearly on the state, as well as jumps governed by a jump measure that depends affine linearly on the state. The fact that the cone of positive self-adjoint Hilbert–Schmidt operators has empty interior calls for a new approach to proving existenc...
AbstractFor an arbitrary Hilbert space-valued Ornstein–Uhlenbeck process we construct the Ornstein–U...
Affine processes have been of great interest to researchers and financial practitioners for many yea...
The concept of pseudo-differential operators allows one to study stochastic processes through their ...
We show the existence of a broad class of affine Markov processes on the cone of positive self-adjoi...
We introduce a flexible and tractable infinite-dimensional stochastic volatility model. More specifi...
We introduce a flexible and tractable infinite-dimensional stochastic volatility model. More specifi...
We consider stochastic partial differential equations appearing as Markovian lifts of matrix-valued ...
AbstractThe theory of affine processes on the space of positive semidefinite d×d matrices has been e...
This article provides the mathematical foundation for stochastically continuous affine processes on ...
AbstractThe theory of affine processes on the space of positive semidefinite d×d matrices has been e...
The theory of affine processes has been recently extended to the framework of stochastic Volterra eq...
The theory of affine processes has been recently extended to the framework of stochastic Volterra eq...
The theory of affine processes has been recently extended to the framework of stochastic Volterra eq...
AbstractWe show the existence of unique global strong solutions of a class of stochastic differentia...
By using lower bound conditions of the Lévy measure w.r.t. a nice reference measure, the coupling a...
AbstractFor an arbitrary Hilbert space-valued Ornstein–Uhlenbeck process we construct the Ornstein–U...
Affine processes have been of great interest to researchers and financial practitioners for many yea...
The concept of pseudo-differential operators allows one to study stochastic processes through their ...
We show the existence of a broad class of affine Markov processes on the cone of positive self-adjoi...
We introduce a flexible and tractable infinite-dimensional stochastic volatility model. More specifi...
We introduce a flexible and tractable infinite-dimensional stochastic volatility model. More specifi...
We consider stochastic partial differential equations appearing as Markovian lifts of matrix-valued ...
AbstractThe theory of affine processes on the space of positive semidefinite d×d matrices has been e...
This article provides the mathematical foundation for stochastically continuous affine processes on ...
AbstractThe theory of affine processes on the space of positive semidefinite d×d matrices has been e...
The theory of affine processes has been recently extended to the framework of stochastic Volterra eq...
The theory of affine processes has been recently extended to the framework of stochastic Volterra eq...
The theory of affine processes has been recently extended to the framework of stochastic Volterra eq...
AbstractWe show the existence of unique global strong solutions of a class of stochastic differentia...
By using lower bound conditions of the Lévy measure w.r.t. a nice reference measure, the coupling a...
AbstractFor an arbitrary Hilbert space-valued Ornstein–Uhlenbeck process we construct the Ornstein–U...
Affine processes have been of great interest to researchers and financial practitioners for many yea...
The concept of pseudo-differential operators allows one to study stochastic processes through their ...