The Skorokhod Embedding problem is well understood when the underlying process is a Brownian motion. We examine the problem when the underlying is the simple symmetric random walk and when no external randomisation is allowed. We prove that any measure on Z can be embedded by means of a minimal stopping time. However, in sharp contrast to the Brownian setting, we show that the set of measures which can be embedded in a uniformly integrable way is strictly smaller then the set of centered probability measures: specifically it is a fractal set which we characterise as an iterated function system. Finally, we define the natural extension of several known constructions from the Brownian setting and show that these constructions require us to fu...
The classical Skorokhod embedding problem for a Brownian motion W asks to find a stopping time τ so ...
AbstractWe develop an explicit non-randomized solution to the Skorokhod embedding problem in an abst...
AbstractSuppose Sn is a mean zero, variance one random walk. Under suitable assumptions on the incre...
We characterize the possible distributions of a stopped simple symmetric random walk Xτ, where τ is ...
AbstractGiven a Brownian motion (Bt)t⩾0 and a general target law μ (not necessarily centered or even...
Motivated by problems in behavioural finance, we provide two explicit constructions of a randomized ...
Suppose X is a time-homogeneous diffusion on an interval IX⊆R and let μ be a probability measure on ...
desirable Type: Theoretical project with potential for a simulation component Description: The class...
With the help of two Skorokhod embeddings, we construct martingales which enjoy the Brownian scaling...
In this work, a class of stopping times for one-dimensional Brownian motion is examined--one which m...
Integrability of solutions of the Skorokhod embedding problem for diffusions David Hobson* Suppose X...
International audienceThe Skorokhod embedding problem aims to represent a given probability measure ...
AbstractWe consider the embedding of a probability distribution in Brownian motion with drift. We fi...
AbstractLet (Xt)t⩾0 be a non-singular (not necessarily recurrent) diffusion on R starting at zero, a...
We solve the Skorokhod embedding problem (SEP) for a general time-homogeneous diffusion X: given a d...
The classical Skorokhod embedding problem for a Brownian motion W asks to find a stopping time τ so ...
AbstractWe develop an explicit non-randomized solution to the Skorokhod embedding problem in an abst...
AbstractSuppose Sn is a mean zero, variance one random walk. Under suitable assumptions on the incre...
We characterize the possible distributions of a stopped simple symmetric random walk Xτ, where τ is ...
AbstractGiven a Brownian motion (Bt)t⩾0 and a general target law μ (not necessarily centered or even...
Motivated by problems in behavioural finance, we provide two explicit constructions of a randomized ...
Suppose X is a time-homogeneous diffusion on an interval IX⊆R and let μ be a probability measure on ...
desirable Type: Theoretical project with potential for a simulation component Description: The class...
With the help of two Skorokhod embeddings, we construct martingales which enjoy the Brownian scaling...
In this work, a class of stopping times for one-dimensional Brownian motion is examined--one which m...
Integrability of solutions of the Skorokhod embedding problem for diffusions David Hobson* Suppose X...
International audienceThe Skorokhod embedding problem aims to represent a given probability measure ...
AbstractWe consider the embedding of a probability distribution in Brownian motion with drift. We fi...
AbstractLet (Xt)t⩾0 be a non-singular (not necessarily recurrent) diffusion on R starting at zero, a...
We solve the Skorokhod embedding problem (SEP) for a general time-homogeneous diffusion X: given a d...
The classical Skorokhod embedding problem for a Brownian motion W asks to find a stopping time τ so ...
AbstractWe develop an explicit non-randomized solution to the Skorokhod embedding problem in an abst...
AbstractSuppose Sn is a mean zero, variance one random walk. Under suitable assumptions on the incre...