J. L. Pedersen and G. Peskir. The Azema-Yor embedding in non-singular di usions. Stochastic Process. Appl., 96(2):305-312, 2001. Home/Search Document Not in Database Summary Related Articles Check |
This paper is cited in the following contexts:
An Optimal Skorokhod Embedding for Diffusions - Cox, Hobson (2002) (Correct)
....it is completely natural for the target measure to have non zero mean in the Brownian scale. We will see that our embedding is a natural one to use in this situation, and we are able to identify the cases where it is possible to embed a given target distribution, thus rederiving a result in [6]. We also identify some properties of the maximum and minimum of the processes in these cases. Our results in this direction can be seen as an extension of the results in [4] for drifting Brownian motion) and [6] However in this last paper the authors use an extension of the Azema Yor embedding ....
....it is possible to embed a given target distribution, thus rederiving a result in [6] We also identify some properties of the maximum and minimum of the processes in these cases. Our results in this direction can be seen as an extension of the results in [4] for drifting Brownian motion) and [6]. However in this last paper the authors use an extension of the Azema Yor embedding which may not be de ned in certain cases of interest. Thus our construction of a Skorokhod embedding is both di erent to, and more general than, the embedding in [6] The remainder of the article is structured ....
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J. L. Pedersen and G. Peskir. The Azema-Yor embedding in non-singular di usions. Stochastic Process. Appl., 96(2):305-312, 2001.
An Optimal Skorokhod Embedding for Di usions A.M.G. Cox - And Hobson Department (Correct)
No context found.
J. L. Pedersen and G. Peskir. The Azema-Yor embedding in non-singular di usions. Stochastic Process. Appl., 96(2):305-312, 2001.
An Optimal Skorokhod Embedding for Diffusions - Cox, Hobson (2002) (Correct)
No context found.
J. L. Pedersen and G. Peskir. The Azema-Yor embedding in non-singular di usions. Stochastic Process. Appl., 96(2):305-312, 2001.
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