Título:
An algorithm to solve optimal stopping problems for onedimensional diffusions
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Autor:
Crocce, Fabián
Mordecki, Ernesto
Mordecki, Ernesto
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Tipo de documento:
Artículo
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Año de publicación:
2022
Contenido:
Resumen:
Considering a real-valued diffusion, a real-valued reward function and a positive discount rate, we provide an algorithm to solve the optimal stopping problem consisting in finding the optimal expected discounted reward and the optimal stopping time at which it is attained. Our approach is based on Dynkin’s characterization of the value function. The combination of Riesz’s representation of α-excessive functions and the inversion formula gives the density of the representing measure, being only necessary to determine its support. This last task is accomplished through an algorithm. The proposed method always arrives to the solution, thus no verification is needed, giving, in particular, the shape of the stopping region. Generalizations to diffusions with atoms in the speed
measure and to non smooth payoffs are analyzed
Descripción:
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Editorial:
ALEA
EN:
Latin American Journal of Probability and Mathematical Statistics, 2022, 19: 1353–1375
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Citación:
Crocce, F y Mordecki, E. "An algorithm to solve optimal stopping problems for onedimensional diffusions". Latin American Journal of Probability and Mathematical Statistics. [en línea] 2022, 19: 1353–1375. 23 h. DOI:10.30757/ALEA.v19-54
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ISSN:
1980-0436
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Licencia:
Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0)
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| Ficheros | Descripción | Tamaño | Formato | ||
|---|---|---|---|---|---|
| 19-54.pdf | — | 594.02 KB | Adobe PDF |