{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,9]],"date-time":"2026-06-09T10:50:07Z","timestamp":1781002207639,"version":"3.54.1"},"reference-count":0,"publisher":"Walter de Gruyter GmbH","issue":"2","funder":[{"name":"ANR France","award":["LIQUIRISK (ANR-11-JS01-0007)"],"award-info":[{"award-number":["LIQUIRISK (ANR-11-JS01-0007)"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2014,6,1]]},"abstract":"<jats:title>Abstract.<\/jats:title>\n               <jats:p>We propose a probabilistic numerical algorithm to solve Backward Stochastic\nDifferential Equations (BSDEs) with nonnegative jumps, a class of BSDEs introduced in [`Feynman\u2013Kac representation for Hamilton\u2013Jacobi\u2013Bellman IPDE', Ann. Probab., to\nappear] for representing fully nonlinear\nHJB equations. This includes in particular numerical resolution for stochastic\ncontrol problems with controlled volatility, possibly degenerate. Our backward scheme, based on least-squares regressions, takes advantage of high-dimensional properties of Monte Carlo methods, and also provides a parametric estimate in feedback form for the optimal control.\nA partial analysis of the algorithm error is presented, as well as numerical tests on the\nproblem of option superreplication with uncertain volatilities and\/or correlations, including a detailed comparison with the numerical\nresults from the alternative scheme proposed in [J. Comput. Finance 14 (2011), 37\u201371].<\/jats:p>","DOI":"10.1515\/mcma-2013-0024","type":"journal-article","created":{"date-parts":[[2014,5,21]],"date-time":"2014-05-21T12:51:16Z","timestamp":1400676676000},"page":"145-165","source":"Crossref","is-referenced-by-count":63,"title":["A numerical algorithm for fully nonlinear HJB equations:\nAn approach by control randomization"],"prefix":"10.1515","volume":"20","author":[{"given":"Idris","family":"Kharroubi","sequence":"first","affiliation":[{"name":"CEREMADE, CNRS UMR 7534, Universit\u00e9 Paris Dauphine, and CREST, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nicolas","family":"Langren\u00e9","sequence":"additional","affiliation":[{"name":"Laboratoire de Probabilit\u00e9s et Mod\u00e8les Al\u00e9atoires, Universit\u00e9 Paris Diderot, and EDF R&D, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huy\u00ean","family":"Pham","sequence":"additional","affiliation":[{"name":"Laboratoire de Probabilit\u00e9s et Mod\u00e8les Al\u00e9atoires, Universit\u00e9 Paris Diderot, and CREST-ENSAE, France"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"374","published-online":{"date-parts":[[2014,4,30]]},"container-title":["Monte Carlo Methods and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.degruyter.com\/document\/doi\/10.1515\/mcma-2013-0024\/xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.degruyter.com\/document\/doi\/10.1515\/mcma-2013-0024\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,4,1]],"date-time":"2023-04-01T21:35:48Z","timestamp":1680384948000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.degruyter.com\/document\/doi\/10.1515\/mcma-2013-0024\/html"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014,4,30]]},"references-count":0,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2014,4,24]]},"published-print":{"date-parts":[[2014,6,1]]}},"alternative-id":["10.1515\/mcma-2013-0024"],"URL":"https:\/\/doi.org\/10.1515\/mcma-2013-0024","relation":{},"ISSN":["0929-9629","1569-3961"],"issn-type":[{"value":"0929-9629","type":"print"},{"value":"1569-3961","type":"electronic"}],"subject":[],"published":{"date-parts":[[2014,4,30]]}}}