{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2013:7ZROTRF2VRWKFEBYRUXRXHXRUC","short_pith_number":"pith:7ZROTRF2","schema_version":"1.0","canonical_sha256":"fe62e9c4baac6ca290388d2f1b9ef1a0ae4ca6c993febe148029165e2cbc7eaf","source":{"kind":"arxiv","id":"1311.4503","version":1},"attestation_state":"computed","paper":{"title":"A numerical algorithm for fully nonlinear HJB equations: an approach by control randomization","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["q-fin.CP","q-fin.PR"],"primary_cat":"math.PR","authors_text":"CEREMADE), Huy\\^en Pham (CREST, Idris Kharroubi (CREST, LPMA), Nicolas Langren\\'e (LPMA)","submitted_at":"2013-11-18T19:27:39Z","abstract_excerpt":"We propose a probabilistic numerical algorithm to solve Backward Stochastic Differential Equations (BSDEs) with nonnegative jumps, a class of BSDEs introduced in [9] for representing fully nonlinear HJB equations. In particular, this allows us to numerically solve stochastic control 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. A partial analysis of the error of the scheme is"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1311.4503","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.PR","submitted_at":"2013-11-18T19:27:39Z","cross_cats_sorted":["q-fin.CP","q-fin.PR"],"title_canon_sha256":"0e6de3b32a66f472fa80d9ebf651d20c63c848be95ae5ef2d0fa175c051af553","abstract_canon_sha256":"f597b86f66559e53c90160fb9d811858c1e05bc502830b9d0e91dd5676a832e6"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:41:01.660509Z","signature_b64":"f2089xhWf8r55kxfMrN/r6CTdzKWxiqqhidgALrdc0UN0xTCZRkjBCPJ1h5F5r76TIaRfXuoqC/SSO7LDoBsBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"fe62e9c4baac6ca290388d2f1b9ef1a0ae4ca6c993febe148029165e2cbc7eaf","last_reissued_at":"2026-05-17T23:41:01.659894Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:41:01.659894Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A numerical algorithm for fully nonlinear HJB equations: an approach by control randomization","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["q-fin.CP","q-fin.PR"],"primary_cat":"math.PR","authors_text":"CEREMADE), Huy\\^en Pham (CREST, Idris Kharroubi (CREST, LPMA), Nicolas Langren\\'e (LPMA)","submitted_at":"2013-11-18T19:27:39Z","abstract_excerpt":"We propose a probabilistic numerical algorithm to solve Backward Stochastic Differential Equations (BSDEs) with nonnegative jumps, a class of BSDEs introduced in [9] for representing fully nonlinear HJB equations. In particular, this allows us to numerically solve stochastic control 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. A partial analysis of the error of the scheme is"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1311.4503","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"1311.4503","created_at":"2026-05-17T23:41:01.659985+00:00"},{"alias_kind":"arxiv_version","alias_value":"1311.4503v1","created_at":"2026-05-17T23:41:01.659985+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1311.4503","created_at":"2026-05-17T23:41:01.659985+00:00"},{"alias_kind":"pith_short_12","alias_value":"7ZROTRF2VRWK","created_at":"2026-05-18T12:27:38.830355+00:00"},{"alias_kind":"pith_short_16","alias_value":"7ZROTRF2VRWKFEBY","created_at":"2026-05-18T12:27:38.830355+00:00"},{"alias_kind":"pith_short_8","alias_value":"7ZROTRF2","created_at":"2026-05-18T12:27:38.830355+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/7ZROTRF2VRWKFEBYRUXRXHXRUC","json":"https://pith.science/pith/7ZROTRF2VRWKFEBYRUXRXHXRUC.json","graph_json":"https://pith.science/api/pith-number/7ZROTRF2VRWKFEBYRUXRXHXRUC/graph.json","events_json":"https://pith.science/api/pith-number/7ZROTRF2VRWKFEBYRUXRXHXRUC/events.json","paper":"https://pith.science/paper/7ZROTRF2"},"agent_actions":{"view_html":"https://pith.science/pith/7ZROTRF2VRWKFEBYRUXRXHXRUC","download_json":"https://pith.science/pith/7ZROTRF2VRWKFEBYRUXRXHXRUC.json","view_paper":"https://pith.science/paper/7ZROTRF2","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1311.4503&json=true","fetch_graph":"https://pith.science/api/pith-number/7ZROTRF2VRWKFEBYRUXRXHXRUC/graph.json","fetch_events":"https://pith.science/api/pith-number/7ZROTRF2VRWKFEBYRUXRXHXRUC/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/7ZROTRF2VRWKFEBYRUXRXHXRUC/action/timestamp_anchor","attest_storage":"https://pith.science/pith/7ZROTRF2VRWKFEBYRUXRXHXRUC/action/storage_attestation","attest_author":"https://pith.science/pith/7ZROTRF2VRWKFEBYRUXRXHXRUC/action/author_attestation","sign_citation":"https://pith.science/pith/7ZROTRF2VRWKFEBYRUXRXHXRUC/action/citation_signature","submit_replication":"https://pith.science/pith/7ZROTRF2VRWKFEBYRUXRXHXRUC/action/replication_record"}},"created_at":"2026-05-17T23:41:01.659985+00:00","updated_at":"2026-05-17T23:41:01.659985+00:00"}