{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:VSIWY26HQBFQCOQFD6DIE2YIOJ","short_pith_number":"pith:VSIWY26H","schema_version":"1.0","canonical_sha256":"ac916c6bc7804b013a051f86826b0872630cc1e118d1695f202ba660b735bf43","source":{"kind":"arxiv","id":"1802.03639","version":2},"attestation_state":"computed","paper":{"title":"Martingale Characterizations of Risk-Averse Stochastic Optimization Problems","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"math.OC","authors_text":"Alois Pichler, Ruben Schlotter","submitted_at":"2018-02-10T18:47:49Z","abstract_excerpt":"This paper addresses risk awareness of stochastic optimization problems. Nested risk measures appear naturally in this context, as they allow beneficial reformulations for algorithmic treatments. The reformulations presented extend usual Hamilton-Jacobi-Bellman equations in dynamic optimization by involving risk awareness in the problem formulation.\n  Nested risk measures are built on risk measures, which originate by conditioning on the history of a stochastic process. We derive martingale properties of these risk measures and use them to prove continuity. It is demonstrated that stochastic o"},"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":"1802.03639","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2018-02-10T18:47:49Z","cross_cats_sorted":[],"title_canon_sha256":"b13c5fdec91795dfc5e338dc6356a4cbae32e6dab311bc4d66827ae6046498d2","abstract_canon_sha256":"479226244c28a1d223c8383e516ec403ce1b030a49d0a4fd5e8e205e305d5e0a"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:23:44.664377Z","signature_b64":"3lXvTDBlYXDalGS0RDjDkR2w3yjfSURSPchJZIDyyFBewkdn1zcD3ZBEX/MO8BAFQD63tub9TlC0N3JVlmTGBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ac916c6bc7804b013a051f86826b0872630cc1e118d1695f202ba660b735bf43","last_reissued_at":"2026-05-18T00:23:44.663902Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:23:44.663902Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Martingale Characterizations of Risk-Averse Stochastic Optimization Problems","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"math.OC","authors_text":"Alois Pichler, Ruben Schlotter","submitted_at":"2018-02-10T18:47:49Z","abstract_excerpt":"This paper addresses risk awareness of stochastic optimization problems. Nested risk measures appear naturally in this context, as they allow beneficial reformulations for algorithmic treatments. The reformulations presented extend usual Hamilton-Jacobi-Bellman equations in dynamic optimization by involving risk awareness in the problem formulation.\n  Nested risk measures are built on risk measures, which originate by conditioning on the history of a stochastic process. We derive martingale properties of these risk measures and use them to prove continuity. It is demonstrated that stochastic o"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1802.03639","kind":"arxiv","version":2},"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":"1802.03639","created_at":"2026-05-18T00:23:44.663970+00:00"},{"alias_kind":"arxiv_version","alias_value":"1802.03639v2","created_at":"2026-05-18T00:23:44.663970+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1802.03639","created_at":"2026-05-18T00:23:44.663970+00:00"},{"alias_kind":"pith_short_12","alias_value":"VSIWY26HQBFQ","created_at":"2026-05-18T12:32:59.047623+00:00"},{"alias_kind":"pith_short_16","alias_value":"VSIWY26HQBFQCOQF","created_at":"2026-05-18T12:32:59.047623+00:00"},{"alias_kind":"pith_short_8","alias_value":"VSIWY26H","created_at":"2026-05-18T12:32:59.047623+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/VSIWY26HQBFQCOQFD6DIE2YIOJ","json":"https://pith.science/pith/VSIWY26HQBFQCOQFD6DIE2YIOJ.json","graph_json":"https://pith.science/api/pith-number/VSIWY26HQBFQCOQFD6DIE2YIOJ/graph.json","events_json":"https://pith.science/api/pith-number/VSIWY26HQBFQCOQFD6DIE2YIOJ/events.json","paper":"https://pith.science/paper/VSIWY26H"},"agent_actions":{"view_html":"https://pith.science/pith/VSIWY26HQBFQCOQFD6DIE2YIOJ","download_json":"https://pith.science/pith/VSIWY26HQBFQCOQFD6DIE2YIOJ.json","view_paper":"https://pith.science/paper/VSIWY26H","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1802.03639&json=true","fetch_graph":"https://pith.science/api/pith-number/VSIWY26HQBFQCOQFD6DIE2YIOJ/graph.json","fetch_events":"https://pith.science/api/pith-number/VSIWY26HQBFQCOQFD6DIE2YIOJ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/VSIWY26HQBFQCOQFD6DIE2YIOJ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/VSIWY26HQBFQCOQFD6DIE2YIOJ/action/storage_attestation","attest_author":"https://pith.science/pith/VSIWY26HQBFQCOQFD6DIE2YIOJ/action/author_attestation","sign_citation":"https://pith.science/pith/VSIWY26HQBFQCOQFD6DIE2YIOJ/action/citation_signature","submit_replication":"https://pith.science/pith/VSIWY26HQBFQCOQFD6DIE2YIOJ/action/replication_record"}},"created_at":"2026-05-18T00:23:44.663970+00:00","updated_at":"2026-05-18T00:23:44.663970+00:00"}