{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:GO2ETOUHJNXMIRF5JBAT6OEAKZ","short_pith_number":"pith:GO2ETOUH","canonical_record":{"source":{"id":"2107.04636","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"q-fin.PM","submitted_at":"2021-07-09T19:13:07Z","cross_cats_sorted":["q-fin.CP"],"title_canon_sha256":"4c1df68a2d514a78bbd585be6391e8914b1e7501b5bf6ed91d6e8f0f72685926","abstract_canon_sha256":"f3b72c3c99ff82ae15c5a2554042d9d2eea74381bb1b615b6a37a4fb8b2fbfdb"},"schema_version":"1.0"},"canonical_sha256":"33b449ba874b6ec444bd48413f38805651baaa30b393efd012fbe2b182045aef","source":{"kind":"arxiv","id":"2107.04636","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2107.04636","created_at":"2026-07-05T02:56:41Z"},{"alias_kind":"arxiv_version","alias_value":"2107.04636v1","created_at":"2026-07-05T02:56:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2107.04636","created_at":"2026-07-05T02:56:41Z"},{"alias_kind":"pith_short_12","alias_value":"GO2ETOUHJNXM","created_at":"2026-07-05T02:56:41Z"},{"alias_kind":"pith_short_16","alias_value":"GO2ETOUHJNXMIRF5","created_at":"2026-07-05T02:56:41Z"},{"alias_kind":"pith_short_8","alias_value":"GO2ETOUH","created_at":"2026-07-05T02:56:41Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:GO2ETOUHJNXMIRF5JBAT6OEAKZ","target":"record","payload":{"canonical_record":{"source":{"id":"2107.04636","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"q-fin.PM","submitted_at":"2021-07-09T19:13:07Z","cross_cats_sorted":["q-fin.CP"],"title_canon_sha256":"4c1df68a2d514a78bbd585be6391e8914b1e7501b5bf6ed91d6e8f0f72685926","abstract_canon_sha256":"f3b72c3c99ff82ae15c5a2554042d9d2eea74381bb1b615b6a37a4fb8b2fbfdb"},"schema_version":"1.0"},"canonical_sha256":"33b449ba874b6ec444bd48413f38805651baaa30b393efd012fbe2b182045aef","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:56:41.094232Z","signature_b64":"TYdFZeR/ZDtrpd4ythfgiSvfqt5QQXnXA4Nw8YAGT+vYu7lloR5BK70XqczJKOV9st/kAmsx94JPxz6RQEYEBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"33b449ba874b6ec444bd48413f38805651baaa30b393efd012fbe2b182045aef","last_reissued_at":"2026-07-05T02:56:41.093846Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:56:41.093846Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2107.04636","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T02:56:41Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"bmrnR59T1g7Cl/fRsfoPBiZ14DbKELQTIULMR8yvZKnpHffvA3aPNfb4Eoq+XYgxEk29Ii4mGNfsdmfCJAJzCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T16:12:18.557127Z"},"content_sha256":"7129eeed75131bb6857d16c91689064531d03f87b2eaa7953287dd67065dc9c4","schema_version":"1.0","event_id":"sha256:7129eeed75131bb6857d16c91689064531d03f87b2eaa7953287dd67065dc9c4"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:GO2ETOUHJNXMIRF5JBAT6OEAKZ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"End-to-End Risk Budgeting Portfolio Optimization with Neural Networks","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["q-fin.CP"],"primary_cat":"q-fin.PM","authors_text":"Ayse Sinem Uysal, John M. Mulvey, Xiaoyue Li","submitted_at":"2021-07-09T19:13:07Z","abstract_excerpt":"Portfolio optimization has been a central problem in finance, often approached with two steps: calibrating the parameters and then solving an optimization problem. Yet, the two-step procedure sometimes encounter the \"error maximization\" problem where inaccuracy in parameter estimation translates to unwise allocation decisions. In this paper, we combine the prediction and optimization tasks in a single feed-forward neural network and implement an end-to-end approach, where we learn the portfolio allocation directly from the input features. Two end-to-end portfolio constructions are included: a "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2107.04636","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2107.04636/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T02:56:41Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Sur84QgLZ7Ii1/YxQkeksqTXYF356SCYJiWGpUrddKGUWDo5p0lj5DWqDlnvPm9GsP1zxT9diGQFONNcXYr6BA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T16:12:18.558076Z"},"content_sha256":"ab8f37c5cc6638f84f620e24af66d018cff23bfe840cb0d644c178089e5ed9e4","schema_version":"1.0","event_id":"sha256:ab8f37c5cc6638f84f620e24af66d018cff23bfe840cb0d644c178089e5ed9e4"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/GO2ETOUHJNXMIRF5JBAT6OEAKZ/bundle.json","state_url":"https://pith.science/pith/GO2ETOUHJNXMIRF5JBAT6OEAKZ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/GO2ETOUHJNXMIRF5JBAT6OEAKZ/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-14T16:12:18Z","links":{"resolver":"https://pith.science/pith/GO2ETOUHJNXMIRF5JBAT6OEAKZ","bundle":"https://pith.science/pith/GO2ETOUHJNXMIRF5JBAT6OEAKZ/bundle.json","state":"https://pith.science/pith/GO2ETOUHJNXMIRF5JBAT6OEAKZ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/GO2ETOUHJNXMIRF5JBAT6OEAKZ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:GO2ETOUHJNXMIRF5JBAT6OEAKZ","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"f3b72c3c99ff82ae15c5a2554042d9d2eea74381bb1b615b6a37a4fb8b2fbfdb","cross_cats_sorted":["q-fin.CP"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"q-fin.PM","submitted_at":"2021-07-09T19:13:07Z","title_canon_sha256":"4c1df68a2d514a78bbd585be6391e8914b1e7501b5bf6ed91d6e8f0f72685926"},"schema_version":"1.0","source":{"id":"2107.04636","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2107.04636","created_at":"2026-07-05T02:56:41Z"},{"alias_kind":"arxiv_version","alias_value":"2107.04636v1","created_at":"2026-07-05T02:56:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2107.04636","created_at":"2026-07-05T02:56:41Z"},{"alias_kind":"pith_short_12","alias_value":"GO2ETOUHJNXM","created_at":"2026-07-05T02:56:41Z"},{"alias_kind":"pith_short_16","alias_value":"GO2ETOUHJNXMIRF5","created_at":"2026-07-05T02:56:41Z"},{"alias_kind":"pith_short_8","alias_value":"GO2ETOUH","created_at":"2026-07-05T02:56:41Z"}],"graph_snapshots":[{"event_id":"sha256:ab8f37c5cc6638f84f620e24af66d018cff23bfe840cb0d644c178089e5ed9e4","target":"graph","created_at":"2026-07-05T02:56:41Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2107.04636/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Portfolio optimization has been a central problem in finance, often approached with two steps: calibrating the parameters and then solving an optimization problem. Yet, the two-step procedure sometimes encounter the \"error maximization\" problem where inaccuracy in parameter estimation translates to unwise allocation decisions. In this paper, we combine the prediction and optimization tasks in a single feed-forward neural network and implement an end-to-end approach, where we learn the portfolio allocation directly from the input features. Two end-to-end portfolio constructions are included: a ","authors_text":"Ayse Sinem Uysal, John M. Mulvey, Xiaoyue Li","cross_cats":["q-fin.CP"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"q-fin.PM","submitted_at":"2021-07-09T19:13:07Z","title":"End-to-End Risk Budgeting Portfolio Optimization with Neural Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2107.04636","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:7129eeed75131bb6857d16c91689064531d03f87b2eaa7953287dd67065dc9c4","target":"record","created_at":"2026-07-05T02:56:41Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"f3b72c3c99ff82ae15c5a2554042d9d2eea74381bb1b615b6a37a4fb8b2fbfdb","cross_cats_sorted":["q-fin.CP"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"q-fin.PM","submitted_at":"2021-07-09T19:13:07Z","title_canon_sha256":"4c1df68a2d514a78bbd585be6391e8914b1e7501b5bf6ed91d6e8f0f72685926"},"schema_version":"1.0","source":{"id":"2107.04636","kind":"arxiv","version":1}},"canonical_sha256":"33b449ba874b6ec444bd48413f38805651baaa30b393efd012fbe2b182045aef","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"33b449ba874b6ec444bd48413f38805651baaa30b393efd012fbe2b182045aef","first_computed_at":"2026-07-05T02:56:41.093846Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:56:41.093846Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"TYdFZeR/ZDtrpd4ythfgiSvfqt5QQXnXA4Nw8YAGT+vYu7lloR5BK70XqczJKOV9st/kAmsx94JPxz6RQEYEBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T02:56:41.094232Z","signed_message":"canonical_sha256_bytes"},"source_id":"2107.04636","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:7129eeed75131bb6857d16c91689064531d03f87b2eaa7953287dd67065dc9c4","sha256:ab8f37c5cc6638f84f620e24af66d018cff23bfe840cb0d644c178089e5ed9e4"],"state_sha256":"939fa25fe2610093b8ff62728c09042daa9e0a212b31ef9a7ab5c4f6252bcdc4"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DnRcc0bZ+L8sDfEQZhBKQw6REQSGW9MKukeLQDPqXSzunfk4PuY3/hNZvviVV/HZ1KJI/DTNaptqnpdnOwfVBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-14T16:12:18.565861Z","bundle_sha256":"f9d0db82824b683cce76a254e2ca6f5774091bf355265b6fec241f76ff6a8f22"}}