{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:F3G3GP55ZQP63K4JC2XGKC6527","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":"d31f5305b166c5919dc090b297f47ff8d6c3ca50605efd57fe6d610567eaf99f","cross_cats_sorted":["q-fin.CP","q-fin.ST","stat.ML"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"q-fin.PM","submitted_at":"2025-09-29T00:42:24Z","title_canon_sha256":"32d25a24925e90c17ee642f4bc51d1c4e982d4bbebf589378adad2b30720379c"},"schema_version":"1.0","source":{"id":"2509.24144","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2509.24144","created_at":"2026-05-27T01:04:51Z"},{"alias_kind":"arxiv_version","alias_value":"2509.24144v2","created_at":"2026-05-27T01:04:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2509.24144","created_at":"2026-05-27T01:04:51Z"},{"alias_kind":"pith_short_12","alias_value":"F3G3GP55ZQP6","created_at":"2026-05-27T01:04:51Z"},{"alias_kind":"pith_short_16","alias_value":"F3G3GP55ZQP63K4J","created_at":"2026-05-27T01:04:51Z"},{"alias_kind":"pith_short_8","alias_value":"F3G3GP55","created_at":"2026-05-27T01:04:51Z"}],"graph_snapshots":[{"event_id":"sha256:9d5f3b78b80c1faeb6d4da34fa0c41b4d11e6091b327b2f2a8ad52ebcb1846ac","target":"graph","created_at":"2026-05-27T01:04:51Z","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/2509.24144/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Deep learning offers new tools for portfolio optimization. We present an end-to-end framework that directly learns portfolio weights by combining Long Short-Term Memory (LSTM) networks to model temporal patterns, Graph Attention Networks (GAT) to capture evolving inter-stock relationships, and sentiment analysis of financial news to reflect market psychology. Unlike prior approaches, our model unifies these elements in a single pipeline that produces daily allocations. It avoids the traditional two-step process of forecasting asset returns and then applying mean--variance optimization (MVO), a","authors_text":"Jiawei Lou, Jinghe Zhang, Yun Lin","cross_cats":["q-fin.CP","q-fin.ST","stat.ML"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"q-fin.PM","submitted_at":"2025-09-29T00:42:24Z","title":"From Headlines to Holdings: Deep Learning for Smarter Portfolio Decisions"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2509.24144","kind":"arxiv","version":2},"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":"sha256:7ff0abe76b02b68caed9d14ed06eb5109a901bfa1d18d046898c3fc5e373ecfa","target":"record","created_at":"2026-05-27T01:04:51Z","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":"d31f5305b166c5919dc090b297f47ff8d6c3ca50605efd57fe6d610567eaf99f","cross_cats_sorted":["q-fin.CP","q-fin.ST","stat.ML"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"q-fin.PM","submitted_at":"2025-09-29T00:42:24Z","title_canon_sha256":"32d25a24925e90c17ee642f4bc51d1c4e982d4bbebf589378adad2b30720379c"},"schema_version":"1.0","source":{"id":"2509.24144","kind":"arxiv","version":2}},"canonical_sha256":"2ecdb33fbdcc1fedab8916ae650bddd7f712ad19c80db83657b92df623499726","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2ecdb33fbdcc1fedab8916ae650bddd7f712ad19c80db83657b92df623499726","first_computed_at":"2026-05-27T01:04:51.277439Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-27T01:04:51.277439Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"lVXGUf7fVHShpTBRCNOzFI/exHxD6olB20AgyWot9wMzjlZs/leg8xfdZUtRr1/i70PeAW9eExf6rwACzBQUCw==","signature_status":"signed_v1","signed_at":"2026-05-27T01:04:51.278283Z","signed_message":"canonical_sha256_bytes"},"source_id":"2509.24144","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:7ff0abe76b02b68caed9d14ed06eb5109a901bfa1d18d046898c3fc5e373ecfa","sha256:9d5f3b78b80c1faeb6d4da34fa0c41b4d11e6091b327b2f2a8ad52ebcb1846ac"],"state_sha256":"afecb2510c5648d0d4c3b4f9a0d727f8b2f1986b4cc15732676840d53cd2e6ae"}