{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:D2OGEVDAY3SSZLWXXYC4IJPKGJ","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":"b8966c6e22fd534bc8cb6cb98bff1525c53e34bcd49f971c0c4a5a33f14cab10","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-fin.MF","submitted_at":"2025-09-02T12:43:46Z","title_canon_sha256":"b9fa44cf58190365c5c104e4b9e5dae16695ac64c00b7cbf82ef1a2f414f5137"},"schema_version":"1.0","source":{"id":"2509.02267","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2509.02267","created_at":"2026-07-05T12:03:35Z"},{"alias_kind":"arxiv_version","alias_value":"2509.02267v1","created_at":"2026-07-05T12:03:35Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2509.02267","created_at":"2026-07-05T12:03:35Z"},{"alias_kind":"pith_short_12","alias_value":"D2OGEVDAY3SS","created_at":"2026-07-05T12:03:35Z"},{"alias_kind":"pith_short_16","alias_value":"D2OGEVDAY3SSZLWX","created_at":"2026-07-05T12:03:35Z"},{"alias_kind":"pith_short_8","alias_value":"D2OGEVDA","created_at":"2026-07-05T12:03:35Z"}],"graph_snapshots":[{"event_id":"sha256:d047ca0edf6acf722b8021b4110ec62b3dae2eeb6dc029bb8506eb1f557f026d","target":"graph","created_at":"2026-07-05T12:03:35Z","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/2509.02267/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In this paper, we first conduct a study of the portfolio selection problem, incorporating both exogenous (proportional) and endogenous (resulting from liquidity risk, characterized by a stochastic process) transaction costs through the utility-based approach. We also consider the intrinsic relationship between these two types of costs. To address the associated nonlinear two-dimensional Hamilton-Jacobi-Bellman (HJB) equation, we propose an innovative deep learning-driven policy iteration scheme with three key advantages: i) it has the potential to address the curse of dimensionality; ii) it is","authors_text":"Dong Yan, Junyi Guo, Nanyi Zhang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-fin.MF","submitted_at":"2025-09-02T12:43:46Z","title":"A deep learning-driven iterative scheme for high-dimensional HJB equations in portfolio selection with exogenous and endogenous costs"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2509.02267","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":"sha256:0c55de4d4788dbe9f42bdcf66f1d0b311ba90b701a8dc383a551e689dd8f0c67","target":"record","created_at":"2026-07-05T12:03:35Z","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":"b8966c6e22fd534bc8cb6cb98bff1525c53e34bcd49f971c0c4a5a33f14cab10","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-fin.MF","submitted_at":"2025-09-02T12:43:46Z","title_canon_sha256":"b9fa44cf58190365c5c104e4b9e5dae16695ac64c00b7cbf82ef1a2f414f5137"},"schema_version":"1.0","source":{"id":"2509.02267","kind":"arxiv","version":1}},"canonical_sha256":"1e9c625460c6e52caed7be05c425ea326e1b11826db8ed878ad285c844971c61","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1e9c625460c6e52caed7be05c425ea326e1b11826db8ed878ad285c844971c61","first_computed_at":"2026-07-05T12:03:35.290560Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T12:03:35.290560Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"7CB76mzU9XdlKM9fce1B0SImmjkAEnUL1kziXzDxNFHHHnScfxbhBSANkPUZx7bGeTLsx2wwu9nA7HpNsw+gAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T12:03:35.291063Z","signed_message":"canonical_sha256_bytes"},"source_id":"2509.02267","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0c55de4d4788dbe9f42bdcf66f1d0b311ba90b701a8dc383a551e689dd8f0c67","sha256:d047ca0edf6acf722b8021b4110ec62b3dae2eeb6dc029bb8506eb1f557f026d"],"state_sha256":"959184903acac44869ce0e9e3dbbe1965def57116f710065d8cf809ca0c305aa"}