{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:55GEZ5RYWPEMITBDXMEOEUGS36","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":"15a4dcdf375906e7c1ca552cb1816f91644bc2f0c511076f0897dadedddbc270","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CE","submitted_at":"2025-06-20T08:03:36Z","title_canon_sha256":"d0dcc8c64b657ddf40001f7d2cd4039164d19a1a9ad5a3c9ca6fa9b88bc3988f"},"schema_version":"1.0","source":{"id":"2506.16813","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.16813","created_at":"2026-07-05T11:24:43Z"},{"alias_kind":"arxiv_version","alias_value":"2506.16813v1","created_at":"2026-07-05T11:24:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.16813","created_at":"2026-07-05T11:24:43Z"},{"alias_kind":"pith_short_12","alias_value":"55GEZ5RYWPEM","created_at":"2026-07-05T11:24:43Z"},{"alias_kind":"pith_short_16","alias_value":"55GEZ5RYWPEMITBD","created_at":"2026-07-05T11:24:43Z"},{"alias_kind":"pith_short_8","alias_value":"55GEZ5RY","created_at":"2026-07-05T11:24:43Z"}],"graph_snapshots":[{"event_id":"sha256:c84c955b1f0eb86308409ea9ac41a3b93e24bc406edea9705d1f746c851f4b6b","target":"graph","created_at":"2026-07-05T11:24:43Z","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/2506.16813/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Traditional technical analysis methods face limitations in accurately predicting trends in today's complex financial markets. This paper introduces ElliottAgents, an multi-agent system that integrates the Elliott Wave Principle with AI for stock market forecasting. The inherent complexity of financial markets, characterized by non-linear dynamics, noise, and susceptibility to unpredictable external factors, poses significant challenges for accurate prediction. To address these challenges, the system employs LLMs to enhance natural language understanding and decision-making capabilities within ","authors_text":"Jaros{\\l}aw A. Chudziak, Micha{\\l} Wawer","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CE","submitted_at":"2025-06-20T08:03:36Z","title":"Integrating Traditional Technical Analysis with AI: A Multi-Agent LLM-Based Approach to Stock Market Forecasting"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.16813","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":"sha256:50751812843057ec1577dc15b673301f193371c2b950efaee50430cd29bbbcd6","target":"record","created_at":"2026-07-05T11:24:43Z","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":"15a4dcdf375906e7c1ca552cb1816f91644bc2f0c511076f0897dadedddbc270","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CE","submitted_at":"2025-06-20T08:03:36Z","title_canon_sha256":"d0dcc8c64b657ddf40001f7d2cd4039164d19a1a9ad5a3c9ca6fa9b88bc3988f"},"schema_version":"1.0","source":{"id":"2506.16813","kind":"arxiv","version":1}},"canonical_sha256":"ef4c4cf638b3c8c44c23bb08e250d2dfa98fbcd1f0d2235ab9df045a4f5fd25a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ef4c4cf638b3c8c44c23bb08e250d2dfa98fbcd1f0d2235ab9df045a4f5fd25a","first_computed_at":"2026-07-05T11:24:43.364998Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:24:43.364998Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"/KyF7DKRXJ5X4/rKRSH1hYJv9quKMT4nUYQC5YNNl8O+qrPpjWEyMQ+0nZ/pKxsladzdc6CT7BRCzpGNV0QDBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:24:43.365492Z","signed_message":"canonical_sha256_bytes"},"source_id":"2506.16813","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:50751812843057ec1577dc15b673301f193371c2b950efaee50430cd29bbbcd6","sha256:c84c955b1f0eb86308409ea9ac41a3b93e24bc406edea9705d1f746c851f4b6b"],"state_sha256":"965fb659118294a30ba20133a8eacbc0b9f1215835776293035ba75c7addc2f1"}