{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:OK3EBBUOH5OUGT37JLBOYEPTT5","short_pith_number":"pith:OK3EBBUO","canonical_record":{"source":{"id":"2407.17866","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"q-fin.ST","submitted_at":"2024-07-25T08:36:58Z","cross_cats_sorted":["cs.AI","cs.CL","q-fin.GN","q-fin.PM"],"title_canon_sha256":"e49ac5775143e6daf7d8effed7c711768c093fc56fb23c5af76e9cc132058393","abstract_canon_sha256":"63917eb0410b1ec47d4470492c0464dc92b6b0743a511b3e1cc0313d71236c36"},"schema_version":"1.0"},"canonical_sha256":"72b640868e3f5d434f7f4ac2ec11f39f63fa43a763481998ee8a2186d2f38b42","source":{"kind":"arxiv","id":"2407.17866","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2407.17866","created_at":"2026-07-05T10:17:48Z"},{"alias_kind":"arxiv_version","alias_value":"2407.17866v3","created_at":"2026-07-05T10:17:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2407.17866","created_at":"2026-07-05T10:17:48Z"},{"alias_kind":"pith_short_12","alias_value":"OK3EBBUOH5OU","created_at":"2026-07-05T10:17:48Z"},{"alias_kind":"pith_short_16","alias_value":"OK3EBBUOH5OUGT37","created_at":"2026-07-05T10:17:48Z"},{"alias_kind":"pith_short_8","alias_value":"OK3EBBUO","created_at":"2026-07-05T10:17:48Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:OK3EBBUOH5OUGT37JLBOYEPTT5","target":"record","payload":{"canonical_record":{"source":{"id":"2407.17866","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"q-fin.ST","submitted_at":"2024-07-25T08:36:58Z","cross_cats_sorted":["cs.AI","cs.CL","q-fin.GN","q-fin.PM"],"title_canon_sha256":"e49ac5775143e6daf7d8effed7c711768c093fc56fb23c5af76e9cc132058393","abstract_canon_sha256":"63917eb0410b1ec47d4470492c0464dc92b6b0743a511b3e1cc0313d71236c36"},"schema_version":"1.0"},"canonical_sha256":"72b640868e3f5d434f7f4ac2ec11f39f63fa43a763481998ee8a2186d2f38b42","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:17:48.178211Z","signature_b64":"VLEopzFpFErhftphZ4rhIz1UQRev1LppOjddvtG9Mb6swI0SNeHuFEyHWcNI73DyFh15iTNrHPmcJI1iVYKhCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"72b640868e3f5d434f7f4ac2ec11f39f63fa43a763481998ee8a2186d2f38b42","last_reissued_at":"2026-07-05T10:17:48.177812Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:17:48.177812Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2407.17866","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T10:17:48Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"wZpYy+T2SW33vAV9/LCN78KSYQbk9/oIuz6W2/x13K16UzoKGkayl3Z/h+LTozjboOcn9yaSLFeRtBOHgFsACw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T06:21:34.438077Z"},"content_sha256":"f57552003dc672ea880e6fbc9700ab637e0d07532d48a35ca70d30bfc01de40e","schema_version":"1.0","event_id":"sha256:f57552003dc672ea880e6fbc9700ab637e0d07532d48a35ca70d30bfc01de40e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:OK3EBBUOH5OUGT37JLBOYEPTT5","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Financial Statement Analysis with Large Language Models","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.AI","cs.CL","q-fin.GN","q-fin.PM"],"primary_cat":"q-fin.ST","authors_text":"Alex Kim, Maximilian Muhn, Valeri Nikolaev","submitted_at":"2024-07-25T08:36:58Z","abstract_excerpt":"We investigate whether large language models (LLMs) can successfully perform financial statement analysis in a way similar to a professional human analyst. We provide standardized and anonymous financial statements to GPT4 and instruct the model to analyze them to determine the direction of firms' future earnings. Even without narrative or industry-specific information, the LLM outperforms financial analysts in its ability to predict earnings changes directionally. The LLM exhibits a relative advantage over human analysts in situations when the analysts tend to struggle. Furthermore, we find t"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2407.17866","kind":"arxiv","version":3},"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/2407.17866/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":"2026-07-05T10:17:48Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+qgs7mfLQuiO/ssVAqmaJbpJMWtD2xDQ7prm9DdmGYCA5Fsb5G3FtWgC9MbxlPEB5/m3E1SzWCD6EgUIESE1Aw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T06:21:34.438587Z"},"content_sha256":"86d2944d8d7fccc2c846bcda9e3e04359aaa4165105cb0dc1fcc8b8615f24d71","schema_version":"1.0","event_id":"sha256:86d2944d8d7fccc2c846bcda9e3e04359aaa4165105cb0dc1fcc8b8615f24d71"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/OK3EBBUOH5OUGT37JLBOYEPTT5/bundle.json","state_url":"https://pith.science/pith/OK3EBBUOH5OUGT37JLBOYEPTT5/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/OK3EBBUOH5OUGT37JLBOYEPTT5/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":"2026-08-06T06:21:34Z","links":{"resolver":"https://pith.science/pith/OK3EBBUOH5OUGT37JLBOYEPTT5","bundle":"https://pith.science/pith/OK3EBBUOH5OUGT37JLBOYEPTT5/bundle.json","state":"https://pith.science/pith/OK3EBBUOH5OUGT37JLBOYEPTT5/state.json","well_known_bundle":"https://pith.science/.well-known/pith/OK3EBBUOH5OUGT37JLBOYEPTT5/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:OK3EBBUOH5OUGT37JLBOYEPTT5","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":"63917eb0410b1ec47d4470492c0464dc92b6b0743a511b3e1cc0313d71236c36","cross_cats_sorted":["cs.AI","cs.CL","q-fin.GN","q-fin.PM"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"q-fin.ST","submitted_at":"2024-07-25T08:36:58Z","title_canon_sha256":"e49ac5775143e6daf7d8effed7c711768c093fc56fb23c5af76e9cc132058393"},"schema_version":"1.0","source":{"id":"2407.17866","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2407.17866","created_at":"2026-07-05T10:17:48Z"},{"alias_kind":"arxiv_version","alias_value":"2407.17866v3","created_at":"2026-07-05T10:17:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2407.17866","created_at":"2026-07-05T10:17:48Z"},{"alias_kind":"pith_short_12","alias_value":"OK3EBBUOH5OU","created_at":"2026-07-05T10:17:48Z"},{"alias_kind":"pith_short_16","alias_value":"OK3EBBUOH5OUGT37","created_at":"2026-07-05T10:17:48Z"},{"alias_kind":"pith_short_8","alias_value":"OK3EBBUO","created_at":"2026-07-05T10:17:48Z"}],"graph_snapshots":[{"event_id":"sha256:86d2944d8d7fccc2c846bcda9e3e04359aaa4165105cb0dc1fcc8b8615f24d71","target":"graph","created_at":"2026-07-05T10:17:48Z","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/2407.17866/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We investigate whether large language models (LLMs) can successfully perform financial statement analysis in a way similar to a professional human analyst. We provide standardized and anonymous financial statements to GPT4 and instruct the model to analyze them to determine the direction of firms' future earnings. Even without narrative or industry-specific information, the LLM outperforms financial analysts in its ability to predict earnings changes directionally. The LLM exhibits a relative advantage over human analysts in situations when the analysts tend to struggle. Furthermore, we find t","authors_text":"Alex Kim, Maximilian Muhn, Valeri Nikolaev","cross_cats":["cs.AI","cs.CL","q-fin.GN","q-fin.PM"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"q-fin.ST","submitted_at":"2024-07-25T08:36:58Z","title":"Financial Statement Analysis with Large Language Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2407.17866","kind":"arxiv","version":3},"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:f57552003dc672ea880e6fbc9700ab637e0d07532d48a35ca70d30bfc01de40e","target":"record","created_at":"2026-07-05T10:17:48Z","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":"63917eb0410b1ec47d4470492c0464dc92b6b0743a511b3e1cc0313d71236c36","cross_cats_sorted":["cs.AI","cs.CL","q-fin.GN","q-fin.PM"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"q-fin.ST","submitted_at":"2024-07-25T08:36:58Z","title_canon_sha256":"e49ac5775143e6daf7d8effed7c711768c093fc56fb23c5af76e9cc132058393"},"schema_version":"1.0","source":{"id":"2407.17866","kind":"arxiv","version":3}},"canonical_sha256":"72b640868e3f5d434f7f4ac2ec11f39f63fa43a763481998ee8a2186d2f38b42","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"72b640868e3f5d434f7f4ac2ec11f39f63fa43a763481998ee8a2186d2f38b42","first_computed_at":"2026-07-05T10:17:48.177812Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:17:48.177812Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"VLEopzFpFErhftphZ4rhIz1UQRev1LppOjddvtG9Mb6swI0SNeHuFEyHWcNI73DyFh15iTNrHPmcJI1iVYKhCg==","signature_status":"signed_v1","signed_at":"2026-07-05T10:17:48.178211Z","signed_message":"canonical_sha256_bytes"},"source_id":"2407.17866","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f57552003dc672ea880e6fbc9700ab637e0d07532d48a35ca70d30bfc01de40e","sha256:86d2944d8d7fccc2c846bcda9e3e04359aaa4165105cb0dc1fcc8b8615f24d71"],"state_sha256":"99c521964fb0a63cef1063051ae90e7284f909b5962c69d01d6ef371e9a859c5"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"RMTVR2ZxrAsx5rFGaKjf7vc/qLiLr3mIGDwEMQT4q0TcUh5E7m0Q2HEcxqIVMw4b5HTnULDaYNaU7aKcbToQAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T06:21:34.442786Z","bundle_sha256":"288cd0fd53296ce209e36ac875685c4818c7633892e763e0124bc741a2c57a78"}}