{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2014:DOHH4UWNON72SCU4IYVDD7BO5Y","short_pith_number":"pith:DOHH4UWN","canonical_record":{"source":{"id":"1406.0824","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-fin.ST","submitted_at":"2014-06-03T19:32:09Z","cross_cats_sorted":["cs.CE","cs.LG","q-fin.PM","stat.ML"],"title_canon_sha256":"05a48d1a48ba6a1188a63ff6d4fabc0ac52518914faf339d8432a53661aef699","abstract_canon_sha256":"4343b0d5fcc7ca1818ad4afbc7dd2e6c050f1a1b005d987bd31d02d65c2a33e4"},"schema_version":"1.0"},"canonical_sha256":"1b8e7e52cd737fa90a9c462a31fc2eee0178d9d0255a83a1420447ac31a5aacd","source":{"kind":"arxiv","id":"1406.0824","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1406.0824","created_at":"2026-05-18T02:50:32Z"},{"alias_kind":"arxiv_version","alias_value":"1406.0824v1","created_at":"2026-05-18T02:50:32Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1406.0824","created_at":"2026-05-18T02:50:32Z"},{"alias_kind":"pith_short_12","alias_value":"DOHH4UWNON72","created_at":"2026-05-18T12:28:25Z"},{"alias_kind":"pith_short_16","alias_value":"DOHH4UWNON72SCU4","created_at":"2026-05-18T12:28:25Z"},{"alias_kind":"pith_short_8","alias_value":"DOHH4UWN","created_at":"2026-05-18T12:28:25Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2014:DOHH4UWNON72SCU4IYVDD7BO5Y","target":"record","payload":{"canonical_record":{"source":{"id":"1406.0824","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-fin.ST","submitted_at":"2014-06-03T19:32:09Z","cross_cats_sorted":["cs.CE","cs.LG","q-fin.PM","stat.ML"],"title_canon_sha256":"05a48d1a48ba6a1188a63ff6d4fabc0ac52518914faf339d8432a53661aef699","abstract_canon_sha256":"4343b0d5fcc7ca1818ad4afbc7dd2e6c050f1a1b005d987bd31d02d65c2a33e4"},"schema_version":"1.0"},"canonical_sha256":"1b8e7e52cd737fa90a9c462a31fc2eee0178d9d0255a83a1420447ac31a5aacd","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:50:32.744014Z","signature_b64":"jIVkCh+6LiaPZw6glrAeyPYIj9akjDqVBMOpubJsgbsvaXPPI8SyzLrg3k+jAHL3E/DlingH2ApZmXpXvTnRBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1b8e7e52cd737fa90a9c462a31fc2eee0178d9d0255a83a1420447ac31a5aacd","last_reissued_at":"2026-05-18T02:50:32.743526Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:50:32.743526Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1406.0824","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":"2026-05-18T02:50:32Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jKAkF42WxzFuXA38SVUUO5rdi5fzDEoIZ/qRWhYd4zBczZpS75IzKVZymYVp8YKinf732VRX4nfyQyn005r/Aw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-11T20:04:45.880813Z"},"content_sha256":"0eb2406db4de16e26e56a932dca2c94923993a98c1a95ac5b5e4cfb7d2547c3f","schema_version":"1.0","event_id":"sha256:0eb2406db4de16e26e56a932dca2c94923993a98c1a95ac5b5e4cfb7d2547c3f"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2014:DOHH4UWNON72SCU4IYVDD7BO5Y","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Supervised classification-based stock prediction and portfolio optimization","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CE","cs.LG","q-fin.PM","stat.ML"],"primary_cat":"q-fin.ST","authors_text":"Adam Goldberg, Sercan Arik, Sukru Burc Eryilmaz","submitted_at":"2014-06-03T19:32:09Z","abstract_excerpt":"As the number of publicly traded companies as well as the amount of their financial data grows rapidly, it is highly desired to have tracking, analysis, and eventually stock selections automated. There have been few works focusing on estimating the stock prices of individual companies. However, many of those have worked with very small number of financial parameters. In this work, we apply machine learning techniques to address automated stock picking, while using a larger number of financial parameters for individual companies than the previous studies. Our approaches are based on the supervi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1406.0824","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":""},"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":"2026-05-18T02:50:32Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"TSe3NAdnYfz+ohS2D5iegxezG8EYfra5BB/kFGyoArZLo9wJ9w1iWBpsxJXziiXV3vTUEArwEGPlHay3fUiLAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-11T20:04:45.881558Z"},"content_sha256":"dd11af386111b7d825210deac9c81c74aa57b7d51dc655a5d1e7695741a5c3a3","schema_version":"1.0","event_id":"sha256:dd11af386111b7d825210deac9c81c74aa57b7d51dc655a5d1e7695741a5c3a3"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/DOHH4UWNON72SCU4IYVDD7BO5Y/bundle.json","state_url":"https://pith.science/pith/DOHH4UWNON72SCU4IYVDD7BO5Y/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/DOHH4UWNON72SCU4IYVDD7BO5Y/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":"2026-06-11T20:04:45Z","links":{"resolver":"https://pith.science/pith/DOHH4UWNON72SCU4IYVDD7BO5Y","bundle":"https://pith.science/pith/DOHH4UWNON72SCU4IYVDD7BO5Y/bundle.json","state":"https://pith.science/pith/DOHH4UWNON72SCU4IYVDD7BO5Y/state.json","well_known_bundle":"https://pith.science/.well-known/pith/DOHH4UWNON72SCU4IYVDD7BO5Y/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2014:DOHH4UWNON72SCU4IYVDD7BO5Y","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":"4343b0d5fcc7ca1818ad4afbc7dd2e6c050f1a1b005d987bd31d02d65c2a33e4","cross_cats_sorted":["cs.CE","cs.LG","q-fin.PM","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-fin.ST","submitted_at":"2014-06-03T19:32:09Z","title_canon_sha256":"05a48d1a48ba6a1188a63ff6d4fabc0ac52518914faf339d8432a53661aef699"},"schema_version":"1.0","source":{"id":"1406.0824","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1406.0824","created_at":"2026-05-18T02:50:32Z"},{"alias_kind":"arxiv_version","alias_value":"1406.0824v1","created_at":"2026-05-18T02:50:32Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1406.0824","created_at":"2026-05-18T02:50:32Z"},{"alias_kind":"pith_short_12","alias_value":"DOHH4UWNON72","created_at":"2026-05-18T12:28:25Z"},{"alias_kind":"pith_short_16","alias_value":"DOHH4UWNON72SCU4","created_at":"2026-05-18T12:28:25Z"},{"alias_kind":"pith_short_8","alias_value":"DOHH4UWN","created_at":"2026-05-18T12:28:25Z"}],"graph_snapshots":[{"event_id":"sha256:dd11af386111b7d825210deac9c81c74aa57b7d51dc655a5d1e7695741a5c3a3","target":"graph","created_at":"2026-05-18T02:50:32Z","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"},"paper":{"abstract_excerpt":"As the number of publicly traded companies as well as the amount of their financial data grows rapidly, it is highly desired to have tracking, analysis, and eventually stock selections automated. There have been few works focusing on estimating the stock prices of individual companies. However, many of those have worked with very small number of financial parameters. In this work, we apply machine learning techniques to address automated stock picking, while using a larger number of financial parameters for individual companies than the previous studies. Our approaches are based on the supervi","authors_text":"Adam Goldberg, Sercan Arik, Sukru Burc Eryilmaz","cross_cats":["cs.CE","cs.LG","q-fin.PM","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-fin.ST","submitted_at":"2014-06-03T19:32:09Z","title":"Supervised classification-based stock prediction and portfolio optimization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1406.0824","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":"sha256:0eb2406db4de16e26e56a932dca2c94923993a98c1a95ac5b5e4cfb7d2547c3f","target":"record","created_at":"2026-05-18T02:50:32Z","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":"4343b0d5fcc7ca1818ad4afbc7dd2e6c050f1a1b005d987bd31d02d65c2a33e4","cross_cats_sorted":["cs.CE","cs.LG","q-fin.PM","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-fin.ST","submitted_at":"2014-06-03T19:32:09Z","title_canon_sha256":"05a48d1a48ba6a1188a63ff6d4fabc0ac52518914faf339d8432a53661aef699"},"schema_version":"1.0","source":{"id":"1406.0824","kind":"arxiv","version":1}},"canonical_sha256":"1b8e7e52cd737fa90a9c462a31fc2eee0178d9d0255a83a1420447ac31a5aacd","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1b8e7e52cd737fa90a9c462a31fc2eee0178d9d0255a83a1420447ac31a5aacd","first_computed_at":"2026-05-18T02:50:32.743526Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T02:50:32.743526Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"jIVkCh+6LiaPZw6glrAeyPYIj9akjDqVBMOpubJsgbsvaXPPI8SyzLrg3k+jAHL3E/DlingH2ApZmXpXvTnRBA==","signature_status":"signed_v1","signed_at":"2026-05-18T02:50:32.744014Z","signed_message":"canonical_sha256_bytes"},"source_id":"1406.0824","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0eb2406db4de16e26e56a932dca2c94923993a98c1a95ac5b5e4cfb7d2547c3f","sha256:dd11af386111b7d825210deac9c81c74aa57b7d51dc655a5d1e7695741a5c3a3"],"state_sha256":"dc6e5660e37b1f0a4e31f856281c64f4efb194a100c1156bd18f45dd5a32fca9"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7ddmMz/eShk09gOnWZZJkVxDG+cpBZpoMJhVp9L/vxxhHIw48D6Kkpali4A8JgQX1y0NBV59MtbHroz94oz+CA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-11T20:04:45.886054Z","bundle_sha256":"52227781025a3f0dc3c240d121054df77b2ea531a44a20e0e97a897fefa9fa3f"}}