{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:4ZHKWOV3SCWLSBH46VWQ7TJBY5","short_pith_number":"pith:4ZHKWOV3","canonical_record":{"source":{"id":"2412.16160","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"q-fin.ST","submitted_at":"2024-11-23T18:30:04Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"130f9ae5d01181b95e03ddd9436069f4e81b0c6c8ecc3450941c57cd9a28e934","abstract_canon_sha256":"3909bca5487c2545daa0e36c1e9e7307889b7da38283791744d73af23ff4639d"},"schema_version":"1.0"},"canonical_sha256":"e64eab3abb90acb904fcf56d0fcd21c7781128765e5e9168d68e33f677842591","source":{"kind":"arxiv","id":"2412.16160","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.16160","created_at":"2026-07-05T09:54:30Z"},{"alias_kind":"arxiv_version","alias_value":"2412.16160v2","created_at":"2026-07-05T09:54:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.16160","created_at":"2026-07-05T09:54:30Z"},{"alias_kind":"pith_short_12","alias_value":"4ZHKWOV3SCWL","created_at":"2026-07-05T09:54:30Z"},{"alias_kind":"pith_short_16","alias_value":"4ZHKWOV3SCWLSBH4","created_at":"2026-07-05T09:54:30Z"},{"alias_kind":"pith_short_8","alias_value":"4ZHKWOV3","created_at":"2026-07-05T09:54:30Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:4ZHKWOV3SCWLSBH46VWQ7TJBY5","target":"record","payload":{"canonical_record":{"source":{"id":"2412.16160","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"q-fin.ST","submitted_at":"2024-11-23T18:30:04Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"130f9ae5d01181b95e03ddd9436069f4e81b0c6c8ecc3450941c57cd9a28e934","abstract_canon_sha256":"3909bca5487c2545daa0e36c1e9e7307889b7da38283791744d73af23ff4639d"},"schema_version":"1.0"},"canonical_sha256":"e64eab3abb90acb904fcf56d0fcd21c7781128765e5e9168d68e33f677842591","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:54:30.662659Z","signature_b64":"30MN6EVz+Cj96OW/+i2OjS76JHx0N7c5oUtIIe38K30kOvdVJQrDBCzfchcavdyupED7aFH0qjydRXHIRSFvCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e64eab3abb90acb904fcf56d0fcd21c7781128765e5e9168d68e33f677842591","last_reissued_at":"2026-07-05T09:54:30.662242Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:54:30.662242Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2412.16160","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:54:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"IzbVv0FZZkz8CVZvMSHzcFlTQFpx0D5mvW6401fMd+eDdwJD6DCLwRbAp4vdsaIuRCkIX5d4Dwcz4ua4Zh7KAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-12T23:17:41.798888Z"},"content_sha256":"ec624758c8595f95fff99f3f426bed41fed8b0f7b9933decf3ae6afb90723caf","schema_version":"1.0","event_id":"sha256:ec624758c8595f95fff99f3f426bed41fed8b0f7b9933decf3ae6afb90723caf"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:4ZHKWOV3SCWLSBH46VWQ7TJBY5","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Online High-Frequency Trading Stock Forecasting with Automated Feature Clustering and Radial Basis Function Neural Networks","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"q-fin.ST","authors_text":"Adamantios Ntakaris, Gbenga Ibikunle","submitted_at":"2024-11-23T18:30:04Z","abstract_excerpt":"This study presents an autonomous experimental machine learning protocol for high-frequency trading (HFT) stock price forecasting that involves a dual competitive feature importance mechanism and clustering via shallow neural network topology for fast training. By incorporating the k-means algorithm into the radial basis function neural network (RBFNN), the proposed method addresses the challenges of manual clustering and the reliance on potentially uninformative features. More specifically, our approach involves a dual competitive mechanism for feature importance, combining the mean-decrease "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.16160","kind":"arxiv","version":2},"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/2412.16160/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":"2026-07-05T09:54:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nRwaFjibeAkZiqa1JsebcuXQMWAdiDqkFUWLleamleGk8YglKcrdI9AiWHduP1fMMri1c0qBWhcA65qCpz3+Cw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-12T23:17:41.799821Z"},"content_sha256":"24c30d584c9813c123044984f23c624eb04758147a6b68749f6d95bd02515749","schema_version":"1.0","event_id":"sha256:24c30d584c9813c123044984f23c624eb04758147a6b68749f6d95bd02515749"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/4ZHKWOV3SCWLSBH46VWQ7TJBY5/bundle.json","state_url":"https://pith.science/pith/4ZHKWOV3SCWLSBH46VWQ7TJBY5/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/4ZHKWOV3SCWLSBH46VWQ7TJBY5/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":"2026-08-12T23:17:41Z","links":{"resolver":"https://pith.science/pith/4ZHKWOV3SCWLSBH46VWQ7TJBY5","bundle":"https://pith.science/pith/4ZHKWOV3SCWLSBH46VWQ7TJBY5/bundle.json","state":"https://pith.science/pith/4ZHKWOV3SCWLSBH46VWQ7TJBY5/state.json","well_known_bundle":"https://pith.science/.well-known/pith/4ZHKWOV3SCWLSBH46VWQ7TJBY5/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:4ZHKWOV3SCWLSBH46VWQ7TJBY5","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":"3909bca5487c2545daa0e36c1e9e7307889b7da38283791744d73af23ff4639d","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"q-fin.ST","submitted_at":"2024-11-23T18:30:04Z","title_canon_sha256":"130f9ae5d01181b95e03ddd9436069f4e81b0c6c8ecc3450941c57cd9a28e934"},"schema_version":"1.0","source":{"id":"2412.16160","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.16160","created_at":"2026-07-05T09:54:30Z"},{"alias_kind":"arxiv_version","alias_value":"2412.16160v2","created_at":"2026-07-05T09:54:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.16160","created_at":"2026-07-05T09:54:30Z"},{"alias_kind":"pith_short_12","alias_value":"4ZHKWOV3SCWL","created_at":"2026-07-05T09:54:30Z"},{"alias_kind":"pith_short_16","alias_value":"4ZHKWOV3SCWLSBH4","created_at":"2026-07-05T09:54:30Z"},{"alias_kind":"pith_short_8","alias_value":"4ZHKWOV3","created_at":"2026-07-05T09:54:30Z"}],"graph_snapshots":[{"event_id":"sha256:24c30d584c9813c123044984f23c624eb04758147a6b68749f6d95bd02515749","target":"graph","created_at":"2026-07-05T09:54:30Z","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/2412.16160/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This study presents an autonomous experimental machine learning protocol for high-frequency trading (HFT) stock price forecasting that involves a dual competitive feature importance mechanism and clustering via shallow neural network topology for fast training. By incorporating the k-means algorithm into the radial basis function neural network (RBFNN), the proposed method addresses the challenges of manual clustering and the reliance on potentially uninformative features. More specifically, our approach involves a dual competitive mechanism for feature importance, combining the mean-decrease ","authors_text":"Adamantios Ntakaris, Gbenga Ibikunle","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"q-fin.ST","submitted_at":"2024-11-23T18:30:04Z","title":"Online High-Frequency Trading Stock Forecasting with Automated Feature Clustering and Radial Basis Function Neural Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.16160","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:ec624758c8595f95fff99f3f426bed41fed8b0f7b9933decf3ae6afb90723caf","target":"record","created_at":"2026-07-05T09:54:30Z","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":"3909bca5487c2545daa0e36c1e9e7307889b7da38283791744d73af23ff4639d","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"q-fin.ST","submitted_at":"2024-11-23T18:30:04Z","title_canon_sha256":"130f9ae5d01181b95e03ddd9436069f4e81b0c6c8ecc3450941c57cd9a28e934"},"schema_version":"1.0","source":{"id":"2412.16160","kind":"arxiv","version":2}},"canonical_sha256":"e64eab3abb90acb904fcf56d0fcd21c7781128765e5e9168d68e33f677842591","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e64eab3abb90acb904fcf56d0fcd21c7781128765e5e9168d68e33f677842591","first_computed_at":"2026-07-05T09:54:30.662242Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:54:30.662242Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"30MN6EVz+Cj96OW/+i2OjS76JHx0N7c5oUtIIe38K30kOvdVJQrDBCzfchcavdyupED7aFH0qjydRXHIRSFvCw==","signature_status":"signed_v1","signed_at":"2026-07-05T09:54:30.662659Z","signed_message":"canonical_sha256_bytes"},"source_id":"2412.16160","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ec624758c8595f95fff99f3f426bed41fed8b0f7b9933decf3ae6afb90723caf","sha256:24c30d584c9813c123044984f23c624eb04758147a6b68749f6d95bd02515749"],"state_sha256":"d11141e0cdcc8230f1016b7b7b670c005051705b0e947f10d5fbe66331edaec6"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"TbPFQYPM2WeeIzyzPqQfdBBAJJ0KRNIAk3N1JF19hNbiq8gFnjjw4VQzkr3ovZGJkS/3osDO/rQZMI4PF9eBBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-12T23:17:41.808136Z","bundle_sha256":"739118698218234fba59e9ffd58e0900837a744df98fb0b8ab794208dab4cc7f"}}