{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:QOUXGCWQZPONWWHIYALBAKZJTG","short_pith_number":"pith:QOUXGCWQ","schema_version":"1.0","canonical_sha256":"83a9730ad0cbdcdb58e8c016102b2999937a1edc6b8a29b091c450febc482b26","source":{"kind":"arxiv","id":"2301.13255","version":1},"attestation_state":"computed","paper":{"title":"Wavelet Analysis for Time Series Financial Signals via Element Analysis","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"q-fin.ST","authors_text":"Nathan Zavanelli","submitted_at":"2023-01-30T19:48:45Z","abstract_excerpt":"The method of element analysis is proposed here as an alternative to traditional wavelet-based approaches to analyzing perturbations in financial signals by scale. In this method, the processes that generate oscillations in financial signals are modelled as scaled, shifted, and isolated events that produce ripples of various frequencies across a sea of noise as opposed to a simple sinusoidal or mixed frequency oscillation or an impulse. This allows one to directly estimate the wavelet parameters derived only from the generating functions, rejecting spurious perturbations driven by noise or ext"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2301.13255","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"q-fin.ST","submitted_at":"2023-01-30T19:48:45Z","cross_cats_sorted":[],"title_canon_sha256":"92cde3cdac3b9a15a927dfa4e24f51fc092db8978e7e7aa773cc074f5eb7a98f","abstract_canon_sha256":"8f955e08a9feab176f4202c8f81fd884874e8897184df0c885cacc09155c8cc4"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:37:12.856201Z","signature_b64":"RCUJCKb88W6H81QcOyuaCy7jZE+yqW73S/zfgZj/MAh1r3zZogzW1T0JN0h1ZzXyRmRcSOQGRUQJEccbyHKOAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"83a9730ad0cbdcdb58e8c016102b2999937a1edc6b8a29b091c450febc482b26","last_reissued_at":"2026-07-05T05:37:12.855779Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:37:12.855779Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Wavelet Analysis for Time Series Financial Signals via Element Analysis","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"q-fin.ST","authors_text":"Nathan Zavanelli","submitted_at":"2023-01-30T19:48:45Z","abstract_excerpt":"The method of element analysis is proposed here as an alternative to traditional wavelet-based approaches to analyzing perturbations in financial signals by scale. In this method, the processes that generate oscillations in financial signals are modelled as scaled, shifted, and isolated events that produce ripples of various frequencies across a sea of noise as opposed to a simple sinusoidal or mixed frequency oscillation or an impulse. This allows one to directly estimate the wavelet parameters derived only from the generating functions, rejecting spurious perturbations driven by noise or ext"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2301.13255","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2301.13255/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2301.13255","created_at":"2026-07-05T05:37:12.855840+00:00"},{"alias_kind":"arxiv_version","alias_value":"2301.13255v1","created_at":"2026-07-05T05:37:12.855840+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2301.13255","created_at":"2026-07-05T05:37:12.855840+00:00"},{"alias_kind":"pith_short_12","alias_value":"QOUXGCWQZPON","created_at":"2026-07-05T05:37:12.855840+00:00"},{"alias_kind":"pith_short_16","alias_value":"QOUXGCWQZPONWWHI","created_at":"2026-07-05T05:37:12.855840+00:00"},{"alias_kind":"pith_short_8","alias_value":"QOUXGCWQ","created_at":"2026-07-05T05:37:12.855840+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/QOUXGCWQZPONWWHIYALBAKZJTG","json":"https://pith.science/pith/QOUXGCWQZPONWWHIYALBAKZJTG.json","graph_json":"https://pith.science/api/pith-number/QOUXGCWQZPONWWHIYALBAKZJTG/graph.json","events_json":"https://pith.science/api/pith-number/QOUXGCWQZPONWWHIYALBAKZJTG/events.json","paper":"https://pith.science/paper/QOUXGCWQ"},"agent_actions":{"view_html":"https://pith.science/pith/QOUXGCWQZPONWWHIYALBAKZJTG","download_json":"https://pith.science/pith/QOUXGCWQZPONWWHIYALBAKZJTG.json","view_paper":"https://pith.science/paper/QOUXGCWQ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2301.13255&json=true","fetch_graph":"https://pith.science/api/pith-number/QOUXGCWQZPONWWHIYALBAKZJTG/graph.json","fetch_events":"https://pith.science/api/pith-number/QOUXGCWQZPONWWHIYALBAKZJTG/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/QOUXGCWQZPONWWHIYALBAKZJTG/action/timestamp_anchor","attest_storage":"https://pith.science/pith/QOUXGCWQZPONWWHIYALBAKZJTG/action/storage_attestation","attest_author":"https://pith.science/pith/QOUXGCWQZPONWWHIYALBAKZJTG/action/author_attestation","sign_citation":"https://pith.science/pith/QOUXGCWQZPONWWHIYALBAKZJTG/action/citation_signature","submit_replication":"https://pith.science/pith/QOUXGCWQZPONWWHIYALBAKZJTG/action/replication_record"}},"created_at":"2026-07-05T05:37:12.855840+00:00","updated_at":"2026-07-05T05:37:12.855840+00:00"}