{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:FL2S4SECNFYG5GPRCOFA76PIJS","short_pith_number":"pith:FL2S4SEC","schema_version":"1.0","canonical_sha256":"2af52e488269706e99f1138a0ff9e84c80e40d19d07266ee23a99f53e6a21835","source":{"kind":"arxiv","id":"1710.10980","version":1},"attestation_state":"computed","paper":{"title":"Statistical validation of financial time series via visibility graph","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.SI","physics.soc-ph","stat.ME"],"primary_cat":"q-fin.RM","authors_text":"Andrea Gabrielli, Giulio Cimini, Guido Caldarelli, Matteo Serafino","submitted_at":"2017-10-30T14:38:04Z","abstract_excerpt":"Statistical physics of complex systems exploits network theory not only to model, but also to effectively extract information from many dynamical real-world systems. A pivotal case of study is given by financial systems: market prediction represents an unsolved scientific challenge yet with crucial implications for society, as financial crises have devastating effects on real economies. Thus, nowadays the quest for a robust estimator of market efficiency is both a scientific and institutional priority. In this work we study the visibility graphs built from the time series of several trade mark"},"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":"1710.10980","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-fin.RM","submitted_at":"2017-10-30T14:38:04Z","cross_cats_sorted":["cs.SI","physics.soc-ph","stat.ME"],"title_canon_sha256":"f20ce06f00cf6b69fcfc0e32b0e677718177e56818689c544482ca4280cbfc82","abstract_canon_sha256":"94cf08cc527c4206489abc23e5a8539dda782e1eabc02ea68993db3d6b20a9a4"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:31:45.952648Z","signature_b64":"MxxziQDz46fmVaZms9uFseoDv2oF7WtWMH+9B3r/O4VIcV82kHQBfvN7fM3gOFCYLw75gatgyrbT2FGIk6RnBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2af52e488269706e99f1138a0ff9e84c80e40d19d07266ee23a99f53e6a21835","last_reissued_at":"2026-05-18T00:31:45.952035Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:31:45.952035Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Statistical validation of financial time series via visibility graph","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.SI","physics.soc-ph","stat.ME"],"primary_cat":"q-fin.RM","authors_text":"Andrea Gabrielli, Giulio Cimini, Guido Caldarelli, Matteo Serafino","submitted_at":"2017-10-30T14:38:04Z","abstract_excerpt":"Statistical physics of complex systems exploits network theory not only to model, but also to effectively extract information from many dynamical real-world systems. A pivotal case of study is given by financial systems: market prediction represents an unsolved scientific challenge yet with crucial implications for society, as financial crises have devastating effects on real economies. Thus, nowadays the quest for a robust estimator of market efficiency is both a scientific and institutional priority. In this work we study the visibility graphs built from the time series of several trade mark"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1710.10980","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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1710.10980","created_at":"2026-05-18T00:31:45.952121+00:00"},{"alias_kind":"arxiv_version","alias_value":"1710.10980v1","created_at":"2026-05-18T00:31:45.952121+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1710.10980","created_at":"2026-05-18T00:31:45.952121+00:00"},{"alias_kind":"pith_short_12","alias_value":"FL2S4SECNFYG","created_at":"2026-05-18T12:31:15.632608+00:00"},{"alias_kind":"pith_short_16","alias_value":"FL2S4SECNFYG5GPR","created_at":"2026-05-18T12:31:15.632608+00:00"},{"alias_kind":"pith_short_8","alias_value":"FL2S4SEC","created_at":"2026-05-18T12:31:15.632608+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/FL2S4SECNFYG5GPRCOFA76PIJS","json":"https://pith.science/pith/FL2S4SECNFYG5GPRCOFA76PIJS.json","graph_json":"https://pith.science/api/pith-number/FL2S4SECNFYG5GPRCOFA76PIJS/graph.json","events_json":"https://pith.science/api/pith-number/FL2S4SECNFYG5GPRCOFA76PIJS/events.json","paper":"https://pith.science/paper/FL2S4SEC"},"agent_actions":{"view_html":"https://pith.science/pith/FL2S4SECNFYG5GPRCOFA76PIJS","download_json":"https://pith.science/pith/FL2S4SECNFYG5GPRCOFA76PIJS.json","view_paper":"https://pith.science/paper/FL2S4SEC","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1710.10980&json=true","fetch_graph":"https://pith.science/api/pith-number/FL2S4SECNFYG5GPRCOFA76PIJS/graph.json","fetch_events":"https://pith.science/api/pith-number/FL2S4SECNFYG5GPRCOFA76PIJS/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/FL2S4SECNFYG5GPRCOFA76PIJS/action/timestamp_anchor","attest_storage":"https://pith.science/pith/FL2S4SECNFYG5GPRCOFA76PIJS/action/storage_attestation","attest_author":"https://pith.science/pith/FL2S4SECNFYG5GPRCOFA76PIJS/action/author_attestation","sign_citation":"https://pith.science/pith/FL2S4SECNFYG5GPRCOFA76PIJS/action/citation_signature","submit_replication":"https://pith.science/pith/FL2S4SECNFYG5GPRCOFA76PIJS/action/replication_record"}},"created_at":"2026-05-18T00:31:45.952121+00:00","updated_at":"2026-05-18T00:31:45.952121+00:00"}