{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:M2ZTKBYVKIRH4SPAJFEWAH4NMA","short_pith_number":"pith:M2ZTKBYV","canonical_record":{"source":{"id":"1708.02073","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-fin.ST","submitted_at":"2017-08-07T11:21:38Z","cross_cats_sorted":[],"title_canon_sha256":"663c125a443d1e7225abc4109b63c6c8360fbbbc3b59f444840fb1c1378ec38e","abstract_canon_sha256":"a8134fe31d20e8b7cc6ca9ff338ef93004a6992b7b7b04755e8cfbdc5336be09"},"schema_version":"1.0"},"canonical_sha256":"66b335071552227e49e04949601f8d60325a522f1be49ef917a5b8d1f9644f70","source":{"kind":"arxiv","id":"1708.02073","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1708.02073","created_at":"2026-05-18T00:38:32Z"},{"alias_kind":"arxiv_version","alias_value":"1708.02073v1","created_at":"2026-05-18T00:38:32Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1708.02073","created_at":"2026-05-18T00:38:32Z"},{"alias_kind":"pith_short_12","alias_value":"M2ZTKBYVKIRH","created_at":"2026-05-18T12:31:28Z"},{"alias_kind":"pith_short_16","alias_value":"M2ZTKBYVKIRH4SPA","created_at":"2026-05-18T12:31:28Z"},{"alias_kind":"pith_short_8","alias_value":"M2ZTKBYV","created_at":"2026-05-18T12:31:28Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:M2ZTKBYVKIRH4SPAJFEWAH4NMA","target":"record","payload":{"canonical_record":{"source":{"id":"1708.02073","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-fin.ST","submitted_at":"2017-08-07T11:21:38Z","cross_cats_sorted":[],"title_canon_sha256":"663c125a443d1e7225abc4109b63c6c8360fbbbc3b59f444840fb1c1378ec38e","abstract_canon_sha256":"a8134fe31d20e8b7cc6ca9ff338ef93004a6992b7b7b04755e8cfbdc5336be09"},"schema_version":"1.0"},"canonical_sha256":"66b335071552227e49e04949601f8d60325a522f1be49ef917a5b8d1f9644f70","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:38:32.387412Z","signature_b64":"j9Wvj17UyXeWT9hibUuC2QqEsWlFRX8hJxFwrZpvDRTjx652F2/Kojha0AkEF6+1Ee1C3NoUpkn1fEPFBV3AAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"66b335071552227e49e04949601f8d60325a522f1be49ef917a5b8d1f9644f70","last_reissued_at":"2026-05-18T00:38:32.386988Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:38:32.386988Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1708.02073","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":"2026-05-18T00:38:32Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"VmiLPpdtDE52ieX2o0ErrX13hTGub38q8a08JtD2oHAouCS1Zj0Ppyv7OYkbGhF2Pmzd58Y4gIBQgkvBoz/bCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-06T12:51:54.655763Z"},"content_sha256":"1fcdbad042eadbc5b3fdb88cb51eeb341dc9c368803a36dfb0e38c443999a99e","schema_version":"1.0","event_id":"sha256:1fcdbad042eadbc5b3fdb88cb51eeb341dc9c368803a36dfb0e38c443999a99e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:M2ZTKBYVKIRH4SPAJFEWAH4NMA","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Volatility Spillovers and Heavy Tails: A Large t-Vector AutoRegressive Approach","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"q-fin.ST","authors_text":"Christophe Croux, Ines Wilms, Luca Barbaglia","submitted_at":"2017-08-07T11:21:38Z","abstract_excerpt":"Volatility is a key measure of risk in financial analysis. The high volatility of one financial asset today could affect the volatility of another asset tomorrow. These lagged effects among volatilities - which we call volatility spillovers - are studied using the Vector AutoRegressive (VAR) model. We account for the possible fat-tailed distribution of the VAR model errors using a VAR model with errors following a multivariate Student t-distribution with unknown degrees of freedom. Moreover, we study volatility spillovers among a large number of assets. To this end, we use penalized estimation"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1708.02073","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":"2026-05-18T00:38:32Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Uk9IN35WT++kzJsw2STeXuex1ziJnM6+MVCazHgCNmaxnJxzudVImoKctcORodkK7SWVr5aJ9D1QaHAMBkysAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-06T12:51:54.656107Z"},"content_sha256":"733224817d9eaff92877ac5305d0df835b9c4cd0db5758a7f65d021c4aa07ab5","schema_version":"1.0","event_id":"sha256:733224817d9eaff92877ac5305d0df835b9c4cd0db5758a7f65d021c4aa07ab5"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/M2ZTKBYVKIRH4SPAJFEWAH4NMA/bundle.json","state_url":"https://pith.science/pith/M2ZTKBYVKIRH4SPAJFEWAH4NMA/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/M2ZTKBYVKIRH4SPAJFEWAH4NMA/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":"2026-06-06T12:51:54Z","links":{"resolver":"https://pith.science/pith/M2ZTKBYVKIRH4SPAJFEWAH4NMA","bundle":"https://pith.science/pith/M2ZTKBYVKIRH4SPAJFEWAH4NMA/bundle.json","state":"https://pith.science/pith/M2ZTKBYVKIRH4SPAJFEWAH4NMA/state.json","well_known_bundle":"https://pith.science/.well-known/pith/M2ZTKBYVKIRH4SPAJFEWAH4NMA/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:M2ZTKBYVKIRH4SPAJFEWAH4NMA","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":"a8134fe31d20e8b7cc6ca9ff338ef93004a6992b7b7b04755e8cfbdc5336be09","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-fin.ST","submitted_at":"2017-08-07T11:21:38Z","title_canon_sha256":"663c125a443d1e7225abc4109b63c6c8360fbbbc3b59f444840fb1c1378ec38e"},"schema_version":"1.0","source":{"id":"1708.02073","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1708.02073","created_at":"2026-05-18T00:38:32Z"},{"alias_kind":"arxiv_version","alias_value":"1708.02073v1","created_at":"2026-05-18T00:38:32Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1708.02073","created_at":"2026-05-18T00:38:32Z"},{"alias_kind":"pith_short_12","alias_value":"M2ZTKBYVKIRH","created_at":"2026-05-18T12:31:28Z"},{"alias_kind":"pith_short_16","alias_value":"M2ZTKBYVKIRH4SPA","created_at":"2026-05-18T12:31:28Z"},{"alias_kind":"pith_short_8","alias_value":"M2ZTKBYV","created_at":"2026-05-18T12:31:28Z"}],"graph_snapshots":[{"event_id":"sha256:733224817d9eaff92877ac5305d0df835b9c4cd0db5758a7f65d021c4aa07ab5","target":"graph","created_at":"2026-05-18T00:38:32Z","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":"Volatility is a key measure of risk in financial analysis. The high volatility of one financial asset today could affect the volatility of another asset tomorrow. These lagged effects among volatilities - which we call volatility spillovers - are studied using the Vector AutoRegressive (VAR) model. We account for the possible fat-tailed distribution of the VAR model errors using a VAR model with errors following a multivariate Student t-distribution with unknown degrees of freedom. Moreover, we study volatility spillovers among a large number of assets. To this end, we use penalized estimation","authors_text":"Christophe Croux, Ines Wilms, Luca Barbaglia","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-fin.ST","submitted_at":"2017-08-07T11:21:38Z","title":"Volatility Spillovers and Heavy Tails: A Large t-Vector AutoRegressive Approach"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1708.02073","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":"sha256:1fcdbad042eadbc5b3fdb88cb51eeb341dc9c368803a36dfb0e38c443999a99e","target":"record","created_at":"2026-05-18T00:38:32Z","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":"a8134fe31d20e8b7cc6ca9ff338ef93004a6992b7b7b04755e8cfbdc5336be09","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-fin.ST","submitted_at":"2017-08-07T11:21:38Z","title_canon_sha256":"663c125a443d1e7225abc4109b63c6c8360fbbbc3b59f444840fb1c1378ec38e"},"schema_version":"1.0","source":{"id":"1708.02073","kind":"arxiv","version":1}},"canonical_sha256":"66b335071552227e49e04949601f8d60325a522f1be49ef917a5b8d1f9644f70","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"66b335071552227e49e04949601f8d60325a522f1be49ef917a5b8d1f9644f70","first_computed_at":"2026-05-18T00:38:32.386988Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:38:32.386988Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"j9Wvj17UyXeWT9hibUuC2QqEsWlFRX8hJxFwrZpvDRTjx652F2/Kojha0AkEF6+1Ee1C3NoUpkn1fEPFBV3AAw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:38:32.387412Z","signed_message":"canonical_sha256_bytes"},"source_id":"1708.02073","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1fcdbad042eadbc5b3fdb88cb51eeb341dc9c368803a36dfb0e38c443999a99e","sha256:733224817d9eaff92877ac5305d0df835b9c4cd0db5758a7f65d021c4aa07ab5"],"state_sha256":"be10cb831c7acc1deecb7e3aa1d04e3d48d7ca7282e7286694a8fd3b43b5e2e7"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"HPPT4BTXw0MF3ywAoCFPxpMZxhr93BoN7Y5BqSUD5MhQK9sDF4Ns81lmdOpVfMSgkDo0QwEGx7FHCPU48pufCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-06T12:51:54.658029Z","bundle_sha256":"c6b8b33998e6f34ef4ca03a4b7c1fbae97b4d6c7e06ecccd260e01369f4e1ee7"}}