{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:XOK7HN4LCJECKOZQBIUFV7GKKM","short_pith_number":"pith:XOK7HN4L","canonical_record":{"source":{"id":"2501.01278","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"q-fin.CP","submitted_at":"2025-01-02T14:21:28Z","cross_cats_sorted":[],"title_canon_sha256":"be63b6ba1611941df51e2a5a82427873d9e938919c371579d9d2628fd0a38a5d","abstract_canon_sha256":"c92d0c67b8c8f94249f03fdad0270e5a48aaf36425aaaeec0fee1ec5369eca0c"},"schema_version":"1.0"},"canonical_sha256":"bb95f3b78b1248253b300a285afcca531d5e9433b68b833cb8553bbbab90176b","source":{"kind":"arxiv","id":"2501.01278","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.01278","created_at":"2026-07-05T09:56:17Z"},{"alias_kind":"arxiv_version","alias_value":"2501.01278v1","created_at":"2026-07-05T09:56:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.01278","created_at":"2026-07-05T09:56:17Z"},{"alias_kind":"pith_short_12","alias_value":"XOK7HN4LCJEC","created_at":"2026-07-05T09:56:17Z"},{"alias_kind":"pith_short_16","alias_value":"XOK7HN4LCJECKOZQ","created_at":"2026-07-05T09:56:17Z"},{"alias_kind":"pith_short_8","alias_value":"XOK7HN4L","created_at":"2026-07-05T09:56:17Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:XOK7HN4LCJECKOZQBIUFV7GKKM","target":"record","payload":{"canonical_record":{"source":{"id":"2501.01278","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"q-fin.CP","submitted_at":"2025-01-02T14:21:28Z","cross_cats_sorted":[],"title_canon_sha256":"be63b6ba1611941df51e2a5a82427873d9e938919c371579d9d2628fd0a38a5d","abstract_canon_sha256":"c92d0c67b8c8f94249f03fdad0270e5a48aaf36425aaaeec0fee1ec5369eca0c"},"schema_version":"1.0"},"canonical_sha256":"bb95f3b78b1248253b300a285afcca531d5e9433b68b833cb8553bbbab90176b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:56:17.261069Z","signature_b64":"a5B1m8FBG+htxRF720Af4ajjxYCCSHWe2uuVbm317p8KGW/HXDmywnr9nP03/BRfFnYU6ctstHeXMXzmmZpgAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"bb95f3b78b1248253b300a285afcca531d5e9433b68b833cb8553bbbab90176b","last_reissued_at":"2026-07-05T09:56:17.260616Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:56:17.260616Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2501.01278","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":"2026-07-05T09:56:17Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"IRwCk3yoCT3kj31c9dzs5kkPxXjwP7Ntp6sp7ZPgfnQQTXv6y5tZ3UpZgNflHqqEp7Rib8x0UUM4zs8pWrcODQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T13:51:19.036306Z"},"content_sha256":"07b2d0b7f93a3be8327c55264c883208281da3d8c6f275d7efe4071ca8b0a977","schema_version":"1.0","event_id":"sha256:07b2d0b7f93a3be8327c55264c883208281da3d8c6f275d7efe4071ca8b0a977"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:XOK7HN4LCJECKOZQBIUFV7GKKM","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Risk forecasting using Long Short-Term Memory Mixture Density Networks","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"q-fin.CP","authors_text":"Nico Herrig","submitted_at":"2025-01-02T14:21:28Z","abstract_excerpt":"This work aims to implement Long Short-Term Memory mixture density networks (LSTM-MDNs) for Value-at-Risk forecasting and compare their performance with established models (historical simulation, CMM, and GARCH) using a defined backtesting procedure. The focus was on the neural network's ability to capture volatility clustering and its real-world applicability. Three architectures were tested: a 2-component mixture density network, a regularized 2-component model (Arimond et al., 2020), and a 3-component mixture model, the latter being tested for the first time in Value-at-Risk forecasting.\n  "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.01278","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/2501.01278/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":"2026-07-05T09:56:17Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"C0jkaiojLTKDfA4rB7T7bDhPcTJEBPSXX+9ckKATo5Xi4FmiABF2qpW4TV47uzDBEx5+HV0Gngm/QOjtS5rYBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T13:51:19.036854Z"},"content_sha256":"179f8a40f46194acc34d973b95a1141bad6c1f469d08b836dc1bdb8f884622d2","schema_version":"1.0","event_id":"sha256:179f8a40f46194acc34d973b95a1141bad6c1f469d08b836dc1bdb8f884622d2"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/XOK7HN4LCJECKOZQBIUFV7GKKM/bundle.json","state_url":"https://pith.science/pith/XOK7HN4LCJECKOZQBIUFV7GKKM/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/XOK7HN4LCJECKOZQBIUFV7GKKM/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":"2026-08-19T13:51:19Z","links":{"resolver":"https://pith.science/pith/XOK7HN4LCJECKOZQBIUFV7GKKM","bundle":"https://pith.science/pith/XOK7HN4LCJECKOZQBIUFV7GKKM/bundle.json","state":"https://pith.science/pith/XOK7HN4LCJECKOZQBIUFV7GKKM/state.json","well_known_bundle":"https://pith.science/.well-known/pith/XOK7HN4LCJECKOZQBIUFV7GKKM/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:XOK7HN4LCJECKOZQBIUFV7GKKM","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":"c92d0c67b8c8f94249f03fdad0270e5a48aaf36425aaaeec0fee1ec5369eca0c","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"q-fin.CP","submitted_at":"2025-01-02T14:21:28Z","title_canon_sha256":"be63b6ba1611941df51e2a5a82427873d9e938919c371579d9d2628fd0a38a5d"},"schema_version":"1.0","source":{"id":"2501.01278","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.01278","created_at":"2026-07-05T09:56:17Z"},{"alias_kind":"arxiv_version","alias_value":"2501.01278v1","created_at":"2026-07-05T09:56:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.01278","created_at":"2026-07-05T09:56:17Z"},{"alias_kind":"pith_short_12","alias_value":"XOK7HN4LCJEC","created_at":"2026-07-05T09:56:17Z"},{"alias_kind":"pith_short_16","alias_value":"XOK7HN4LCJECKOZQ","created_at":"2026-07-05T09:56:17Z"},{"alias_kind":"pith_short_8","alias_value":"XOK7HN4L","created_at":"2026-07-05T09:56:17Z"}],"graph_snapshots":[{"event_id":"sha256:179f8a40f46194acc34d973b95a1141bad6c1f469d08b836dc1bdb8f884622d2","target":"graph","created_at":"2026-07-05T09:56:17Z","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/2501.01278/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This work aims to implement Long Short-Term Memory mixture density networks (LSTM-MDNs) for Value-at-Risk forecasting and compare their performance with established models (historical simulation, CMM, and GARCH) using a defined backtesting procedure. The focus was on the neural network's ability to capture volatility clustering and its real-world applicability. Three architectures were tested: a 2-component mixture density network, a regularized 2-component model (Arimond et al., 2020), and a 3-component mixture model, the latter being tested for the first time in Value-at-Risk forecasting.\n  ","authors_text":"Nico Herrig","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"q-fin.CP","submitted_at":"2025-01-02T14:21:28Z","title":"Risk forecasting using Long Short-Term Memory Mixture Density Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.01278","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":"sha256:07b2d0b7f93a3be8327c55264c883208281da3d8c6f275d7efe4071ca8b0a977","target":"record","created_at":"2026-07-05T09:56:17Z","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":"c92d0c67b8c8f94249f03fdad0270e5a48aaf36425aaaeec0fee1ec5369eca0c","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"q-fin.CP","submitted_at":"2025-01-02T14:21:28Z","title_canon_sha256":"be63b6ba1611941df51e2a5a82427873d9e938919c371579d9d2628fd0a38a5d"},"schema_version":"1.0","source":{"id":"2501.01278","kind":"arxiv","version":1}},"canonical_sha256":"bb95f3b78b1248253b300a285afcca531d5e9433b68b833cb8553bbbab90176b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"bb95f3b78b1248253b300a285afcca531d5e9433b68b833cb8553bbbab90176b","first_computed_at":"2026-07-05T09:56:17.260616Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:56:17.260616Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"a5B1m8FBG+htxRF720Af4ajjxYCCSHWe2uuVbm317p8KGW/HXDmywnr9nP03/BRfFnYU6ctstHeXMXzmmZpgAA==","signature_status":"signed_v1","signed_at":"2026-07-05T09:56:17.261069Z","signed_message":"canonical_sha256_bytes"},"source_id":"2501.01278","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:07b2d0b7f93a3be8327c55264c883208281da3d8c6f275d7efe4071ca8b0a977","sha256:179f8a40f46194acc34d973b95a1141bad6c1f469d08b836dc1bdb8f884622d2"],"state_sha256":"ed9b846b1a945371802f4c806633a9502a5b57cf44993aa3d6c5fbe9b28a1da2"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"EiXo7IeChrfJvbcGPv9X5ZKa+svBUOa9eu6c5AfW7x2hknRLvfbHhfg2fZ6uRck8hy9lEyOAj6rOW8RfMdoABg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-19T13:51:19.041073Z","bundle_sha256":"27c5d648031e160517d903485f4d95f590717de49a1420ff7ae2a89f6d90bcb3"}}