{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:LM7GBL5GLU42X7S23UL2P72WLW","short_pith_number":"pith:LM7GBL5G","canonical_record":{"source":{"id":"1709.09822","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-fin.PM","submitted_at":"2017-09-28T06:48:48Z","cross_cats_sorted":[],"title_canon_sha256":"2d4b9802e17ce5938339ac5f48d06ed30ab076c31580b68a6769806f1d4d6de6","abstract_canon_sha256":"501e5a93977a09d819fd961a601c00ad825627233498a7543c06b3b846eeacae"},"schema_version":"1.0"},"canonical_sha256":"5b3e60afa65d39abfe5add17a7ff565d94c13af7815353859e106438a8e74fcc","source":{"kind":"arxiv","id":"1709.09822","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1709.09822","created_at":"2026-05-18T00:09:04Z"},{"alias_kind":"arxiv_version","alias_value":"1709.09822v2","created_at":"2026-05-18T00:09:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1709.09822","created_at":"2026-05-18T00:09:04Z"},{"alias_kind":"pith_short_12","alias_value":"LM7GBL5GLU42","created_at":"2026-05-18T12:31:28Z"},{"alias_kind":"pith_short_16","alias_value":"LM7GBL5GLU42X7S2","created_at":"2026-05-18T12:31:28Z"},{"alias_kind":"pith_short_8","alias_value":"LM7GBL5G","created_at":"2026-05-18T12:31:28Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:LM7GBL5GLU42X7S23UL2P72WLW","target":"record","payload":{"canonical_record":{"source":{"id":"1709.09822","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-fin.PM","submitted_at":"2017-09-28T06:48:48Z","cross_cats_sorted":[],"title_canon_sha256":"2d4b9802e17ce5938339ac5f48d06ed30ab076c31580b68a6769806f1d4d6de6","abstract_canon_sha256":"501e5a93977a09d819fd961a601c00ad825627233498a7543c06b3b846eeacae"},"schema_version":"1.0"},"canonical_sha256":"5b3e60afa65d39abfe5add17a7ff565d94c13af7815353859e106438a8e74fcc","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:09:04.234699Z","signature_b64":"a4w/RbpYbwxYFx3oGVfxwcJqMY23ObutK7HISweO8nKDRuiHouCsl8xkfPRfJhih63BiDhQmS0awHvENK9zNAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5b3e60afa65d39abfe5add17a7ff565d94c13af7815353859e106438a8e74fcc","last_reissued_at":"2026-05-18T00:09:04.233998Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:09:04.233998Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1709.09822","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":"2026-05-18T00:09:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GKdv+saafBGhfJKwcY1ZptgusdWSFh2dYSDeYdFQE4sQqNhNwy82VF0RFxGdX5PnzN4p7vi7+HpqBOMWdQfXDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-27T08:57:18.311566Z"},"content_sha256":"616c65e3a4b9dc757d7798877d6a48b97e8db013977f566bb5773c8cfd3f3b62","schema_version":"1.0","event_id":"sha256:616c65e3a4b9dc757d7798877d6a48b97e8db013977f566bb5773c8cfd3f3b62"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:LM7GBL5GLU42X7S23UL2P72WLW","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Threshold-Based Portfolio: The Role of the Threshold and Its Applications","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"q-fin.PM","authors_text":"Sang Il Lee, Seong Joon Yoo","submitted_at":"2017-09-28T06:48:48Z","abstract_excerpt":"This paper aims at developing a new method by which to build a data-driven portfolio featuring a target risk-return. We first present a comparative study of recurrent neural network models (RNNs), including a simple RNN, long short-term memory (LSTM), and gated recurrent unit (GRU) for selecting the best predictor to use in portfolio construction. The models are applied to the investment universe consisted of ten stocks in the S&P500. The experimental results shows that LSTM outperforms the others in terms of hit ratio of one-month-ahead forecasts. We then build predictive threshold-based port"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1709.09822","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":""},"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":"2026-05-18T00:09:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"OWR4sWp2VquJg1hJX9zLghp6CN79D7mEK3qihd46CFN3hS361zJ+tCkNuUhHR1HwvBtj2OJDK6BgsxCrISZjCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-27T08:57:18.311905Z"},"content_sha256":"719a64e1f3c6644eedc162f076fe4cd55b02a53602fec91d5ae6847abd9f4697","schema_version":"1.0","event_id":"sha256:719a64e1f3c6644eedc162f076fe4cd55b02a53602fec91d5ae6847abd9f4697"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/LM7GBL5GLU42X7S23UL2P72WLW/bundle.json","state_url":"https://pith.science/pith/LM7GBL5GLU42X7S23UL2P72WLW/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/LM7GBL5GLU42X7S23UL2P72WLW/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":"2026-06-27T08:57:18Z","links":{"resolver":"https://pith.science/pith/LM7GBL5GLU42X7S23UL2P72WLW","bundle":"https://pith.science/pith/LM7GBL5GLU42X7S23UL2P72WLW/bundle.json","state":"https://pith.science/pith/LM7GBL5GLU42X7S23UL2P72WLW/state.json","well_known_bundle":"https://pith.science/.well-known/pith/LM7GBL5GLU42X7S23UL2P72WLW/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:LM7GBL5GLU42X7S23UL2P72WLW","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":"501e5a93977a09d819fd961a601c00ad825627233498a7543c06b3b846eeacae","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-fin.PM","submitted_at":"2017-09-28T06:48:48Z","title_canon_sha256":"2d4b9802e17ce5938339ac5f48d06ed30ab076c31580b68a6769806f1d4d6de6"},"schema_version":"1.0","source":{"id":"1709.09822","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1709.09822","created_at":"2026-05-18T00:09:04Z"},{"alias_kind":"arxiv_version","alias_value":"1709.09822v2","created_at":"2026-05-18T00:09:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1709.09822","created_at":"2026-05-18T00:09:04Z"},{"alias_kind":"pith_short_12","alias_value":"LM7GBL5GLU42","created_at":"2026-05-18T12:31:28Z"},{"alias_kind":"pith_short_16","alias_value":"LM7GBL5GLU42X7S2","created_at":"2026-05-18T12:31:28Z"},{"alias_kind":"pith_short_8","alias_value":"LM7GBL5G","created_at":"2026-05-18T12:31:28Z"}],"graph_snapshots":[{"event_id":"sha256:719a64e1f3c6644eedc162f076fe4cd55b02a53602fec91d5ae6847abd9f4697","target":"graph","created_at":"2026-05-18T00:09:04Z","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":"This paper aims at developing a new method by which to build a data-driven portfolio featuring a target risk-return. We first present a comparative study of recurrent neural network models (RNNs), including a simple RNN, long short-term memory (LSTM), and gated recurrent unit (GRU) for selecting the best predictor to use in portfolio construction. The models are applied to the investment universe consisted of ten stocks in the S&P500. The experimental results shows that LSTM outperforms the others in terms of hit ratio of one-month-ahead forecasts. We then build predictive threshold-based port","authors_text":"Sang Il Lee, Seong Joon Yoo","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-fin.PM","submitted_at":"2017-09-28T06:48:48Z","title":"Threshold-Based Portfolio: The Role of the Threshold and Its Applications"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1709.09822","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":"sha256:616c65e3a4b9dc757d7798877d6a48b97e8db013977f566bb5773c8cfd3f3b62","target":"record","created_at":"2026-05-18T00:09:04Z","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":"501e5a93977a09d819fd961a601c00ad825627233498a7543c06b3b846eeacae","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-fin.PM","submitted_at":"2017-09-28T06:48:48Z","title_canon_sha256":"2d4b9802e17ce5938339ac5f48d06ed30ab076c31580b68a6769806f1d4d6de6"},"schema_version":"1.0","source":{"id":"1709.09822","kind":"arxiv","version":2}},"canonical_sha256":"5b3e60afa65d39abfe5add17a7ff565d94c13af7815353859e106438a8e74fcc","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5b3e60afa65d39abfe5add17a7ff565d94c13af7815353859e106438a8e74fcc","first_computed_at":"2026-05-18T00:09:04.233998Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:09:04.233998Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"a4w/RbpYbwxYFx3oGVfxwcJqMY23ObutK7HISweO8nKDRuiHouCsl8xkfPRfJhih63BiDhQmS0awHvENK9zNAA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:09:04.234699Z","signed_message":"canonical_sha256_bytes"},"source_id":"1709.09822","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:616c65e3a4b9dc757d7798877d6a48b97e8db013977f566bb5773c8cfd3f3b62","sha256:719a64e1f3c6644eedc162f076fe4cd55b02a53602fec91d5ae6847abd9f4697"],"state_sha256":"09a0d52b5c2ac8203dd9c164d102b403f8cd1dcc2c3c7f086154afbcc2d345b1"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"AN4CT2nWxmH/5e0O7aPcfiuSeLTrJELGN4sXCh+aZhKqZvtL6LwCgsu30Xhx2Gk+rrZ5c6zY6b9Rjfk1PBSFAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-27T08:57:18.314073Z","bundle_sha256":"88e2da10ac5830b5dd52638826463a61d317c9e1b7f4977893fbb012bb6267f0"}}