{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:UCITIRM452BBMVCI32HFDDFEAQ","short_pith_number":"pith:UCITIRM4","canonical_record":{"source":{"id":"2011.09607","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-fin.TR","submitted_at":"2020-11-19T01:35:05Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"cdec1f208ca650d0fc5fcf30b8f2d72f1f7d8b83cbf7d54fe12761d1573bd7b3","abstract_canon_sha256":"5477f5c3266b3afcff03b31524b04f7d87eac3473f7215bb6579cbf838f1ee90"},"schema_version":"1.0"},"canonical_sha256":"a09134459cee82165448de8e518ca4041647e06e6ef2a316dcb14e94fa029ccc","source":{"kind":"arxiv","id":"2011.09607","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2011.09607","created_at":"2026-07-05T04:01:29Z"},{"alias_kind":"arxiv_version","alias_value":"2011.09607v2","created_at":"2026-07-05T04:01:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2011.09607","created_at":"2026-07-05T04:01:29Z"},{"alias_kind":"pith_short_12","alias_value":"UCITIRM452BB","created_at":"2026-07-05T04:01:29Z"},{"alias_kind":"pith_short_16","alias_value":"UCITIRM452BBMVCI","created_at":"2026-07-05T04:01:29Z"},{"alias_kind":"pith_short_8","alias_value":"UCITIRM4","created_at":"2026-07-05T04:01:29Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:UCITIRM452BBMVCI32HFDDFEAQ","target":"record","payload":{"canonical_record":{"source":{"id":"2011.09607","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-fin.TR","submitted_at":"2020-11-19T01:35:05Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"cdec1f208ca650d0fc5fcf30b8f2d72f1f7d8b83cbf7d54fe12761d1573bd7b3","abstract_canon_sha256":"5477f5c3266b3afcff03b31524b04f7d87eac3473f7215bb6579cbf838f1ee90"},"schema_version":"1.0"},"canonical_sha256":"a09134459cee82165448de8e518ca4041647e06e6ef2a316dcb14e94fa029ccc","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:01:29.862931Z","signature_b64":"XjEHc5T385RyABz0jlOiiNJjQaPhvTVsftsI30mRQ+PZA15TXYQ4lpqS/6c9tyO0mcUfhfK/3Ae7davRCOB1Cg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a09134459cee82165448de8e518ca4041647e06e6ef2a316dcb14e94fa029ccc","last_reissued_at":"2026-07-05T04:01:29.862511Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:01:29.862511Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2011.09607","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":"2026-07-05T04:01:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"HU42rbQjHT9PH/Cu/CYQMvsNrvYYM8h8LHM8B3lps2uRLJ6R2C22lE4NFwaI4bOvssIpftPZ42GVjdDdAoBMBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-08T17:19:05.853023Z"},"content_sha256":"cc00d11ceaf1e29153c1c32ad8b3e590f843d83689b061055e2d4c2004aa0448","schema_version":"1.0","event_id":"sha256:cc00d11ceaf1e29153c1c32ad8b3e590f843d83689b061055e2d4c2004aa0448"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:UCITIRM452BBMVCI32HFDDFEAQ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"FinRL: A Deep Reinforcement Learning Library for Automated Stock Trading in Quantitative Finance","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"q-fin.TR","authors_text":"Bowen Xiao, Christina Dan Wang, Hongyang Yang, Liuqing Yang, Qian Chen, Runjia Zhang, Xiao-Yang Liu","submitted_at":"2020-11-19T01:35:05Z","abstract_excerpt":"As deep reinforcement learning (DRL) has been recognized as an effective approach in quantitative finance, getting hands-on experiences is attractive to beginners. However, to train a practical DRL trading agent that decides where to trade, at what price, and what quantity involves error-prone and arduous development and debugging. In this paper, we introduce a DRL library FinRL that facilitates beginners to expose themselves to quantitative finance and to develop their own stock trading strategies. Along with easily-reproducible tutorials, FinRL library allows users to streamline their own de"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2011.09607","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2011.09607/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":"2026-07-05T04:01:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/aPJeywJH2NnME9BYlx/JBjwlFnrdmsWzeh94QLwzTikaNdvW98zx+JBsiZ7COPeh9egmsBdVPhRbvKBhUG0Dg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-08T17:19:05.853393Z"},"content_sha256":"402ccd107daec9fc0440124094cf8de54a09343ae2151539a857a37d5708fb06","schema_version":"1.0","event_id":"sha256:402ccd107daec9fc0440124094cf8de54a09343ae2151539a857a37d5708fb06"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/UCITIRM452BBMVCI32HFDDFEAQ/bundle.json","state_url":"https://pith.science/pith/UCITIRM452BBMVCI32HFDDFEAQ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/UCITIRM452BBMVCI32HFDDFEAQ/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":"2026-07-08T17:19:05Z","links":{"resolver":"https://pith.science/pith/UCITIRM452BBMVCI32HFDDFEAQ","bundle":"https://pith.science/pith/UCITIRM452BBMVCI32HFDDFEAQ/bundle.json","state":"https://pith.science/pith/UCITIRM452BBMVCI32HFDDFEAQ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/UCITIRM452BBMVCI32HFDDFEAQ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:UCITIRM452BBMVCI32HFDDFEAQ","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":"5477f5c3266b3afcff03b31524b04f7d87eac3473f7215bb6579cbf838f1ee90","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-fin.TR","submitted_at":"2020-11-19T01:35:05Z","title_canon_sha256":"cdec1f208ca650d0fc5fcf30b8f2d72f1f7d8b83cbf7d54fe12761d1573bd7b3"},"schema_version":"1.0","source":{"id":"2011.09607","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2011.09607","created_at":"2026-07-05T04:01:29Z"},{"alias_kind":"arxiv_version","alias_value":"2011.09607v2","created_at":"2026-07-05T04:01:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2011.09607","created_at":"2026-07-05T04:01:29Z"},{"alias_kind":"pith_short_12","alias_value":"UCITIRM452BB","created_at":"2026-07-05T04:01:29Z"},{"alias_kind":"pith_short_16","alias_value":"UCITIRM452BBMVCI","created_at":"2026-07-05T04:01:29Z"},{"alias_kind":"pith_short_8","alias_value":"UCITIRM4","created_at":"2026-07-05T04:01:29Z"}],"graph_snapshots":[{"event_id":"sha256:402ccd107daec9fc0440124094cf8de54a09343ae2151539a857a37d5708fb06","target":"graph","created_at":"2026-07-05T04:01:29Z","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/2011.09607/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"As deep reinforcement learning (DRL) has been recognized as an effective approach in quantitative finance, getting hands-on experiences is attractive to beginners. However, to train a practical DRL trading agent that decides where to trade, at what price, and what quantity involves error-prone and arduous development and debugging. In this paper, we introduce a DRL library FinRL that facilitates beginners to expose themselves to quantitative finance and to develop their own stock trading strategies. Along with easily-reproducible tutorials, FinRL library allows users to streamline their own de","authors_text":"Bowen Xiao, Christina Dan Wang, Hongyang Yang, Liuqing Yang, Qian Chen, Runjia Zhang, Xiao-Yang Liu","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-fin.TR","submitted_at":"2020-11-19T01:35:05Z","title":"FinRL: A Deep Reinforcement Learning Library for Automated Stock Trading in Quantitative Finance"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2011.09607","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:cc00d11ceaf1e29153c1c32ad8b3e590f843d83689b061055e2d4c2004aa0448","target":"record","created_at":"2026-07-05T04:01:29Z","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":"5477f5c3266b3afcff03b31524b04f7d87eac3473f7215bb6579cbf838f1ee90","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-fin.TR","submitted_at":"2020-11-19T01:35:05Z","title_canon_sha256":"cdec1f208ca650d0fc5fcf30b8f2d72f1f7d8b83cbf7d54fe12761d1573bd7b3"},"schema_version":"1.0","source":{"id":"2011.09607","kind":"arxiv","version":2}},"canonical_sha256":"a09134459cee82165448de8e518ca4041647e06e6ef2a316dcb14e94fa029ccc","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a09134459cee82165448de8e518ca4041647e06e6ef2a316dcb14e94fa029ccc","first_computed_at":"2026-07-05T04:01:29.862511Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:01:29.862511Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"XjEHc5T385RyABz0jlOiiNJjQaPhvTVsftsI30mRQ+PZA15TXYQ4lpqS/6c9tyO0mcUfhfK/3Ae7davRCOB1Cg==","signature_status":"signed_v1","signed_at":"2026-07-05T04:01:29.862931Z","signed_message":"canonical_sha256_bytes"},"source_id":"2011.09607","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:cc00d11ceaf1e29153c1c32ad8b3e590f843d83689b061055e2d4c2004aa0448","sha256:402ccd107daec9fc0440124094cf8de54a09343ae2151539a857a37d5708fb06"],"state_sha256":"21f11aab5436b540117227192e8ecb452e9a25b2d69b36cd3d3ea46cebd91252"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5WR7aHQImEnNMpt7YIJoquoVzYh3CfgmtYZ6L0TLryojtsL0qrexpioYepoEJaPv+NQKy7TiUENcNGDMC9+kAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-08T17:19:05.855705Z","bundle_sha256":"82e08b6cd666ca5f72019caaf868971793c39b3d8f4ac53229603e2537cea793"}}