{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:Q57DEHIFVHY3K4437Z5AFFCYG2","short_pith_number":"pith:Q57DEHIF","canonical_record":{"source":{"id":"2209.05559","kind":"arxiv","version":6},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-fin.ST","submitted_at":"2022-09-12T19:18:48Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"3c10978fc4c09d0ef8600d5b32f0e77fc7383218bc59875e39f3bef723065b4c","abstract_canon_sha256":"c164ed54e91cf8387c2cc0652b9eda752aeb68fec10a4f5cbd93e8a2582cdcc7"},"schema_version":"1.0"},"canonical_sha256":"877e321d05a9f1b5739bfe7a029458369fbf21e13021863b06c84a69a37b2472","source":{"kind":"arxiv","id":"2209.05559","version":6},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2209.05559","created_at":"2026-07-05T05:37:08Z"},{"alias_kind":"arxiv_version","alias_value":"2209.05559v6","created_at":"2026-07-05T05:37:08Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2209.05559","created_at":"2026-07-05T05:37:08Z"},{"alias_kind":"pith_short_12","alias_value":"Q57DEHIFVHY3","created_at":"2026-07-05T05:37:08Z"},{"alias_kind":"pith_short_16","alias_value":"Q57DEHIFVHY3K443","created_at":"2026-07-05T05:37:08Z"},{"alias_kind":"pith_short_8","alias_value":"Q57DEHIF","created_at":"2026-07-05T05:37:08Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:Q57DEHIFVHY3K4437Z5AFFCYG2","target":"record","payload":{"canonical_record":{"source":{"id":"2209.05559","kind":"arxiv","version":6},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-fin.ST","submitted_at":"2022-09-12T19:18:48Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"3c10978fc4c09d0ef8600d5b32f0e77fc7383218bc59875e39f3bef723065b4c","abstract_canon_sha256":"c164ed54e91cf8387c2cc0652b9eda752aeb68fec10a4f5cbd93e8a2582cdcc7"},"schema_version":"1.0"},"canonical_sha256":"877e321d05a9f1b5739bfe7a029458369fbf21e13021863b06c84a69a37b2472","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:37:08.083776Z","signature_b64":"xiF9Wxjzm9s5F2ljuMVchEodnbdQbiDg0u4QudonKfzTN22AJX6ZBioc35mPkrPut/Uma+ixOttcvOi0XdMYCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"877e321d05a9f1b5739bfe7a029458369fbf21e13021863b06c84a69a37b2472","last_reissued_at":"2026-07-05T05:37:08.083216Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:37:08.083216Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2209.05559","source_version":6,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T05:37:08Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"9DiaGSnLzyyvCbgAEmulf5Vc9x6ShonPmY0ep3M95fqraM8AdaGyx7Z9561M/qCh9WUTSA8wcgbKvmSbVtlPBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-03T20:55:55.492429Z"},"content_sha256":"4368500eae2b43074b76bfc2b889207540db60128147a599a69d69e310d8f152","schema_version":"1.0","event_id":"sha256:4368500eae2b43074b76bfc2b889207540db60128147a599a69d69e310d8f152"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:Q57DEHIFVHY3K4437Z5AFFCYG2","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Deep Reinforcement Learning for Cryptocurrency Trading: Practical Approach to Address Backtest Overfitting","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"q-fin.ST","authors_text":"Berend Jelmer Dirk Gort, Christina Dan Wang, Jiechao Gao, Shuaiyu Chen, Xiao-Yang Liu, Xinghang Sun","submitted_at":"2022-09-12T19:18:48Z","abstract_excerpt":"Designing profitable and reliable trading strategies is challenging in the highly volatile cryptocurrency market. Existing works applied deep reinforcement learning methods and optimistically reported increased profits in backtesting, which may suffer from the false positive issue due to overfitting. In this paper, we propose a practical approach to address backtest overfitting for cryptocurrency trading using deep reinforcement learning. First, we formulate the detection of backtest overfitting as a hypothesis test. Then, we train the DRL agents, estimate the probability of overfitting, and r"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2209.05559","kind":"arxiv","version":6},"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/2209.05559/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":"2026-07-05T05:37:08Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XD1BfBwQwxdNsOln2o05tNv7tC3ng3JKMpEZ3xQfcp0C0z9mYS3lvmKJH14oQ8EvNWaS6JoQgHx6nHXBd6D8DA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-03T20:55:55.493135Z"},"content_sha256":"04ff236d6f0429f934c94c8dd706550053f31f6f28e383981149a535bf171e2b","schema_version":"1.0","event_id":"sha256:04ff236d6f0429f934c94c8dd706550053f31f6f28e383981149a535bf171e2b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/Q57DEHIFVHY3K4437Z5AFFCYG2/bundle.json","state_url":"https://pith.science/pith/Q57DEHIFVHY3K4437Z5AFFCYG2/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/Q57DEHIFVHY3K4437Z5AFFCYG2/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":"2026-08-03T20:55:55Z","links":{"resolver":"https://pith.science/pith/Q57DEHIFVHY3K4437Z5AFFCYG2","bundle":"https://pith.science/pith/Q57DEHIFVHY3K4437Z5AFFCYG2/bundle.json","state":"https://pith.science/pith/Q57DEHIFVHY3K4437Z5AFFCYG2/state.json","well_known_bundle":"https://pith.science/.well-known/pith/Q57DEHIFVHY3K4437Z5AFFCYG2/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:Q57DEHIFVHY3K4437Z5AFFCYG2","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":"c164ed54e91cf8387c2cc0652b9eda752aeb68fec10a4f5cbd93e8a2582cdcc7","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-fin.ST","submitted_at":"2022-09-12T19:18:48Z","title_canon_sha256":"3c10978fc4c09d0ef8600d5b32f0e77fc7383218bc59875e39f3bef723065b4c"},"schema_version":"1.0","source":{"id":"2209.05559","kind":"arxiv","version":6}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2209.05559","created_at":"2026-07-05T05:37:08Z"},{"alias_kind":"arxiv_version","alias_value":"2209.05559v6","created_at":"2026-07-05T05:37:08Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2209.05559","created_at":"2026-07-05T05:37:08Z"},{"alias_kind":"pith_short_12","alias_value":"Q57DEHIFVHY3","created_at":"2026-07-05T05:37:08Z"},{"alias_kind":"pith_short_16","alias_value":"Q57DEHIFVHY3K443","created_at":"2026-07-05T05:37:08Z"},{"alias_kind":"pith_short_8","alias_value":"Q57DEHIF","created_at":"2026-07-05T05:37:08Z"}],"graph_snapshots":[{"event_id":"sha256:04ff236d6f0429f934c94c8dd706550053f31f6f28e383981149a535bf171e2b","target":"graph","created_at":"2026-07-05T05:37:08Z","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/2209.05559/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Designing profitable and reliable trading strategies is challenging in the highly volatile cryptocurrency market. Existing works applied deep reinforcement learning methods and optimistically reported increased profits in backtesting, which may suffer from the false positive issue due to overfitting. In this paper, we propose a practical approach to address backtest overfitting for cryptocurrency trading using deep reinforcement learning. First, we formulate the detection of backtest overfitting as a hypothesis test. Then, we train the DRL agents, estimate the probability of overfitting, and r","authors_text":"Berend Jelmer Dirk Gort, Christina Dan Wang, Jiechao Gao, Shuaiyu Chen, Xiao-Yang Liu, Xinghang Sun","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-fin.ST","submitted_at":"2022-09-12T19:18:48Z","title":"Deep Reinforcement Learning for Cryptocurrency Trading: Practical Approach to Address Backtest Overfitting"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2209.05559","kind":"arxiv","version":6},"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":"sha256:4368500eae2b43074b76bfc2b889207540db60128147a599a69d69e310d8f152","target":"record","created_at":"2026-07-05T05:37:08Z","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":"c164ed54e91cf8387c2cc0652b9eda752aeb68fec10a4f5cbd93e8a2582cdcc7","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-fin.ST","submitted_at":"2022-09-12T19:18:48Z","title_canon_sha256":"3c10978fc4c09d0ef8600d5b32f0e77fc7383218bc59875e39f3bef723065b4c"},"schema_version":"1.0","source":{"id":"2209.05559","kind":"arxiv","version":6}},"canonical_sha256":"877e321d05a9f1b5739bfe7a029458369fbf21e13021863b06c84a69a37b2472","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"877e321d05a9f1b5739bfe7a029458369fbf21e13021863b06c84a69a37b2472","first_computed_at":"2026-07-05T05:37:08.083216Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:37:08.083216Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"xiF9Wxjzm9s5F2ljuMVchEodnbdQbiDg0u4QudonKfzTN22AJX6ZBioc35mPkrPut/Uma+ixOttcvOi0XdMYCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T05:37:08.083776Z","signed_message":"canonical_sha256_bytes"},"source_id":"2209.05559","source_kind":"arxiv","source_version":6}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4368500eae2b43074b76bfc2b889207540db60128147a599a69d69e310d8f152","sha256:04ff236d6f0429f934c94c8dd706550053f31f6f28e383981149a535bf171e2b"],"state_sha256":"0d044b1d8eaa60b3743d88cac1a9f31dfaaeba10bef54a445a876319c6eb406c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3q9UXUgTy4hnbCdO68O7x8M+HlQ4aUXIHAQshzChyOeL35NucHJb/wXSitvZqZq/HB/nArXgbHioS+BQLgpeBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-03T20:55:55.497025Z","bundle_sha256":"5aa713148ef50f1f00b6b0c99a959b59822f55e841e04ad975eb089c07dccb59"}}