{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:4NCWFCCJK5GM4LTNVDAHJWZ6AD","short_pith_number":"pith:4NCWFCCJ","canonical_record":{"source":{"id":"2412.18202","kind":"arxiv","version":6},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-12-24T06:14:34Z","cross_cats_sorted":["q-fin.ST"],"title_canon_sha256":"95cbde5795fa9d0ae2f6f381a9df92380949adb97398e0230d1cce1c881fab6b","abstract_canon_sha256":"3d9ad1e4eb7323d877a32fd984fb5b5411a9073d06714746ba37e328df7ab3e0"},"schema_version":"1.0"},"canonical_sha256":"e345628849574cce2e6da8c074db3e00c67f31bd8a42574ee134de69453cd240","source":{"kind":"arxiv","id":"2412.18202","version":6},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.18202","created_at":"2026-07-05T11:39:46Z"},{"alias_kind":"arxiv_version","alias_value":"2412.18202v6","created_at":"2026-07-05T11:39:46Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.18202","created_at":"2026-07-05T11:39:46Z"},{"alias_kind":"pith_short_12","alias_value":"4NCWFCCJK5GM","created_at":"2026-07-05T11:39:46Z"},{"alias_kind":"pith_short_16","alias_value":"4NCWFCCJK5GM4LTN","created_at":"2026-07-05T11:39:46Z"},{"alias_kind":"pith_short_8","alias_value":"4NCWFCCJ","created_at":"2026-07-05T11:39:46Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:4NCWFCCJK5GM4LTNVDAHJWZ6AD","target":"record","payload":{"canonical_record":{"source":{"id":"2412.18202","kind":"arxiv","version":6},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-12-24T06:14:34Z","cross_cats_sorted":["q-fin.ST"],"title_canon_sha256":"95cbde5795fa9d0ae2f6f381a9df92380949adb97398e0230d1cce1c881fab6b","abstract_canon_sha256":"3d9ad1e4eb7323d877a32fd984fb5b5411a9073d06714746ba37e328df7ab3e0"},"schema_version":"1.0"},"canonical_sha256":"e345628849574cce2e6da8c074db3e00c67f31bd8a42574ee134de69453cd240","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:39:46.660607Z","signature_b64":"4WjTAB1SY5AIQpoYPshGCUtIFg1pi8utXBpK7pFgLZetuSS1IxL+fstFTLlvNFXTRfPL60oMXorsyoFvLqVJCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e345628849574cce2e6da8c074db3e00c67f31bd8a42574ee134de69453cd240","last_reissued_at":"2026-07-05T11:39:46.660095Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:39:46.660095Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2412.18202","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":"2026-07-05T11:39:46Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XbRR4OlF3sY98bv4cDHi1Vr9cS+ZiroVOt0LziTI956Uk9njPIB4QK/VVsv93wNdjwh6omyKFffl6CC83WKYCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-12T15:39:40.807878Z"},"content_sha256":"fd1b5f13b634aaced7d1ba90345cccf4fd3249d2ff2a370f6b14985709017e68","schema_version":"1.0","event_id":"sha256:fd1b5f13b634aaced7d1ba90345cccf4fd3249d2ff2a370f6b14985709017e68"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:4NCWFCCJK5GM4LTNVDAHJWZ6AD","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Developing Cryptocurrency Trading Strategy Based on Autoencoder-CNN-GANs Algorithms","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["q-fin.ST"],"primary_cat":"cs.LG","authors_text":"Haoran Zheng, Qianying Liu, Richard Yu, Yining Zhou, Zhuohuan Hu, Zizhou Zhang","submitted_at":"2024-12-24T06:14:34Z","abstract_excerpt":"This paper leverages machine learning algorithms to forecast and analyze financial time series. The process begins with a denoising autoencoder to filter out random noise fluctuations from the main contract price data. Then, one-dimensional convolution reduces the dimensionality of the filtered data and extracts key information. The filtered and dimensionality-reduced price data is fed into a GANs network, and its output serve as input of a fully connected network. Through cross-validation, a model is trained to capture features that precede large price fluctuations. The model predicts the lik"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.18202","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/2412.18202/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":"2026-07-05T11:39:46Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Y89Gr1TpItYjMGyhOWl6m3sMLVsctdelAo+kFG+2/kj3uI6jUwYN+OgnJoEVj/PazY2d70KOl+p2KcrloMssBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-12T15:39:40.808406Z"},"content_sha256":"fd09daf53d86e759a469b3a5591f70e19cb8a94d0c03a65598c5edd04b854613","schema_version":"1.0","event_id":"sha256:fd09daf53d86e759a469b3a5591f70e19cb8a94d0c03a65598c5edd04b854613"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/4NCWFCCJK5GM4LTNVDAHJWZ6AD/bundle.json","state_url":"https://pith.science/pith/4NCWFCCJK5GM4LTNVDAHJWZ6AD/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/4NCWFCCJK5GM4LTNVDAHJWZ6AD/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":"2026-08-12T15:39:40Z","links":{"resolver":"https://pith.science/pith/4NCWFCCJK5GM4LTNVDAHJWZ6AD","bundle":"https://pith.science/pith/4NCWFCCJK5GM4LTNVDAHJWZ6AD/bundle.json","state":"https://pith.science/pith/4NCWFCCJK5GM4LTNVDAHJWZ6AD/state.json","well_known_bundle":"https://pith.science/.well-known/pith/4NCWFCCJK5GM4LTNVDAHJWZ6AD/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:4NCWFCCJK5GM4LTNVDAHJWZ6AD","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":"3d9ad1e4eb7323d877a32fd984fb5b5411a9073d06714746ba37e328df7ab3e0","cross_cats_sorted":["q-fin.ST"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-12-24T06:14:34Z","title_canon_sha256":"95cbde5795fa9d0ae2f6f381a9df92380949adb97398e0230d1cce1c881fab6b"},"schema_version":"1.0","source":{"id":"2412.18202","kind":"arxiv","version":6}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.18202","created_at":"2026-07-05T11:39:46Z"},{"alias_kind":"arxiv_version","alias_value":"2412.18202v6","created_at":"2026-07-05T11:39:46Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.18202","created_at":"2026-07-05T11:39:46Z"},{"alias_kind":"pith_short_12","alias_value":"4NCWFCCJK5GM","created_at":"2026-07-05T11:39:46Z"},{"alias_kind":"pith_short_16","alias_value":"4NCWFCCJK5GM4LTN","created_at":"2026-07-05T11:39:46Z"},{"alias_kind":"pith_short_8","alias_value":"4NCWFCCJ","created_at":"2026-07-05T11:39:46Z"}],"graph_snapshots":[{"event_id":"sha256:fd09daf53d86e759a469b3a5591f70e19cb8a94d0c03a65598c5edd04b854613","target":"graph","created_at":"2026-07-05T11:39:46Z","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/2412.18202/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This paper leverages machine learning algorithms to forecast and analyze financial time series. The process begins with a denoising autoencoder to filter out random noise fluctuations from the main contract price data. Then, one-dimensional convolution reduces the dimensionality of the filtered data and extracts key information. The filtered and dimensionality-reduced price data is fed into a GANs network, and its output serve as input of a fully connected network. Through cross-validation, a model is trained to capture features that precede large price fluctuations. The model predicts the lik","authors_text":"Haoran Zheng, Qianying Liu, Richard Yu, Yining Zhou, Zhuohuan Hu, Zizhou Zhang","cross_cats":["q-fin.ST"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-12-24T06:14:34Z","title":"Developing Cryptocurrency Trading Strategy Based on Autoencoder-CNN-GANs Algorithms"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.18202","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:fd1b5f13b634aaced7d1ba90345cccf4fd3249d2ff2a370f6b14985709017e68","target":"record","created_at":"2026-07-05T11:39:46Z","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":"3d9ad1e4eb7323d877a32fd984fb5b5411a9073d06714746ba37e328df7ab3e0","cross_cats_sorted":["q-fin.ST"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-12-24T06:14:34Z","title_canon_sha256":"95cbde5795fa9d0ae2f6f381a9df92380949adb97398e0230d1cce1c881fab6b"},"schema_version":"1.0","source":{"id":"2412.18202","kind":"arxiv","version":6}},"canonical_sha256":"e345628849574cce2e6da8c074db3e00c67f31bd8a42574ee134de69453cd240","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e345628849574cce2e6da8c074db3e00c67f31bd8a42574ee134de69453cd240","first_computed_at":"2026-07-05T11:39:46.660095Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:39:46.660095Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"4WjTAB1SY5AIQpoYPshGCUtIFg1pi8utXBpK7pFgLZetuSS1IxL+fstFTLlvNFXTRfPL60oMXorsyoFvLqVJCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:39:46.660607Z","signed_message":"canonical_sha256_bytes"},"source_id":"2412.18202","source_kind":"arxiv","source_version":6}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:fd1b5f13b634aaced7d1ba90345cccf4fd3249d2ff2a370f6b14985709017e68","sha256:fd09daf53d86e759a469b3a5591f70e19cb8a94d0c03a65598c5edd04b854613"],"state_sha256":"058cbe1212cfc1275656c1081eb3021d474c9ffc691bd27ac7027fb62e4c1c73"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"pYiU0Gin/gBVT99ftedQkpSQtwlqpO6RjpD+1yFrKanTWcr1ZpqfNhkR8NYKC0TzM2p+5TpCu3ccX9mV5Q7DAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-12T15:39:40.814440Z","bundle_sha256":"c681ce0c259324594d0dc5221ce2d7767a012b639656b24e1f94ac943189e8ee"}}