{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:UAQJGHM4L74VBFZ6CYLZPW5SJM","short_pith_number":"pith:UAQJGHM4","canonical_record":{"source":{"id":"2507.02011","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"q-fin.RM","submitted_at":"2025-07-02T07:47:56Z","cross_cats_sorted":["cs.LG","q-fin.PM"],"title_canon_sha256":"f40e5d40f1995b3330004d9efbb5218f0086bf28364637cb7b963b4289e450ac","abstract_canon_sha256":"711ba52f733dec5b9951c24ba5f22b1a38b02aef012943d1fef8df5a926ad8a8"},"schema_version":"1.0"},"canonical_sha256":"a020931d9c5ff950973e161797dbb24b3a621f7b3797495fdad76327b5b8ef6f","source":{"kind":"arxiv","id":"2507.02011","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.02011","created_at":"2026-07-05T11:31:10Z"},{"alias_kind":"arxiv_version","alias_value":"2507.02011v1","created_at":"2026-07-05T11:31:10Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.02011","created_at":"2026-07-05T11:31:10Z"},{"alias_kind":"pith_short_12","alias_value":"UAQJGHM4L74V","created_at":"2026-07-05T11:31:10Z"},{"alias_kind":"pith_short_16","alias_value":"UAQJGHM4L74VBFZ6","created_at":"2026-07-05T11:31:10Z"},{"alias_kind":"pith_short_8","alias_value":"UAQJGHM4","created_at":"2026-07-05T11:31:10Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:UAQJGHM4L74VBFZ6CYLZPW5SJM","target":"record","payload":{"canonical_record":{"source":{"id":"2507.02011","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"q-fin.RM","submitted_at":"2025-07-02T07:47:56Z","cross_cats_sorted":["cs.LG","q-fin.PM"],"title_canon_sha256":"f40e5d40f1995b3330004d9efbb5218f0086bf28364637cb7b963b4289e450ac","abstract_canon_sha256":"711ba52f733dec5b9951c24ba5f22b1a38b02aef012943d1fef8df5a926ad8a8"},"schema_version":"1.0"},"canonical_sha256":"a020931d9c5ff950973e161797dbb24b3a621f7b3797495fdad76327b5b8ef6f","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:31:10.482542Z","signature_b64":"r9Xz3fis+BUuTC7YihQ7spjwyAvFKuhwzb2oi87ZIZxiPJi6FojIZ86abrMvlCB6Qi2oGaO6/hA5JlnT1XufAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a020931d9c5ff950973e161797dbb24b3a621f7b3797495fdad76327b5b8ef6f","last_reissued_at":"2026-07-05T11:31:10.482075Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:31:10.482075Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2507.02011","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":"2026-07-05T11:31:10Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5s2t6FL7mVmmdgNp9aJBOGGEp4aoEH0nGeEfrZBUIwTTzL6F5ttrfONEOwsnFnDXgGHK+uYiLg30qcl/gdXzAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T12:28:29.432440Z"},"content_sha256":"c3999c3e417f19f4133af6b6ec2326828cab94d7081f333e82a76514798a91b3","schema_version":"1.0","event_id":"sha256:c3999c3e417f19f4133af6b6ec2326828cab94d7081f333e82a76514798a91b3"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:UAQJGHM4L74VBFZ6CYLZPW5SJM","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Machine Learning Based Stress Testing Framework for Indian Financial Market Portfolios","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG","q-fin.PM"],"primary_cat":"q-fin.RM","authors_text":"Shifat Ali, Siddhartha P. Chakrabarty, Vidya Sagar G","submitted_at":"2025-07-02T07:47:56Z","abstract_excerpt":"This paper presents a machine learning driven framework for sectoral stress testing in the Indian financial market, focusing on financial services, information technology, energy, consumer goods, and pharmaceuticals. Initially, we address the limitations observed in conventional stress testing through dimensionality reduction and latent factor modeling via Principal Component Analysis and Autoencoders. Building on this, we extend the methodology using Variational Autoencoders, which introduces a probabilistic structure to the latent space. This enables Monte Carlo-based scenario generation, al"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.02011","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/2507.02011/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":"2026-07-05T11:31:10Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"l0mLdGqtaVq5u1EAs8r5dDDg0BHS8LCiggyxu3Crin1KylAGAP7BPqv3alVxZsDXtlr3GHBEAWjqG2u3KNrwAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T12:28:29.432996Z"},"content_sha256":"740f26229d5c63ea1308443f8f1cda928515cc455c3d284652c6d885db838d08","schema_version":"1.0","event_id":"sha256:740f26229d5c63ea1308443f8f1cda928515cc455c3d284652c6d885db838d08"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/UAQJGHM4L74VBFZ6CYLZPW5SJM/bundle.json","state_url":"https://pith.science/pith/UAQJGHM4L74VBFZ6CYLZPW5SJM/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/UAQJGHM4L74VBFZ6CYLZPW5SJM/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":"2026-08-09T12:28:29Z","links":{"resolver":"https://pith.science/pith/UAQJGHM4L74VBFZ6CYLZPW5SJM","bundle":"https://pith.science/pith/UAQJGHM4L74VBFZ6CYLZPW5SJM/bundle.json","state":"https://pith.science/pith/UAQJGHM4L74VBFZ6CYLZPW5SJM/state.json","well_known_bundle":"https://pith.science/.well-known/pith/UAQJGHM4L74VBFZ6CYLZPW5SJM/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:UAQJGHM4L74VBFZ6CYLZPW5SJM","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":"711ba52f733dec5b9951c24ba5f22b1a38b02aef012943d1fef8df5a926ad8a8","cross_cats_sorted":["cs.LG","q-fin.PM"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"q-fin.RM","submitted_at":"2025-07-02T07:47:56Z","title_canon_sha256":"f40e5d40f1995b3330004d9efbb5218f0086bf28364637cb7b963b4289e450ac"},"schema_version":"1.0","source":{"id":"2507.02011","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.02011","created_at":"2026-07-05T11:31:10Z"},{"alias_kind":"arxiv_version","alias_value":"2507.02011v1","created_at":"2026-07-05T11:31:10Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.02011","created_at":"2026-07-05T11:31:10Z"},{"alias_kind":"pith_short_12","alias_value":"UAQJGHM4L74V","created_at":"2026-07-05T11:31:10Z"},{"alias_kind":"pith_short_16","alias_value":"UAQJGHM4L74VBFZ6","created_at":"2026-07-05T11:31:10Z"},{"alias_kind":"pith_short_8","alias_value":"UAQJGHM4","created_at":"2026-07-05T11:31:10Z"}],"graph_snapshots":[{"event_id":"sha256:740f26229d5c63ea1308443f8f1cda928515cc455c3d284652c6d885db838d08","target":"graph","created_at":"2026-07-05T11:31:10Z","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/2507.02011/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This paper presents a machine learning driven framework for sectoral stress testing in the Indian financial market, focusing on financial services, information technology, energy, consumer goods, and pharmaceuticals. Initially, we address the limitations observed in conventional stress testing through dimensionality reduction and latent factor modeling via Principal Component Analysis and Autoencoders. Building on this, we extend the methodology using Variational Autoencoders, which introduces a probabilistic structure to the latent space. This enables Monte Carlo-based scenario generation, al","authors_text":"Shifat Ali, Siddhartha P. Chakrabarty, Vidya Sagar G","cross_cats":["cs.LG","q-fin.PM"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"q-fin.RM","submitted_at":"2025-07-02T07:47:56Z","title":"Machine Learning Based Stress Testing Framework for Indian Financial Market Portfolios"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.02011","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:c3999c3e417f19f4133af6b6ec2326828cab94d7081f333e82a76514798a91b3","target":"record","created_at":"2026-07-05T11:31:10Z","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":"711ba52f733dec5b9951c24ba5f22b1a38b02aef012943d1fef8df5a926ad8a8","cross_cats_sorted":["cs.LG","q-fin.PM"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"q-fin.RM","submitted_at":"2025-07-02T07:47:56Z","title_canon_sha256":"f40e5d40f1995b3330004d9efbb5218f0086bf28364637cb7b963b4289e450ac"},"schema_version":"1.0","source":{"id":"2507.02011","kind":"arxiv","version":1}},"canonical_sha256":"a020931d9c5ff950973e161797dbb24b3a621f7b3797495fdad76327b5b8ef6f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a020931d9c5ff950973e161797dbb24b3a621f7b3797495fdad76327b5b8ef6f","first_computed_at":"2026-07-05T11:31:10.482075Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:31:10.482075Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"r9Xz3fis+BUuTC7YihQ7spjwyAvFKuhwzb2oi87ZIZxiPJi6FojIZ86abrMvlCB6Qi2oGaO6/hA5JlnT1XufAw==","signature_status":"signed_v1","signed_at":"2026-07-05T11:31:10.482542Z","signed_message":"canonical_sha256_bytes"},"source_id":"2507.02011","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c3999c3e417f19f4133af6b6ec2326828cab94d7081f333e82a76514798a91b3","sha256:740f26229d5c63ea1308443f8f1cda928515cc455c3d284652c6d885db838d08"],"state_sha256":"8638223843abb8e15c4b0984fe1114e312681dc7d3613c24b05d6c3f6939f09c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"QeKyxaNoLzetudYWhPCF65VlmntVZBBdeSncgNTKgbWh/2X7UjnhHvAAHOzeUv0xjTIDMNNCHQ+T9s7GrdD2Bw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T12:28:29.438633Z","bundle_sha256":"e6429916de3d197eaebf9d7df70c486b3f6295ccc5f9b5f345c3f20ce39b26b9"}}