{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2012:TKXZB2HAN7SLOALSR6IWG4TZJY","short_pith_number":"pith:TKXZB2HA","schema_version":"1.0","canonical_sha256":"9aaf90e8e06fe4b701728f916372794e2c1d6b8e7ce7a23ab1e2e9895cf30157","source":{"kind":"arxiv","id":"1205.0106","version":1},"attestation_state":"computed","paper":{"title":"Using high performance computing and Monte Carlo simulation for pricing american options","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["q-fin.CP"],"primary_cat":"cs.DC","authors_text":"Toni Stojanovski, Verche Cvetanoska","submitted_at":"2012-05-01T07:46:11Z","abstract_excerpt":"High performance computing (HPC) is a very attractive and relatively new area of research, which gives promising results in many applications. In this paper HPC is used for pricing of American options. Although the American options are very significant in computational finance; their valuation is very challenging, especially when the Monte Carlo simulation techniques are used. For getting the most accurate price for these types of options we use Quasi Monte Carlo simulation, which gives the best convergence. Furthermore, this algorithm is implemented on both GPU and CPU. Additionally, the CUDA"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1205.0106","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2012-05-01T07:46:11Z","cross_cats_sorted":["q-fin.CP"],"title_canon_sha256":"35242b49299b26f7d5c1f2811e6167126061f9e21628f0f1f19111d6c3d4accc","abstract_canon_sha256":"e6402abfe1d9c51cfcfaa87614a6cfc7dd98386c397b7abcf7117aa1523927cc"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T03:56:35.860844Z","signature_b64":"YVqMobZeUjOfL8MSSDJgpDwaB8q6H8uPAXxNeE8/LUiATkLy4+3AyhCznWfIXEemG9hoAfXRpHh09kW6K98WCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9aaf90e8e06fe4b701728f916372794e2c1d6b8e7ce7a23ab1e2e9895cf30157","last_reissued_at":"2026-05-18T03:56:35.860378Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T03:56:35.860378Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Using high performance computing and Monte Carlo simulation for pricing american options","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["q-fin.CP"],"primary_cat":"cs.DC","authors_text":"Toni Stojanovski, Verche Cvetanoska","submitted_at":"2012-05-01T07:46:11Z","abstract_excerpt":"High performance computing (HPC) is a very attractive and relatively new area of research, which gives promising results in many applications. In this paper HPC is used for pricing of American options. Although the American options are very significant in computational finance; their valuation is very challenging, especially when the Monte Carlo simulation techniques are used. For getting the most accurate price for these types of options we use Quasi Monte Carlo simulation, which gives the best convergence. Furthermore, this algorithm is implemented on both GPU and CPU. Additionally, the CUDA"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1205.0106","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":""},"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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1205.0106","created_at":"2026-05-18T03:56:35.860446+00:00"},{"alias_kind":"arxiv_version","alias_value":"1205.0106v1","created_at":"2026-05-18T03:56:35.860446+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1205.0106","created_at":"2026-05-18T03:56:35.860446+00:00"},{"alias_kind":"pith_short_12","alias_value":"TKXZB2HAN7SL","created_at":"2026-05-18T12:27:23.164592+00:00"},{"alias_kind":"pith_short_16","alias_value":"TKXZB2HAN7SLOALS","created_at":"2026-05-18T12:27:23.164592+00:00"},{"alias_kind":"pith_short_8","alias_value":"TKXZB2HA","created_at":"2026-05-18T12:27:23.164592+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/TKXZB2HAN7SLOALSR6IWG4TZJY","json":"https://pith.science/pith/TKXZB2HAN7SLOALSR6IWG4TZJY.json","graph_json":"https://pith.science/api/pith-number/TKXZB2HAN7SLOALSR6IWG4TZJY/graph.json","events_json":"https://pith.science/api/pith-number/TKXZB2HAN7SLOALSR6IWG4TZJY/events.json","paper":"https://pith.science/paper/TKXZB2HA"},"agent_actions":{"view_html":"https://pith.science/pith/TKXZB2HAN7SLOALSR6IWG4TZJY","download_json":"https://pith.science/pith/TKXZB2HAN7SLOALSR6IWG4TZJY.json","view_paper":"https://pith.science/paper/TKXZB2HA","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1205.0106&json=true","fetch_graph":"https://pith.science/api/pith-number/TKXZB2HAN7SLOALSR6IWG4TZJY/graph.json","fetch_events":"https://pith.science/api/pith-number/TKXZB2HAN7SLOALSR6IWG4TZJY/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/TKXZB2HAN7SLOALSR6IWG4TZJY/action/timestamp_anchor","attest_storage":"https://pith.science/pith/TKXZB2HAN7SLOALSR6IWG4TZJY/action/storage_attestation","attest_author":"https://pith.science/pith/TKXZB2HAN7SLOALSR6IWG4TZJY/action/author_attestation","sign_citation":"https://pith.science/pith/TKXZB2HAN7SLOALSR6IWG4TZJY/action/citation_signature","submit_replication":"https://pith.science/pith/TKXZB2HAN7SLOALSR6IWG4TZJY/action/replication_record"}},"created_at":"2026-05-18T03:56:35.860446+00:00","updated_at":"2026-05-18T03:56:35.860446+00:00"}