{"id":"https://openalex.org/W2603486066","doi":"https://doi.org/10.1137/15m1050380","title":"Efficient Computation of Option Prices and Greeks by Quasi--Monte Carlo Method with Smoothing and Dimension Reduction","display_name":"Efficient Computation of Option Prices and Greeks by Quasi--Monte Carlo Method with Smoothing and Dimension Reduction","publication_year":2017,"publication_date":"2017-01-01","ids":{"openalex":"https://openalex.org/W2603486066","doi":"https://doi.org/10.1137/15m1050380","mag":"2603486066"},"language":"en","primary_location":{"id":"doi:10.1137/15m1050380","is_oa":false,"landing_page_url":"https://doi.org/10.1137/15m1050380","pdf_url":null,"source":{"id":"https://openalex.org/S165512578","display_name":"SIAM Journal on Scientific Computing","issn_l":"1064-8275","issn":["1064-8275","1095-7197"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320508","host_organization_name":"Society for Industrial and Applied Mathematics","host_organization_lineage":["https://openalex.org/P4310320508"],"host_organization_lineage_names":["Society for Industrial and Applied Mathematics"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIAM Journal on Scientific Computing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5029051555","display_name":"Chengfeng Weng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chengfeng Weng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101625376","display_name":"Xiaoqun Wang","orcid":"https://orcid.org/0000-0003-3440-2617"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiaoqun Wang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5058665232","display_name":"Zhijian He","orcid":"https://orcid.org/0000-0002-0730-5953"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhijian He","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.4213,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":{"value":0.88309441,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"39","issue":"2","first_page":"B298","last_page":"B322"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12404","display_name":"Mathematical Approximation and Integration","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2612","display_name":"Numerical Analysis"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12404","display_name":"Mathematical Approximation and Integration","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2612","display_name":"Numerical Analysis"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12056","display_name":"Markov Chains and Monte Carlo Methods","score":0.9765999913215637,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11191","display_name":"Mathematical functions and polynomials","score":0.9422000050544739,"subfield":{"id":"https://openalex.org/subfields/2604","display_name":"Applied Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.6374915242195129},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.6332995295524597},{"id":"https://openalex.org/keywords/effective-dimension","display_name":"Effective dimension","score":0.6328356266021729},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.6308168172836304},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.5422966480255127},{"id":"https://openalex.org/keywords/variance-reduction","display_name":"Variance reduction","score":0.5123380422592163},{"id":"https://openalex.org/keywords/quasi-monte-carlo-method","display_name":"Quasi-Monte Carlo method","score":0.49595341086387634},{"id":"https://openalex.org/keywords/classification-of-discontinuities","display_name":"Classification of discontinuities","score":0.4808293581008911},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.4615056812763214},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.4081882834434509},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3909909725189209},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.378134548664093},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.314362108707428},{"id":"https://openalex.org/keywords/hybrid-monte-carlo","display_name":"Hybrid Monte Carlo","score":0.1307350993156433},{"id":"https://openalex.org/keywords/markov-chain-monte-carlo","display_name":"Markov chain Monte Carlo","score":0.12982898950576782},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.12257140874862671},{"id":"https://openalex.org/keywords/hausdorff-dimension","display_name":"Hausdorff dimension","score":0.109201580286026},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.08976772427558899}],"concepts":[{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.6374915242195129},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.6332995295524597},{"id":"https://openalex.org/C115311070","wikidata":"https://www.wikidata.org/wiki/Q5347255","display_name":"Effective dimension","level":3,"score":0.6328356266021729},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.6308168172836304},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5422966480255127},{"id":"https://openalex.org/C62644790","wikidata":"https://www.wikidata.org/wiki/Q3454689","display_name":"Variance reduction","level":3,"score":0.5123380422592163},{"id":"https://openalex.org/C63320529","wikidata":"https://www.wikidata.org/wiki/Q7269435","display_name":"Quasi-Monte Carlo method","level":5,"score":0.49595341086387634},{"id":"https://openalex.org/C15627037","wikidata":"https://www.wikidata.org/wiki/Q541961","display_name":"Classification of discontinuities","level":2,"score":0.4808293581008911},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.4615056812763214},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.4081882834434509},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3909909725189209},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.378134548664093},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.314362108707428},{"id":"https://openalex.org/C13153151","wikidata":"https://www.wikidata.org/wiki/Q1639846","display_name":"Hybrid Monte Carlo","level":4,"score":0.1307350993156433},{"id":"https://openalex.org/C111350023","wikidata":"https://www.wikidata.org/wiki/Q1191869","display_name":"Markov chain Monte Carlo","level":3,"score":0.12982898950576782},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.12257140874862671},{"id":"https://openalex.org/C194198291","wikidata":"https://www.wikidata.org/wiki/Q565186","display_name":"Hausdorff dimension","level":2,"score":0.109201580286026},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.08976772427558899},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1137/15m1050380","is_oa":false,"landing_page_url":"https://doi.org/10.1137/15m1050380","pdf_url":null,"source":{"id":"https://openalex.org/S165512578","display_name":"SIAM Journal on Scientific Computing","issn_l":"1064-8275","issn":["1064-8275","1095-7197"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320508","host_organization_name":"Society for Industrial and Applied Mathematics","host_organization_lineage":["https://openalex.org/P4310320508"],"host_organization_lineage_names":["Society for Industrial and Applied Mathematics"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIAM Journal on Scientific Computing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3401499039","display_name":null,"funder_award_id":"71471100","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5989192156","display_name":"\u57fa\u4e8e\u62df\u8499\u7279\u5361\u7f57\u6a21\u62df\u7684VaR\u548cCVaR\u8ba1\u7b97\u95ee\u9898\u7814\u7a76","funder_award_id":"71601189","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W39759813","https://openalex.org/W187931435","https://openalex.org/W1977556410","https://openalex.org/W2002274796","https://openalex.org/W2004971474","https://openalex.org/W2009147603","https://openalex.org/W2034638017","https://openalex.org/W2035206081","https://openalex.org/W2035743118","https://openalex.org/W2037364779","https://openalex.org/W2082845472","https://openalex.org/W2097511294","https://openalex.org/W2124189866","https://openalex.org/W2146261346","https://openalex.org/W2275195990","https://openalex.org/W3100633452"],"related_works":["https://openalex.org/W2883727740","https://openalex.org/W2076304939","https://openalex.org/W2081241186","https://openalex.org/W1577753449","https://openalex.org/W2155294049","https://openalex.org/W2004971474","https://openalex.org/W1994596455","https://openalex.org/W2113457044","https://openalex.org/W2146299225","https://openalex.org/W2065756054"],"abstract_inverted_index":{"Discontinuities":[0],"and":[1,11,48,68,142,196,211,222],"high":[2,70,234,242],"dimensionality":[3,71,243],"are":[4,169],"common":[5],"in":[6,121,165,225,233],"the":[7,23,26,36,42,61,66,69,74,79,84,87,91,94,105,110,115,135,138,143,166,177,188,202,216,219],"problems":[8,63],"of":[9,13,25,64,86,118,137,153,176,187,218],"pricing":[10,210],"hedging":[12],"derivative":[14],"securities.":[15],"Both":[16],"factors":[17],"have":[18],"a":[19,56,99,150,173,193],"tremendous":[20],"impact":[21],"on":[22,134,208],"accuracy":[24],"quasi--Monte":[27],"Carlo":[28],"(QMC)":[29],"method.":[30],"An":[31],"ideal":[32],"approach":[33],"to":[34,40,44,59,82,108,158,171,200],"improve":[35],"QMC":[37,119,226],"method":[38,81,103,131,221],"is":[39,132,156,198],"transform":[41],"functions":[43],"make":[45],"them":[46],"smoother":[47],"having":[49],"smaller":[50],"effective":[51,111],"dimension.":[52],"This":[53],"paper":[54],"develops":[55],"two-step":[57],"procedure":[58],"tackle":[60],"challenging":[62],"both":[65],"discontinuity":[67],"concurrently.":[72],"In":[73,93],"first":[75],"step,":[76,96],"we":[77,97],"adopt":[78],"smoothing":[80,220],"remove":[83],"discontinuities":[85,240],"payoff":[88],"function,":[89,167],"improving":[90],"smoothness.":[92],"second":[95],"propose":[98],"general":[100],"dimension":[101,112,223,235],"reduction":[102,224,231],"(called":[104],"CQR":[106,130],"method)":[107],"reduce":[109],"such":[113],"that":[114,215],"better":[116],"quality":[117],"points":[120],"their":[122],"initial":[123],"dimensions":[124],"can":[125],"be":[126],"fully":[127],"exploited.":[128],"The":[129,146,180],"based":[133],"combination":[136,217],"$k$-means":[139,147],"clustering":[140,148],"algorithm":[141,152],"QR":[144],"decomposition.":[145],"algorithm,":[149],"classical":[151],"machine":[154],"learning,":[155],"used":[157,170,199],"find":[159,201],"some":[160],"representative":[161],"linear":[162],"structures":[163],"inherent":[164],"which":[168],"construct":[172],"matching":[174,181],"function":[175,182,190],"smoothed":[178,189],"function.":[179],"serves":[183],"as":[184],"an":[185],"approximation":[186],"but":[191],"has":[192],"simpler":[194],"form,":[195],"it":[197],"required":[203],"transformation.":[204],"Extensive":[205],"numerical":[206],"experiments":[207],"option":[209],"Greeks":[212],"estimation":[213],"demonstrate":[214],"achieves":[227],"substantially":[228],"larger":[229],"variance":[230],"even":[232],"than":[236],"dealing":[237],"with":[238],"either":[239],"or":[241],"single":[244],"sidedly.":[245]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}