{"id":"https://openalex.org/W3122224265","doi":"https://doi.org/10.1145/2830556.2830562","title":"Implementing deep neural networks for financial market prediction on the Intel Xeon Phi","display_name":"Implementing deep neural networks for financial market prediction on the Intel Xeon Phi","publication_year":2015,"publication_date":"2015-11-11","ids":{"openalex":"https://openalex.org/W3122224265","doi":"https://doi.org/10.1145/2830556.2830562","mag":"3122224265"},"language":"en","primary_location":{"id":"doi:10.1145/2830556.2830562","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2830556.2830562","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 8th Workshop on High Performance Computational Finance","raw_type":"proceedings-article"},"type":"conference-paper","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/A5036435050","display_name":"Matthew Dixon","orcid":"https://orcid.org/0000-0001-5908-1747"},"institutions":[{"id":"https://openalex.org/I180949307","display_name":"Illinois Institute of Technology","ror":"https://ror.org/037t3ry66","country_code":"US","type":"education","lineage":["https://openalex.org/I180949307"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Matthew Dixon","raw_affiliation_strings":["Stuart School of Business, Illinois Institute of Technology, Chicago, IL"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Stuart School of Business, Illinois Institute of Technology, Chicago, IL","institution_ids":["https://openalex.org/I180949307"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013049879","display_name":"Diego Klabjan","orcid":"https://orcid.org/0000-0003-4213-9281"},"institutions":[{"id":"https://openalex.org/I111979921","display_name":"Northwestern University","ror":"https://ror.org/000e0be47","country_code":"US","type":"education","lineage":["https://openalex.org/I111979921"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Diego Klabjan","raw_affiliation_strings":["Northwestern University, Evanston, IL"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northwestern University, Evanston, IL","institution_ids":["https://openalex.org/I111979921"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002954193","display_name":"Jin Hoon Bang","orcid":null},"institutions":[{"id":"https://openalex.org/I111979921","display_name":"Northwestern University","ror":"https://ror.org/000e0be47","country_code":"US","type":"education","lineage":["https://openalex.org/I111979921"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jin Hoon Bang","raw_affiliation_strings":["Northwestern University, Evanston, IL"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northwestern University, Evanston, IL","institution_ids":["https://openalex.org/I111979921"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.0578,"has_fulltext":false,"cited_by_count":55,"citation_normalized_percentile":{"value":0.89693701,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":0.9857000112533569,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/xeon-phi","display_name":"Xeon Phi","score":0.9256534576416016},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.799213171005249},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.7708354592323303},{"id":"https://openalex.org/keywords/xeon","display_name":"Xeon","score":0.7536559700965881},{"id":"https://openalex.org/keywords/stochastic-gradient-descent","display_name":"Stochastic gradient descent","score":0.6768414378166199},{"id":"https://openalex.org/keywords/speedup","display_name":"Speedup","score":0.6736453175544739},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5522131323814392},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5520741939544678},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.4766836166381836},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.4766819477081299},{"id":"https://openalex.org/keywords/computational-finance","display_name":"Computational finance","score":0.44799134135246277},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.443251371383667},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3681197166442871},{"id":"https://openalex.org/keywords/finance","display_name":"Finance","score":0.23721283674240112}],"concepts":[{"id":"https://openalex.org/C96972482","wikidata":"https://www.wikidata.org/wiki/Q1049168","display_name":"Xeon Phi","level":2,"score":0.9256534576416016},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.799213171005249},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.7708354592323303},{"id":"https://openalex.org/C145108525","wikidata":"https://www.wikidata.org/wiki/Q656154","display_name":"Xeon","level":2,"score":0.7536559700965881},{"id":"https://openalex.org/C206688291","wikidata":"https://www.wikidata.org/wiki/Q7617819","display_name":"Stochastic gradient descent","level":3,"score":0.6768414378166199},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.6736453175544739},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5522131323814392},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5520741939544678},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.4766836166381836},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.4766819477081299},{"id":"https://openalex.org/C146880194","wikidata":"https://www.wikidata.org/wiki/Q61715222","display_name":"Computational finance","level":2,"score":0.44799134135246277},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.443251371383667},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3681197166442871},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.23721283674240112},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2830556.2830562","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2830556.2830562","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 8th Workshop on High Performance Computational Finance","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6399999856948853,"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320307102","display_name":"Intel Corporation","ror":"https://ror.org/01ek73717"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W348433680","https://openalex.org/W1446138737","https://openalex.org/W1481230657","https://openalex.org/W1503544267","https://openalex.org/W1514205146","https://openalex.org/W1969067576","https://openalex.org/W1983925612","https://openalex.org/W2089942891","https://openalex.org/W2098063401","https://openalex.org/W2110450942","https://openalex.org/W2122226354","https://openalex.org/W2145856394","https://openalex.org/W2163605009","https://openalex.org/W2604272474","https://openalex.org/W3124185353","https://openalex.org/W4241395986","https://openalex.org/W6676496625"],"related_works":["https://openalex.org/W1974923383","https://openalex.org/W2475524688","https://openalex.org/W2739740241","https://openalex.org/W2085105049","https://openalex.org/W2592417500","https://openalex.org/W2526069705","https://openalex.org/W2024016913","https://openalex.org/W2019153376","https://openalex.org/W2981664121","https://openalex.org/W2583801396"],"abstract_inverted_index":{"Deep":[0],"neural":[1,9],"networks":[2,10],"(DNNs)":[3],"are":[4],"powerful":[5],"types":[6],"of":[7,58,67,81,117],"artificial":[8],"(ANNs)":[11],"that":[12],"use":[13],"several":[14],"hidden":[15],"layers.":[16],"They":[17],"have":[18],"recently":[19],"gained":[20],"considerable":[21],"attention":[22],"in":[23,78,84],"the":[24,65,79,82,87,92,112,118,130,139],"speech":[25],"transcription":[26],"and":[27,124],"image":[28],"recognition":[29],"community":[30],"(Krizhevsky":[31],"et":[32],"al.,":[33],"2012)":[34],"for":[35,114],"their":[36,45,59],"superior":[37],"predictive":[38],"properties":[39],"including":[40],"robustness":[41],"to":[42,47,69,89],"overfitting.":[43],"However":[44],"application":[46,66],"financial":[48,71],"market":[49,72],"prediction":[50],"has":[51],"not":[52],"been":[53],"previously":[54],"researched,":[55],"partly":[56],"because":[57],"computational":[60],"complexity.":[61],"This":[62],"paper":[63],"describes":[64],"DNNs":[68],"predicting":[70],"movement":[73],"directions.":[74],"A":[75],"critical":[76],"step":[77],"viability":[80],"approach":[83],"practice":[85],"is":[86],"ability":[88],"effectively":[90],"deploy":[91],"algorithm":[93,123],"on":[94,129,138],"general":[95],"purpose":[96],"high":[97],"performance":[98],"computing":[99],"infrastructure.":[100],"Using":[101],"an":[102],"Intel":[103,131,140],"Xeon":[104,132],"Phi":[105,133],"co-processor":[106],"with":[107],"61":[108],"cores,":[109],"we":[110],"describe":[111],"process":[113],"efficient":[115],"implementation":[116,137],"batched":[119],"stochastic":[120],"gradient":[121],"descent":[122],"demonstrate":[125],"a":[126,135],"11.4x":[127],"speedup":[128],"over":[134],"serial":[136],"Xeon.":[141]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":10},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}