{"id":"https://openalex.org/W2083743164","doi":"https://doi.org/10.1145/1363686.1363910","title":"Data stream mining for market-neutral algorithmic trading","display_name":"Data stream mining for market-neutral algorithmic trading","publication_year":2008,"publication_date":"2008-03-16","ids":{"openalex":"https://openalex.org/W2083743164","doi":"https://doi.org/10.1145/1363686.1363910","mag":"2083743164"},"language":"en","primary_location":{"id":"doi:10.1145/1363686.1363910","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1363686.1363910","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2008 ACM symposium on Applied computing","raw_type":"proceedings-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/A5010581004","display_name":"Giovanni Montana","orcid":"https://orcid.org/0000-0003-3942-3900"},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Giovanni Montana","raw_affiliation_strings":["Imperial College London, London, UK","#N#Imperial College London, London, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Imperial College London, London, UK","institution_ids":["https://openalex.org/I47508984"]},{"raw_affiliation_string":"#N#Imperial College London, London, UK","institution_ids":["https://openalex.org/I47508984"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072944307","display_name":"Kostas Triantafyllopoulos","orcid":"https://orcid.org/0000-0002-4144-4092"},"institutions":[{"id":"https://openalex.org/I91136226","display_name":"University of Sheffield","ror":"https://ror.org/05krs5044","country_code":"GB","type":"education","lineage":["https://openalex.org/I91136226"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Kostas Triantafyllopoulos","raw_affiliation_strings":["University of Sheffield, Sheffield, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Sheffield, Sheffield, UK","institution_ids":["https://openalex.org/I91136226"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025446711","display_name":"Theodoros Tsagaris","orcid":null},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Theodoros Tsagaris","raw_affiliation_strings":["Imperial College London, London, UK","#N#Imperial College London, London, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Imperial College London, London, UK","institution_ids":["https://openalex.org/I47508984"]},{"raw_affiliation_string":"#N#Imperial College London, London, UK","institution_ids":["https://openalex.org/I47508984"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":7.1967,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.96670435,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"966","last_page":"970"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11270","display_name":"Complex Systems and Time Series Analysis","score":0.9947999715805054,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11270","display_name":"Complex Systems and Time Series Analysis","score":0.9947999715805054,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9927999973297119,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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":0.9904000163078308,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/futures-contract","display_name":"Futures contract","score":0.7432547807693481},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6863137483596802},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6238534450531006},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.6003547310829163},{"id":"https://openalex.org/keywords/data-stream-mining","display_name":"Data stream mining","score":0.590162992477417},{"id":"https://openalex.org/keywords/trading-strategy","display_name":"Trading strategy","score":0.5626810789108276},{"id":"https://openalex.org/keywords/data-stream","display_name":"Data stream","score":0.5043803453445435},{"id":"https://openalex.org/keywords/pairs-trade","display_name":"Pairs trade","score":0.48455682396888733},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4662102162837982},{"id":"https://openalex.org/keywords/ordinary-least-squares","display_name":"Ordinary least squares","score":0.44975608587265015},{"id":"https://openalex.org/keywords/algorithmic-trading","display_name":"Algorithmic trading","score":0.43889933824539185},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.41480347514152527},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.37559622526168823},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.26380234956741333},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.21596035361289978},{"id":"https://openalex.org/keywords/finance","display_name":"Finance","score":0.14487296342849731},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.144497811794281},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.09810331463813782},{"id":"https://openalex.org/keywords/alternative-trading-system","display_name":"Alternative trading system","score":0.09464991092681885}],"concepts":[{"id":"https://openalex.org/C106306483","wikidata":"https://www.wikidata.org/wiki/Q183984","display_name":"Futures contract","level":2,"score":0.7432547807693481},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6863137483596802},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6238534450531006},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.6003547310829163},{"id":"https://openalex.org/C89198739","wikidata":"https://www.wikidata.org/wiki/Q3079880","display_name":"Data stream mining","level":2,"score":0.590162992477417},{"id":"https://openalex.org/C131562839","wikidata":"https://www.wikidata.org/wiki/Q1574928","display_name":"Trading strategy","level":2,"score":0.5626810789108276},{"id":"https://openalex.org/C2778484313","wikidata":"https://www.wikidata.org/wiki/Q1172540","display_name":"Data stream","level":2,"score":0.5043803453445435},{"id":"https://openalex.org/C158876240","wikidata":"https://www.wikidata.org/wiki/Q17105131","display_name":"Pairs trade","level":4,"score":0.48455682396888733},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4662102162837982},{"id":"https://openalex.org/C99656134","wikidata":"https://www.wikidata.org/wiki/Q2912993","display_name":"Ordinary least squares","level":2,"score":0.44975608587265015},{"id":"https://openalex.org/C78508483","wikidata":"https://www.wikidata.org/wiki/Q139445","display_name":"Algorithmic trading","level":2,"score":0.43889933824539185},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.41480347514152527},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.37559622526168823},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.26380234956741333},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.21596035361289978},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.14487296342849731},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.144497811794281},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.09810331463813782},{"id":"https://openalex.org/C172428447","wikidata":"https://www.wikidata.org/wiki/Q438711","display_name":"Alternative trading system","level":3,"score":0.09464991092681885},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/1363686.1363910","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1363686.1363910","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2008 ACM symposium on Applied computing","raw_type":"proceedings-article"},{"id":"pmh:oai:eprints.whiterose.ac.uk:10626","is_oa":false,"landing_page_url":"http://eprints.whiterose.ac.uk/10626/","pdf_url":null,"source":{"id":"https://openalex.org/S4306400854","display_name":"White Rose Research Online (University of Leeds, The University of Sheffield, University of York)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I2800616092","host_organization_name":"White Rose University Consortium","host_organization_lineage":["https://openalex.org/I2800616092"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Proceedings Paper"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W1967108537","https://openalex.org/W2019851767","https://openalex.org/W2035366415","https://openalex.org/W2035899217","https://openalex.org/W2073570880","https://openalex.org/W2107600015","https://openalex.org/W2141681031","https://openalex.org/W3122010751","https://openalex.org/W6837831485"],"related_works":["https://openalex.org/W4400426774","https://openalex.org/W2392556764","https://openalex.org/W4385489135","https://openalex.org/W4399587225","https://openalex.org/W3195402399","https://openalex.org/W4300619693","https://openalex.org/W3209680969","https://openalex.org/W4388830163","https://openalex.org/W2523594540","https://openalex.org/W2785550510"],"abstract_inverted_index":{"In":[0],"algorithmic":[1,78],"trading":[2,79,102],"applications,":[3],"a":[4,25,54,76,83],"large":[5],"number":[6],"of":[7,57,86],"co-evolving":[8],"financial":[9],"data":[10],"streams":[11],"are":[12],"observed":[13],"and":[14,18,38,90],"analyzed.":[15],"A":[16],"recurrent":[17],"important":[19],"task":[20],"is":[21],"to":[22,98],"determine":[23],"how":[24,49],"given":[26],"stream":[27],"depends":[28],"on":[29,82],"others,":[30],"over":[31],"time,":[32],"accounting":[33],"for":[34,63],"dynamic":[35,64],"dependence":[36],"patterns":[37],"without":[39],"imposing":[40],"any":[41],"probabilistic":[42],"law":[43],"governing":[44],"this":[45,72],"dependence.":[46],"We":[47,74],"demonstrate":[48],"Flexible":[50],"Least":[51],"Squares":[52],"(FLS),":[53],"penalized":[55],"version":[56],"ordinary":[58],"least":[59],"squares":[60],"that":[61],"accommodates":[62],"regression":[65],"coefficients,":[66],"can":[67],"be":[68],"deployed":[69],"successfully":[70,100],"in":[71],"context.":[73],"describe":[75],"market-neutral":[77],"system":[80,94],"based":[81],"combined":[84],"use":[85],"on-line":[87],"feature":[88],"extraction":[89],"recursive":[91],"regression.":[92],"The":[93],"has":[95],"been":[96],"proved":[97],"perform":[99],"when":[101],"the":[103],"S&P":[104],"500":[105],"Futures":[106],"Index.
\\n
\\n":[107]},"counts_by_year":[{"year":2020,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}