{"id":"https://openalex.org/W2110107237","doi":"https://doi.org/10.1145/2659532.2659622","title":"Intraday stock forecasting","display_name":"Intraday stock forecasting","publication_year":2014,"publication_date":"2014-06-27","ids":{"openalex":"https://openalex.org/W2110107237","doi":"https://doi.org/10.1145/2659532.2659622","mag":"2110107237"},"language":"en","primary_location":{"id":"doi:10.1145/2659532.2659622","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2659532.2659622","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 15th International Conference on Computer Systems and Technologies","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/A5058768953","display_name":"Victor Louwerse","orcid":null},"institutions":[{"id":"https://openalex.org/I98358874","display_name":"Delft University of Technology","ror":"https://ror.org/02e2c7k09","country_code":"NL","type":"education","lineage":["https://openalex.org/I98358874"]}],"countries":["NL"],"is_corresponding":true,"raw_author_name":"Victor Louwerse","raw_affiliation_strings":["Delft University of Technology, Mekelweg, CD Delft, The Netherlands","[Delft University of Technology, Mekelweg, CD Delft, The Netherlands]"],"affiliations":[{"raw_affiliation_string":"Delft University of Technology, Mekelweg, CD Delft, The Netherlands","institution_ids":["https://openalex.org/I98358874"]},{"raw_affiliation_string":"[Delft University of Technology, Mekelweg, CD Delft, The Netherlands]","institution_ids":["https://openalex.org/I98358874"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039878081","display_name":"L\u00e9on Rothkrantz","orcid":"https://orcid.org/0000-0001-9821-088X"},"institutions":[{"id":"https://openalex.org/I98358874","display_name":"Delft University of Technology","ror":"https://ror.org/02e2c7k09","country_code":"NL","type":"education","lineage":["https://openalex.org/I98358874"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"L\u00e9on Rothkrantz","raw_affiliation_strings":["Delft University of Technology, Mekelweg, CD Delft, The Netherlands","[Delft University of Technology, Mekelweg, CD Delft, The Netherlands]"],"affiliations":[{"raw_affiliation_string":"Delft University of Technology, Mekelweg, CD Delft, The Netherlands","institution_ids":["https://openalex.org/I98358874"]},{"raw_affiliation_string":"[Delft University of Technology, Mekelweg, CD Delft, The Netherlands]","institution_ids":["https://openalex.org/I98358874"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5058768953"],"corresponding_institution_ids":["https://openalex.org/I98358874"],"apc_list":null,"apc_paid":null,"fwci":0.8116,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.78505425,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"202","last_page":"209"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9994999766349792,"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"}},"topics":[{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9994999766349792,"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/T11918","display_name":"Forecasting Techniques and Applications","score":0.9973000288009644,"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/T11052","display_name":"Energy Load and Power Forecasting","score":0.9925000071525574,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6461451649665833},{"id":"https://openalex.org/keywords/stock","display_name":"Stock (firearms)","score":0.6314222812652588},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6160770058631897},{"id":"https://openalex.org/keywords/stock-market","display_name":"Stock market","score":0.5789213180541992},{"id":"https://openalex.org/keywords/stock-price","display_name":"Stock price","score":0.5103427767753601},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.4848983883857727},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4231465458869934},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3289051055908203},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.21205353736877441},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.08742424845695496},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.08685028553009033}],"concepts":[{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6461451649665833},{"id":"https://openalex.org/C204036174","wikidata":"https://www.wikidata.org/wiki/Q909380","display_name":"Stock (firearms)","level":2,"score":0.6314222812652588},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6160770058631897},{"id":"https://openalex.org/C2780299701","wikidata":"https://www.wikidata.org/wiki/Q475000","display_name":"Stock market","level":3,"score":0.5789213180541992},{"id":"https://openalex.org/C2988984586","wikidata":"https://www.wikidata.org/wiki/Q1020013","display_name":"Stock price","level":3,"score":0.5103427767753601},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.4848983883857727},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4231465458869934},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3289051055908203},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.21205353736877441},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.08742424845695496},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.08685028553009033},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2659532.2659622","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2659532.2659622","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 15th International Conference on Computer Systems and Technologies","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.44999998807907104,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W185810578","https://openalex.org/W1586335931","https://openalex.org/W2015262594","https://openalex.org/W2015393497","https://openalex.org/W2111860494","https://openalex.org/W2117829824","https://openalex.org/W6981857433"],"related_works":["https://openalex.org/W2370669686","https://openalex.org/W247222457","https://openalex.org/W1488120909","https://openalex.org/W3124131549","https://openalex.org/W3008476150","https://openalex.org/W2152348935","https://openalex.org/W2887069341","https://openalex.org/W2554106722","https://openalex.org/W1797892342","https://openalex.org/W4240248738"],"abstract_inverted_index":{"The":[0,64],"objective":[1],"of":[2,8,53],"this":[3,81],"study":[4,48],"is":[5],"the":[6,42,51,76],"development":[7],"a":[9,24,46,57],"forecasting":[10,32,43],"system":[11,55],"for":[12],"intraday":[13,18],"stock":[14,21],"price":[15],"movement.":[16],"Here,":[17],"refers":[19],"to":[20],"movement":[22],"within":[23],"single":[25],"trading":[26],"day.":[27],"To":[28],"identify":[29],"trends":[30],"and":[31,61,75],"market":[33],"movements,":[34],"artificial":[35],"neural":[36],"networks":[37],"(ANN)":[38],"are":[39,78],"employed":[40],"by":[41],"system.":[44],"In":[45],"simulation":[47],"we":[49],"compared":[50],"performance":[52],"our":[54],"with":[56],"buy":[58],"&":[59],"hold":[60],"naive":[62],"strategy.":[63],"model":[65],"has":[66],"been":[67],"tested":[68],"in":[69,80],"some":[70],"experiments":[71],"on":[72],"real":[73],"data":[74],"results":[77],"reported":[79],"paper.":[82]},"counts_by_year":[{"year":2017,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
