{"id":"https://openalex.org/W7135057966","doi":"https://doi.org/10.31449/inf.v50i9.9069","title":"DCAGAT: A Graph Attention-Based Model with Reconstruction Regularization for Dollar-Cost Averaging Investment Prediction","display_name":"DCAGAT: A Graph Attention-Based Model with Reconstruction Regularization for Dollar-Cost Averaging Investment Prediction","publication_year":2026,"publication_date":"2026-03-12","ids":{"openalex":"https://openalex.org/W7135057966","doi":"https://doi.org/10.31449/inf.v50i9.9069"},"language":null,"primary_location":{"id":"doi:10.31449/inf.v50i9.9069","is_oa":true,"landing_page_url":"https://doi.org/10.31449/inf.v50i9.9069","pdf_url":"https://www.informatica.si/index.php/informatica/article/download/9069/6554","source":{"id":"https://openalex.org/S4210173311","display_name":"Informatica","issn_l":"0350-5596","issn":["0350-5596","1854-3871"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310314525","host_organization_name":"Slovenian Society Informatika","host_organization_lineage":["https://openalex.org/P4310314525"],"host_organization_lineage_names":["Slovenian Society Informatika"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Informatica","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://www.informatica.si/index.php/informatica/article/download/9069/6554","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5128903943","display_name":"Zhongli Lv","orcid":null},"institutions":[{"id":"https://openalex.org/I154893126","display_name":"Guizhou Normal University","ror":"https://ror.org/02x1pa065","country_code":"CN","type":"education","lineage":["https://openalex.org/I154893126"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhongli Lv","raw_affiliation_strings":["Guizhou Normal University, Guiyang,550001, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guizhou Normal University, Guiyang,550001, China","institution_ids":["https://openalex.org/I154893126"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5128903943"],"corresponding_institution_ids":["https://openalex.org/I154893126"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.25541754,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"50","issue":"9","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.6743999719619751,"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":0.6743999719619751,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.06109999865293503,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.05590000003576279,"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/overfitting","display_name":"Overfitting","score":0.5896999835968018},{"id":"https://openalex.org/keywords/volatility","display_name":"Volatility (finance)","score":0.5194000005722046},{"id":"https://openalex.org/keywords/financial-market","display_name":"Financial market","score":0.5004000067710876},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.45910000801086426},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.45399999618530273},{"id":"https://openalex.org/keywords/interdependence","display_name":"Interdependence","score":0.4458000063896179},{"id":"https://openalex.org/keywords/investment-strategy","display_name":"Investment strategy","score":0.42719998955726624},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4244000017642975},{"id":"https://openalex.org/keywords/market-data","display_name":"Market data","score":0.39010000228881836},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.37720000743865967}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6036999821662903},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.5896999835968018},{"id":"https://openalex.org/C91602232","wikidata":"https://www.wikidata.org/wiki/Q756115","display_name":"Volatility (finance)","level":2,"score":0.5194000005722046},{"id":"https://openalex.org/C19244329","wikidata":"https://www.wikidata.org/wiki/Q208697","display_name":"Financial market","level":2,"score":0.5004000067710876},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4745999872684479},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.45910000801086426},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.45399999618530273},{"id":"https://openalex.org/C185874996","wikidata":"https://www.wikidata.org/wiki/Q269699","display_name":"Interdependence","level":2,"score":0.4458000063896179},{"id":"https://openalex.org/C103144560","wikidata":"https://www.wikidata.org/wiki/Q2670999","display_name":"Investment strategy","level":3,"score":0.42719998955726624},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4244000017642975},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.42340001463890076},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.420199990272522},{"id":"https://openalex.org/C114118609","wikidata":"https://www.wikidata.org/wiki/Q3036837","display_name":"Market data","level":2,"score":0.39010000228881836},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.37720000743865967},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.37059998512268066},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.365200012922287},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.35740000009536743},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.35429999232292175},{"id":"https://openalex.org/C27548731","wikidata":"https://www.wikidata.org/wiki/Q88272","display_name":"Investment (military)","level":3,"score":0.3463999927043915},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3425000011920929},{"id":"https://openalex.org/C84749600","wikidata":"https://www.wikidata.org/wiki/Q5449714","display_name":"Financial engineering","level":2,"score":0.33180001378059387},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32710000872612},{"id":"https://openalex.org/C139043278","wikidata":"https://www.wikidata.org/wiki/Q837171","display_name":"Financial services","level":2,"score":0.32510000467300415},{"id":"https://openalex.org/C118315980","wikidata":"https://www.wikidata.org/wiki/Q375350","display_name":"Market timing","level":3,"score":0.32260000705718994},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.32249999046325684},{"id":"https://openalex.org/C131562839","wikidata":"https://www.wikidata.org/wiki/Q1574928","display_name":"Trading strategy","level":2,"score":0.3199999928474426},{"id":"https://openalex.org/C2781170535","wikidata":"https://www.wikidata.org/wiki/Q30587856","display_name":"Noisy data","level":2,"score":0.3116999864578247},{"id":"https://openalex.org/C78508483","wikidata":"https://www.wikidata.org/wiki/Q139445","display_name":"Algorithmic trading","level":2,"score":0.30550000071525574},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.301800012588501},{"id":"https://openalex.org/C2776760741","wikidata":"https://www.wikidata.org/wiki/Q25325235","display_name":"Financial networks","level":4,"score":0.2784000039100647},{"id":"https://openalex.org/C116409475","wikidata":"https://www.wikidata.org/wiki/Q1385056","display_name":"External Data Representation","level":2,"score":0.27570000290870667},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.27079999446868896},{"id":"https://openalex.org/C160623529","wikidata":"https://www.wikidata.org/wiki/Q273088","display_name":"Arbitrage","level":2,"score":0.2667999863624573},{"id":"https://openalex.org/C27564746","wikidata":"https://www.wikidata.org/wiki/Q913709","display_name":"Market research","level":2,"score":0.26030001044273376},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.2599000036716461},{"id":"https://openalex.org/C97713585","wikidata":"https://www.wikidata.org/wiki/Q6770534","display_name":"Mark to model","level":5,"score":0.25609999895095825},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.25209999084472656},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.25110000371932983}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.31449/inf.v50i9.9069","is_oa":true,"landing_page_url":"https://doi.org/10.31449/inf.v50i9.9069","pdf_url":"https://www.informatica.si/index.php/informatica/article/download/9069/6554","source":{"id":"https://openalex.org/S4210173311","display_name":"Informatica","issn_l":"0350-5596","issn":["0350-5596","1854-3871"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310314525","host_organization_name":"Slovenian Society Informatika","host_organization_lineage":["https://openalex.org/P4310314525"],"host_organization_lineage_names":["Slovenian Society Informatika"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Informatica","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.31449/inf.v50i9.9069","is_oa":true,"landing_page_url":"https://doi.org/10.31449/inf.v50i9.9069","pdf_url":"https://www.informatica.si/index.php/informatica/article/download/9069/6554","source":{"id":"https://openalex.org/S4210173311","display_name":"Informatica","issn_l":"0350-5596","issn":["0350-5596","1854-3871"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310314525","host_organization_name":"Slovenian Society Informatika","host_organization_lineage":["https://openalex.org/P4310314525"],"host_organization_lineage_names":["Slovenian Society Informatika"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Informatica","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.5481058955192566,"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320326674","display_name":"Department of Education of Guizhou Province","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7135057966.pdf","grobid_xml":"https://content.openalex.org/works/W7135057966.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0],"financial":[1,68,197],"market":[2,73,86,111,198,223],"is":[3,91],"characterized":[4],"by":[5,103,200],"high":[6],"volatility":[7],"and":[8,19,77,129,144,151,156],"noisy":[9],"data,":[10],"making":[11],"it":[12,168],"a":[13,82,193],"formidable":[14],"challenge":[15],"to":[16,41,61,133,216],"forecast":[17],"trends":[18,112],"design":[20],"robust":[21,194],"investment":[22,219],"strategies.":[23,51],"In":[24],"this":[25],"paper,":[26],"we":[27],"propose":[28],"an":[29,95],"innovative":[30],"prediction":[31],"model":[32,80,107],"that":[33,105],"integrates":[34],"multi-feature":[35],"fusion":[36],"with":[37,176,206],"graph":[38],"attention":[39],"mechanisms":[40],"address":[42],"these":[43],"challenges,":[44],"specifically":[45],"tailored":[46],"for":[47,196,213],"dollar-cost":[48],"averaging":[49],"(DCA)":[50],"Our":[52],"model,":[53],"termed":[54],"DCAGAT,":[55],"leverages":[56],"Graph":[57],"Attention":[58],"Networks":[59],"(GATs)":[60],"dynamically":[62],"assess":[63],"the":[64,92,106,119,163,173,180],"interdependencies":[65],"among":[66],"various":[67],"assets.":[69],"By":[70],"incorporating":[71],"multiple":[72],"features\u2014historical":[74],"price":[75],"fluctuations":[76],"trading":[78],"volumes\u2014the":[79],"constructs":[81],"comprehensive":[83],"representation":[84],"of":[85,94,121],"dynamics.":[87],"A":[88],"key":[89],"innovation":[90],"inclusion":[93],"autoencoder-inspired":[96],"reconstruction":[97],"verification":[98],"mechanism,":[99],"which":[100],"mitigates":[101],"overfitting":[102],"ensuring":[104],"focuses":[108],"on":[109,166],"persistent":[110],"rather":[113],"than":[114],"transient":[115],"noise.":[116],"We":[117,135],"validate":[118],"effectiveness":[120],"DCAGAT":[122,137,161],"using":[123],"historical":[124],"data":[125,208],"from":[126,131],"Yahoo":[127],"Finance":[128],"ETF":[130],"2012":[132],"2022.":[134],"benchmark":[136],"against":[138],"four":[139],"neural":[140],"baselines\u2014DNN,":[141],"Conv1D,":[142],"GCN":[143],"ST-GCN\u2014on":[145],"three":[146],"DCA-oriented":[147],"metrics:":[148],"one-,":[149],"seven-":[150],"fourteen-day":[152],"directional":[153],"accuracy":[154],"(Adir)":[155],"Top-5":[157],"hit-rate":[158],"(Aselect).":[159],"While":[160],"matches":[162],"best":[164],"baseline":[165],"Adir,":[167],"consistently":[169],"improves":[170],"Aselect":[171],"across":[172],"evaluated":[174],"scenarios,":[175],"every":[177],"gain":[178],"passing":[179],"paired":[181],"statistical-significance":[182],"test.,":[183],"underscoring":[184],"its":[185],"superior":[186],"stock-selection":[187],"capability.":[188],"Overall,":[189],"our":[190],"research":[191],"provides":[192],"framework":[195],"forecasting":[199],"combining":[201],"advanced":[202],"graph-based":[203],"learning":[204],"techniques":[205],"feature-rich":[207],"integration,":[209],"offering":[210],"valuable":[211],"insights":[212],"investors":[214],"seeking":[215],"optimize":[217],"multi-day":[218],"decisions":[220],"in":[221],"unpredictable":[222],"environments.":[224]},"counts_by_year":[],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2026-03-13T00:00:00"}
