{"id":"https://openalex.org/W7140093551","doi":"https://doi.org/10.48550/arxiv.2603.20063","title":"Fine-tuning Timeseries Predictors Using Reinforcement Learning","display_name":"Fine-tuning Timeseries Predictors Using Reinforcement Learning","publication_year":2026,"publication_date":"2026-03-20","ids":{"openalex":"https://openalex.org/W7140093551","doi":"https://doi.org/10.48550/arxiv.2603.20063"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2603.20063","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2603.20063","pdf_url":"https://arxiv.org/pdf/2603.20063","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"parent_works":[],"lineage":["https://openalex.org/W7140093551"],"child_works_count":0,"type":"preprint","is_traditional":true,"indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2603.20063","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5116498964","display_name":"Hugo Cazaux","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I123185442","display_name":"Reykjav\u00edk University","ror":"https://ror.org/05d2kyx68","country_code":"IS","type":"education","lineage":["https://openalex.org/I123185442"]}],"countries":["IS"],"is_corresponding":false,"raw_author_name":"Cazaux, Hugo","raw_affiliation_strings":["Reykjavik University , Department of Engineering , Menntavegur 1 , Reykjavik , 102 , Iceland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Reykjavik University , Department of Engineering , Menntavegur 1 , Reykjavik , 102 , Iceland","institution_ids":["https://openalex.org/I123185442"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008877452","display_name":"Ralph Rudd","orcid":"https://orcid.org/0000-0002-7782-7941","observed_orcids":["https://orcid.org/0000-0002-7782-7941"]},"institutions":[{"id":"https://openalex.org/I123185442","display_name":"Reykjav\u00edk University","ror":"https://ror.org/05d2kyx68","country_code":"IS","type":"education","lineage":["https://openalex.org/I123185442"]}],"countries":["IS"],"is_corresponding":false,"raw_author_name":"Rudd, Ralph","raw_affiliation_strings":["Reykjavik University , Department of Engineering , Menntavegur 1 , Reykjavik , 102 , Iceland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Reykjavik University , Department of Engineering , Menntavegur 1 , Reykjavik , 102 , Iceland","institution_ids":["https://openalex.org/I123185442"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088032846","display_name":"Hlynur Stef\u00e1nsson","orcid":"https://orcid.org/0000-0001-8689-8074","observed_orcids":["https://orcid.org/0000-0001-8689-8074"]},"institutions":[{"id":"https://openalex.org/I123185442","display_name":"Reykjav\u00edk University","ror":"https://ror.org/05d2kyx68","country_code":"IS","type":"education","lineage":["https://openalex.org/I123185442"]}],"countries":["IS"],"is_corresponding":false,"raw_author_name":"Stef\u00e1nsson, Hlynur","raw_affiliation_strings":["Reykjavik University , Department of Engineering , Menntavegur 1 , Reykjavik , 102 , Iceland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Reykjavik University , Department of Engineering , Menntavegur 1 , Reykjavik , 102 , Iceland","institution_ids":["https://openalex.org/I123185442"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001803855","display_name":"Sverrir \u00d3lafsson","orcid":"https://orcid.org/0000-0002-6627-0244","observed_orcids":["https://orcid.org/0000-0002-6627-0244"]},"institutions":[{"id":"https://openalex.org/I123185442","display_name":"Reykjav\u00edk University","ror":"https://ror.org/05d2kyx68","country_code":"IS","type":"education","lineage":["https://openalex.org/I123185442"]}],"countries":["IS"],"is_corresponding":false,"raw_author_name":"\u00d3lafsson, Sverrir","raw_affiliation_strings":["Reykjavik University , Department of Engineering , Menntavegur 1 , Reykjavik , 102 , Iceland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Reykjavik University , Department of Engineering , Menntavegur 1 , Reykjavik , 102 , Iceland","institution_ids":["https://openalex.org/I123185442"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025260479","display_name":"Eyj\u00f3lfur Ingi \u00c1sgeirsson","orcid":"https://orcid.org/0000-0001-6719-0150","observed_orcids":["https://orcid.org/0000-0001-6719-0150"]},"institutions":[{"id":"https://openalex.org/I123185442","display_name":"Reykjav\u00edk University","ror":"https://ror.org/05d2kyx68","country_code":"IS","type":"education","lineage":["https://openalex.org/I123185442"]}],"countries":["IS"],"is_corresponding":false,"raw_author_name":"\u00c1sgeirsson, Eyj\u00f3lfur Ingi","raw_affiliation_strings":["Reykjavik University , Department of Engineering , Menntavegur 1 , Reykjavik , 102 , Iceland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Reykjavik University , Department of Engineering , Menntavegur 1 , Reykjavik , 102 , Iceland","institution_ids":["https://openalex.org/I123185442"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I123185442"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"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":1.0,"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":1.0,"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":9.999999747378752e-05,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.0,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"reinforcement learning","score":0.7770000100135803},{"id":"https://openalex.org/keywords/fine-tuning","display_name":"fine-tuning","score":0.9190000295639038},{"id":"https://openalex.org/keywords/time-series-forecasting","display_name":"time series forecasting","score":0.800000011920929},{"id":"https://openalex.org/keywords/financial-forecasting","display_name":"financial forecasting","score":0.9679999947547913},{"id":"https://openalex.org/keywords/transfer-learning","display_name":"transfer learning","score":0.8100000023841858},{"id":"https://openalex.org/keywords/backpropagation","display_name":"backpropagation","score":0.6309999823570251},{"id":"https://openalex.org/keywords/supervised-learning-models","display_name":"supervised learning models","score":0.5950000286102295},{"id":"https://openalex.org/keywords/model-performance-improvement","display_name":"model performance improvement","score":0.43299999833106995}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8598999977111816},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7573999762535095},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6926000118255615},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6714000105857849},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6230999827384949},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5266000032424927},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.524399995803833},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.38370001316070557},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.37929999828338623},{"id":"https://openalex.org/C28006648","wikidata":"https://www.wikidata.org/wiki/Q6934509","display_name":"Multi-task learning","level":3,"score":0.3732999861240387},{"id":"https://openalex.org/C67203356","wikidata":"https://www.wikidata.org/wiki/Q1321905","display_name":"Reinforcement","level":2,"score":0.3671000003814697},{"id":"https://openalex.org/C199190896","wikidata":"https://www.wikidata.org/wiki/Q3509276","display_name":"Learning classifier system","level":3,"score":0.3666999936103821},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.36230000853538513},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.31189998984336853},{"id":"https://openalex.org/C2776505523","wikidata":"https://www.wikidata.org/wiki/Q4785468","display_name":"Plan (archaeology)","level":2,"score":0.30959999561309814},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.30399999022483826},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.2856999933719635},{"id":"https://openalex.org/C58973888","wikidata":"https://www.wikidata.org/wiki/Q1041418","display_name":"Semi-supervised learning","level":2,"score":0.2786000072956085},{"id":"https://openalex.org/C120936955","wikidata":"https://www.wikidata.org/wiki/Q2155640","display_name":"Empirical research","level":2,"score":0.26969999074935913}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2603.20063","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2603.20063","pdf_url":"https://arxiv.org/pdf/2603.20063","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2603.20063","doi":"https://doi.org/10.48550/arxiv.2603.20063","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.20063","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2603.20063","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2603.20063","pdf_url":"https://arxiv.org/pdf/2603.20063","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7140093551.pdf","grobid_xml":"https://content.openalex.org/works/W7140093551.grobid-xml"},"referenced_works_count":25,"referenced_works":["https://openalex.org/W2158782408","https://openalex.org/W2507373853","https://openalex.org/W2556958149","https://openalex.org/W2736601468","https://openalex.org/W2798812533","https://openalex.org/W2896457183","https://openalex.org/W2920362155","https://openalex.org/W2939228328","https://openalex.org/W2996037775","https://openalex.org/W2999596312","https://openalex.org/W3032398409","https://openalex.org/W3034709122","https://openalex.org/W3088484880","https://openalex.org/W3096565276","https://openalex.org/W3168867926","https://openalex.org/W3174770825","https://openalex.org/W3175870271","https://openalex.org/W3176693010","https://openalex.org/W4225546850","https://openalex.org/W4361229539","https://openalex.org/W4362598952","https://openalex.org/W4394973259","https://openalex.org/W4405903187","https://openalex.org/W4407838869","https://openalex.org/W7125799258"],"related_works":["https://openalex.org/W7134944872","https://openalex.org/W7160178388","https://openalex.org/W4416539969","https://openalex.org/W4389474157","https://openalex.org/W2969829860","https://openalex.org/W2899279621","https://openalex.org/W7119243990","https://openalex.org/W4417070801","https://openalex.org/W7171508934","https://openalex.org/W4396667313"],"abstract_inverted_index":{"This":[0],"chapter":[1],"presents":[2],"three":[3],"major":[4],"reinforcement":[5,25],"learning":[6,26,54],"algorithms":[7],"used":[8],"for":[9,19,73],"fine-tuning":[10],"financial":[11],"forecasters.":[12],"We":[13,44,64],"propose":[14],"a":[15,24,29],"clear":[16],"implementation":[17,75],"plan":[18],"backpropagating":[20],"the":[21,37,42,57,60,67],"loss":[22],"of":[23,62],"task":[27],"to":[28,56],"model":[30],"trained":[31],"using":[32],"supervised":[33],"learning,":[34],"and":[35,40,52,70],"compare":[36],"performance":[38,49],"before":[39],"after":[41,50],"fine-tuning.":[43,63],"find":[45],"an":[46],"increase":[47],"in":[48],"fine-tuning,":[51],"transfer":[53],"properties":[55],"models,":[58],"indicating":[59],"benefits":[61],"also":[65],"highlight":[66],"tuning":[68],"process":[69],"empirical":[71],"results":[72],"future":[74],"by":[76],"practitioners.":[77]},"counts_by_year":[],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2026-03-24T00:00:00"}
