{"id":"https://openalex.org/W2034315841","doi":"https://doi.org/10.1142/s0129065797000410","title":"Nonlinear Trading Models Through Sharpe Ratio Maximization","display_name":"Nonlinear Trading Models Through Sharpe Ratio Maximization","publication_year":1997,"publication_date":"1997-08-01","ids":{"openalex":"https://openalex.org/W2034315841","doi":"https://doi.org/10.1142/s0129065797000410","mag":"2034315841","pmid":"https://pubmed.ncbi.nlm.nih.gov/9730018"},"language":"en","primary_location":{"id":"doi:10.1142/s0129065797000410","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0129065797000410","pdf_url":null,"source":{"id":"https://openalex.org/S197665576","display_name":"International Journal of Neural Systems","issn_l":"0129-0657","issn":["0129-0657","1793-6462"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Neural Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5055947238","display_name":"Mark Choey","orcid":null},"institutions":[{"id":"https://openalex.org/I4210136600","display_name":"Diebold Nixdorf (United States)","ror":"https://ror.org/03t94kt09","country_code":"US","type":"company","lineage":["https://openalex.org/I4210136600"]},{"id":"https://openalex.org/I4210137693","display_name":"Siemens (United States)","ror":"https://ror.org/04axb7e79","country_code":"US","type":"company","lineage":["https://openalex.org/I1325886976","https://openalex.org/I4210137693"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mark Choey","raw_affiliation_strings":["Advanced Technology Group, Siemens Nixdorf Information Systems, Inc., 200 Wheeler Road, Burlington, MA 01803, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Advanced Technology Group, Siemens Nixdorf Information Systems, Inc., 200 Wheeler Road, Burlington, MA 01803, USA","institution_ids":["https://openalex.org/I4210136600","https://openalex.org/I4210137693"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037027451","display_name":"Andreas S. Weigend","orcid":null},"institutions":[{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Andreas S. Weigend","raw_affiliation_strings":["Department of Information Systems, Leonard N. Stern School of Business, New York University, 44 West Fourth Street, MEC 9-74, New York, NY 10012, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Information Systems, Leonard N. Stern School of Business, New York University, 44 West Fourth Street, MEC 9-74, New York, NY 10012, USA","institution_ids":["https://openalex.org/I57206974"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.7785,"has_fulltext":false,"cited_by_count":29,"citation_normalized_percentile":{"value":0.85015866,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"08","issue":"04","first_page":"417","last_page":"431"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9993000030517578,"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":0.9993000030517578,"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/T11674","display_name":"Sports Analytics and Performance","score":0.9927999973297119,"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/T11918","display_name":"Forecasting Techniques and Applications","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/sharpe-ratio","display_name":"Sharpe ratio","score":0.9723168611526489},{"id":"https://openalex.org/keywords/maximization","display_name":"Maximization","score":0.6289404034614563},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6199619174003601},{"id":"https://openalex.org/keywords/trading-strategy","display_name":"Trading strategy","score":0.5966732501983643},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.5199440717697144},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.4449804425239563},{"id":"https://openalex.org/keywords/profit-maximization","display_name":"Profit maximization","score":0.4252728223800659},{"id":"https://openalex.org/keywords/equity","display_name":"Equity (law)","score":0.41634559631347656},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.37828996777534485},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.36110401153564453},{"id":"https://openalex.org/keywords/profit","display_name":"Profit (economics)","score":0.268624484539032},{"id":"https://openalex.org/keywords/financial-economics","display_name":"Financial economics","score":0.228877454996109},{"id":"https://openalex.org/keywords/microeconomics","display_name":"Microeconomics","score":0.2124907672405243},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.18919315934181213},{"id":"https://openalex.org/keywords/portfolio","display_name":"Portfolio","score":0.13926073908805847}],"concepts":[{"id":"https://openalex.org/C139938925","wikidata":"https://www.wikidata.org/wiki/Q1501898","display_name":"Sharpe ratio","level":3,"score":0.9723168611526489},{"id":"https://openalex.org/C2776330181","wikidata":"https://www.wikidata.org/wiki/Q18358244","display_name":"Maximization","level":2,"score":0.6289404034614563},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6199619174003601},{"id":"https://openalex.org/C131562839","wikidata":"https://www.wikidata.org/wiki/Q1574928","display_name":"Trading strategy","level":2,"score":0.5966732501983643},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.5199440717697144},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.4449804425239563},{"id":"https://openalex.org/C2777780509","wikidata":"https://www.wikidata.org/wiki/Q1377422","display_name":"Profit maximization","level":3,"score":0.4252728223800659},{"id":"https://openalex.org/C199728807","wikidata":"https://www.wikidata.org/wiki/Q2578557","display_name":"Equity (law)","level":2,"score":0.41634559631347656},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.37828996777534485},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.36110401153564453},{"id":"https://openalex.org/C181622380","wikidata":"https://www.wikidata.org/wiki/Q26911","display_name":"Profit (economics)","level":2,"score":0.268624484539032},{"id":"https://openalex.org/C106159729","wikidata":"https://www.wikidata.org/wiki/Q2294553","display_name":"Financial economics","level":1,"score":0.228877454996109},{"id":"https://openalex.org/C175444787","wikidata":"https://www.wikidata.org/wiki/Q39072","display_name":"Microeconomics","level":1,"score":0.2124907672405243},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18919315934181213},{"id":"https://openalex.org/C2780821815","wikidata":"https://www.wikidata.org/wiki/Q5340806","display_name":"Portfolio","level":2,"score":0.13926073908805847},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001185","descriptor_name":"Artificial Intelligence","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D001185","descriptor_name":"Artificial Intelligence","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D001185","descriptor_name":"Artificial Intelligence","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D003627","descriptor_name":"Data Interpretation, Statistical","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003627","descriptor_name":"Data Interpretation, Statistical","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003627","descriptor_name":"Data Interpretation, Statistical","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D017711","descriptor_name":"Nonlinear Dynamics","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D017711","descriptor_name":"Nonlinear Dynamics","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D017711","descriptor_name":"Nonlinear Dynamics","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D018803","descriptor_name":"Models, Economic","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D018803","descriptor_name":"Models, Economic","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D018803","descriptor_name":"Models, Economic","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true}],"locations_count":3,"locations":[{"id":"doi:10.1142/s0129065797000410","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0129065797000410","pdf_url":null,"source":{"id":"https://openalex.org/S197665576","display_name":"International Journal of Neural Systems","issn_l":"0129-0657","issn":["0129-0657","1793-6462"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Neural Systems","raw_type":"journal-article"},{"id":"pmid:9730018","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/9730018","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International journal of neural systems","raw_type":null},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.95.2929","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.95.2929","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www-psych.stanford.edu/~andreas/Research/Papers/SharpeRatio/Choey.Weigend_NNCM96.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Partnerships for the goals","score":0.5099999904632568,"id":"https://metadata.un.org/sdg/17"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320308931","display_name":"U.S. Department of the Treasury","ror":"https://ror.org/028t43p77"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W589966460","https://openalex.org/W1709719830","https://openalex.org/W1800955719","https://openalex.org/W2005752521","https://openalex.org/W2009225465","https://openalex.org/W2106644119","https://openalex.org/W2153580489","https://openalex.org/W2740357385"],"related_works":["https://openalex.org/W3124375115","https://openalex.org/W2001839669","https://openalex.org/W3156897841","https://openalex.org/W3121486519","https://openalex.org/W2129004047","https://openalex.org/W2791387620","https://openalex.org/W2013957197","https://openalex.org/W3186897576","https://openalex.org/W3009706689","https://openalex.org/W2034315841"],"abstract_inverted_index":{"While":[0],"many":[1],"trading":[2,82],"strategies":[3],"are":[4,13,73],"based":[5,103],"on":[6,88,104],"price":[7,28],"prediction,":[8],"traders":[9],"in":[10,16],"financial":[11],"markets":[12],"typically":[14],"interested":[15],"optimizing":[17,127],"risk-adjusted":[18,129],"performance":[19],"such":[20],"as":[21,50],"the":[22,27,44,58,97,124],"Sharpe":[23,45,105],"Ratio,":[24],"rather":[25],"than":[26],"predictions":[29],"themselves.":[30],"This":[31],"paper":[32],"introduces":[33],"an":[34],"approach":[35],"which":[36],"generates":[37],"a":[38,51,62,65],"nonlinear":[39,137],"strategy":[40,83],"that":[41,123],"explicitly":[42],"maximizes":[43],"Ratio.":[46],"It":[47],"is":[48,57,84],"expressed":[49],"neural":[52],"network":[53],"model":[54],"whose":[55],"output":[56],"position":[59],"size":[60],"between":[61],"risky":[63],"and":[64,75,86,92,114],"risk-free":[66],"asset.":[67],"The":[68,80,120],"iterative":[69],"parameter":[70],"update":[71],"rules":[72],"derived":[74],"compared":[76],"to":[77,110],"alternative":[78],"approaches.":[79],"resulting":[81],"evaluated":[85],"analyzed":[87],"both":[89,111],"computer-generated":[90],"data":[91,95],"real":[93],"world":[94],"(DAX,":[96],"daily":[98],"German":[99],"equity":[100],"index).":[101],"Trading":[102],"Ratio":[106],"maximization":[107],"compares":[108],"favorably":[109],"profit":[112,130],"optimization":[113],"probability":[115],"matching":[116],"(through":[117],"cross-entropy":[118],"optimization).":[119],"results":[121],"show":[122],"goal":[125],"of":[126],"out-of-sample":[128],"can":[131],"indeed":[132],"be":[133],"achieved":[134],"with":[135],"this":[136],"approach.":[138]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":2},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}