{"id":"https://openalex.org/W4312294324","doi":"https://doi.org/10.1145/3557738.3557943","title":"Performance Evaluation of Systematic Option Trading Strategies Using Entry and Exit Points Predicted by Machine Learning","display_name":"Performance Evaluation of Systematic Option Trading Strategies Using Entry and Exit Points Predicted by Machine Learning","publication_year":2022,"publication_date":"2022-09-21","ids":{"openalex":"https://openalex.org/W4312294324","doi":"https://doi.org/10.1145/3557738.3557943"},"language":"en","primary_location":{"id":"doi:10.1145/3557738.3557943","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3557738.3557943","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 International Conference on Engineering and Information Technology for Sustainable Industry","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/A5042861758","display_name":"Tan Meilisa Tansil","orcid":null},"institutions":[{"id":"https://openalex.org/I100406981","display_name":"Swiss German University","ror":"https://ror.org/047rtk203","country_code":"ID","type":"education","lineage":["https://openalex.org/I100406981"]}],"countries":["ID"],"is_corresponding":true,"raw_author_name":"Tan Meilisa Tansil","raw_affiliation_strings":["Swiss German University, Indonesia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Swiss German University, Indonesia","institution_ids":["https://openalex.org/I100406981"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060742900","display_name":"Leonard P. Rusli","orcid":null},"institutions":[{"id":"https://openalex.org/I100406981","display_name":"Swiss German University","ror":"https://ror.org/047rtk203","country_code":"ID","type":"education","lineage":["https://openalex.org/I100406981"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Leonard P. Rusli","raw_affiliation_strings":["Swiss German University, Indonesia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Swiss German University, Indonesia","institution_ids":["https://openalex.org/I100406981"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030016527","display_name":"Eka Budiarto","orcid":"https://orcid.org/0009-0000-6642-260X"},"institutions":[{"id":"https://openalex.org/I100406981","display_name":"Swiss German University","ror":"https://ror.org/047rtk203","country_code":"ID","type":"education","lineage":["https://openalex.org/I100406981"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Eka Budiarto","raw_affiliation_strings":["Swiss German University, Indonesia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Swiss German University, Indonesia","institution_ids":["https://openalex.org/I100406981"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5042861758"],"corresponding_institution_ids":["https://openalex.org/I100406981"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.18586908,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9980000257492065,"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":0.9980000257492065,"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/T11059","display_name":"Market Dynamics and Volatility","score":0.9883999824523926,"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/T11052","display_name":"Energy Load and Power Forecasting","score":0.9857000112533569,"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/computer-science","display_name":"Computer science","score":0.630420982837677},{"id":"https://openalex.org/keywords/yield","display_name":"Yield (engineering)","score":0.488727331161499},{"id":"https://openalex.org/keywords/systematic-review","display_name":"Systematic review","score":0.46709200739860535},{"id":"https://openalex.org/keywords/trading-strategy","display_name":"Trading strategy","score":0.4569133222103119},{"id":"https://openalex.org/keywords/phase","display_name":"Phase (matter)","score":0.4226158857345581},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.41910502314567566},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3766672611236572},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.3377513289451599},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.14098432660102844}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.630420982837677},{"id":"https://openalex.org/C134121241","wikidata":"https://www.wikidata.org/wiki/Q899301","display_name":"Yield (engineering)","level":2,"score":0.488727331161499},{"id":"https://openalex.org/C189708586","wikidata":"https://www.wikidata.org/wiki/Q1504425","display_name":"Systematic review","level":3,"score":0.46709200739860535},{"id":"https://openalex.org/C131562839","wikidata":"https://www.wikidata.org/wiki/Q1574928","display_name":"Trading strategy","level":2,"score":0.4569133222103119},{"id":"https://openalex.org/C44280652","wikidata":"https://www.wikidata.org/wiki/Q104837","display_name":"Phase (matter)","level":2,"score":0.4226158857345581},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41910502314567566},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3766672611236572},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.3377513289451599},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.14098432660102844},{"id":"https://openalex.org/C2779473830","wikidata":"https://www.wikidata.org/wiki/Q1540899","display_name":"MEDLINE","level":2,"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/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","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},{"id":"https://openalex.org/C191897082","wikidata":"https://www.wikidata.org/wiki/Q11467","display_name":"Metallurgy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3557738.3557943","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3557738.3557943","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 International Conference on Engineering and Information Technology for Sustainable Industry","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/17","score":0.4300000071525574,"display_name":"Partnerships for the goals"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W595395280","https://openalex.org/W1526812571","https://openalex.org/W1571851576","https://openalex.org/W2050790090","https://openalex.org/W2052403396","https://openalex.org/W2065610112","https://openalex.org/W2579503507","https://openalex.org/W2602977295","https://openalex.org/W2809597102","https://openalex.org/W2893718114","https://openalex.org/W2946805352","https://openalex.org/W3002449440","https://openalex.org/W3108280472","https://openalex.org/W3125595766","https://openalex.org/W3168485664","https://openalex.org/W4238461350","https://openalex.org/W4243037160","https://openalex.org/W6768971453"],"related_works":["https://openalex.org/W2386800167","https://openalex.org/W2384315363","https://openalex.org/W1990212788","https://openalex.org/W2395691387","https://openalex.org/W2792383399","https://openalex.org/W3024289321","https://openalex.org/W2766255174","https://openalex.org/W2377343822","https://openalex.org/W4200400515","https://openalex.org/W2131099179"],"abstract_inverted_index":{"In":[0],"option":[1,23,38,85],"trading,":[2],"there":[3],"are":[4,17,88],"various":[5,19,84],"technical":[6,49],"indicators":[7,50],"that":[8,99],"can":[9],"be":[10],"used":[11],"to":[12,32,70,94],"determine":[13],"entry":[14,42,72],"signals.":[15],"There":[16],"also":[18],"setups":[20,87],"for":[21],"systematic":[22,37],"trading":[24,39,86],"strategies.":[25],"The":[26],"objective":[27],"of":[28,36],"this":[29,55],"research":[30],"is":[31,60,68],"evaluate":[33],"the":[34,91,101],"performance":[35],"strategies":[40],"using":[41],"signals":[43,73],"generated":[44],"by":[45],"machine":[46,65],"learning":[47,66],"with":[48],"as":[51],"predictors.":[52],"To":[53],"achieve":[54],"objective,":[56],"a":[57],"two-phase":[58],"study":[59],"conducted.":[61],"During":[62],"Phase":[63,92],"1,":[64],"algorithm":[67],"utilized":[69],"generate":[71],"based":[74],"on":[75,81],"support":[76],"and":[77],"resistance":[78],"prediction.":[79],"Based":[80],"these":[82],"signals,":[83],"evaluated":[89],"in":[90],"2":[93],"find":[95],"an":[96],"optimal":[97],"setup":[98],"yield":[100],"highest":[102],"ROC.":[103]},"counts_by_year":[],"updated_date":"2026-05-13T06:04:23.736269","created_date":"2025-10-10T00:00:00"}