{"id":"https://openalex.org/W3202667440","doi":"https://doi.org/10.1016/j.jjimei.2021.100039","title":"Introspecting predictability of market fear in Indian context during COVID-19 pandemic: An integrated approach of applied predictive modelling and explainable AI","display_name":"Introspecting predictability of market fear in Indian context during COVID-19 pandemic: An integrated approach of applied predictive modelling and explainable AI","publication_year":2021,"publication_date":"2021-09-27","ids":{"openalex":"https://openalex.org/W3202667440","doi":"https://doi.org/10.1016/j.jjimei.2021.100039","mag":"3202667440"},"language":"en","primary_location":{"id":"doi:10.1016/j.jjimei.2021.100039","doi":"https://doi.org/10.1016/j.jjimei.2021.100039","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.jjimei.2021.100039","pdf_url":"https://www.sciencedirect.com/science/article/pii/S266709682100032X/pdf","source":{"id":"https://openalex.org/S4210226089","display_name":"International Journal of Information Management Data Insights","issn_l":"2667-0968","issn":["2667-0968"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","jufo-1","norway-1","poland-20"],"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Information Management Data Insights","raw_type":"journal-article"},"volume":null,"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.sciencedirect.com/science/article/pii/S266709682100032X/pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5030400756","display_name":"Indranil Ghosh","orcid":"https://orcid.org/0000-0001-7064-4774","observed_orcids":["https://orcid.org/0000-0001-7064-4774"]},"institutions":[{"id":"https://openalex.org/I166533956","display_name":"Institute of Management Technology","ror":"https://ror.org/05k0kb696","country_code":"IN","type":"education","lineage":["https://openalex.org/I166533956"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Indranil Ghosh","raw_affiliation_strings":["IT & Analytics Area, Institute of Management Technology, Hyderabad, Telangana, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IT & Analytics Area, Institute of Management Technology, Hyderabad, Telangana, India","institution_ids":["https://openalex.org/I166533956"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5089278108","display_name":"Manas Kumar Sanyal","orcid":"https://orcid.org/0000-0002-5760-8207","observed_orcids":["https://orcid.org/0000-0002-5760-8207"]},"institutions":[{"id":"https://openalex.org/I77501641","display_name":"University of Kalyani","ror":"https://ror.org/03v783k16","country_code":"IN","type":"education","lineage":["https://openalex.org/I77501641"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Manas K. Sanyal","raw_affiliation_strings":["University of Kalyani, Kalyani, West Bengal, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Kalyani, Kalyani, West Bengal, India","institution_ids":["https://openalex.org/I77501641"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5030400756"],"corresponding_institution_ids":["https://openalex.org/I166533956"],"apc_list":{"value":1500,"currency":"USD","value_usd":1500},"apc_paid":{"value":1500,"currency":"USD","value_usd":1500},"fwci":4.8607,"has_fulltext":true,"cited_by_count":39,"citation_normalized_percentile":{"value":0.95473035,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":93,"max":99},"biblio":{"volume":"1","issue":"2","first_page":"100039","last_page":"100039"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9750999808311462,"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":0.9750999808311462,"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/T10282","display_name":"Financial Risk and Volatility Modeling","score":0.015699999406933784,"subfield":{"id":"https://openalex.org/subfields/2003","display_name":"Finance"},"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/T11711","display_name":"COVID-19 Pandemic Impacts","score":0.006500000134110451,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/market-fear","display_name":"market fear","score":0.921999990940094},{"id":"https://openalex.org/keywords/volatility-predictability","display_name":"volatility predictability","score":0.6919999718666077},{"id":"https://openalex.org/keywords/covid-19","display_name":"COVID-19 pandemic","score":0.8740000128746033},{"id":"https://openalex.org/keywords/india-vix","display_name":"India VIX","score":0.8920000195503235},{"id":"https://openalex.org/keywords/implied-volatility","display_name":"implied volatility","score":0.9819999933242798},{"id":"https://openalex.org/keywords/historical-volatility","display_name":"historical volatility","score":0.8579999804496765},{"id":"https://openalex.org/keywords/google-search-volume-index","display_name":"Google Search Volume Index","score":0.8379999995231628},{"id":"https://openalex.org/keywords/macroeconomic-indicators","display_name":"macroeconomic indicators","score":0.9089999794960022},{"id":"https://openalex.org/keywords/technical-indicators","display_name":"technical indicators","score":0.9620000123977661},{"id":"https://openalex.org/keywords/boruta-feature-selection","display_name":"Boruta feature selection","score":0.8610000014305115},{"id":"https://openalex.org/keywords/explainable-ai","display_name":"explainable AI","score":0.8059999942779541},{"id":"https://openalex.org/keywords/gradient-boosting","display_name":"gradient boosting","score":0.8180000185966492},{"id":"https://openalex.org/keywords/lstm","display_name":"LSTM","score":0.6230000257492065},{"id":"https://openalex.org/keywords/deep-neural-network","display_name":"deep neural network","score":0.6340000033378601},{"id":"https://openalex.org/keywords/indian-stock-market","display_name":"Indian stock market","score":0.6349999904632568}],"concepts":[{"id":"https://openalex.org/C197640229","wikidata":"https://www.wikidata.org/wiki/Q2534066","display_name":"Predictability","level":2,"score":0.8567909002304077},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5287437438964844},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.5179740190505981},{"id":"https://openalex.org/C91602232","wikidata":"https://www.wikidata.org/wiki/Q756115","display_name":"Volatility (finance)","level":2,"score":0.5154305696487427},{"id":"https://openalex.org/C199728807","wikidata":"https://www.wikidata.org/wiki/Q2578557","display_name":"Equity (law)","level":2,"score":0.5006425380706787},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4681302309036255},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.4401966333389282},{"id":"https://openalex.org/C24189920","wikidata":"https://www.wikidata.org/wiki/Q1660345","display_name":"Implied volatility","level":3,"score":0.431481271982193},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40811413526535034},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.3920831084251404},{"id":"https://openalex.org/C106159729","wikidata":"https://www.wikidata.org/wiki/Q2294553","display_name":"Financial economics","level":1,"score":0.38003361225128174},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.16991722583770752},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16577255725860596},{"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":[],"locations_count":4,"locations":[{"id":"doi:10.1016/j.jjimei.2021.100039","doi":"https://doi.org/10.1016/j.jjimei.2021.100039","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.jjimei.2021.100039","pdf_url":"https://www.sciencedirect.com/science/article/pii/S266709682100032X/pdf","source":{"id":"https://openalex.org/S4210226089","display_name":"International Journal of Information Management Data Insights","issn_l":"2667-0968","issn":["2667-0968"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","jufo-1","norway-1","poland-20"],"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Information Management Data Insights","raw_type":"journal-article"},{"id":"pmh:oai:europepmc.org:7362278","doi":null,"is_oa":true,"landing_page_url":"http://europepmc.org/pmc/articles/PMC8463332","pdf_url":null,"source":{"id":"https://openalex.org/S4306400806","display_name":"Europe PMC (PubMed Central)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1303153112","host_organization_name":"European Bioinformatics Institute","host_organization_lineage":["https://openalex.org/I1303153112"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:8463332","doi":null,"is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8463332","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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 Information Management Data Insights","raw_type":"Text"},{"id":"pmh:oai:doaj.org/article:af37017530ea4292900c7a7a06efad59","doi":null,"is_oa":true,"landing_page_url":"https://doaj.org/article/af37017530ea4292900c7a7a06efad59","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"International Journal of Information Management Data Insights, Vol 1, Iss 2, Pp 100039- (2021)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1016/j.jjimei.2021.100039","doi":"https://doi.org/10.1016/j.jjimei.2021.100039","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.jjimei.2021.100039","pdf_url":"https://www.sciencedirect.com/science/article/pii/S266709682100032X/pdf","source":{"id":"https://openalex.org/S4210226089","display_name":"International Journal of Information Management Data Insights","issn_l":"2667-0968","issn":["2667-0968"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","jufo-1","norway-1","poland-20"],"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Information Management Data Insights","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.46810001134872437,"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3202667440.pdf","grobid_xml":"https://content.openalex.org/works/W3202667440.grobid-xml"},"referenced_works_count":82,"referenced_works":["https://openalex.org/W1678356000","https://openalex.org/W1700449338","https://openalex.org/W2056132907","https://openalex.org/W2062645616","https://openalex.org/W2064675550","https://openalex.org/W2079735306","https://openalex.org/W2122585011","https://openalex.org/W2125536334","https://openalex.org/W2156665896","https://openalex.org/W2282821441","https://openalex.org/W2516809705","https://openalex.org/W2565516711","https://openalex.org/W2611849481","https://openalex.org/W2616881109","https://openalex.org/W2624385633","https://openalex.org/W2771020017","https://openalex.org/W2777209651","https://openalex.org/W2901699584","https://openalex.org/W2922854612","https://openalex.org/W2940603351","https://openalex.org/W2942100831","https://openalex.org/W2950967628","https://openalex.org/W2952160332","https://openalex.org/W2952342634","https://openalex.org/W2956962028","https://openalex.org/W2966861509","https://openalex.org/W2971818267","https://openalex.org/W2981055133","https://openalex.org/W2982342283","https://openalex.org/W2991122145","https://openalex.org/W2996564144","https://openalex.org/W2998515840","https://openalex.org/W2998736303","https://openalex.org/W3002119178","https://openalex.org/W3012083138","https://openalex.org/W3021785726","https://openalex.org/W3040674358","https://openalex.org/W3043359482","https://openalex.org/W3044177347","https://openalex.org/W3044883444","https://openalex.org/W3058775173","https://openalex.org/W3081905268","https://openalex.org/W3083811368","https://openalex.org/W3088160921","https://openalex.org/W3089147409","https://openalex.org/W3091997463","https://openalex.org/W3094730969","https://openalex.org/W3116990199","https://openalex.org/W3119962516","https://openalex.org/W3122555608","https://openalex.org/W3122758356","https://openalex.org/W3128476111","https://openalex.org/W3129310709","https://openalex.org/W3130799379","https://openalex.org/W3134207303","https://openalex.org/W3134765302","https://openalex.org/W3135241214","https://openalex.org/W3136993477","https://openalex.org/W3138927248","https://openalex.org/W3143493396","https://openalex.org/W3159066560","https://openalex.org/W3159148887","https://openalex.org/W3159252119","https://openalex.org/W3160609737","https://openalex.org/W3164166942","https://openalex.org/W3165474314","https://openalex.org/W3165537959","https://openalex.org/W3166924356","https://openalex.org/W3167211760","https://openalex.org/W3168335548","https://openalex.org/W3171454962","https://openalex.org/W3171904039","https://openalex.org/W3172100389","https://openalex.org/W3172498855","https://openalex.org/W3173302161","https://openalex.org/W3194725190","https://openalex.org/W3196626876","https://openalex.org/W3196770257","https://openalex.org/W3197841947","https://openalex.org/W3201508216","https://openalex.org/W4240230541","https://openalex.org/W6797090782"],"related_works":["https://openalex.org/W4389146835","https://openalex.org/W4375928375","https://openalex.org/W4320035644","https://openalex.org/W7127575217","https://openalex.org/W4385143714","https://openalex.org/W4401582861","https://openalex.org/W4382677582","https://openalex.org/W4377043493","https://openalex.org/W4390965899","https://openalex.org/W4399157272"],"abstract_inverted_index":{"Financial":[0],"markets":[1,38],"across":[2],"the":[3,30,104,180,214,242],"globe":[4],"have":[5,121,191,209],"seen":[6],"rapid":[7],"volatility":[8,77,101,237],"and":[9,14,39,75,87,99,113,148,199,235,246],"uncertainty":[10],"owing":[11],"to":[12,52,95,142,177,194,202,212],"scary":[13],"disruptive":[15],"impacts":[16],"of":[17,33,48,55,63,73,78,92,182,184,197,216,218,229],"COVID-19":[18,106],"pandemic.":[19],"Mayhem":[20],"wrecked":[21],"by":[22],"frequent":[23],"lockdowns,":[24],"curfews,":[25],"emergencies,":[26],"etc.":[27],"has":[28,135],"stoked":[29],"high":[31,227],"quantum":[32,181],"chaotic":[34],"movement":[35],"in":[36,41,71,138],"equity":[37,79],"resulted":[40],"perplexed":[42],"investor":[43],"behaviour.":[44],"It,":[45],"therefore,":[46],"is":[47],"paramount":[49],"practical":[50,248],"relevance":[51],"measure":[53],"predictability":[54,183],"market":[56],"fear":[57,66],"at":[58],"such":[59],"a":[60,139,195],"crucial":[61],"juncture":[62],"time.":[64],"Market":[65],"can":[67,238],"effectively":[68,245],"be":[69,239],"measured":[70],"terms":[72],"implied":[74,98],"historic":[76,100,236],"markets.":[80],"The":[81,187],"present":[82],"study":[83],"chooses":[84],"India":[85,233],"VIX":[86,234],"20-day":[88],"rolling":[89],"standard":[90],"deviation":[91],"NIFTY":[93],"returns":[94],"account":[96],"for":[97,128],"respectively":[102],"during":[103],"ongoing":[105],"timeline.":[107],"Pertinent":[108],"macroeconomic":[109],"constructs,":[110],"technical":[111],"indicators":[112],"Google":[114],"search":[115],"volume":[116],"index":[117],"on":[118,173],"meaningful":[119],"keywords":[120],"been":[122,136,192,210],"chosen":[123],"as":[124],"raw":[125],"explanatory":[126],"features":[127],"inspecting":[129],"predictability.":[130],"Boruta":[131],"feature":[132,175],"selection":[133],"methodology":[134],"used":[137,172,211],"supervised":[140],"manner":[141],"select":[143],"significant":[144],"features.":[145,220],"State-Of-The-Art":[146],"machine":[147],"deep":[149],"learning":[150],"algorithms":[151],"namely":[152],"Gradient":[153],"Boosting":[154],"(GB),":[155],"Extra":[156],"Tree":[157],"Regression":[158],"(ERT),":[159],"Deep":[160],"Neural":[161],"Network":[162,168],"(DNN),":[163],"Long":[164],"Short":[165],"Term":[166],"Memory":[167],"(LSTM)":[169],"are":[170],"then":[171],"processed":[174],"set":[176],"scrupulously":[178],"evaluate":[179],"said":[185],"assets.":[186],"integrated":[188],"predictive":[189],"frameworks":[190,208],"subjected":[193],"battery":[196],"numerical":[198],"statistical":[200],"checks":[201],"draw":[203],"inferences.":[204],"Additionally,":[205],"Explainable":[206],"AI":[207],"analyse":[213],"nature":[215],"influence":[217],"respective":[219],"Findings":[221],"indeed":[222],"suggest":[223],"that":[224],"despite":[225],"exhibiting":[226],"degree":[228],"volatile":[230],"traits,":[231],"both":[232],"predicted":[240],"utilizing":[241],"proposed":[243],"architectures":[244],"serve":[247],"actionable":[249],"insights.":[250]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":13},{"year":2021,"cited_by_count":2}],"updated_date":"2026-10-27T15:51:10.671819","created_date":"2021-10-11T00:00:00"}
