{"id":"https://openalex.org/W2528930360","doi":"https://doi.org/10.1002/for.2443","title":"Realized Volatility Forecasting of Agricultural Commodity Futures Using Long Memory and Regime Switching","display_name":"Realized Volatility Forecasting of Agricultural Commodity Futures Using Long Memory and Regime Switching","publication_year":2016,"publication_date":"2016-09-27","ids":{"openalex":"https://openalex.org/W2528930360","doi":"https://doi.org/10.1002/for.2443","mag":"2528930360"},"language":"en","primary_location":{"id":"doi:10.1002/for.2443","doi":"https://doi.org/10.1002/for.2443","is_oa":false,"landing_page_url":"https://doi.org/10.1002/for.2443","pdf_url":null,"source":{"id":"https://openalex.org/S122161766","display_name":"Journal of Forecasting","issn_l":"0277-6693","issn":["0277-6693","1099-131X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["abdc-a","anvur-class-a","anvur-scientific","cwts-core","fnege-3","jufo-1","ki-jl-1","norway-1","poland-70","russia-white-list-2","vabb-shw"],"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Forecasting","raw_type":"journal-article"},"volume":null,"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/A5111581230","display_name":"Fengping Tian","orcid":"https://orcid.org/0000-0002-8303-5828","observed_orcids":["https://orcid.org/0000-0002-8303-5828"]},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fengping Tian","raw_affiliation_strings":["International School of Business and Finance, Sun Yat-sen University, Guangzhou, Guangdong, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"International School of Business and Finance, Sun Yat-sen University, Guangzhou, Guangdong, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102022823","display_name":"Ke Yang","orcid":"https://orcid.org/0000-0002-3065-5062","observed_orcids":["https://orcid.org/0000-0002-3065-5062"]},"institutions":[{"id":"https://openalex.org/I101479585","display_name":"South China Agricultural University","ror":"https://ror.org/05v9jqt67","country_code":"CN","type":"education","lineage":["https://openalex.org/I101479585"]},{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ke Yang","raw_affiliation_strings":["College of Economics and Management, South China Agricultural University, Guangzhou, Guangdong, China","School of Economics and Commerce, South China University of Technology, Guangzhou, Guangdong, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Economics and Management, South China Agricultural University, Guangzhou, Guangdong, China","institution_ids":["https://openalex.org/I101479585"]},{"raw_affiliation_string":"School of Economics and Commerce, South China University of Technology, Guangzhou, Guangdong, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043657586","display_name":"Langnan Chen","orcid":"https://orcid.org/0000-0002-9317-4047","observed_orcids":["https://orcid.org/0000-0002-9317-4047"]},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Langnan Chen","raw_affiliation_strings":["Lingnan College, Sun Yat-sen University, Guangzhou, Guangdong, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Lingnan College, Sun Yat-sen University, Guangzhou, Guangdong, China","institution_ids":["https://openalex.org/I157773358"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5043657586"],"corresponding_institution_ids":["https://openalex.org/I157773358"],"apc_list":{"value":3400,"currency":"USD","value_usd":3400},"apc_paid":null,"fwci":1.1134,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":{"value":0.84156725,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":98},"biblio":{"volume":"36","issue":"4","first_page":"421","last_page":"430"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10282","display_name":"Financial Risk and Volatility Modeling","score":0.9980000257492065,"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"}},"topics":[{"id":"https://openalex.org/T10282","display_name":"Financial Risk and Volatility Modeling","score":0.9980000257492065,"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/T11059","display_name":"Market Dynamics and Volatility","score":0.0003000000142492354,"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":0.0003000000142492354,"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/realized-volatility","display_name":"realized volatility","score":0.9829999804496765},{"id":"https://openalex.org/keywords/agricultural-futures","display_name":"agricultural futures","score":0.9480000138282776},{"id":"https://openalex.org/keywords/long-range-dependence","display_name":"long-range dependence","score":0.9660000205039978},{"id":"https://openalex.org/keywords/regime-switching-models","display_name":"regime switching","score":0.9959999918937683},{"id":"https://openalex.org/keywords/volatility-forecasting","display_name":"volatility forecasting","score":0.8479999899864197},{"id":"https://openalex.org/keywords/high-frequency-data","display_name":"high-frequency data","score":0.9110000133514404},{"id":"https://openalex.org/keywords/chinese-futures-market","display_name":"Chinese futures market","score":0.7369999885559082},{"id":"https://openalex.org/keywords/out-of-sample-forecast-accuracy","display_name":"out-of-sample forecast accuracy","score":0.703000009059906}],"concepts":[{"id":"https://openalex.org/C91602232","wikidata":"https://www.wikidata.org/wiki/Q756115","display_name":"Volatility (finance)","level":2,"score":0.858142614364624},{"id":"https://openalex.org/C1297061","wikidata":"https://www.wikidata.org/wiki/Q4826945","display_name":"Autoregressive fractionally integrated moving average","level":4,"score":0.7810474634170532},{"id":"https://openalex.org/C60092789","wikidata":"https://www.wikidata.org/wiki/Q7301291","display_name":"Realized variance","level":3,"score":0.7600599527359009},{"id":"https://openalex.org/C106306483","wikidata":"https://www.wikidata.org/wiki/Q183984","display_name":"Futures contract","level":2,"score":0.7475641369819641},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.6945710182189941},{"id":"https://openalex.org/C117996083","wikidata":"https://www.wikidata.org/wiki/Q5473296","display_name":"Forward volatility","level":4,"score":0.6310311555862427},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.6103629469871521},{"id":"https://openalex.org/C192620184","wikidata":"https://www.wikidata.org/wiki/Q7940002","display_name":"Volatility swap","level":4,"score":0.5910155177116394},{"id":"https://openalex.org/C24189920","wikidata":"https://www.wikidata.org/wiki/Q1660345","display_name":"Implied volatility","level":3,"score":0.5356525778770447},{"id":"https://openalex.org/C85393063","wikidata":"https://www.wikidata.org/wiki/Q596307","display_name":"Stochastic volatility","level":3,"score":0.5243818163871765},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.4948548674583435},{"id":"https://openalex.org/C13290067","wikidata":"https://www.wikidata.org/wiki/Q915788","display_name":"Volatility smile","level":3,"score":0.4794953465461731},{"id":"https://openalex.org/C2986394398","wikidata":"https://www.wikidata.org/wiki/Q1805477","display_name":"Long memory","level":3,"score":0.4699649512767792},{"id":"https://openalex.org/C44731940","wikidata":"https://www.wikidata.org/wiki/Q7940001","display_name":"Volatility risk premium","level":4,"score":0.44815289974212646},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.4172506332397461},{"id":"https://openalex.org/C106159729","wikidata":"https://www.wikidata.org/wiki/Q2294553","display_name":"Financial economics","level":1,"score":0.33527135848999023},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1641356348991394},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.12511494755744934}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1002/for.2443","doi":"https://doi.org/10.1002/for.2443","is_oa":false,"landing_page_url":"https://doi.org/10.1002/for.2443","pdf_url":null,"source":{"id":"https://openalex.org/S122161766","display_name":"Journal of Forecasting","issn_l":"0277-6693","issn":["0277-6693","1099-131X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["abdc-a","anvur-class-a","anvur-scientific","cwts-core","fnege-3","jufo-1","ki-jl-1","norway-1","poland-70","russia-white-list-2","vabb-shw"],"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Forecasting","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6735000014305115,"id":"https://metadata.un.org/sdg/2","display_name":"Zero hunger"}],"study_designs":[],"awards":[{"id":"https://openalex.org/G5806492353","display_name":null,"funder_award_id":"201408440382","funder_id":"https://openalex.org/F4320322725","funder_display_name":"China Scholarship Council"},{"id":"https://openalex.org/G5823779949","display_name":null,"funder_award_id":"201406385054","funder_id":"https://openalex.org/F4320322725","funder_display_name":"China Scholarship Council"},{"id":"https://openalex.org/G6383533268","display_name":null,"funder_award_id":"71203067","funder_id":"https://openalex.org/F4320322868","funder_display_name":"Natural Science Foundation of Inner Mongolia"}],"funders":[{"id":"https://openalex.org/F4320322725","display_name":"China Scholarship Council","ror":"https://ror.org/04atp4p48"},{"id":"https://openalex.org/F4320322868","display_name":"Natural Science Foundation of Inner Mongolia","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W68212274","https://openalex.org/W1512538456","https://openalex.org/W1585628947","https://openalex.org/W1967260842","https://openalex.org/W1967985636","https://openalex.org/W1969607834","https://openalex.org/W1972477706","https://openalex.org/W1983818306","https://openalex.org/W2008361621","https://openalex.org/W2014452709","https://openalex.org/W2022314986","https://openalex.org/W2033780024","https://openalex.org/W2035586499","https://openalex.org/W2041492724","https://openalex.org/W2042536367","https://openalex.org/W2054038204","https://openalex.org/W2057936711","https://openalex.org/W2060213060","https://openalex.org/W2068138154","https://openalex.org/W2073445562","https://openalex.org/W2074812030","https://openalex.org/W2093074410","https://openalex.org/W2119301009","https://openalex.org/W2132090039","https://openalex.org/W2133709764","https://openalex.org/W2134356662","https://openalex.org/W2135034406","https://openalex.org/W2140585983","https://openalex.org/W2146134639","https://openalex.org/W2146270957","https://openalex.org/W2151526656","https://openalex.org/W2154008832","https://openalex.org/W2165008828","https://openalex.org/W2168109836","https://openalex.org/W2184797284","https://openalex.org/W3121364726","https://openalex.org/W3121726954","https://openalex.org/W3123604414","https://openalex.org/W3123723806","https://openalex.org/W3124975989","https://openalex.org/W3125360608","https://openalex.org/W3126049498","https://openalex.org/W4238816640"],"related_works":["https://openalex.org/W4392160353","https://openalex.org/W2991122145","https://openalex.org/W2748431603","https://openalex.org/W7113104097","https://openalex.org/W1536108390","https://openalex.org/W290091234","https://openalex.org/W2588069723","https://openalex.org/W4410314708","https://openalex.org/W2253549106","https://openalex.org/W4221073957"],"abstract_inverted_index":{"Abstract":[0],"We":[1],"investigate":[2],"the":[3,7,17,26,55,60,74,86,89,107,111,114,118,123,131,141,150,157,168],"dynamic":[4],"properties":[5,39],"of":[6,10,88,92,101,143,152],"realized":[8,27,56,90,153,164],"volatility":[9,28,57,91,136,154,165],"five":[11],"agricultural":[12,93],"commodity":[13,94],"futures":[14,95],"by":[15,58,98],"employing":[16],"high\u2010frequency":[18],"data":[19],"from":[20],"Chinese":[21],"markets":[22],"and":[23,33,68,110,117,156],"find":[24],"that":[25,85,129,140],"exhibits":[29],"both":[30],"long":[31,61,102,144],"memory":[32,62,145],"regime":[34,65,109,125],"switching.":[35],"To":[36],"capture":[37],"these":[38],"simultaneously,":[40],"we":[41],"utilize":[42],"a":[43,161],"Markov":[44],"switching":[45,66,147],"autoregressive":[46],"fractionally":[47],"integrated":[48],"moving":[49],"average":[50],"(MS\u2010ARFIMA)":[51],"model":[52,159],"to":[53,120,167],"forecast":[54,71,137,166],"combining":[59],"process":[63],"with":[64,73,106,113,146],"component,":[67],"compare":[69],"its":[70],"performances":[72],"competing":[75,169],"models":[76],"at":[77],"various":[78],"horizons.":[79],"The":[80,134],"full\u2010sample":[81],"estimation":[82],"results":[83,138],"show":[84,139],"dynamics":[87],"are":[96],"characterized":[97],"two":[99],"levels":[100],"memory:":[103],"one":[104],"associated":[105],"low\u2010volatility":[108,124],"other":[112],"high\u2010volatility":[115,132],"regime,":[116],"probability":[119],"stay":[121],"in":[122,130],"is":[126],"higher":[127],"than":[128],"regime.":[133],"out\u2010of\u2010sample":[135,163],"combination":[142],"regimes":[148],"improves":[149],"performance":[151],"forecast,":[155],"proposed":[158],"represents":[160],"superior":[162],"models.":[170],"Copyright":[171],"\u00a9":[172],"2016":[173],"John":[174],"Wiley":[175],"&":[176],"Sons,":[177],"Ltd.":[178]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":4},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":2}],"updated_date":"2026-10-30T12:39:25.321706","created_date":"2016-10-14T00:00:00"}
