{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,6]],"date-time":"2025-10-06T05:45:03Z","timestamp":1759729503321,"version":"3.41.2"},"reference-count":21,"publisher":"Emerald","issue":"5","license":[{"start":{"date-parts":[[2010,6,15]],"date-time":"2010-06-15T00:00:00Z","timestamp":1276560000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2010,6,15]]},"abstract":"<jats:sec><jats:title content-type=\"abstract-heading\">Purpose<\/jats:title><jats:p>The purpose of this paper is to deal with the different phases of volatility behavior and the dependence of the variability of the time series on its own past, models allowing for heteroscedasticity like autoregressive conditional heteroscedasticity (ARCH), generalized autoregressive conditional heteroscedasticity (GARCH), or regime\u2010switching models have been suggested by reserachers. Both types of models are widely used in practice.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Design\/methodology\/approach<\/jats:title><jats:p>Both regime\u2010switching models and GARCH are used in this paper to model and explain the behavior of crude oil prices in order to forecast their volatility. In regime\u2010switching models, the oil return volatility has a dynamic process whose mean is subject to shifts, which is governed by a two\u2010state first\u2010order Markov process.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Findings<\/jats:title><jats:p>The GARCH models are found to be very useful in modeling a unique stochastic process with conditional variance; regime\u2010switching models have the advantage of dividing the observed stochastic behavior of a time series into several separate phases with different underlying stochastic processes.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Originality\/value<\/jats:title><jats:p>The regime\u2010switching models show similar goodness\u2010of\u2010fit result to GARCH modeling, while has the advantage of capturing major events affecting the oil market. Daily data of crude oil prices are used from NYMEX Crude Oil market for the period 13 February 2006 up to 21 July 2009.<\/jats:p><\/jats:sec>","DOI":"10.1108\/03684921011043233","type":"journal-article","created":{"date-parts":[[2010,7,3]],"date-time":"2010-07-03T07:12:13Z","timestamp":1278141133000},"page":"750-769","source":"Crossref","is-referenced-by-count":8,"title":["Risk modeling in crude oil market: a comparison of Markov switching and GARCH models"],"prefix":"10.1108","volume":"39","author":[{"given":"Cuicui","family":"Luo","sequence":"first","affiliation":[]},{"given":"Luis A.","family":"Seco","sequence":"additional","affiliation":[]},{"given":"Haofei","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Desheng","family":"Dash Wu","sequence":"additional","affiliation":[]}],"member":"140","reference":[{"key":"key2022022020264586700_b1","doi-asserted-by":"crossref","unstructured":"Agnolucci, P. 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