{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,12]],"date-time":"2026-03-12T14:01:48Z","timestamp":1773324108255,"version":"3.50.1"},"reference-count":29,"publisher":"World Scientific Pub Co Pte Lt","issue":"03","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Info. Tech. Dec. Mak."],"published-print":{"date-parts":[[2006,9]]},"abstract":"<jats:p> The main purpose of this study is to devise a general regression neural network (GRNN)-based currency crisis forecasting model for Southeast Asian economies based upon the disastrous 1997\u20131998 currency crisis experience. For this some typical indicators of currency exchange rates volatility are first chosen, then these indicators are input into GRNN for training, and finally the trained GRNN is used for future crisis prediction. To verify the effectiveness of the proposed currency crisis forecasting approach, four typical Southeast Asian currencies, Indonesian rupiah, Philippine peso, Singapore dollar and Thai baht, are selected. Meantime we compare its performance with those of other forecasting methods to evaluate the forecasting ability of the proposed approach. Empirical results obtained reveal that the proposed currency crisis forecasting model has a surprisingly high degree of accuracy in judging the currency crisis level of each country in specified time period, implying that our proposed approach can be used as a feasible currency crisis early-warning system to predict currency crisis level for other countries around the world. <\/jats:p>","DOI":"10.1142\/s0219622006002040","type":"journal-article","created":{"date-parts":[[2006,10,2]],"date-time":"2006-10-02T07:02:56Z","timestamp":1159772576000},"page":"437-454","source":"Crossref","is-referenced-by-count":19,"title":["CURRENCY CRISIS FORECASTING WITH GENERAL REGRESSION NEURAL NETWORKS"],"prefix":"10.1142","volume":"05","author":[{"given":"LEAN","family":"YU","sequence":"first","affiliation":[{"name":"Institute of Systems Science, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100080, China"},{"name":"Department of Management Sciences, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong, China"}]},{"given":"KIN KEUNG","family":"LAI","sequence":"additional","affiliation":[{"name":"Department of Management Sciences, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong, China"},{"name":"College of Business Administration, Hunan University, Changsha 410082, China"}]},{"given":"SHOU-YANG","family":"WANG","sequence":"additional","affiliation":[{"name":"Institute of Systems Science, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100080, China"},{"name":"Graduate School of Systems and Information Engineering, University of Tsukuba, Tsukuba, Ibaraki 305-8573, Japan"}]}],"member":"219","published-online":{"date-parts":[[2011,11,20]]},"reference":[{"key":"rf1","doi-asserted-by":"publisher","DOI":"10.1002\/(SICI)1099-1158(199901)4:1<1::AID-IJFE89>3.0.CO;2-3"},{"key":"rf2","doi-asserted-by":"publisher","DOI":"10.2307\/3867328"},{"key":"rf3","doi-asserted-by":"publisher","DOI":"10.1016\/S0927-5398(02)00068-3"},{"key":"rf4","series-title":"Economic papers 46","volume-title":"The seven deadly sins \u2014 presumptive indicators of vulnerability to financial crises in emerging economies: Origin and policy options","author":"Goldstein M.","year":"1996"},{"key":"rf5","doi-asserted-by":"publisher","DOI":"10.1016\/S1049-0078(02)00243-9"},{"key":"rf7","doi-asserted-by":"publisher","DOI":"10.1016\/S0261-5606(99)00024-8"},{"key":"rf8","doi-asserted-by":"publisher","DOI":"10.3386\/w5576"},{"key":"rf10","doi-asserted-by":"publisher","DOI":"10.1016\/S0022-1996(96)01441-9"},{"key":"rf11","volume-title":"Assessing financial vulnerability: An early warning system for emerging markets","author":"Goldstein M.","year":"2000"},{"key":"rf12","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2003.12.009"},{"key":"rf13","doi-asserted-by":"publisher","DOI":"10.1086\/261366"},{"key":"rf14","first-page":"111","volume":"17","author":"Cumby R.","journal-title":"Journal of International Economics"},{"key":"rf15","doi-asserted-by":"publisher","DOI":"10.1016\/S0022-1996(99)00007-0"},{"key":"rf16","doi-asserted-by":"publisher","DOI":"10.1016\/S0022-1996(96)01439-0"},{"key":"rf17","doi-asserted-by":"publisher","DOI":"10.1257\/aer.89.3.473"},{"key":"rf19","first-page":"249","volume":"21","author":"Eichengreen B.","journal-title":"Economic Policy"},{"key":"rf20","doi-asserted-by":"publisher","DOI":"10.1109\/72.97934"},{"key":"rf21","doi-asserted-by":"publisher","DOI":"10.1016\/S0305-0548(99)00144-6"},{"key":"rf22","doi-asserted-by":"publisher","DOI":"10.1007\/BF02869528"},{"key":"rf23","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"crossref","first-page":"790","DOI":"10.1007\/11758501_106","volume":"3991","author":"Lai K. 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