{"title":"英国股市与中东和北非股市的关系:小波变换和MS-VECM模型","authors":"Amel Abdoullah Ahmed Dghais, M. Ismail","doi":"10.1109/ISTMET.2015.7359048","DOIUrl":null,"url":null,"abstract":"This study explores a newly developed technique; combining wavelet filtering and Markov-Switching Vector Error Correction model (MS-VECM), to investigate the dynamic relationship among financial time series. Wavelet filter has been used to annihilate noise data in monthly data set of the UK stock market and four stock markets of Middle East and North Africa (MENA) region namely, Egypt, Morocco, Saudi Arabia, and Istanbul using the stock prices data from May1, 2001 to December 30, 2011. The series generated by the discrete wavelet transform is then analyzed to determine the long-term and short-term relationships between the stock markets by using a cointegration test and a MS-VECM. The comparison between the proposed and traditional models demonstrates that the former dominates the latter in performance and fitting the financial stock market series. The cointegration test affirms the existence of long-term relationship between the studied series. The proposed model also shows the existence of a short-term relationship between stock market in UK and all other stock markets except that of Saudi Arabia. In additional, the DWTMS-VECM manages to capture a satisfactory timing of the crises period that had affected those stock markets and provides positive information on the relationships among these stock markets.","PeriodicalId":302732,"journal":{"name":"2015 International Symposium on Technology Management and Emerging Technologies (ISTMET)","volume":"424 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Relationship between stock market of UK and MENA: Wavelet transform and MS-VECM model\",\"authors\":\"Amel Abdoullah Ahmed Dghais, M. Ismail\",\"doi\":\"10.1109/ISTMET.2015.7359048\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study explores a newly developed technique; combining wavelet filtering and Markov-Switching Vector Error Correction model (MS-VECM), to investigate the dynamic relationship among financial time series. Wavelet filter has been used to annihilate noise data in monthly data set of the UK stock market and four stock markets of Middle East and North Africa (MENA) region namely, Egypt, Morocco, Saudi Arabia, and Istanbul using the stock prices data from May1, 2001 to December 30, 2011. The series generated by the discrete wavelet transform is then analyzed to determine the long-term and short-term relationships between the stock markets by using a cointegration test and a MS-VECM. The comparison between the proposed and traditional models demonstrates that the former dominates the latter in performance and fitting the financial stock market series. The cointegration test affirms the existence of long-term relationship between the studied series. The proposed model also shows the existence of a short-term relationship between stock market in UK and all other stock markets except that of Saudi Arabia. In additional, the DWTMS-VECM manages to capture a satisfactory timing of the crises period that had affected those stock markets and provides positive information on the relationships among these stock markets.\",\"PeriodicalId\":302732,\"journal\":{\"name\":\"2015 International Symposium on Technology Management and Emerging Technologies (ISTMET)\",\"volume\":\"424 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-12-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 International Symposium on Technology Management and Emerging Technologies (ISTMET)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISTMET.2015.7359048\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Symposium on Technology Management and Emerging Technologies (ISTMET)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISTMET.2015.7359048","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Relationship between stock market of UK and MENA: Wavelet transform and MS-VECM model
This study explores a newly developed technique; combining wavelet filtering and Markov-Switching Vector Error Correction model (MS-VECM), to investigate the dynamic relationship among financial time series. Wavelet filter has been used to annihilate noise data in monthly data set of the UK stock market and four stock markets of Middle East and North Africa (MENA) region namely, Egypt, Morocco, Saudi Arabia, and Istanbul using the stock prices data from May1, 2001 to December 30, 2011. The series generated by the discrete wavelet transform is then analyzed to determine the long-term and short-term relationships between the stock markets by using a cointegration test and a MS-VECM. The comparison between the proposed and traditional models demonstrates that the former dominates the latter in performance and fitting the financial stock market series. The cointegration test affirms the existence of long-term relationship between the studied series. The proposed model also shows the existence of a short-term relationship between stock market in UK and all other stock markets except that of Saudi Arabia. In additional, the DWTMS-VECM manages to capture a satisfactory timing of the crises period that had affected those stock markets and provides positive information on the relationships among these stock markets.