{"title":"金砖国家股票市场溢出效应分析:Copula和DCC- MGARCH模型的应用","authors":"Naliniprava Tripathy, Pradiptarathi Panda","doi":"10.1142/s0219091523500236","DOIUrl":null,"url":null,"abstract":"This study examines the nonlinear dependence and tail dependence of BRICS countries’ stock markets and the contagion effect among Brazil, Russia, India, China, and South Africa (BRICS) countries’ daily stock markets using the COPULA model from January 2000 to February 2019. The study employs the DCC-MGARCH model and Diebold and Yilmaz volatility spillover model to assess the interdependence dynamics across BRICS countries’ stock markets. The copula results suggest that the BRICS country’s stock markets are independent of each other. The conditional correlation between BRICS is negative and statistically significant, suggesting that the negative relationship among BRICS is an important signal for international investors to diversify among these countries and get the economic value of their investment. Further, Brazil, China, and South Africa are the net volatility transmitter, at the same time India and Russia are the net volatility receiver during the study period. The study proposes that policymaker of BRICS needs to interchange views and mutually map policies to appeal to global investment more.","PeriodicalId":45653,"journal":{"name":"Review of Pacific Basin Financial Markets and Policies","volume":"26 4","pages":"0"},"PeriodicalIF":0.3000,"publicationDate":"2023-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Analyzing Spillover effects among BRICS Stock Markets: Application of Copula and DCC- MGARCH model\",\"authors\":\"Naliniprava Tripathy, Pradiptarathi Panda\",\"doi\":\"10.1142/s0219091523500236\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study examines the nonlinear dependence and tail dependence of BRICS countries’ stock markets and the contagion effect among Brazil, Russia, India, China, and South Africa (BRICS) countries’ daily stock markets using the COPULA model from January 2000 to February 2019. The study employs the DCC-MGARCH model and Diebold and Yilmaz volatility spillover model to assess the interdependence dynamics across BRICS countries’ stock markets. The copula results suggest that the BRICS country’s stock markets are independent of each other. The conditional correlation between BRICS is negative and statistically significant, suggesting that the negative relationship among BRICS is an important signal for international investors to diversify among these countries and get the economic value of their investment. Further, Brazil, China, and South Africa are the net volatility transmitter, at the same time India and Russia are the net volatility receiver during the study period. The study proposes that policymaker of BRICS needs to interchange views and mutually map policies to appeal to global investment more.\",\"PeriodicalId\":45653,\"journal\":{\"name\":\"Review of Pacific Basin Financial Markets and Policies\",\"volume\":\"26 4\",\"pages\":\"0\"},\"PeriodicalIF\":0.3000,\"publicationDate\":\"2023-11-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Review of Pacific Basin Financial Markets and Policies\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1142/s0219091523500236\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"BUSINESS, FINANCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Review of Pacific Basin Financial Markets and Policies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1142/s0219091523500236","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
Analyzing Spillover effects among BRICS Stock Markets: Application of Copula and DCC- MGARCH model
This study examines the nonlinear dependence and tail dependence of BRICS countries’ stock markets and the contagion effect among Brazil, Russia, India, China, and South Africa (BRICS) countries’ daily stock markets using the COPULA model from January 2000 to February 2019. The study employs the DCC-MGARCH model and Diebold and Yilmaz volatility spillover model to assess the interdependence dynamics across BRICS countries’ stock markets. The copula results suggest that the BRICS country’s stock markets are independent of each other. The conditional correlation between BRICS is negative and statistically significant, suggesting that the negative relationship among BRICS is an important signal for international investors to diversify among these countries and get the economic value of their investment. Further, Brazil, China, and South Africa are the net volatility transmitter, at the same time India and Russia are the net volatility receiver during the study period. The study proposes that policymaker of BRICS needs to interchange views and mutually map policies to appeal to global investment more.
期刊介绍:
This journal concentrates on global interdisciplinary research in finance, economics and accounting. The major topics include: 1. Business, economic and financial relations among the Pacific rim countries. 2. Financial markets and industries. 3. Options and futures markets of the United States and other Pacific rim countries. 4. International accounting issues related to U.S. companies investing in Pacific rim countries. 5. The issue of and strategy for developing Tokyo, Taipei, Shanghai, Sydney, Seoul, Hong Kong, Singapore, Kuala Lumpur, Bangkok, Jakarta, and Manila as international or regional financial centers. 6. Global monetary and foreign exchange policy, and 7. Other high quality interdisciplinary research in global accounting, business, economics and finance.