{"title":"Smart Beta 交易所交易基金的溢出效应和杠杆效应:来自印度的证据","authors":"C. Vijaya, M. Thenmozhi","doi":"10.1007/s40622-024-00376-1","DOIUrl":null,"url":null,"abstract":"<p>This study is unique in examining the spillover and leverage effect of Smart Beta Exchange Traded Funds (SB ETFs) and their underlying indices and Cap-Weighted (CW) indices. We find unidirectional return spillover from most SB ETFs to CW indices and bidirectional return spillover between SB ETFs and SB indices using VAR/VECM model. Besides, we find that information is transmitted faster from SB ETFs to the indices than from indices to SB ETFs. Interestingly, we observe that innovations in SB ETFs explain 97% of variance in SB indices and 81% of variance in CW indices. Hasbrouck’s information share of SB ETFs is highest (88%) followed by CW indices (5.6%). ARIMA-GARCH model shows that bidirectional volatility spillover exists between SB ETFs and the indices. ARIMA-EGARCH model provides evidence of leverage effect in SB ETFs, highlighting that volatility increases more after negative shocks than after positive shocks. Our study provides evidence of greater information transmission from SB ETFs to SB indices and to CW indices.</p>","PeriodicalId":43923,"journal":{"name":"Decision","volume":"9 1","pages":""},"PeriodicalIF":1.5000,"publicationDate":"2024-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Spillover and leverage effect in Smart Beta Exchange Traded Funds: Evidence from India\",\"authors\":\"C. Vijaya, M. Thenmozhi\",\"doi\":\"10.1007/s40622-024-00376-1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>This study is unique in examining the spillover and leverage effect of Smart Beta Exchange Traded Funds (SB ETFs) and their underlying indices and Cap-Weighted (CW) indices. We find unidirectional return spillover from most SB ETFs to CW indices and bidirectional return spillover between SB ETFs and SB indices using VAR/VECM model. Besides, we find that information is transmitted faster from SB ETFs to the indices than from indices to SB ETFs. Interestingly, we observe that innovations in SB ETFs explain 97% of variance in SB indices and 81% of variance in CW indices. Hasbrouck’s information share of SB ETFs is highest (88%) followed by CW indices (5.6%). ARIMA-GARCH model shows that bidirectional volatility spillover exists between SB ETFs and the indices. ARIMA-EGARCH model provides evidence of leverage effect in SB ETFs, highlighting that volatility increases more after negative shocks than after positive shocks. Our study provides evidence of greater information transmission from SB ETFs to SB indices and to CW indices.</p>\",\"PeriodicalId\":43923,\"journal\":{\"name\":\"Decision\",\"volume\":\"9 1\",\"pages\":\"\"},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2024-03-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Decision\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1007/s40622-024-00376-1\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"MANAGEMENT\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Decision","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s40622-024-00376-1","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MANAGEMENT","Score":null,"Total":0}
Spillover and leverage effect in Smart Beta Exchange Traded Funds: Evidence from India
This study is unique in examining the spillover and leverage effect of Smart Beta Exchange Traded Funds (SB ETFs) and their underlying indices and Cap-Weighted (CW) indices. We find unidirectional return spillover from most SB ETFs to CW indices and bidirectional return spillover between SB ETFs and SB indices using VAR/VECM model. Besides, we find that information is transmitted faster from SB ETFs to the indices than from indices to SB ETFs. Interestingly, we observe that innovations in SB ETFs explain 97% of variance in SB indices and 81% of variance in CW indices. Hasbrouck’s information share of SB ETFs is highest (88%) followed by CW indices (5.6%). ARIMA-GARCH model shows that bidirectional volatility spillover exists between SB ETFs and the indices. ARIMA-EGARCH model provides evidence of leverage effect in SB ETFs, highlighting that volatility increases more after negative shocks than after positive shocks. Our study provides evidence of greater information transmission from SB ETFs to SB indices and to CW indices.
期刊介绍:
The aim of the Journal, Decision, is to publish qualitative, quantitative, survey-based, simulation-based research articles at the national and sub-national levels. While there is no stated regional focus of the journal, we are more interested in examining if and how individuals, firms and governments in emerging economies may make decisions differently. Published for the management scholars, business executives and managers, the Journal aims to advance the management research by publishing empirically and theoretically grounded articles in management decision making process. The Editors aim to provide an efficient and high-quality review process to the authors.
The Journal accepts submissions in several formats such as original research papers, case studies, review articles and book reviews (book reviews are only by invitation).
The Journal welcomes research-based, original and insightful articles on organizational, individual, socio-economic-political, environmental decision making with relevance to theory and practice of business. It also focusses on the managerial decision-making challenges in private, public, private-public partnership and non-profit organizations. The Journal also encourages case studies that provide a rich description of the business or societal contexts in managerial decision-making process including areas – but not limited to – conflict over natural resources, product innovation and copyright laws, legislative or policy change, socio-technical embedding of financial markets, particularly in developing economy, an ethnographic understanding of relations at a workplace, or social network in marketing management, etc.
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