{"title":"Index futures mispricing: a multi-regime approach to the NIFTY 50 Index futures","authors":"Kithsiri Samarakoon, Rudra P. Pradhan","doi":"10.1108/mf-03-2024-0166","DOIUrl":null,"url":null,"abstract":"<h3>Purpose</h3>\n<p>This study investigates the mispricing dynamics of NIFTY 50 Index futures, drawing upon daily data spanning from January 2008 to July 2023.</p><!--/ Abstract__block -->\n<h3>Design/methodology/approach</h3>\n<p>The study employs both a single regime analysis and a tri-regime model to understand the fluctuations in NIFTY 50 Index futures mispricing.</p><!--/ Abstract__block -->\n<h3>Findings</h3>\n<p>The study reveals a complex interplay between various market factors and mispricing, including forward-looking volatility (measured by the NIFVIX index), changes in open interest, underlying index return, futures volume, index volume and time to maturity. Additionally, the relationships are regime-dependent, specifically identifying the regime-dependent nature of the relationship between forward-looking volatility and mispricing, the impact of futures volume on mispricing, the effect of open interest on mispricing, the varying influence of index volume and the influence of time to maturity across the three distinct regimes.</p><!--/ Abstract__block -->\n<h3>Practical implications</h3>\n<p>These findings offer valuable insights for policymakers and investors by providing a detailed understanding of futures market efficiency and potential arbitrage opportunities. The study emphasizes the importance of understanding market dynamics, transaction costs and timing, offering guidance to enhance market efficiency and capitalize on trading opportunities in the evolving Indian derivatives market.</p><!--/ Abstract__block -->\n<h3>Originality/value</h3>\n<p>The Vector Autoregression (VAR) and Threshold Vector Autoregression Regression (TVAR) models are deployed to disentangle the interrelationships between NIFTY 50 Index futures mispricing and related endogenous determinants.</p><!--/ Abstract__block -->\n<h3>Research highlights</h3>\n<p> </p><ul list-type=\"simple\"><li><span>(1)</span><p>This study investigates the Nifty 50 Index futures mispricing across three distinct market regimes.</p></li><li><span>(2)</span><p>We highlight how factors like volatility, futures volume, and open interest vary in their impact.</p></li><li><span>(3)</span><p>The study employs vector auto-regressive and threshold vector auto-regressive models to explore the complex relationships influencing mispricing.</p></li><li><span>(4)</span><p>We provide valuable insights for investors and policymakers on improving market efficiency and identifying potential arbitrage opportunities.</p></li></ul><!--/ Abstract__block -->","PeriodicalId":18140,"journal":{"name":"Managerial Finance","volume":null,"pages":null},"PeriodicalIF":1.9000,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Managerial Finance","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1108/mf-03-2024-0166","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
引用次数: 0
Abstract
Purpose
This study investigates the mispricing dynamics of NIFTY 50 Index futures, drawing upon daily data spanning from January 2008 to July 2023.
Design/methodology/approach
The study employs both a single regime analysis and a tri-regime model to understand the fluctuations in NIFTY 50 Index futures mispricing.
Findings
The study reveals a complex interplay between various market factors and mispricing, including forward-looking volatility (measured by the NIFVIX index), changes in open interest, underlying index return, futures volume, index volume and time to maturity. Additionally, the relationships are regime-dependent, specifically identifying the regime-dependent nature of the relationship between forward-looking volatility and mispricing, the impact of futures volume on mispricing, the effect of open interest on mispricing, the varying influence of index volume and the influence of time to maturity across the three distinct regimes.
Practical implications
These findings offer valuable insights for policymakers and investors by providing a detailed understanding of futures market efficiency and potential arbitrage opportunities. The study emphasizes the importance of understanding market dynamics, transaction costs and timing, offering guidance to enhance market efficiency and capitalize on trading opportunities in the evolving Indian derivatives market.
Originality/value
The Vector Autoregression (VAR) and Threshold Vector Autoregression Regression (TVAR) models are deployed to disentangle the interrelationships between NIFTY 50 Index futures mispricing and related endogenous determinants.
Research highlights
(1)
This study investigates the Nifty 50 Index futures mispricing across three distinct market regimes.
(2)
We highlight how factors like volatility, futures volume, and open interest vary in their impact.
(3)
The study employs vector auto-regressive and threshold vector auto-regressive models to explore the complex relationships influencing mispricing.
(4)
We provide valuable insights for investors and policymakers on improving market efficiency and identifying potential arbitrage opportunities.
期刊介绍：
Managerial Finance provides an international forum for the publication of high quality and topical research in the area of finance, such as corporate finance, financial management, financial markets and institutions, international finance, banking, insurance and risk management, real estate and financial education. Theoretical and empirical research is welcome as well as cross-disciplinary work, such as papers investigating the relationship of finance with other sectors.
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