Index futures mispricing: a multi-regime approach to the NIFTY 50 Index futures

IF 1.9 Q2 BUSINESS, FINANCE Managerial Finance Pub Date : 2024-08-28 DOI:10.1108/mf-03-2024-0166
Kithsiri Samarakoon, Rudra P. Pradhan
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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.

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指数期货错误定价:针对 NIFTY 50 指数期货的多制度方法
目的本研究利用 2008 年 1 月至 2023 年 7 月期间的每日数据,对 NIFTY 50 指数期货的错误定价动态进行了调查。研究结果该研究揭示了各种市场因素与错误定价之间复杂的相互作用,包括前瞻性波动率(以 NIFVIX 指数衡量)、未平仓合约的变化、相关指数回报率、期货成交量、指数成交量和到期时间。此外,这些关系还与制度有关,特别是确定了前瞻性波动率与错误定价之间关系的制度依赖性、期货成交量对错误定价的影响、未平仓合约对错误定价的影响、指数成交量的不同影响以及到期时间对三种不同制度的影响。研究强调了了解市场动态、交易成本和时机的重要性,为在不断发展的印度衍生品市场中提高市场效率和利用交易机会提供了指导。原创性/价值采用向量自回归(VAR)和阈值向量自回归回归(TVAR)模型来厘清 NIFTY 50 指数期货错误定价与相关内生决定因素之间的相互关系。研究亮点 (1)本研究调查了三种不同市场制度下的 Nifty 50 指数期货错误定价。(2)我们强调了波动率、期货成交量和未平仓合约等因素的不同影响。(3)本研究采用向量自回归模型和阈值向量自回归模型来探索影响错误定价的复杂关系。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Managerial Finance
Managerial Finance BUSINESS, FINANCE-
CiteScore
3.30
自引率
12.50%
发文量
103
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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