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Intraday return dynamics and volatility spillovers between NSE S&P CNX Nifty stock index and stock index futures

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  • Pratap Chandra Pati
  • Prabina Rajib

Abstract

Using 5-min intraday transaction prices, this study investigates the relationship between the National Stock Exchange (NSE) S&P CNX Nifty futures and its underlying spot index in terms of both return and volatility. By applying Johansen-Juselius (J-J) cointegration analysis, we find evidence of single common stochastic trend, to which spot and futures prices move together in a long-run equilibrium path. The vector error correction model (VECM) and Granger causality test find that there is unidirectional causality running from futures to spot market. To examine the volatility spillovers between the markets, this study has used bivariate Generalized Autoregressive Conditional Heteroscedastic (GARCH) (1, 1) model with Baba, Engle, Kraft and Kroner (BEKK) parameterization and finds evidence of bidirectional volatility spillovers between spot and futures markets. However, there is pronounced spillover effect of a previous shock and volatility from the futures market to spot market. Hence, we conclude that Nifty futures prices lead spot prices and futures market largely contributes to price discovery. These findings have significant implications for traders in implementing hedging and arbitrage trading strategies, for portfolio managers in managing risk and also for policymakers in assessing market stability.

Suggested Citation

  • Pratap Chandra Pati & Prabina Rajib, 2011. "Intraday return dynamics and volatility spillovers between NSE S&P CNX Nifty stock index and stock index futures," Applied Economics Letters, Taylor & Francis Journals, vol. 18(6), pages 567-574.
    • Handle: RePEc:taf:apeclt:v:18:y:2011:i:6:p:567-574
    DOI: 10.1080/13504851003742442
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    Citations

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    Cited by:

    1. Jian, Zhihong & Li, Xupei & Zhu, Zhican, 2022. "Extreme risk transmission channels between the stock index futures and spot markets: Evidence from China," The North American Journal of Economics and Finance, Elsevier, vol. 59(C).
    2. Yi-Tsung Lee & Wei-Shao Wu & Yun Yang, 2013. "Informed Futures Trading and Price Discovery: Evidence from Taiwan Futures and Stock Markets," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 20(3), pages 219-242, September.
    3. Jusoh, Hashim & Bacha, Obiyathulla & Masih, Abul Mansur M., 2014. "Multi-scale Lead-Lag Relationship between the Stock and Futures Markets: Malaysia as a Case Study," MPRA Paper 56954, University Library of Munich, Germany.
    4. Krauss, Christopher & Herrmann, Klaus & Teis, Stefan, 2015. "On the power and size properties of cointegration tests in the light of high-frequency stylized facts," FAU Discussion Papers in Economics 11/2015, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
    5. Antonakakis, Nikolaos & Floros, Christos & Kizys, Renatas, 2016. "Dynamic spillover effects in futures markets: UK and US evidence," International Review of Financial Analysis, Elsevier, vol. 48(C), pages 406-418.
    6. Mandal, Nivedita & Das, Rituparna, 2022. "Price Discovery Efficiency and Resilience of Financial Futures - A Case Study of Indian Banking Sector," MPRA Paper 112844, University Library of Munich, Germany.
    7. Christopher Krauss & Klaus Herrmann, 2017. "On the Power and Size Properties of Cointegration Tests in the Light of High-Frequency Stylized Facts," JRFM, MDPI, vol. 10(1), pages 1-24, February.
    8. Antonakakis, Nikolaos & Kizys, Renatas & Floros, Christos, 2014. "Dynamic Spillover Effects in Futures Markets," MPRA Paper 53876, University Library of Munich, Germany.
    9. Aravind Sampath & Arun Kumar Gopalaswamy, 2020. "Intraday Variability and Trading Volume: Evidence from National Stock Exchange," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 19(3), pages 271-295, December.
    10. Gagan Sharma & Parthajit Kayal & Piyush Pandey, 2019. "Information Linkages Among BRICS Countries: Empirical Evidence from Implied Volatility Indices," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 18(3), pages 263-289, December.
    11. Sanjay Sehgal & Mala Dutt, 2016. "Domestic and international information linkages between NSE Nifty spot and futures markets: an empirical study for India," DECISION: Official Journal of the Indian Institute of Management Calcutta, Springer;Indian Institute of Management Calcutta, vol. 43(3), pages 239-258, September.
    12. Mohammed Arshad Khan & Md. Mobashshir Hussain & Asif Pervez & Mohd Atif & Rohit Bansal & Hamad A. Alhumoudi & Miaochao Chen, 2022. "Intraday Price Discovery between Spot and Futures Markets of NIFTY 50: An Empirical Study during the Times of COVID-19," Journal of Mathematics, Hindawi, vol. 2022, pages 1-9, August.
    13. Sarveshwar Kumar Inani, 2017. "Price discovery in Indian stock index futures market: new evidence based on intraday data," International Journal of Indian Culture and Business Management, Inderscience Enterprises Ltd, vol. 14(1), pages 23-43.
    14. Huo, Rui & Ahmed, Abdullahi D., 2018. "Relationships between Chinese stock market and its index futures market: Evaluating the impact of QFII scheme," Research in International Business and Finance, Elsevier, vol. 44(C), pages 135-152.
    15. Gong, Chen-Chen & Ji, Shen-Dan & Su, Li-Ling & Li, Sai-Ping & Ren, Fei, 2016. "The lead–lag relationship between stock index and stock index futures: A thermal optimal path method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 63-72.

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