Examining the Relationship Between Implied Volatility, Index Returns, and Trading Volume in the Indian Stock Market
DOI:
https://doi.org/10.17010/ijf/2024/v18i3/173616Keywords:
Implied Volatility
, Index Returns, Trading Volume, Contemporaneous, Quantile Regression.JEL Classification Codes
, G13, G14, G15Paper Submission Date
, December 15, 2023, Paper sent back for Revision, January 10, 2024, Paper Acceptance Date, January 30, Paper Published Online, March 15, 2024Abstract
Purpose : Investors’ short-term fears or expectations are expressed in India through the India Volatility Index, a volatility index based on Nifty call options. The microstructure of the market was largely composed of trading volume, stock index returns, and implied volatility. Understanding the microstructure of the market is crucial because it gives investors important knowledge about its dynamics and empowers them to make wise decisions.
Methodology : For the years 2018 through 2023, the study took into account the closing values of the Nifty, volatility index, and trading volume. To examine the dynamic link between the variables, quantile regression and Granger causality models were applied.
Findings : The findings suggested that the volatility index’s lag returns cause fluctuations in the current returns of the Nifty. The Nifty returns and changes in trading volume are unrelated. It is observed that Nifty returns have an asymmetric relationship with returns from the volatility index and a positive association with trading volume. Markets responded more strongly to negative news shocks when the Nifty had negative returns.
Practical Implications : The volatility index would be used by investors as a hedging tool to forecast near-term Nifty volatility as well as diversify the risk in their portfolio.
Originality : The current work investigated a new temporal regime in light of the pandemic era and is an attempt to understand the dynamics of the market since downturns cause markets to become more volatile.
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Al-Awadhi, A. M., Alsaifi, K., Al-Awadhi, A., & Alhammadi, S. (2020). Death and contagious infectious diseases: Impact of the COVID-19 virus on stock market returns. Journal of Behavioral and Experimental Finance, 27, 100326. https://doi.org/10.1016/j.jbef.2020.100326
Alhussayen, H. (2022). The relationship between trading volume and market returns: A VAR/Granger causality testing approach in the context of Saudi Arabia. Organizations and Markets in Emerging Economies, 13(1), 260–275. https://doi.org/10.15388/omee.2022.13.79
Baig, A. S., Butt, H. A., Haroon, O., & Rizvi, S. A. (2021). Deaths, panic, lockdowns and US equity markets: The case of COVID-19 pandemic. Finance Research Letters, 38, 101701. https://doi.org/10.1016/j.frl.2020.101701
Bora, D., & Basistha, D. (2021). The outbreak of COVID-19 pandemic and its impact on stock market volatility: Evidence from a worst-affected economy. Journal of Public Affairs, 21(4), e2623. https://doi.org/10.1002/pa.2623
Chandra, A., & Thenmozhi, M. (2015). On asymmetric relationship of India volatility index (India VIX) with stock market return and risk management. Decision, 42, 33–55. https://doi.org/10.1007/s40622-014-0070-0
Dungore, P. P., & Patel, S. H. (2021). Analysis of volatility volume and open interest for nifty index futures using GARCH analysis and VAR model. International Journal of Financial Studies, 9(1), 7. https://doi.org/10.3390/ijfs9010007
Gul, F., & Javed, T. (2009). Relationship between trading volume and stock exchange performance: A case from Karachi stock exchange. International Business & Economics Research Journal, 8(8), 13–20. https://clutejournals.com/index.php/IBER/article/view/3155/3203
Jiang, G. J., & Tian, Y. S. (2005). The model-free implied volatility and its information content. The Review of Financial Studies, 18(4), 1305–1342. https://doi.org/10.1093/rfs/hhi027
Joshi, N. A. (2021). Volatility, open interest, and trading volume in Indian futures markets. Indian Journal of Finance, 15(11), 41–54. https://doi.org/10.17010/ijf/2021/v15i11/166831
Kamaludin, K., Sundarasen, S., & Ibrahim, I. (2021). Covid-19, Dow Jones and equity market movement in ASEAN-5 countries: Evidence from wavelet analyses. Heliyon, 7(1), E05851. https://doi.org/10.1016/j.heliyon.2020.e05851
Kumar, B., & Singh, P. (2009). The dynamic relationship between stock returns, trading volume and volatility: Evidence from Indian stock market. National Stock Exchange of India Research Paper 226, 1–49. https://nsearchives.nseindia.com/content/research/res_paper_final226.pdf
Kumar, S. S. (2012). A first look at the properties of India's volatility index. International Journal of Emerging Markets, 7(2), 160–176. https://doi.org/10.1108/17468801211209938
Mehrabanpoor, M., Bahador, B. V., & Jandaghi, G. (2011). Stock exchange indices and turnover value-evidence from Tehran Stock Exchange. African Journal of Business Management, 5(3), 783–791. https://doi.org/10.5897/AJBM10.880
Mishra, S. (2014). Dynamics of time varying volatility of Indian stock market: Evidence from BSE & CNX Nifty. AIMT Journal of Management. https://www.aimt.ac.in/pdfs/journal/Volume-3-Number-1-2-Jan-December-2014.pdf#page=7
Muthukamu, M., Amutha, S., & Amudha, R. (2024). Exploring the asymmetric price behavior of health care and pharma sector stocks of NSE in the pandemic period. Indian Journal of Finance, 18(1), 57–71. https://doi.org/10.17010/ijf/2024/v18i1/171878
Nagina, R. (2022). The nexus of stock markets among BRICS nations: An empirical analysis pre and post spread of the COVID-19 pandemic. Indian Journal of Finance, 16(10), 24–42. https://doi.org/10.17010/ijf/2022/v16i10/172386
Naik, P. K., Gupta, R., & Padhi, P. (2018). The relationship between stock market volatility and trading volume: Evidence from South Africa. The Journal of Developing Areas, 52(1), 99–114. https://doi.org/10.1353/jda.2018.0007
Pinto, A. C. (2022). Implied volatility as a predictor of stock returns: A Brazilian empirical experience (Doctoral dissertation, PUC-Rio). https://www.maxwell.vrac.puc-rio.br/60040/60040.PDF
Sahoo, S., & Kumar, S. (2023). Volatility spillover among the sectoral indices of the Indian capital market: Evidence from the COVID Period. Indian Journal of Finance, 17(9), 41–57. https://doi.org/10.17010/ijf/2023/v17i9/173183
Siddiqui, S., & Roy, P. (2019). Asymmetric relationship between implied volatility, index returns and trading volume: An application of quantile regression model. Decision, 46, 239–252. https://doi.org/10.1007/s40622-019-00218-5
Syed, A. A., Tripathi, R., & Deewan, J. (2021). Investigating the impact of the first and second waves of the COVID-19 pandemic on the Indian stock and commodity markets: An ARDL Analysis of gold, oil, and stock market prices. Indian Journal of Finance, 15(12), 8–21. https://doi.org/10.17010/ijf/2021/v15i12/167306
Tripathy, N. (2010). The empirical relationship between trading volumes & stock return volatility in Indian stock market. European Journal of Economics, Finance and Administrative Sciences, 24(1), 59–77.
Vo, D. H., Ho, C. M., & Dang, T. H.-N. (2022). Stock market volatility from the Covid-19 pandemic: New evidence from the Asia-Pacific region. Heliyon, 8(9), E10763. https://doi.org/10.1016/j.heliyon.2022.e10763