Indian Journal of Research in Capital Markets

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Government Bonds and Stock Market : Volatility Spillover Effect


Affiliations
1 Assistant Professor, Department of Commerce, Christ Academy Institute for Advanced Studies, Bengaluru- 560 083, Karnataka, India
2 Independent Researcher, Bengaluru, Karnataka, India

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A new data set of government bond prices, that is, the Clearing Corporation of India Limited’s Broad Total Return Index (BTRI) was introduced in this paper. The Total Returns Index (TRI) provides the change due to both the price movements and accrued interest. TRI reflects the change in the index due to market capitalized weighted price movement and accrued interest. This paper investigated volatility spillovers between government bonds and the stock market in India by following the GARCH (1, 1). By using a broad weekly data set during 2004 – 2019, with a total of 835 observations, this paper addressed a key research question : Does the effect of volatility spillover exist between government bonds and Nifty ? Does causality exist between government bonds and Nifty ? The results of Granger causality indicated that BTRI did not Granger cause Nifty. Further, the reverse was also not true, meaning that there existed no lead-lag relationship between BTRI and Nifty. The squared residuals’ coefficient of Nifty had a positive sign but was insignificant, showing that there was no effect of volatility spillover from the Nifty to the BTRI. Hence, the volatility in Nifty did not influence volatility in the BTRI but vice versa, this statement is also not true. This research is mainly useful to those investors who invest in both government bond market and stock market.

Keywords

Broad Return Index, Clearing Corporation of India Limited, Government Bond Prices, India, Nifty, Stock Market, Total Return Index.

JEL Classification : C1, C58, G11, G12.

Paper Submission Date : January 15, 2021 ; Paper sent back for Revision : February 5, 2021 ; Paper Acceptance Date : March 1, 2021.

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  • Adesina, K. S. (2013). Modelling stock market return volatility : GARCH evidence from Nigerian Stock Exchange. International Journal of Financial Management, 3(3), 37–46.

  • Aggarwal, D. (2017). Exploring relation between Indian market sentiments and stock market returns. Asian Journal of Empirical Research, 7(7), 147–159. https://doi.org/10.18488/journal.1007/2017.7.7/1007.7.147.159

  • Akram, T.,s & Das, A. (2019). The long-run determinants of Indian government bond yields. Asian Development Review, 36(1), 168–205. https://doi.org/10.1162/adev_a_00127

  • Al-Tarawneh, A., & Al-Assaf, G. (2018). Macroeconomic drivers of stock market development : Evidence from Jordan. International Journal of Financial Research, 9(3), 117–124. https://doi.org/10.5430/ijfr.v9n3p117

  • Altavilla, C., Giannone, D., & Modugno, M. (2017). Low frequency effects of macroeconomic news on government bond yields. Journal of Monetary Economics, 92, 31–46. https://doi.org/10.1016/j.jmoneco.2017.08.004

  • Brooks, R. D., & Ragunathan, V. (2003). Returns and volatility on the Chinese stock markets. Applied Financial Economics, 13(10), 747–752. https://doi.org/10.1080/09603100210148212

  • Chellaswamy, K. P., Natchimuthu, N., & Faniband, M. (2020). Stock market sensitivity to macroeconomic factors : Evidence from China and India. Asian Economic and Financial Review, 10(2), 146–159. https://doi.org/10.18488/journal.aefr.2020.102.146.159

  • Chellaswamy, K. P., Natchimuthu, N., & Faniband, M. (2021a.). Chinese and Indian stock markets : Linkages and interdependencies. Research in World Economy, 12(2), 228–239. https://doi.org/10.5430/rwe.v12n2p228

  • Chellaswamy, K. P., Natchimuthu, N., & Faniband, M. (2021b.). Stock market reforms and stock market performance. International Journal of Financial Research, 12(2), 202–209. https://doi.org/10.5430/ijfr.v12n2p202

  • Connolly, R., Stivers, C., & Sun, L. (2005). Stock market uncertainty and the stock-bond return relation. The Journal of Financial and Quantitative Analysis, 40(1), 161–194. https://www.jstor.org/stable/27647190

  • Dean, W. G., Faff, R. W., & Loudon, G. F. (2010). Asymmetry in return and volatility spillover between equity and bond markets in Australia. Pacific - Basin Finance Journal, 18(3), 272–289. https://doi.org/10.1016/j.pacfin.2009.09.003

  • Faniband, M. M., & Marulkar, K. V. (2019). Do quarterly numbers impact the share price on the date of earnings announcement? A panel causality approach. Prajnan, 48(2), 123–134.

  • Faniband, M. M., & Marulkar, K. V. (2020). Quarterly results and share prices : What happens on the date of earnings announcement ? Finance India, 34(1), 153–162.

  • Faniband, M., & Karthigai Prakasam, C. (2019). Determinants of differential voting rights share prices and ordinary share prices : Evidence from dual-class companies in India. Indian Journal of Research in Capital Markets, 6(4), 36–49. https://doi.org/10.17010/ijrcm/2019/v6/i4/150270

  • Francová, B. (2017). Valuation of government bonds : The exchange rate is an important aspect. Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, 65(6), 1911–1916. https://doi.org/10.11118/actaun201765061911

  • Ilmanen, A. (2003). Stock-bond correlations. The Journal of Fixed Income, 13(2), 55–66. https://doi.org/10.3905/jfi.2003.319353

  • Kumar, A., & Khanna, S. (2018). GARCH - BEKK approach to volatility behavior and spillover : Evidence from India, China, Hong Kong, and Japan. Indian Journal of Finance, 12(4), 7–19. https://doi.org/10.17010/ijf/2018/v12i4/122791

  • Lee, B. - S., & Rui, O. M. (2002). The dynamic relationship between stock returns and trading volume : Domestic and cross-country evidence. Journal of Banking & Finance, 26(1), 51–78. https://doi.org/10.1016/S0378-4266(00)00173-4

  • McMillan, D. G. (2020). Explaining the stock-stock, bond-bond and stock-bond correlation across countries. International Journal of Monetary Economics and Finance, 13(5), 429–445. https://doi.org/https://dx.doi.org/10.1504/IJMEF.2020.110553

  • Nieto, B., Novales, A., & Rubio, G. (2015). Macroeconomic and financial determinants of the volatility of corporate bond returns. The Quarterly Journal of Finance, 05(04), 1–41. https://doi.org/10.1142/s2010139215500214

  • Panwar, V., & Nidugala, G. K. (2019). Impact of budget and GDP announcements on Indian stock market. Finance India, 33(4), 929–946. https://www.financeindia.org/data/2019/FI334/FI-334-Art02.pdf

  • Shabarisha, N., & Madegowda, J. (2020). Impact of information asymmetry on return volatility–Domestic and cross-country evidence. Indian Journal of Research in Capital Markets, 7(2–3), 39–52. https://doi.org/10.17010/ijrcm/2020/v7i2-3/154512

  • Sulistiawan, D., & Rudiawarni, F. A. (2020). The use of moving average trading rules in Indonesian Stock Market. International Journal of Business and Globalisation, 24(1), 139–150. https://doi.org/https://dx.doi.org/10.1504/IJBG.2020.104965


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  • Government Bonds and Stock Market : Volatility Spillover Effect

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Authors

Muhammadriyaj Faniband
Assistant Professor, Department of Commerce, Christ Academy Institute for Advanced Studies, Bengaluru- 560 083, Karnataka, India
Taranum Faniband
Independent Researcher, Bengaluru, Karnataka, India

Abstract


A new data set of government bond prices, that is, the Clearing Corporation of India Limited’s Broad Total Return Index (BTRI) was introduced in this paper. The Total Returns Index (TRI) provides the change due to both the price movements and accrued interest. TRI reflects the change in the index due to market capitalized weighted price movement and accrued interest. This paper investigated volatility spillovers between government bonds and the stock market in India by following the GARCH (1, 1). By using a broad weekly data set during 2004 – 2019, with a total of 835 observations, this paper addressed a key research question : Does the effect of volatility spillover exist between government bonds and Nifty ? Does causality exist between government bonds and Nifty ? The results of Granger causality indicated that BTRI did not Granger cause Nifty. Further, the reverse was also not true, meaning that there existed no lead-lag relationship between BTRI and Nifty. The squared residuals’ coefficient of Nifty had a positive sign but was insignificant, showing that there was no effect of volatility spillover from the Nifty to the BTRI. Hence, the volatility in Nifty did not influence volatility in the BTRI but vice versa, this statement is also not true. This research is mainly useful to those investors who invest in both government bond market and stock market.

Keywords


Broad Return Index, Clearing Corporation of India Limited, Government Bond Prices, India, Nifty, Stock Market, Total Return Index.

JEL Classification : C1, C58, G11, G12.

Paper Submission Date : January 15, 2021 ; Paper sent back for Revision : February 5, 2021 ; Paper Acceptance Date : March 1, 2021.


References





DOI: https://doi.org/10.17010/ijrcm%2F2021%2Fv8i1-2%2F165087