Government Bonds and Stock Market : Volatility Spillover Effect

Authors

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

DOI:

https://doi.org/10.17010/ijrcm/2021/v8i1-2/165087

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, Paper Acceptance Date, March 1, 2021.

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.

Downloads

Download data is not yet available.

Author Biographies

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

ORCID iD : 0000-0001-6775-3582

Taranum Faniband, Independent Researcher, Bengaluru, Karnataka

ORCID iD : 0000-0001-5117-595X

Downloads

Published

2021-06-30

How to Cite

Faniband, M., & Faniband, T. (2021). Government Bonds and Stock Market : Volatility Spillover Effect. Indian Journal of Research in Capital Markets, 8(1-2), 61–71. https://doi.org/10.17010/ijrcm/2021/v8i1-2/165087

Issue

Volume 8, Issue 1-2, January-June 2021

Section

Articles
Crossref
Scopus
Google Scholar
Europe PMC

References

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