Browse > Article
http://dx.doi.org/10.13106/jafeb.2021.vol8.no4.0857

A Study on Unfolding Asymmetric Volatility: A Case Study of National Stock Exchange in India  

SAMINENI, Ravi Kumar (Department of Management Studies, K L Deemed to be University)
PUPPALA, Raja Babu (Department of Management Studies, K L Deemed to be University)
KULAPATHI, Syamsundar (Department of MBA, Vignan Degree and PG College)
MADAPATHI, Shiva Kumar (Vishwa Vishwani Institute of Systems & Management)
Publication Information
The Journal of Asian Finance, Economics and Business / v.8, no.4, 2021 , pp. 857-861 More about this Journal
Abstract
The study aims to find the asymmetric effect in National Stock Exchange in which the Nifty50 is considered as proxy for NSE. A return can be stated as the change in value of a security over a certain time period. Volatility is the rate of change in security value. It is an arithmetical assessment of the dispersion of yields of security prices. Stock prices are extremely unpredictable and make the investment in equities risky. Predicting volatility and modeling are the most profuse areas to explore. The current study describes the association between two variables, namely, stock yields and volatility in equity market in India. The volatility is measured by employing asymmetric GARCH technique, i.e., the EGARCH (1,1) tool, which was used in building the study. The closing prices of Nifty on day-to-day basis were used for analysis from the period 2011 to 2020 with 2,478 observations in the study. The model arrests the lopsided volatility during the mentioned period. The outcome of asymmetric GARCH model revealed the subsistence of leverage effect in the index and confirms the impact of conditional variance as well. Furthermore, the EGARCH technique was evidenced to be apt in seizure of unsymmetrical volatility.
Keywords
Volatility; Asymmetric Effect; Conditional Variance; Nifty Index; India;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Hongsakulvasu, N., & Liammukda, A. (2020). Asian Stock Markets Analysis: The New Evidence from Time-Varying Coefficient Autoregressive Model. Journal of Asian Finance, Economics and Business, 7(9), 95-104. https://doi.org/10.13106/jafeb.2020.vol7.no9.095   DOI
2 Horpestad, J. B., Lyocsa, S., Molnar, P., & Olsen, T. B. (2019). Asymmetric volatility in equity markets around the world. The North American Journal of Economics and Finance, 48, 540-554. https://doi.org/10.1016/j.najef.2018.07.011   DOI
3 Jayasuriya, S., Shambora, W., & Rossiter, R. (2009). Asymmetric volatility in emerging and mature markets. Journal of Emerging Market Finance, 8(1), 25-43. https://doi.org/10.1177/097265270900800102   DOI
4 Karmakar, M. (2007). Asymmetric volatility and risk-return relation-ship in the Indian stock market. South Asia Economic Journal, 8(1), 99-116. https://doi.org/10.1177/139156140600800106   DOI
5 Kristoufek, L. (2014). Leverage effect in energy futures. Energy Economics, 45, 1-9. http://dx.doi.org/10.1016/j.eneco.2014.06.009   DOI
6 Lama, A., Jha, G. K., Paul, R. K., & Gurung, B. (2015). Modelling and forecasting of price volatility: An application of GARCH and EGARCH models. Agricultural Economics Research Review, 28(347-2016-17165), 73-82. https://doi.org/10.5958/0974-0279.2015.00005.1   DOI
7 Malik, F. (2011). Estimating the impact of good news on stock market volatility. Applied Financial Economics, 21(8), 545-554. https://doi.org/10.1080/09603107.2010.534063   DOI
8 Ndwiga, D., & Muriu, P. W. (2016). Stock Returns and Volatility In An Emerging Equity Market. Evidence from Kenya. European Scientific Journal, 12(4), 79. https://doi.org/10.19044/esj.2016.v12n4p79   DOI
9 Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica: Journal of the Econometric Society, 347-370. https://doi.org/10.2307/2938260   DOI
10 Raja Babu, P., Kumar, S. R., & Naganjaneyulu, A. V. (2020). Modeling Asymmetric Volatility: Evidence from India. Journal of Critical Reviews, 7(9), 845-850. https://doi.org/10.31838/jcr.07.09.158   DOI
11 Samineni, R. K., Puppala, R. B., Muthangi, R., & Kulapathi, S. (2020). Expiration-Day Effects on Index Futures: Evidence from Indian Market. Journal of Asian Finance, Economics and Business, 7(11), 95-100. https://doi:10.13106/jafeb.2020.vol7.no11.095   DOI
12 Sharma, P. (2015). Forecasting stock index volatility with GARCH models: international evidence. Studies in Economics and Finance. https://doi.org/10.1108/SEF-11-2014-0212   DOI
13 Srinivasan, P., & Ibrahim, P. (2010). Forecasting stock market volatility of BSE-30 index using GARCH models. Asia Pacific Business Review, 6(3), 47-60. https://doi.org/10.1177/097324701000600304   DOI
14 Thanatawee, Y. (2021). The Impact of Foreign Ownership on Stock Price Volatility: Evidence from Thailand. Journal of Asian Finance, Economics and Business, 8(1), 7-14. https://doi.org/10.13106/jafeb.2021.vol8.no1.007   DOI
15 Tripathy, N., Rao, S. R., & Kanagaraj, A. (2009). Impact of derivatives trading on spot market volatility: an empirical study. International Journal of Applied Decision Sciences, 2(2), 209-232. https://doi.org/10.1504/IJADS.2009.026553   DOI
16 Wu, G. (2001). The determinants of asymmetric volatility. The Review of Financial Studies, 14(3), 837-859. https://doi.org/10.1093/rfs/14.3.837   DOI
17 Katsiampa, P. (2019). Volatility co-movement between Bitcoin and Ether. Finance Research Letters, 30, 221-227. https://doi.org/10.1016/j.frl.2018.10.005   DOI
18 Balaban, E., & Bayar, A. (2005). Stock returns and volatility: empirical evidence from fourteen countries. Applied Economics Letters, 12(10), 603-611. https://doi.org/10.1080/13504850500120607   DOI
19 Uyaebo, S. O., Atoi, V. N., & Usman, F. (2015). Nigeria stock market volatility in comparison with some countries: Application of asymmetric GARCH models. CBN Journal of Applied Statistics, 6(2), 133-160. http://hdl.handle.net/10419/142109
20 Alberg, D., Shalit, H., & Yosef, R. (2008). Estimating stock market volatility using asymmetric GARCH models. Applied Financial Economics, 18(15), 1201-1208. https://doi.org/10.1080/09603100701604225   DOI
21 Baur, D. G. (2012). Asymmetric volatility in the gold market. The Journal of Alternative Investments, 14(4), 26-38. https://doi.org/10.3905/jai.2012.14.4.026   DOI
22 Bekaert, G., & Wu, G. (2000). Asymmetric volatility and risk in equity markets. The Review of Financial Studies, 13(1), 1-42. https://doi.org/10.1093/rfs/13.1.1   DOI
23 Christie, A. A. (1982). The stochastic behaviour of common stock variances: Value, leverage and interest rate effects. Journal of Financial Economics, 10(4), 407-432. https://doi.org/10.1016/0304-405X(82)90018-6   DOI
24 Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity. Journal of econometrics, 31(3), 307-327. https://doi.org/10.1016/0304-4076(86)90063-1   DOI
25 Caiado, J. (2004). Modelling and forecasting the volatility of the Portuguese stock index PSI-20. Estudos de Gestao, 9(1), 3-22. http://hdl.handle.net/10400.5/9973
26 Chiang, M. H., & Huang, H. Y. (2011). Stock market momentum, business conditions, and GARCH option pricing models. Journal of Empirical Finance, 18(3), 488-505. https://doi.org/10.1016/j.jempfin.2011.01.004   DOI
27 Chu, J., Chan, S., Nadarajah, S., & Osterrieder, J. (2017). GARCH modelling of cryptocurrencies. Journal of Risk and Financial Management, 10(4), 17. https://doi.org/10.3390/jrfm10040017   DOI
28 Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica: Journal of the Econometric Society, 987-1007. https://doi.org/10.2307/1912773   DOI
29 Hansen, P. R., & Lunde, A. (2006). Consistent ranking of volatility models. Journal of Econometrics, 131(1-2), 97-121. https://doi.org/10.1016/j.jeconom.2005.01.005   DOI
30 Ewing, B. T., & Malik, F. (2017). Modelling asymmetric volatility in oil prices under structural breaks. Energy Economics, 63, 227-233. https://doi.org/10.1016/j.eneco.2017.03.001   DOI
31 Herbert, W. E., Ugwuanyi, G. O., & Nwaocha, E. I. (2019). Volatility clustering, leverage effects and risk-return trade-off in the Nigerian stock market. Journal of Finance and Economics, 7(1), 1-13. https://doi.org/10.12691/jfe-7-1-1   DOI