The article analyzes the leverage effect for Indian stock market. The effect of good and bad news on volatility during the period of growth, recession and the post-recession period is investigated taking American recession of 2008–2009 as the benchmark. Bombay Stock Exchange (BSE) 30 index was used as the proxy for Indian stock market. Using suitable asymmetric generalized autoregressive conditional heteroscedasticity (GARCH) models based on information criterions to study the asymmetry for the period and sub-periods, it was found that Indian stock market reacts differently to positive and negative news confirming leverage effect in all periods considered. However, the leverage effect was seen prominent during the period of gloom than other periods shown by the news impact curve.
BatraA. (2004). Stock return volatility patterns in India (pp. 1–34). Working Paper, 124. India: Indian Council for Research on International Economic Relations.
4.
BekaertG., & WuG. (2000). Asymmetric volatility and risk in equity markets. Review of Financial Studies, 13(1), 1–42.
5.
BlackF. (1976) Studies of stock market volatility changes. Proceedings of the American Statistical Association, Business and Economic Statistics Section, pp. 177–181, Washington DC, US.
BraunP.A., NelsonD.B., & SunierA.M. (1995). Good news, bad news, volatility, and betas. The Journal of Finance, 50(5), 1575–1603.
8.
CappielloL., EngleR.F., & SheppardK. (2006). Asymmetric dynamics in the correlations of global equity and bond returns. Journal of Financial Econometrics, 4(4), 537–572.
9.
ConradJ., CornellB., & LandsmanW.R. (2002). When is bad news really bad news?The Journal of Finance, 57(6), 2507–2532.
10.
DingZ., GrangerC.W., & EngleR.F. (1993). A long memory property of stock market returns and a new model. Journal of empirical finance, 1(1), 83–106.
11.
EngleR. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(5), 987–1007.
12.
FlanneryM., & ProtopapadakisA. (2002). Macroeconomic factors do influence aggregate stock returns. The Review of Financial Studies, 15(3), 751–782.
13.
GlostenL.R., JagannathanR., & RunkleD.E. (1993). On the relation between the expected value and the volatility of the nominal excess return on stocks. Journal of Finance, 48(5), 1779–1801.
14.
GoudarziH., & RamanarayananC.S. (2011). Modeling asymmetric volatility in the Indian stock market. International Journal of Business and Management, 6(3), 221.
15.
HamiltonJ.D., & SusmelR. (1994). Autoregressive conditional heteroskedasticity and changes in regime. Journal of Econometrics, 64(1), 307–333.
16.
KarmakarM. (2007). Asymmetric volatility and risk-return relationship in the Indian stock market. South Asia Economic Journal, 8(1), 99–116.
17.
KoutmosG., & BoothG.G. (1995). Asymmetric volatility transmission in international stock markets. Journal of International Money and Finance, 14(6), 747–762.
18.
LiuQ., WongI., AnY., & ZhangJ. (2014). Asymmetric information and volatility forecasting in commodity futures markets. Pacific-Basin Finance Journal, 26, 79–97.
19.
McQueenG., & RoleyV.V. (1993). Stock prices, news and business conditions. The Review of Financial Studies, 6(3), 683–707.
20.
MittalA.K., AroraD.D., & GoyalN. (2012). Modelling the volatility of Indian stock market. Gitam Journal of Management, 10(1), 224–243.
21.
NelsonD.B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370.
22.
SeďaP. (2011). Asymmetric conditional volatility modeling: Evidence from Central European stock markets. Proceedings of Finančnířízenípodniků a finančníchinstitucí 2011, pp. 375–383, Ostrava, Czech Republic.
23.
TripathyN. (2010). The empirical relationship between trading volumes & stock return volatility in Indian stock market. European Journal of Economics, Finance and Administrative Sciences, (24), 1450–2275.
