In this article, we have investigated whether the precision of one-step-ahead forecast of the market volatility can be improved by incorporating the spillover effect of other markets. For this, we have used the MGARCH model and shown empirically that if the group of markets is chosen judiciously so as to avoid multicollinearity, then it is indeed possible to obtain better forecasts. For this purpose, we have employed a BEKK parameterization of MGARCH models on the daily data of 10 sectors of the Bombay Stock Exchange (BSE).
EngleRF. Autoregressive conditional heteroskedasticity with estimates of the variance of United Kingdom inflation. Econometrica. 1982; 50(4):987–1006.
2.
BollerslevT, EngleRF, NelsonDBARCH models. In: EngleRF, McFaddenDL, editors. Handbook of econometrics. Vol. 4. Amsterdam: Elsevier Science; 1994. pp. 2959–3038.
3.
PalmFCGARCH models of volatility. In: RaoCR, MaddalaGS, editors. Handbook of statistics. Vol. 14. Amsterdam: Elsevier Science; 1996. pp. 209–240.
4.
ShephardN.Statistical aspects of ARCH and stochastic volatility. In: CoxDR, HinkleyDV, Barndorff-NielsenOE, editors. Time series models in econometrics, finance and other fields. London: Chapman and Hall; 1996. pp. 1–67.
5.
BoothGB, MartikainenT, TseY.Price and volatility spillover in Scandinavian stock markets. Journal of Banking and Finance. 1997; 21(6):811–823.
6.
HuangB, Chin-WeiY, HuJW. Causality and cointegration of stock markets among the United States, Japan, and the South China Growth Triangle. International Review of Financial Analysis. 2000; 9(3):281–297.
7.
BollerslevT.Generalized autoregressive conditional heteroskedasticity. Journal of Econometrics. 1986; 31(3):307–327.
8.
EngleR, ItoT, LinWL. Meteor showers or heat waves? Heteroscedasticity intra-daily volatility in the foreign exchange markets. Econometrica. 1990; 58(3):525–542.
9.
ChanK, ChanKC, KarolyiGA. Intraday volatility in the stock index and stock index futures markets. Review of Financial Studies. 1991; 4(4):657–684.
10.
RossS.Information and volatility: The no-arbitrage martingale approach to timing and resolution irrelevancy. Journal of Finance. 1989; 44(1):1–17.
11.
HamaoYR, MasulisRW, NgVK. Correlation in price changes and volatility across international stock markets. Review of Financial Studies. 1990; 3(2):281–307.
12.
KoutmosG, BoothGG. Asymmetric volatility transmission in international stock markets. Journal of International Money and Finance. 1995; 14(6):747–762.
13.
LinWL, EngleRF, ItoT.Do bulls and bears move across borders? International transmission of stock returns and volatility. Review of Financial Studies. 1994; 7(3):507–538.
14.
ChristofiA.PericliA.Correlation in price changes and volatility of major Latin American stock markets. Journal of Multinational Financial Management. 1999; 9(1):79–93.
15.
WangZ, KutanAM, YangJ.Information flows within and across sectors in Chinese stock markets. The Quarterly Review of Economics and Finance. 2005; 45(4&5):767–780.
16.
HassanSA, MalikF.Multivariate GARCH modeling of sector volatility transmission. The Quarterly Review of Economics and Finance. 2007; 47(3):470–480.
17.
LiH, MajerowskaE.Testing stock market linkages for Poland and Hungary: A multivariate GARCH approach. Research in International Business and Finance. 2008; 22(3):247–266.
18.
HarrisonB, MooreW.Spillover effects from London and Frankfurt to Central and Eastern European stock markets. Applied Financial Economics. 2009; 19(18):1509–1521.
19.
MalikF, EwingBT. Volatility transmission between oil prices and equity sector returns. International Review of Financial Analysis. 2009; 18(3):95–100.
20.
KarmakarM.Information transmission between small and large stocks in the National Stock Exchange in India: An empirical study. The Quarterly Review of Economics and Finance. 2010; 50(1):110–120.
21.
BubakV, KocendaE, ZikesF.Volatility transmission in emerging European foreign exchange markets. Journal of Banking & Finance. 2011; 35(11):2829–2841.
22.
PaganAR, SchwertGW. Alternative models for conditional stock volatility. Journal of Econometrics. 1990; 45(1): 267–290.
23.
BollerslevT, GhyselsE.Periodic autoregressive conditional heteroskedasticity. Journal of Business and Economic Statistics. 1996; 14(2):139–151.
24.
LopezJA. Evaluating the predictive accuracy of volatility models. Journal of Forecasting. 2001; 20(2):87–109.
25.
PoonSH. A practical guide to forecasting financial market volatility. West Sussex, England: John Wiley & Sons, Ltd.; 2005.