Volatility Forecasting Models and Market Co-Integration: A Study on South-East Asian Markets
Volatility forecasting is an imperative research field in financial markets and crucial component in most financial decisions. Nevertheless, which model should be used to assess volatility remains a complex issue as different volatility models result in different volatility approximations. The concern becomes more complicated when one tries to use the forecasting for asset distribution and risk management purposes in the linked regional markets. This paper aims at observing the effectiveness of the contending models of statistical and econometric volatility forecasting in the three South-east Asian prominent capital markets, i.e. STI, KLSE, and JKSE. In this paper, we evaluate eleven different models based on two classes of evaluation measures, i.e. symmetric and asymmetric error statistics, following Kumar’s (2006) framework. We employ 10-year data as in sample and 6-month data as out of sample to construct and test the models, consecutively. The resulting superior methods, which are selected based on the out of sample forecasts and some evaluation measures in the respective markets, are then used to assess the markets cointegration. We find that the best volatility forecasting models for JKSE, KLSE, and STI are GARCH (2,1), GARCH(3,1), and GARCH (1,1), respectively. We also find that international portfolio investors cannot benefit from diversification among these three equity markets as they are cointegrated.
|Date of creation:||Sep 2009|
|Date of revision:||Sep 2009|
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- MacKinnon, James G & Haug, Alfred A & Michelis, Leo, 1999.
"Numerical Distribution Functions of Likelihood Ratio Tests for Cointegration,"
Journal of Applied Econometrics,
John Wiley & Sons, Ltd., vol. 14(5), pages 563-77, Sept.-Oct.
- James G. MacKinnon & Alfred A. Haug & Leo Michelis, 1996. "Numerical Distribution Functions of Likelihood Ratio Tests for Cointegration," Working Papers 1996_07, York University, Department of Economics.
- Mackinnon, J.G. & Haug, A.A. & Michelis, L., 1996. "Numerical Distribution Functions of Likelihood Ratio Tests for Cointegration," G.R.E.Q.A.M. 96a09, Universite Aix-Marseille III.
- French, Kenneth R & Poterba, James M, 1991.
"Investor Diversification and International Equity Markets,"
American Economic Review,
American Economic Association, vol. 81(2), pages 222-26, May.
- Kenneth R. French & James M. Poterba, 1991. "Investor Diversification and International Equity Markets," NBER Working Papers 3609, National Bureau of Economic Research, Inc.
- Aggarwal, Reena & Inclan, Carla & Leal, Ricardo, 1999. "Volatility in Emerging Stock Markets," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 34(01), pages 33-55, March.
- Kasa, Kenneth, 1992. "Common stochastic trends in international stock markets," Journal of Monetary Economics, Elsevier, vol. 29(1), pages 95-124, February.
- Knif, Johan & Pynnonen, Seppo, 1999. "Local and global price memory of international stock markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 9(2), pages 129-147, April.
- Tim Bollerslev, 1986.
"Generalized autoregressive conditional heteroskedasticity,"
EERI Research Paper Series
EERI RP 1986/01, Economics and Econometrics Research Institute (EERI), Brussels.
- Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
- Louis H. Ederington & Wei Guan, 2005. "Forecasting volatility," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 25(5), pages 465-490, 05.
- Granger, Clive W J & Hallman, Jeffrey J, 1991. "Long Memory Series with Attractors," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 53(1), pages 11-26, February.
- Andrew W. Lo & Craig A. MacKinlay, .
"An Econometric Analysis of Nonsyschronous-Trading,"
Rodney L. White Center for Financial Research Working Papers
19-89, Wharton School Rodney L. White Center for Financial Research.
- Søren Tolver Jensen & Anders Rahbek, 2004. "Asymptotic Normality of the QMLE Estimator of ARCH in the Nonstationary Case," Econometrica, Econometric Society, vol. 72(2), pages 641-646, 03.
- Kam C. Chan & Benton E. Gup & Ming-Shiun Pan, 1997. "International Stock Market Efficiency and Integration: A Study of Eighteen Nations," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 24(6), pages 803-813.
- Carol Alexander & Anca Dimitriu, 2003. "Equity Indexing: Conitegration and Stock Price Dispersion: A Regime Switiching Approach to market Efficiency," ICMA Centre Discussion Papers in Finance icma-dp2003-02, Henley Business School, Reading University.
- Robert-Jan Gerrits & Ayse Yuce, 1999. "Short- and long-term links among European and US stock markets," Applied Financial Economics, Taylor & Francis Journals, vol. 9(1), pages 1-9.
- Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2001.
"Modeling and Forecasting Realized Volatility,"
Center for Financial Institutions Working Papers
01-01, Wharton School Center for Financial Institutions, University of Pennsylvania.
- Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2001. "Modeling and Forecasting Realized Volatility," NBER Working Papers 8160, National Bureau of Economic Research, Inc.
- Anderson, Torben G. & Bollerslev, Tim & Diebold, Francis X. & Labys, Paul, 2002. "Modeling and Forecasting Realized Volatility," Working Papers 02-12, Duke University, Department of Economics.
- Dwyer, Gerald Jr. & Wallace, Myles S., 1992. "Cointegration and market efficiency," Journal of International Money and Finance, Elsevier, vol. 11(4), pages 318-327, August.
- Benoit Mandelbrot, 1963. "The Variation of Certain Speculative Prices," The Journal of Business, University of Chicago Press, vol. 36, pages 394.
- MacKinnon, James G, 1996.
"Numerical Distribution Functions for Unit Root and Cointegration Tests,"
Journal of Applied Econometrics,
John Wiley & Sons, Ltd., vol. 11(6), pages 601-18, Nov.-Dec..
- James G. MacKinnon, 1995. "Numerical Distribution Functions for Unit Root and Cointegration Tests," Working Papers 918, Queen's University, Department of Economics.
- Johansen, Soren & Juselius, Katarina, 1990. "Maximum Likelihood Estimation and Inference on Cointegration--With Applications to the Demand for Money," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 52(2), pages 169-210, May.
- Granger, C. W. J., 1981. "Some properties of time series data and their use in econometric model specification," Journal of Econometrics, Elsevier, vol. 16(1), pages 121-130, May.
- French, Kenneth R. & Schwert, G. William & Stambaugh, Robert F., 1987. "Expected stock returns and volatility," Journal of Financial Economics, Elsevier, vol. 19(1), pages 3-29, September.
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