Performance of Heterogeneous Autoregressive Models of Realized Volatility: Evidence from U.S. Stock Market

Authors: Petr Seďa

Abstract:

This paper deals with heterogeneous autoregressive models of realized volatility (HAR-RV models) on high-frequency data of stock indices in the USA. Its aim is to capture the behavior of three groups of market participants trading on a daily, weekly and monthly basis and assess their role in predicting the daily realized volatility. The benefits of this work lies mainly in the application of heterogeneous autoregressive models of realized volatility on stock indices in the USA with a special aim to analyze an impact of the global financial crisis on applied models forecasting performance. We use three data sets, the first one from the period before the global financial crisis occurred in the years 2006-2007, the second one from the period when the global financial crisis fully hit the U.S. financial market in 2008-2009 years, and the last period was defined over 2010-2011 years. The model output indicates that estimated realized volatility in the market is very much determined by daily traders and in some cases excludes the impact of those market participants who trade on monthly basis.

Keywords: Global financial crisis, heterogeneous autoregressive model, in-sample forecast, realized volatility, U.S. stock market.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1079638

References:

[1] T. G. Andersen, T. Bollerslev, F. X. Diebold, and P. Labys, "The distribution of exchange rate volatility," Journal of the American Statistical Association, vol. 96, pp. 42-55, 2003.
[2] T. G. Andersen, T. Bollerslev, and F. Diebold, "Roughing it up: Including jump components in the measurement, modelling and forecasting of return volatility," Review of Economics and Statistics, vol. 89, pp. 701-720, 2007.
[3] K. Back, "Asset pricing for general processes," Journal of Mathematics Economics, vol. 20, pp. 371-395, 1991.
[4] O. Barndorff-Nielsen, and N. Shephard, "Power and bipower variation with stochastic volatility and jumps," Journal of Financial Econometrics, vol. 2, pp. 1-37, 2004.
[5] O. Barndorff-Nielsen, and N. Shephard, "Econometrics of testing for jumps in financial economics using bipower variation," Journal of Financial Econometrics, vol. 4, pp. 1-30, 2006.
[6] O. Barndorff-Nielsen, and N. Shephard, "Variation, jumps, market frictions and high frequency data in financial econometrics," Economics Series Working Papers no. 240, University of Oxford, 2007.
[7] L. Bauwens, Ch. Hafner, and S. Laurent, Handbook of Volatility Models and Their Applications, New York: John Wiley&Sons, 2012.
[8] F. Corsi, "A Simple Long Memory Model of Realized Volatility," Journal of Financial Econometrics, vol. 7, pp. 174-196, 2009.
[9] F. Corsi, M. Dacorogna, U. Műller, and G. Zumbach, "Consistent Highprecision Volatility from High-frequency Data, ÔÇ×Economic Notes", vol. 30, pp. 183-204, 2001.
[10] F. Corsi., U. Kretschmer, S. Mittnik, and C. Pigorsch, "The volatility of realized volatility," Economic Review, vol. 27, pp.1-33, 2008.
[11] F. Corsi, F., D. Pirino, and R. Reno, "Volatility forecasting: The jumps do matter," Hitotsubashi University Discussion paper series 36, 2009.
[12] J. Hanclova, "The effects of domestic and external shocks on a small open country: the evidence from the Czech Economy," International Journal of Mathematical Models and Methods in Applied Sciences, vol. 6, pp. 366-375, 2012.
[13] A. Lo, J. Y. Campbell, and C. A, Mackinlay, The Econometrics of Financial Markets, New York: Princeton University Press, 1997.
[14] T. Lux, and M. Marchesi, "Scaling and criticality in a stochastic multiagent model of financial market," Nature, vol. 397, pp. 498-500, 1999.
[15] U. Műller, M. Dacorogna, R. Davé, R. Olsen, O. Pietet, and J. von Weizsacker, "Volatilities of different time resolutions - analysing the dynamics of market components," Journal of Empirical Finance , vol. 4, pp. 213-239, 1997.
[16] E. Peters, Fractal Market Analysis, New York: John Wiley&Sons, 1994.
[17] J. Sucháček, Territorial Development Reconsidered. Ostrava: VŠB-TU Ostrava, 2009.