Performance of Heterogeneous Autoregressive Models of Realized Volatility: Evidence from U.S. Stock Market
Autor: | Seďa, Petr |
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Jazyk: | angličtina |
Rok vydání: | 2012 |
Předmět: | |
DOI: | 10.5281/zenodo.1079638 |
Popis: | 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. {"references":["T. G. Andersen, T. Bollerslev, F. X. Diebold, and P. Labys, \"The\ndistribution of exchange rate volatility,\" Journal of the American\nStatistical Association, vol. 96, pp. 42-55, 2003.","T. G. Andersen, T. Bollerslev, and F. Diebold, \"Roughing it up:\nIncluding jump components in the measurement, modelling and\nforecasting of return volatility,\" Review of Economics and Statistics, vol.\n89, pp. 701-720, 2007.","K. Back, \"Asset pricing for general processes,\" Journal of Mathematics\nEconomics, vol. 20, pp. 371-395, 1991.","O. Barndorff-Nielsen, and N. Shephard, \"Power and bipower variation\nwith stochastic volatility and jumps,\" Journal of Financial\nEconometrics, vol. 2, pp. 1-37, 2004.","O. Barndorff-Nielsen, and N. Shephard, \"Econometrics of testing for\njumps in financial economics using bipower variation,\" Journal of\nFinancial Econometrics, vol. 4, pp. 1-30, 2006.","O. Barndorff-Nielsen, and N. Shephard, \"Variation, jumps, market\nfrictions and high frequency data in financial econometrics,\" Economics\nSeries Working Papers no. 240, University of Oxford, 2007.","L. Bauwens, Ch. Hafner, and S. Laurent, Handbook of Volatility Models\nand Their Applications, New York: John Wiley&Sons, 2012.","F. Corsi, \"A Simple Long Memory Model of Realized Volatility,\"\nJournal of Financial Econometrics, vol. 7, pp. 174-196, 2009.","F. Corsi, M. Dacorogna, U. Műller, and G. Zumbach, \"Consistent Highprecision\nVolatility from High-frequency Data, ÔÇ×Economic Notes\", vol.\n30, pp. 183-204, 2001.\n[10] F. Corsi., U. Kretschmer, S. Mittnik, and C. Pigorsch, \"The volatility of\nrealized volatility,\" Economic Review, vol. 27, pp.1-33, 2008.\n[11] F. Corsi, F., D. Pirino, and R. Reno, \"Volatility forecasting: The jumps\ndo matter,\" Hitotsubashi University Discussion paper series 36, 2009.\n[12] J. Hanclova, \"The effects of domestic and external shocks on a small\nopen country: the evidence from the Czech Economy,\" International\nJournal of Mathematical Models and Methods in Applied Sciences, vol.\n6, pp. 366-375, 2012.\n[13] A. Lo, J. Y. Campbell, and C. A, Mackinlay, The Econometrics of\nFinancial Markets, New York: Princeton University Press, 1997.\n[14] T. Lux, and M. Marchesi, \"Scaling and criticality in a stochastic\nmultiagent model of financial market,\" Nature, vol. 397, pp. 498-500,\n1999.\n[15] U. Műller, M. Dacorogna, R. Davé, R. Olsen, O. Pietet, and J. von\nWeizsacker, \"Volatilities of different time resolutions - analysing the\ndynamics of market components,\" Journal of Empirical Finance , vol. 4,\npp. 213-239, 1997.\n[16] E. Peters, Fractal Market Analysis, New York: John Wiley&Sons, 1994.\n[17] J. Such├í─ìek, Territorial Development Reconsidered. Ostrava: V┼áB-TU\nOstrava, 2009."]} |
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