Volume 16, Issue 4, June 2016, Pages 873–881
Moustapha HAMZAOUI1, Issam BOUSALAM2, and Otman ZOUHAYR3
1 Department of Economics, Faculty of Law and Economics, Abdelmalek Essaädi University of Tangier, Morocco
2 Department of Economics, Faculty of Law and Economics, Abdelmalek Essaädi University of Tangier, Morocco
3 Albanki-Alternative Banking Institute, France
Original language: English
Copyright © 2016 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
In this paper we decompose the realized volatility of the GARCH-RV model into continuous sample path variation and discontinuous jump variation to provide a practical and robust framework for non- parametrically measuring the jump component in asset return volatility. By using 5-minute high-frequency data of MASI Index in Morocco for the period (January 15, 2010 - January 29, 2016), we estimate parameters of the constructed GARCH and EGARCH-type models (namely, GARCH, GARCH-RV, GARCH-CJ, EGARCH, EGARCH-RV, and EGARCH-CJ) and evaluate their predictive power to forecast future volatility. The results show that the realized volatility and the continuous sample path variation have certain predictive power for future volatility while the discontinuous jump variation contains relatively less information for forecasting volatility. More interestingly, the findings show that the GARCH-CJ-type models have stronger predictive power for future volatility than the other two types of models. These results have a major contribution in financial practices such as financial derivatives pricing, capital asset pricing, and risk measures.
Author Keywords: GARCH-CJ, Jumps variation, Realized volatility, MASI Index, Morocco.
Moustapha HAMZAOUI1, Issam BOUSALAM2, and Otman ZOUHAYR3
1 Department of Economics, Faculty of Law and Economics, Abdelmalek Essaädi University of Tangier, Morocco
2 Department of Economics, Faculty of Law and Economics, Abdelmalek Essaädi University of Tangier, Morocco
3 Albanki-Alternative Banking Institute, France
Original language: English
Copyright © 2016 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
In this paper we decompose the realized volatility of the GARCH-RV model into continuous sample path variation and discontinuous jump variation to provide a practical and robust framework for non- parametrically measuring the jump component in asset return volatility. By using 5-minute high-frequency data of MASI Index in Morocco for the period (January 15, 2010 - January 29, 2016), we estimate parameters of the constructed GARCH and EGARCH-type models (namely, GARCH, GARCH-RV, GARCH-CJ, EGARCH, EGARCH-RV, and EGARCH-CJ) and evaluate their predictive power to forecast future volatility. The results show that the realized volatility and the continuous sample path variation have certain predictive power for future volatility while the discontinuous jump variation contains relatively less information for forecasting volatility. More interestingly, the findings show that the GARCH-CJ-type models have stronger predictive power for future volatility than the other two types of models. These results have a major contribution in financial practices such as financial derivatives pricing, capital asset pricing, and risk measures.
Author Keywords: GARCH-CJ, Jumps variation, Realized volatility, MASI Index, Morocco.
How to Cite this Article
Moustapha HAMZAOUI, Issam BOUSALAM, and Otman ZOUHAYR, “Does Jump Variation Accounts for Volatility Forecasting? Evidence from the Moroccan Stock Market,” International Journal of Innovation and Applied Studies, vol. 16, no. 4, pp. 873–881, June 2016.
