USE OF ARCH MODELS TO FORECAST CAPITAL MARKET VOLATILITY - THE STATUS OF THE SAUDI TADAWUL INDEX
Keywords:
Market Efficiency, Negative Shock, Volatility Cluster, Leverage, Trading Index
Abstract
This paper aimed to find out the effectiveness of the self-regression models conditional on inconsistency and disparity in estimating the fluctuations of the returns of the Saudi stock market during the period between 2007-2017, and by using the daily data of the market index, the study concluded that the Saudi stock market is inefficient at the level of the weak, and that the models ARCH gave the best representation of its fluctuations during the study period.
References
- محمد، شيخي (2012)، طرق الاقتصاد القياسي، محاضرات وتطبيقات، ط1، دار ومكتبة الحامد، عمان.
- محمد، سام، محمد، الحسين، عدنان، غانم (2013)، اختبار أثر الرافعة وسلوك التذبذب في سوق دمشق للأوراق المالية، مجلة جامعة تشرين للبحوث والدراسات العلمية، المجلد 35 العدد (7).
- ACMA, M. Q. (2015). Estimating and forecasting volatility of stock indices using asymmetric GARCH models and Student-t densities: Evidence from Chittagong Stock Exchange.
- Brooks, C. (2008). Introductory econometrics for finance. Cambridge England: Cambridge University Press.
- Ebeid, S. T., Alkholi, B., & Gamal, B. (2004). Volatility modeling and forecasting of the Egyptian stock market index using ARCH models.
- Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica: Journal of the econometric society, 987-1007.
- Hull, J. C. (2006). Options, futures, and other derivatives: Pearson Education India.
- Hol, E. M. J. (2003). Empirical Studies on Volatility in International Stock Markets. Boston, MA: Springer US.
- KUAN, C.M. (2005). Lecture on time series diagnostic tests. Institute of Economics Academia.
- Knight, J. L., Satchell, S., & John, K. (2007). Forecasting Volatility in the Financial Markets ,Third Edition: Butterworth-Heinemann.
- Poon, S.H. (2005). A practical guide to forecasting financial market volatility. Chichester: John Wiley.
- Schmitt, C. (1996). Option pricing using EGARCH models. Mannheim: ZEW.
- Teräsvirta, T. (2009). An introduction to univariate GARCH models. Handbook of Financial time series, 17-42.
- Tuyen, T. M. (2011). Modeling volatility using GARCH models: evidence from Vietnam. Economics Bulletin, 31(3), 1935-1942.
- Villalba, F. I., & Flores, M. (2013). Forecasting the variance and return of Mexican financial series with symmetric GARCH models. Theoretical & Applied Economics, 20(3).
- محمد، سام، محمد، الحسين، عدنان، غانم (2013)، اختبار أثر الرافعة وسلوك التذبذب في سوق دمشق للأوراق المالية، مجلة جامعة تشرين للبحوث والدراسات العلمية، المجلد 35 العدد (7).
- ACMA, M. Q. (2015). Estimating and forecasting volatility of stock indices using asymmetric GARCH models and Student-t densities: Evidence from Chittagong Stock Exchange.
- Brooks, C. (2008). Introductory econometrics for finance. Cambridge England: Cambridge University Press.
- Ebeid, S. T., Alkholi, B., & Gamal, B. (2004). Volatility modeling and forecasting of the Egyptian stock market index using ARCH models.
- Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica: Journal of the econometric society, 987-1007.
- Hull, J. C. (2006). Options, futures, and other derivatives: Pearson Education India.
- Hol, E. M. J. (2003). Empirical Studies on Volatility in International Stock Markets. Boston, MA: Springer US.
- KUAN, C.M. (2005). Lecture on time series diagnostic tests. Institute of Economics Academia.
- Knight, J. L., Satchell, S., & John, K. (2007). Forecasting Volatility in the Financial Markets ,Third Edition: Butterworth-Heinemann.
- Poon, S.H. (2005). A practical guide to forecasting financial market volatility. Chichester: John Wiley.
- Schmitt, C. (1996). Option pricing using EGARCH models. Mannheim: ZEW.
- Teräsvirta, T. (2009). An introduction to univariate GARCH models. Handbook of Financial time series, 17-42.
- Tuyen, T. M. (2011). Modeling volatility using GARCH models: evidence from Vietnam. Economics Bulletin, 31(3), 1935-1942.
- Villalba, F. I., & Flores, M. (2013). Forecasting the variance and return of Mexican financial series with symmetric GARCH models. Theoretical & Applied Economics, 20(3).
Published
2021-03-10
Section
Articles
