Modeling Of Volatility In The Romanian Capital Market
This paper aims to analyze the volatility of capital market in Romania by selecting a portfolio of representative indices (BET BET_FI and RASDAQ_C). In this respect, we want to identify the most appropriate model to estimate volatility by using modern econometric tools and useful GARCH models respectively. The study results highlight that EGARCH(1,1) model has managed to eliminate all traces of statistically significant autocorrelation and ARCH effects from the residuals from daily series, giving an accurate image of the Romanian capital market volatility.
Volume (Year): 7 (2012)
Issue (Month): 3 (December)
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Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
- Bollerslev, Tim & Chou, Ray Y. & Kroner, Kenneth F., 1992. "ARCH modeling in finance : A review of the theory and empirical evidence," Journal of Econometrics, Elsevier, vol. 52(1-2), pages 5-59.
- Radu Lupu & Iulia Lupu, 2007. "Testing for Heteroskedasticity on the Bucharest Stock Exchange," Romanian Economic Journal, Department of International Business and Economics from the Academy of Economic Studies Bucharest, vol. 10(23), pages 19-28, June.
- Miron, Dumitru & Tudor, Cristiana, 2010. "Asymmetric Conditional Volatility Models: Empirical Estimation and Comparison of Forecasting Accuracy," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), September.
- Bollerslev, Tim, 1986.
"Generalized autoregressive conditional heteroskedasticity,"
Journal of Econometrics,
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- Tim Bollerslev, 1986. "Generalized autoregressive conditional heteroskedasticity," EERI Research Paper Series EERI RP 1986/01, Economics and Econometrics Research Institute (EERI), Brussels.
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