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A publicação pode ser exportada nos seguintes formatos: referência da APA (American Psychological Association), referência do IEEE (Institute of Electrical and Electronics Engineers), BibTeX e RIS.

Exportar Referência (APA) 
Bentes, S. & Menezes, R. (2013). On the predictability of realized volatility using feasible GLS. Journal of Asian Economics. 28, 58-66
Exportar Referência (IEEE) 
S. M. Bentes and R. M. Menezes,  "On the predictability of realized volatility using feasible GLS", in Journal of Asian Economics, vol. 28, pp. 58-66, 2013
Exportar BibTeX 
@article{bentes2013_1714275906290,
	author = "Bentes, S. and Menezes, R.",
	title = "On the predictability of realized volatility using feasible GLS",
	journal = "Journal of Asian Economics",
	year = "2013",
	volume = "28",
	number = "",
	doi = "10.1016/j.asieco.2013.08.002",
	pages = "58-66",
	url = "http://www.sciencedirect.com/science/article/pii/S1049007813000821"
}
Exportar RIS 
TY  - JOUR
TI  - On the predictability of realized volatility using feasible GLS
T2  - Journal of Asian Economics
VL  - 28
AU  - Bentes, S.
AU  - Menezes, R.
PY  - 2013
SP  - 58-66
SN  - 1049-0078
DO  - 10.1016/j.asieco.2013.08.002
UR  - http://www.sciencedirect.com/science/article/pii/S1049007813000821
AB  - This study deals with the out-of-sample predictability of realized volatility induced by implied volatility using FGLS. The original dataset was collected from Bloomberg and includes price and implied volatility indices from the US, Hong Kong, China, South Korea and India. Prices were then transformed into realized volatility indices. The relation between realized and implied volatility is important insofar as market expectations about future turbulence may affect the investor's behavior in advance. However, there are some features of the financial data which turn problematic the choice of the OLS estimator. These features include endogeneity and persistence of the predictor, and also conditional heteroskedasticity of the predicted innovations. Consequently, OLS becomes biased and inefficient. The FGLS estimator accounts for these characteristics and, therefore, performs better than OLS-based estimators, as indicated by many of our results.
ER  -