DocumentCode :
1656086
Title :
Notice of Retraction
Forecasting financial volatility using intraday information
Author :
Hongquan Li
Author_Institution :
Coll. of Bus., Hunan Normal Univ., Changsha, China
Volume :
3
fYear :
2010
Firstpage :
518
Lastpage :
521
Abstract :
Notice of Retraction

After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.

We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.

The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.

This study introduces and extends the range-based autoregressive volatility (henceforth, AV) model to properly model the dynamics of return volatility. The traditional ARCH-type model is also adopted as a benchmark. Therefore, two types of volatility models are discussed and estimated: return-based GARCH models and range-based AV models. Examination of in-sample and out-of-sample volatility forecasts reveals that the AV model consistently outperforms the GARCH model. Our findings confirm that extreme-value volatility can retain its superiority in forecasting volatility by properly modeling the dynamic process. It would be beneficial to encompass intraday information especially price range to do volatility forecasting and risk management in financial markets.
Keywords :
autoregressive processes; economic forecasting; financial management; pricing; risk management; asset pricing; extreme-value volatility; financial market; financial volatility forecasting; intraday information; range-based autoregressive volatility; return volatility; return-based GARCH model; risk management; Forecasting; Predictive models; intraday information; price range; volatility model;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced Management Science (ICAMS), 2010 IEEE International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-6931-4
Type :
conf
DOI :
10.1109/ICAMS.2010.5553185
Filename :
5553185
Link To Document :
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