Notice of RetractionForecasting financial volatility using intraday information

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.