We present an intraday volatility model for equally spaced data and apply it for the WIG Index- a broad market index of the Warsaw Stock Exchange. The current study is an application and extension of the model proposed by Engle and Sokalska [2010]. We decompose the conditional variance of intraday returns into components that have a natural interpretation and can be easily estimated.
Several competing intraday volatility forecasting models for equally spaced data have been proposed in the literature. This study reviews a number of models and compares their forecasting performance using data on the market index of the Warsaw Stock Exchange. We also discuss choice criteria and issues specific to volatility forecast evaluation.
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