Template-Type: ReDIF-Paper 1.0 Series: Tinbergen Institute Discussion Papers Creation-Date: 2004-06-09 Number: 04-067/4 Author-Name: Martin Martens Author-Email: mmartens@few.eur.nl Author-Workplace-Name: Faculty of Economics, Erasmus Universiteit Rotterdam Author-Name: Dick van Dijk Author-Email: djvandijk@few.eur.nl Author-Workplace-Name: Faculty of Economics, Erasmus Universiteit Rotterdam Author-Name: Michiel de Pooter Author-Email: depooter@few.eur.nl Author-Workplace-Name: Faculty of Economics, Erasmus Universiteit Rotterdam Title: Modeling and Forecasting S&P 500 Volatility: Long Memory, Structural Breaks and Nonlinearity Abstract: This discussion paper resulted in a publication in the 'International Journal of Forecasting', 2009, 27, 282-303.

The sum of squared intraday returns provides an unbiased and almost error-free measure of ex-post volatility. In this paper we develop a nonlinear Autoregressive Fractionally Integrated Moving Average (ARFIMA) model for realized volatility, which accommodates level shifts, day-of-the-week effects, leverage effects and volatility level effects. Applying the model to realized volatilities of the S&P 500 stock index and three exchange rates produces forecasts that clearly improve upon the ones obtained from a linear ARFIMA model and from conventional time-series models based on daily returns, treating volatility as a latent variable. Classification-JEL: C22; C53; G15 Keywords: Realized volatility; high-frequency data; long memory; day-of-the-week effect; leverage effect; volatility forecasting; smooth transition File-Url: https://papers.tinbergen.nl/04067.pdf File-Format: application/pdf File-Size: 1913431 bytes Handle: RePEc:tin:wpaper:20040067