Forecasting S&P 500 volatility: Long memory, level shifts, leverage effects, day-of-the-week seasonality, and macroeconomic announcements

Martin Martens, Dick van Dijk and Michiel De Pooter

International Journal of Forecasting, 2009, vol. 25, issue 2, 282-303

Abstract: We evaluate the forecasting performance of time series models for realized volatility, which accommodate long memory, level shifts, leverage effects, day-of-the-week and holiday effects, as well as macroeconomic news announcements. Applying the models to daily realized volatility for the S&P 500 futures index, we find that explicitly accounting for these stylized facts of volatility improves out-of-sample forecast accuracy for horizons up to 20 days ahead. Capturing the long memory feature of realized volatility by means of a flexible high-order AR-approximation instead of a parsimonious but stringent fractionally integrated specification also leads to improvements in forecast accuracy, especially for longer horizon forecasts.

Keywords: Realized; volatility; Long; memory; Day-of-the-week; effect; Leverage; effect; Volatility; forecasting; Model; confidence; set; Macroeconomic; news; announcements (search for similar items in EconPapers)
Date: 2009
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Citations: View citations in EconPapers (104)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:intfor:v:25:y:2009:i:2:p:282-303

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