Fourier volatility forecasting with high-frequency data and microstructure noise
β Scribed by Barucci, Emilio; Magno, Davide; Mancino, Maria Elvira
- Book ID
- 120630466
- Publisher
- Taylor and Francis Group
- Year
- 2012
- Tongue
- English
- Weight
- 415 KB
- Volume
- 12
- Category
- Article
- ISSN
- 1469-7688
No coin nor oath required. For personal study only.
π SIMILAR VOLUMES
## Abstract In the 24βhr foreign exchange market, Andersen and Bollerslev measure and forecast volatility using intraday returns rather than daily returns. Trading in equity markets only occurs during part of the day, and volatility during nontrading hours may differ from the volatility during trad
## Abstract Financial data series are often described as exhibiting two nonβstandard time series features. First, variance often changes over time, with alternating phases of high and low volatility. Such behaviour is well captured by ARCH models. Second, long memory may cause a slower decay of the
## Abstract We study intraday return volatility dynamics using a timeβvarying components approach, and the method is applied to analyze IBM intraday returns. Empirical evidence indicates that with three additive componentsβa timeβvarying mean of absolute returns and two cosine components with timeβ