Intraday Forecasts of a Volatility Index: Functional Time Series Methods with Dynamic Updating

Han Lin Shang, Yang Yang, Fearghal Kearney

Research output: Contribution to journalArticle

1 Citation (Scopus)
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Abstract

As a forward-looking measure of future equity market volatility, the VIX index has gained immense popularity in recent years to become a key measure of risk for market analysts and academics. We consider discrete reported intraday VIX tick values as realisations of a collection of curves observed sequentially on equally spaced and dense grids over time and utilise functional data analysis techniques to produce one-day-ahead forecasts of these curves. The proposed method facilitates the investigation of dynamic changes in the index over very short time intervals as showcased using the 15-second high-frequency VIX index values. With the help of dynamic updating techniques, our point and interval forecasts are shown to enjoy improved accuracy over conventional time series models.
Original languageEnglish
Number of pages24
JournalAnnals of Operations Research
Early online date07 Dec 2018
DOIs
Publication statusEarly online date - 07 Dec 2018

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