## Abstract How to measure and model volatility is an important issue in finance. Recent research uses highโfrequency intraday data to construct __ex post__ measures of daily volatility. This paper uses a Bayesian modelโaveraging approach to forecast realized volatility. Candidate models include au
Modelling and forecasting multivariate realized volatility
โ Scribed by Roxana Chiriac; Valeri Voev
- Publisher
- John Wiley and Sons
- Year
- 2010
- Tongue
- English
- Weight
- 288 KB
- Volume
- 26
- Category
- Article
- ISSN
- 0883-7252
- DOI
- 10.1002/jae.1152
No coin nor oath required. For personal study only.
โฆ Synopsis
This paper proposes a methodology for dynamic modelling and forecasting of realized covariance matrices based on fractionally integrated processes. The approach allows for flexible dependence patterns and automatically guarantees positive definiteness of the forecast. We provide an empirical application of the model, which shows that it outperforms other approaches in the extant literature, both in terms of statistical precision as well as in terms of providing a superior mean-variance trade-off in a classical investment decision setting.
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