Rolling-Sample Volatility Estimators
By E. Andreou, Eric Ghysels. 2002
125 citations recorded by the source corpus.
Subfields: Economics and Econometrics, Finance
View Paper: https://www.semanticscholar.org/paper/2109afc152324e9927c47c706b4b690574a64089
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Economics and Econometrics
- Tim Bollerslev
- N. Shephard
- Ole E. Barndorff-Nielsen
- Torben G. Andersen
- V. Todorov
- Nour Meddahi
- Andrew J. Patton
- Jeannette H. C. Woerner
In Finance
- N. Shephard
- Tim Bollerslev
- Ole E. Barndorff-Nielsen
- V. Todorov
- Torben G. Andersen
- Andrew J. Patton
- Mark Podolskij
- Nour Meddahi
Citations in the corpus
- Power variation and stochastic volatility: a review and some new results (2004, background): “…Andersen, Bollerslev, Diebold, and Labys (2001) due to the lack of appropriate theory for the sum of absolute returns as 8 t 0, although recently Andreou and Ghysels (2002) have performed some interesting Monte Carlo studies in this context, while Shiryaev (1999, pp. 349-350) and Maheswaran and…”
- Roughing It Up: Including Jump Components in the Measurement, Modeling, and Forecasting of Return Volatility (2007, unknown): “The related results for the realized variation measures in, for example, Bandi and Russell (2004, 2006), Hansen and Lunde (2006), and Zhang, Mykland, and Aı̈t-Sahalia (2005), should be helpful.”
- Estimation of integrated volatility in stochastic volatility models (2005, methodology): “by ( 5 ). For the second inequality we used that for p 1 applying |a + b|p”
- Variational sums and power variation: a unifying approach to model selection and estimation in semimartingale models (2003, background): “Furthermore, this implies that the quadratic variation is not a good estimate for the integrated volatility since it possesses an additional term coming from the jump component, as we can see in ( 6 ).”
- Correcting the errors: Volatility forecast evaluation using high-frequency data and realized volatilities (2005, background): “(see, e.g., the numerical calculations in Andreou and Ghysels, 2002, and Bai, Russell, and”
- Do High-Frequency Measures of Volatility Improve Forecasts of Return Distributions? (2011, unknown): “sen, Bollerslev, Diebold, and Ebens (2001), Andreou and Ghysels (2002) , Barndorfi-Nielsen and”
- Power and bipower variation with stochastic volatility and jumps (2003, background): “…and Andersen, Bollerslev, Diebold, and Labys (2001) due to the lack of appropriate theory for the sum of absolute returns as M → ∞, although recently Andreou and Ghysels (2002) have performed some interesting Monte Carlo studies in this context, while Shiryaev (1999, pp. 349–350) and Maheswaran…”