Volatility Forecasting and Microstructure Noise

By Eric Ghysels, A. Sinko. 2011

93 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/efb708b10a5e12940f3e32a8d59b73441151e5b5

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

1. S. J. Koopman
2. Tim Bollerslev
3. Andrew J. Patton
4. Marcel Scharth
5. Torben G. Andersen
6. Kevin Sheppard
7. Nour Meddahi
8. R. Quaedvlieg

In Finance

1. Andrew J. Patton
2. S. J. Koopman
3. Tim Bollerslev
4. Marcel Scharth
5. Torben G. Andersen
6. Kevin Sheppard
7. Nour Meddahi
8. R. Quaedvlieg

Citations in the corpus

• Exploiting the errors: A simple approach for improved volatility forecasting (2016, background): “Forecasting in the presence of microstructure ‘‘noise’’ has also been studied by Aït-Sahalia and Mancini (2008), Andersen et al. (2011), Ghysels and Sinko (2011) and Bandi et al. (2013).”
• Do High-Frequency Measures of Volatility Improve Forecasts of Return Distributions? (2011, unknown): “Examples include Andersen, Bollerslev, Diebold, and Labys (2003), Andersen, Bollerslev, and Diebold (2007), Andersen, Bollerslev, and Meddahi (2004), Ghysels and Sinko (2006), Ghysels, Santa-Clara, and Valkanov (2006), Koopman, Jungbacker, and Hol (2005), Maheu and McCurdy (2002, 2007), Martens,…”
• Can Internet search queries help to predict stock market volatility (2016, unknown): “We compute these price changes over 10 minute intervals in order to circumvent the well-documented microstructure effects (see e.g. Andersen et al. 2003, Andersen, Bollerslev and Meddahi 2011, Ghysels and Sinko 2011).”
• Realized volatility forecasting and market microstructure noise (2011, methodology): “Consequently, maximizing this R is equivalent to minimizing the variance of V ar[RVt(h)], as first noted out by Ghysels and Sinko (2006). To minimize this variance, we follow Jacod and Protter (1998), BarndorffNielsen and Shephard (2002), and Meddahi (2002a), in approximating the variance of the cor”
• The Analysis of Stochastic Volatility in the Presence of Daily Realised Measures (2011, methodology): “For example, microstructure noise may distort predictive accuracy; see, for example, Andersen, Bollerslev, and Meddahi (2011a), Ghysels and Sinko (2011) and Asai, McAleer, and Medeiros (2012). Additionally, jump robust estimates such as the median-RV measure are less noisy and may produce better pre”