Realized Volatility Forecasting in the Presence of Time-Varying Noise
Observed high-frequency financial prices can be considered as having two components, a true price and a market microstructure noise perturbation. It is an empirical regularity, coherent with classical market microstructure theories of price determination, that the second moment of market microstructure noise is time-varying. We study the optimal, from a finite-sample forecast mean squared error (MSE) standpoint, frequency selection for realized variance in linear variance forecasting models with time-varying market microstructure noise. We show that the resulting sampling frequencies are generally considerably lower than those that would be optimally chosen when time-variation in the second moment of the noise is unaccounted for. These optimal, lower frequencies have the potential to translate into considerable out-of-sample MSE gains. When forecasting using high-frequency variance estimates, we recommend treating the relevant frequency as a parameter and evaluating it <italic>jointly</italic> with the parameters of the forecasting model. The proposed joint solution is robust to the features of the true price formation mechanism and generally applicable to a variety of forecasting models and high-frequency variance estimators, including those for which the typical choice variable is a smoothing parameter, rather than a frequency.
Year of publication: |
2013
|
---|---|
Authors: | Bandi, Federico M. ; Russell, Jeffrey R. ; Yang, Chen |
Published in: |
Journal of Business & Economic Statistics. - Taylor & Francis Journals, ISSN 0735-0015. - Vol. 31.2013, 3, p. 331-345
|
Publisher: |
Taylor & Francis Journals |
Saved in:
Online Resource
Saved in favorites
Similar items by person
-
Realized volatility forecasting and option pricing
Bandi, Federico M., (2008)
-
Realized volatility forecasting in the presence of time-varying noise
Bandi, Federico M., (2013)
-
Realized volatility forecasting and option pricing
Bandi, Federico M., (2008)
- More ...