Asymptotic equivalence and sufficiency for volatility estimation under microstructure noise
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The basic model for high-frequency data in finance is considered,
where an efficient price process is observed under microstructure
noise. It is shown that this nonparametric model is in Le Cam’s sense
asymptotically equivalent to a Gaussian shift experiment in terms of
the square root of the volatility function $\sigma$. As an
application, simple rate-optimal estimators of the volatility and
efficient estimators of the integrated volatility are constructed.
http://www.mathematik.hu-berlin.de/~mreiss/
This talk is part of the Statistics series.
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