An improved two-step regularization scheme for spot volatility estimation
We are concerned with the problem of parameter estimation in Finance, namely the estimation of the spot volatility in the presence of the so-called microstructure noise. In  a scheme based on the technique of multi-step regularization was presented. It was shown that this scheme can work in a real-time manner. However, the main drawback of this scheme is that it needs a lot of observation data. The aim of the present paper is to introduce an improvement of the scheme such that the modified estimator can work more efficiently and with a data set of smaller size. The technical aspects of implementation of the scheme and its performance on simulated data are analyzed. The proposed scheme is tested against other estimators, namely a realized volatility type estimator, the Fourier estimator and two kernel estimators.
|Date of creation:||2008|
|Date of revision:|
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- Morten Ørregaard Nielsen & Per Houmann Frederiksen, 2005.
"Finite Sample Accuracy of Integrated Volatility Estimators,"
1225, Queen's University, Department of Economics.
- Nielsen, Morten Ørregaard & Frederiksen, Per, 2008. "Finite sample accuracy and choice of sampling frequency in integrated volatility estimation," Journal of Empirical Finance, Elsevier, vol. 15(2), pages 265-286, March.
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