SeminarsEstimation Of Integrated Covolatility For Non-synchronous Assets In The Presence Of Microstructure Noise
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The use of high-frequency return data has led to dramatic improvements in both theoretical and applied finance research. Estimators of covariance among multiple processes have been proposed, such as realized variance and Hayashi-Yoshida estimator. We are introducing our new estimator, the random lead-lag (RLL) estimator, which coincides with the Hayashi-Yoshida estimator at very high frequency. We studied the performance of RLL estimator both with and without microstructure noise for non-synchronous data and obtained the optimal estimator with good bias-variance trade-off. Our result is confirmed by simulation. We also applied our method to stock data from Nasdaq Exchange (1990).
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Qiuyan Xu
2008-10-31
13:30:00 - 15:00:00
405 , Mathematics Research Center Building (ori. New Math. Bldg.)
The use of high-frequency return data has led to dramatic improvements in both theoretical and applied finance research. Estimators of covariance among multiple processes have been proposed, such as realized variance and Hayashi-Yoshida estimator. We are introducing our new estimator, the random lead-lag (RLL) estimator, which coincides with the Hayashi-Yoshida estimator at very high frequency. We studied the performance of RLL estimator both with and without microstructure noise for non-synchronous data and obtained the optimal estimator with good bias-variance trade-off. Our result is confirmed by simulation. We also applied our method to stock data from Nasdaq Exchange (1990).