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- W2106206078 abstract "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 a new estimator, random lead-lag estimator (RLLE), which coincides with the Hayashi-Yoshida estimator at very high frequency and with the realized covariance at low frequency. We studied the performance of RLLE both with and without microstructure noise for non-synchronous data and obtained the optimal estimation with good bias-variance trade-off. Our result is conformed by simulation and real data applications in stock and online auction markets." @default.
- W2106206078 created "2016-06-24" @default.
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- W2106206078 date "2007-01-01" @default.
- W2106206078 modified "2023-09-24" @default.
- W2106206078 title "Estimation of Integrated Covolatility for Asynchronous Assets in the Presence of Microstructure Noise" @default.
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- W2106206078 doi "https://doi.org/10.2139/ssrn.1014171" @default.
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