Jump-robust volatility estimation using nearest neighbor truncation |
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Authors: | Torben G Andersen Dobrislav Dobrev Ernst Schaumburg |
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Institution: | 1. Northwestern University, NBER, CREATES, United States;2. Federal Reserve Board of Governors, United States;3. Federal Reserve Bank of New York, United States |
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Abstract: | We propose two new jump-robust estimators of integrated variance that allow for an asymptotic limit theory in the presence of jumps. Specifically, our MedRV estimator has better efficiency properties than the tripower variation measure and displays better finite-sample robustness to jumps and small (“zero”) returns. We stress the benefits of local volatility measures using short return blocks, as this greatly alleviates the downward biases stemming from rapid fluctuations in volatility, including diurnal (intraday) U-shape patterns. An empirical investigation of the Dow Jones 30 stocks and extensive simulations corroborate the robustness and efficiency properties of our nearest neighbor truncation estimators. |
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Keywords: | C14 C15 C22 C80 G10 |
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