José E. Figueroa-López, Bei Wu
arXiv 4 Apr 2020 · Econometrics · publishedEconometric Theory (2022) · 18 citations (OpenAlex)
arXiv:2004.01865 · PDF · DOI · OpenAlex · Extracted main text
We first revisit the problem of estimating the spot volatility of an It\^o semimartingale using a kernel estimator. We prove a Central Limit Theorem with optimal convergence rate for a general two-sided kernel. Next, we introduce a new pre-averaging/kernel estimator for spot volatility to handle the microstructure noise of ultra high-frequency observations. We prove a Central Limit Theorem for the estimation error with an optimal rate and study the optimal selection of the bandwidth and kernel functions. We show that the pre-averaging/kernel estimator's asymptotic variance is minimal for exponential kernels, hence, justifying the need of working with kernels of unbounded support as proposed in this work. We also develop a feasible implementation of the proposed estimators with optimal bandwidth. Monte Carlo experiments confirm the superior performance of the devised method.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Yu, C., Fang, Y., Li, Z., Zhang, B., & Zhao, X (2014) Kernel Filtering of Spot Volatility in Presence of Lévy Jumps and Market Microstructure Noise | 1.000 | 8 | 3 | 100% |
| 2 | Jacod, J., Li, Y., Mykland, P. A., Podolskij, M. & Vetter, M (2009) Microstructure noise in the continuous case: the pre-averaging approach | 1.000 | 6 | 3 | 100% |
| 3 | Zhang, L., Mykland, P. A. & Aït-Sahalia, Y (2005) A tale of two time scales: Determining integrated volatility with noisy high-frequency data | 1.000 | 6 | 3 | 100% |
| 4 | Kristensen, D (2010) Nonparametric filtering of the realized spot volatility: A kernel-based approach | 1.000 | 5 | 3 | 100% |
| 5 | Figueroa-López, J.E. & Li, C (2020) Optimal kernel estimation of spot volatility of stochastic differential equations | 0.974 | 13 | 5 | 92% |
| 6 | Aït-Sahalia, Y. & Jacod, J (2014) High-frequency financial econometrics | 0.888 | 10 | 4 | 70% |
| 7 | Zu, Y. & Boswijk, H. P (2014) Estimating spot volatility with high-frequency financial data | 0.874 | 11 | 2 | 100% |
| 8 | Yu, C., Fang, Y., Li, Z., Zhang, B., & Zhao, X (2014) Non-parametric estimation of high-frequency spot volatility for Brownian semimartingale with jumps | 0.874 | 6 | 2 | 100% |
| 9 | Chen, R. Y (2019) Inference for volatility functionals of multivariate Blue Itô semimartingales observed with jump and noise | 0.830 | 7 | 4 | 57% |
| 10 | Barndorff-Nielsen, O. E., Hansen, P. R., Lunde, A. & Shephard, N (2008) Designing realized kernels to measure the ex post variation of equity prices in the presence of noise | 0.737 | 3 | 2 | 100% |
Showing the top 10 of 40 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | Estimating spot volatility under infinite variation jumps with dependent market microstructure noise | 1.000 | 13 | 3 |
| 2 | Estimation of Integrated Volatility Functionals with Kernel Spot Volatility Estimators | 0.843 | 4 | 3 |