Carsten H. Chong, Viktor Todorov
arXiv 6 May 2023 · Econometrics · publishedJournal of Econometrics (2024) · 9 citations (OpenAlex)
arXiv:2305.04137 · PDF · DOI · OpenAlex · Extracted main text
We propose model-free (nonparametric) estimators of the volatility of volatility and leverage effect using high-frequency observations of short-dated options. At each point in time, we integrate available options into estimates of the conditional characteristic function of the price increment until the options' expiration and we use these estimates to recover spot volatility. Our volatility of volatility estimator is then formed from the sample variance and first-order autocovariance of the spot volatility increments, with the latter correcting for the bias in the former due to option observation errors. The leverage effect estimator is the sample covariance between price increments and the estimated volatility increments. The rate of convergence of the estimators depends on the diffusive innovations in the latent volatility process as well as on the observation error in the options with strikes in the vicinity of the current spot price. Feasible inference is developed in a way that does not require prior knowledge of the source of estimation error that is asymptotically dominating.
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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 | I. Kalnina and D. Xiu (2017) Nonparametric estimation of the leverage effect: A trade-off between robustness and efficiency | 1.000 | 8 | 3 | 100% |
| 2 | T. G. Andersen, O. Bondarenko, and M. T. Gonzalez-Perez (2015) Exploring return dynamics via corridor implied volatility | 1.000 | 5 | 3 | 100% |
| 3 | V. Todorov (2019) Nonparametric spot volatility from options | 0.956 | 8 | 5 | 88% |
| 4 | V. Todorov and Y. Zhang (2023) Bias reduction in spot volatility estimation from options | 0.843 | 3 | 3 | 100% |
| 5 | M. Vetter (2015) Estimation of integrated volatility of volatility with applications to goodness-of-fit testing | 0.811 | 4 | 2 | 100% |
| 6 | C. H. Chong and V. Todorov (2023) Asymptotic expansions for high-frequency option data self | 0.737 | 5 | 3 | 40% |
| 7 | Y. Aẗ-Sahalia, J. Fan, R. J. A. Laeven, C. D. Wang, and X. Yang (2017) Estimation of the continuous and discontinuous leverage effects | 0.737 | 3 | 2 | 100% |
| 8 | C. D. Wang and P. A. Mykland (2014) The estimation of leverage effect with high-frequency data | 0.737 | 3 | 2 | 100% |
| 9 | Y. Li, G. Liu, and Z. Zhang (2022) Volatility of volatility: Estimation and tests based on noisy high frequency data with jumps | 0.737 | 3 | 2 | 100% |
| 10 | D. Duffie, J. Pan, and K. Singleton (2000) Transform Analysis and Asset Pricing for Affine Jump-Diffusions | 0.644 | 2 | 2 | 100% |
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