arXiv 2 Nov 2025 · Statistics — Methodology
arXiv:2511.00944 · PDF · DOI · OpenAlex · Extracted main text
We study the estimation of leverage effect and volatility of volatility by using high-frequency data with the presence of jumps. We first construct spot volatility estimator by using the empirical characteristic function of the high-frequency increments to deal with the effect of jumps, based on which the estimators of leverage effect and volatility of volatility are proposed. Compared with existing estimators, our method is valid under more general jumps, making it a better alternative for empirical applications. Under some mild conditions, the asymptotic normality of the estimators is established and consistent estimators of the limiting variances are proposed based on the estimation of volatility functionals. We conduct extensive simulation study to verify the theoretical results. The results demonstrate that our estimators have relative better performance than the existing ones, especially when the jump is of infinite variation. Besides, we apply our estimators to a real high-frequency dataset, which reveals nonzero leverage effect and volatility of volatility in the market.
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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 | Y. Aït-Sahalia and J. Jacod (2014) High-Frequency Financial Econometrics | 1.000 | 11 | 3 | 100% |
| 2 | Wang, Christina D and Mykland, Per A (2014) The estimation of leverage effect with high-frequency data | 1.000 | 8 | 3 | 100% |
| 3 | Vetter, Mathias (2015) Estimation of integrated volatility of volatility with applications to goodness-of-fit testing | 1.000 | 5 | 3 | 100% |
| 4 | Jean Jacod and Viktor Todorov (2014) Efficient Estimation of Integrated Volatility in Presence of Infinite Variation Jumps | 0.961 | 9 | 6 | 89% |
| 5 | A\"it-Sahalia, Yacine and Fan, Jianqing and Laeven, Roger JA and Wan… (2017) Estimation of the continuous and discontinuous leverage effects | 0.941 | 12 | 4 | 83% |
| 6 | Liu, Qiang and Liu, Yiqi and Liu, Zhi (2018) Estimating spot volatility in the presence of infinite variation jumps self | 0.862 | 25 | 5 | 64% |
| 7 | Kalnina, Ilze and Xiu, Dacheng (2017) Nonparametric estimation of the leverage effect: A trade-off between robustness and efficiency | 0.843 | 3 | 3 | 100% |
| 8 | Barndorff-Nielsen, Ole E and Veraart, Almut (2009) Stochastic volatility of volatility in continuous time | 0.737 | 3 | 2 | 100% |
| 9 | Jing, B. Y and Kong, X. B. and Liu, Z. and Mykland, P. A (2012) On the jump activity index for semimartingales self | 0.737 | 3 | 2 | 100% |
| 10 | Jacod, J. and Protter, P (2012) Discretization of Processes | 0.693 | 9 | 3 | 33% |
Showing the top 10 of 35 scored citations.