Donggyu Kim, Minseok Shin, Yazhen Wang
arXiv 24 Feb 2021 · Finance — Statistical Finance · publishedJournal of Business and Economic Statistics (2022) · 8 citations (OpenAlex)
arXiv:2102.13467 · PDF · DOI · OpenAlex · Extracted main text
Various parametric volatility models for financial data have been developed to incorporate high-frequency realized volatilities and better capture market dynamics. However, because high-frequency trading data are not available during the close-to-open period, the volatility models often ignore volatility information over the close-to-open period and thus may suffer from loss of important information relevant to market dynamics. In this paper, to account for whole-day market dynamics, we propose an overnight volatility model based on It\^o diffusions to accommodate two different instantaneous volatility processes for the open-to-close and close-to-open periods. We develop a weighted least squares method to estimate model parameters for two different periods and investigate its asymptotic properties. We conduct a simulation study to check the finite sample performance of the proposed model and method. Finally, we apply the proposed approaches to real trading data.
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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 | Jacod, J., Li, Y., Mykland, P. A., Podolskij, M., and Vetter, M (2009) Microstructure noise in the continuous case: the pre-averaging approach | 1.000 | 7 | 3 | 100% |
| 2 | Song, X., Kim, D., Yuan, H., Cui, X., Lu, Z., Zhou, Y., and Yazhen, W (2020) Volatility analysis with realized garch-ito models self | 1.000 | 5 | 3 | 100% |
| 3 | Barndorff-Nielsen, O. E., Hansen, P. R., Lunde, A., and Shephard, N (2008) Designing realized kernels to measure the ex post variation of equity prices in the presence of noise | 1.000 | 5 | 3 | 100% |
| 4 | Corsi, F (2009) A simple approximate long-memory model of realized volatility | 1.000 | 5 | 3 | 100% |
| 5 | Hansen, P. R., Huang, Z., and Shek, H. H (2012) Realized garch: a joint model for returns and realized measures of volatility | 1.000 | 5 | 3 | 100% |
| 6 | Kim, D. and Wang, Y (2016) Unified discrete-time and continuous-time models and statistical inferences for merged low-frequency and high-frequency financia… self | 1.000 | 5 | 3 | 100% |
| 7 | Zhang, L (2006) Efficient estimation of stochastic volatility using noisy observations: A multi-scale approach | 1.000 | 5 | 3 | 100% |
| 8 | Shephard, N. and Sheppard, K (2010) Realising the future: forecasting with high-frequency-based volatility (heavy) models | 0.737 | 3 | 2 | 100% |
| 9 | Xiu, D (2010) Quasi-maximum likelihood estimation of volatility with high frequency data | 0.737 | 3 | 2 | 100% |
| 10 | Zhang, X., Kim, D., and Wang, Y (2016) Jump variation estimation with noisy high frequency financial data via wavelets self | 0.737 | 3 | 2 | 100% |
Showing the top 10 of 47 scored citations.