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Overnight GARCH-Itô Volatility Models

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

Abstract

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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45
references
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in-text mentions
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distinct cited
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Most heavily cited references

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.

ReferenceIntensityMentionsSectionsMain text
1Jacod, J., Li, Y., Mykland, P. A., Podolskij, M., and Vetter, M (2009) Microstructure noise in the continuous case: the pre-averaging approach1.00073100%
2Song, X., Kim, D., Yuan, H., Cui, X., Lu, Z., Zhou, Y., and Yazhen, W (2020) Volatility analysis with realized garch-ito models self1.00053100%
3Barndorff-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 noise1.00053100%
4Corsi, F (2009) A simple approximate long-memory model of realized volatility1.00053100%
5Hansen, P. R., Huang, Z., and Shek, H. H (2012) Realized garch: a joint model for returns and realized measures of volatility1.00053100%
6Kim, D. and Wang, Y (2016) Unified discrete-time and continuous-time models and statistical inferences for merged low-frequency and high-frequency financia… self1.00053100%
7Zhang, L (2006) Efficient estimation of stochastic volatility using noisy observations: A multi-scale approach1.00053100%
8Shephard, N. and Sheppard, K (2010) Realising the future: forecasting with high-frequency-based volatility (heavy) models0.73732100%
9Xiu, D (2010) Quasi-maximum likelihood estimation of volatility with high frequency data0.73732100%
10Zhang, X., Kim, D., and Wang, Y (2016) Jump variation estimation with noisy high frequency financial data via wavelets self0.73732100%

Showing the top 10 of 47 scored citations.