Copula Estimation for Nonsynchronous Financial Data
Author:
Publisher
Springer Science and Business Media LLC
Subject
Applied Mathematics,Statistics, Probability and Uncertainty,Statistics and Probability
Link
https://link.springer.com/content/pdf/10.1007/s13571-022-00276-3.pdf
Reference27 articles.
1. Aït-Sahalia, Y., Fan, J. and Xiu, D. (2010). High-frequency covariance estimates with noisy and asynchronous financial data. Journal of the American Statistical Association 105, 492, 1504–1517.
2. Ait-Sahalia, Y., Mykland, P.A. and Zhang, L. (2005). How often to sample a continuous-time process in the presence of market microstructure noise. The Review of Financial Studies 18, 2, 351–416.
3. Barndorff-Nielsen, O.E., Hansen, P.R., Lunde, A. and Shephard, N. (2011). Multivariate realised kernels: consistent positive semi-definite estimators of the covariation of equity prices with noise and non-synchronous trading. Journal of Econometrics 162, 2, 149–169.
4. Breymann, W., Dias, A. and Embrechts, P. (2003). Dependence structures for multivariate high-frequency data in finance. Quantitative Finance 3(1), 1–14.
5. Buccheri, G., Bormetti, G., Corsi, F. and Lillo, F. (2020). A score-driven conditional correlation model for noisy and asynchronous data: An application to high-frequency covariance dynamics. Journal of Business & Economic Statistics, 1–17.
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1. Major Issues in High-frequency Financial Data Analysis: A Survey of Solutions;SSRN Electronic Journal;2024
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