| Item Type |
Journal paper
|
| Abstract |
Motivated by the need of a positive-semidefinite estimator of multivariate realized covariance matrices, we model noisy and asynchronous ultra-high-frequency asset prices in a state-space framework with missing data. We then estimate the covariance matrix of the latent states through a Kalman smoother and Expectation Maximization (KEM) algorithm. Iterating between the two EM steps, we obtain a covariance matrix estimate which is robust to both asynchronicity and microstructure noise, and positive-semidefinite by construction. We show the performance of the KEM estimator using extensive Monte Carlo simulations that mimic the liquidity and market microstructure characteristics of the S&P 500 universe as well as in an high-dimensional application on US stocks. KEM provides very accurate covariance matrix estimates and significantly outperforms alternative approaches recently introduced in the literature. |
| Authors |
Corsi, Fulvio; Peluso, Stefano & Audrino, Francesco |
| Projects |
Fengler, Matthias; Buncic, Daniel & Audrino, Francesco
(2012)
Analysis and models of cross asset dependency structures in high-frequency data
[applied research project]
|
| Journal or Publication Title |
Journal of Applied Econometrics |
| Language |
English |
| Keywords |
High frequency data; Realized covariance matrix; Missing data; Kalman filter; EM algorithm. |
| Subjects |
economics |
| HSG Classification |
contribution to scientific community |
| HSG Profile Area |
SEPS - Quantitative Economic Methods |
| Refereed |
Yes |
| Date |
1 May 2015 |
| Publisher |
Wiley-Blackwell |
| Place of Publication |
Chichester |
| Volume |
30 |
| Number |
3 |
| Page Range |
377-397 |
| Number of Pages |
21 |
| ISSN |
0883-7252 |
| ISSN-Digital |
1099-1255 |
| Publisher DOI |
https://doi.org/10.1002/jae.2378 |
| Depositing User |
Prof. Ph.D Francesco Audrino
|
| Date Deposited |
21 Nov 2013 18:39 |
| Last Modified |
03 Jul 2022 00:23 |
| URI: |
https://www.alexandria.unisg.ch/publications/227469 |
Missing in Asynchronicity: A Kalman-EM Approach for Multivariate Realized Covariance Estimation
