Publication Type
Journal Article
Version
publishedVersion
Publication Date
5-2019
Abstract
We develop tests for deciding whether a large cross-section of asset prices obey an exact factor structure at the times of factor jumps. Such jump dependence is implied by standard linear factor models. Our inference is based on a panel of asset returns with asymptotically increasing cross-sectional dimension and sampling frequency, and essentially no restriction on the relative magnitude of these two dimensions of the panel. The test is formed from the high-frequency returns at the times when the risk factors are detected to have a jump. The test statistic is a cross-sectional average of a measure of discrepancy in the estimated jump factor loadings of the assets at consecutive jump times. Under the null hypothesis, the discrepancy in the factor loadings is due to a measurement error, which shrinks with the increase of the sampling frequency, while under an alternative of a noisy jump factor model this discrepancy contains also nonvanishing firm-specific shocks. The limit behavior of the test under the null hypothesis is nonstandard and reflects the strong-dependence in the cross-section of returns as well as their heteroskedasticity which is left unspecified. We further develop estimators for assessing the magnitude of firm-specific risk in asset prices at the factor jump events. Empirical application to S&P 100 stocks provides evidence for exact one-factor structure at times of big market-wide jump events
Keywords
Factor model, panel high-frequency data, jumps, semimartingale, specification test, stochastic volatility
Discipline
Econometrics
Research Areas
Econometrics
Publication
Quantitative Economics
Volume
10
Issue
2
First Page
419
Last Page
456
ISSN
1759-7323
Identifier
10.3982/QE1060
Publisher
Econometric Society
Citation
LI, Jia; TODOROV, Viktor; and TAUCHEN, George..
Jump factor models in large cross-sections. (2019). Quantitative Economics. 10, (2), 419-456.
Available at: https://ink.library.smu.edu.sg/soe_research/2587
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Additional URL
https://doi.org/10.3982/QE1060