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Inference theory for volatility functional dependencies

Publication ,  Journal Article
Li, J; Todorov, V; Tauchen, G
Published in: Journal of Econometrics
July 1, 2016

We develop inference theory for models involving possibly nonlinear transforms of the elements of the spot covariance matrix of a multivariate continuous-time process observed at high frequency. The framework can be used to study the relationship among the elements of the latent spot covariance matrix and processes defined on the basis of it such as systematic and idiosyncratic variances, factor betas and correlations on a fixed interval of time. The estimation is based on matching model-implied moment conditions under the occupation measure induced by the spot covariance process. We prove consistency and asymptotic mixed normality of our estimator of the (random) coefficients in the volatility model and further develop model specification tests. We apply our inference methods to study variance and correlation risks in nine sector portfolios comprising the S&P 500 index. We document sector-specific variance risks in addition to that of the market and time-varying heterogeneous correlation risk among the market-neutral components of the sector portfolio returns.

Duke Scholars

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Published In

Journal of Econometrics

DOI

EISSN

1872-6895

ISSN

0304-4076

Publication Date

July 1, 2016

Volume

193

Issue

1

Start / End Page

17 / 34

Related Subject Headings

  • Econometrics
  • 4905 Statistics
  • 3802 Econometrics
  • 3801 Applied economics
  • 1403 Econometrics
  • 1402 Applied Economics
  • 0104 Statistics
 

Citation

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Li, J., Todorov, V., & Tauchen, G. (2016). Inference theory for volatility functional dependencies. Journal of Econometrics, 193(1), 17–34. https://doi.org/10.1016/j.jeconom.2016.01.004
Li, J., V. Todorov, and G. Tauchen. “Inference theory for volatility functional dependencies.” Journal of Econometrics 193, no. 1 (July 1, 2016): 17–34. https://doi.org/10.1016/j.jeconom.2016.01.004.
Li J, Todorov V, Tauchen G. Inference theory for volatility functional dependencies. Journal of Econometrics. 2016 Jul 1;193(1):17–34.
Li, J., et al. “Inference theory for volatility functional dependencies.” Journal of Econometrics, vol. 193, no. 1, July 2016, pp. 17–34. Scopus, doi:10.1016/j.jeconom.2016.01.004.
Li J, Todorov V, Tauchen G. Inference theory for volatility functional dependencies. Journal of Econometrics. 2016 Jul 1;193(1):17–34.
Journal cover image

Published In

Journal of Econometrics

DOI

EISSN

1872-6895

ISSN

0304-4076

Publication Date

July 1, 2016

Volume

193

Issue

1

Start / End Page

17 / 34

Related Subject Headings

  • Econometrics
  • 4905 Statistics
  • 3802 Econometrics
  • 3801 Applied economics
  • 1403 Econometrics
  • 1402 Applied Economics
  • 0104 Statistics