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Nonparametric estimation of infinite order regression and its application to the risk-return tradeoff (2018)
Journal Article
Hong, S. Y., & Linton, O. (in press). Nonparametric estimation of infinite order regression and its application to the risk-return tradeoff . Journal of Econometrics,

This paper studies nonparametric estimation of the infinite order regression E(Y k t |F t−1), k ∈ Z with stationary and weakly dependent data. We propose a Nadaraya-Watson type estimator that operates with an infinite number of conditioning variables... Read More about Nonparametric estimation of infinite order regression and its application to the risk-return tradeoff .

An investigation into multivariate variance ratio statistics and their application to stock market predictability (2017)
Journal Article
Hong, S., Linton, O., & Zhang, H. (2017). An investigation into multivariate variance ratio statistics and their application to stock market predictability. Journal of Financial Econometrics, 15(2), (173-222). doi:10.1093/jjfinec/nbw014. ISSN 1479-8409

We propose several multivariate variance ratio statistics for “testing” the weak form Efficient Market Hypothesis and for measuring the direction and magnitude of departures from this hypothesis. We derive the asymptotic distribution of the statistic... Read More about An investigation into multivariate variance ratio statistics and their application to stock market predictability.

Small deviations in L2-norm for Gaussian dependent sequences (2016)
Journal Article
Young Hong, S., Lifshits, M., & Nazarov, A. (2016). Small deviations in L2-norm for Gaussian dependent sequences. Electronic Communications in Probability, 21(41), (1-9). doi:10.1214/16-ECP4708. ISSN 1083-589X

Let be a centered Gaussian stationary sequence satisfying some minor regularity condition. We study the asymptotic behavior of its weighted -norm small deviation probabilities. It is shown that whenever using the arguments based on the spectral theor... Read More about Small deviations in L2-norm for Gaussian dependent sequences.

Estimating the quadratic covariation matrix for asynchronously observed high frequency stock returns corrupted by additive measurement error (2015)
Journal Article
Park, S., Young Hong, S., & Linton, O. (2016). Estimating the quadratic covariation matrix for asynchronously observed high frequency stock returns corrupted by additive measurement error. Journal of Econometrics, 191(2), (325-347). doi:10.1016/j.jeconom.2015.12.005. ISSN 0304-4076

This paper studies the estimation problem of the covariance matrices of asset returns in the presence of microstructure noise and asynchronicity between the observations across different assets. Motivated by Malliavin and Mancino (2002, 2009) we prop... Read More about Estimating the quadratic covariation matrix for asynchronously observed high frequency stock returns corrupted by additive measurement error.