O
Oliver Linton
Researcher at University of Cambridge
Publications - 447
Citations - 13008
Oliver Linton is an academic researcher from University of Cambridge. The author has contributed to research in topics: Estimator & Nonparametric statistics. The author has an hindex of 55, co-authored 425 publications receiving 12055 citations. Previous affiliations of Oliver Linton include University of Illinois at Urbana–Champaign & Yale University.
Papers
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Semiparametric Estimation of a Characteristic-Based Factor Model of Stock Returns
Gregory Connor,Oliver Linton +1 more
TL;DR: In this article, the authors developed a new estimation procedure for characteristic-based factor models of stock returns for UK and US common stocks using book-to-price ratio, market capitalization, and dividend yield.
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Semiparametric ultra-high dimensional model averaging of nonlinear dynamic time series
TL;DR: In this paper, the authors proposed two semi-parametric model averaging schemes for nonlinear dynamic time series regression models with a very large number of covariates including exogenous regressors and auto-regressive lags.
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Is there chaos in the world economy? : a nonparametric test using consistent standard errors
Mototsugu Shintani,Oliver Linton +1 more
TL;DR: In this article, the authors developed a formal test for chaos in a noisy system based on the consistent standard errors of the nonparametric Lyapunov exponent estimators, and applied it to international real output series.
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A closed-form estimator for the garch(1,1) model
Dennis Kristensen,Oliver Linton +1 more
TL;DR: In this article, a closed-form estimator for the linear GARCH(1,1) model is proposed, which can be easily implemented and does not require the use of any numerical optimization procedures or the choice of initial values of the conditional variance process.
Journal ArticleDOI
Is there Chaos in the World Economy? A Nonparametric Test Using Consistent Standard Errors
Mototsugu Shintani,Oliver Linton +1 more
TL;DR: In this paper, the authors developed a formal test for chaos in a noisy system based on the consistent standard errors of the nonparametric Lyapunov exponent estimators, which is one practical definition of chaos.