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pro vyhledávání: '"Oliver Linton"'
Autor:
Oliver Linton
Probability, Statistics and Econometrics provides a concise, yet rigorous, treatment of the field that is suitable for graduate students studying econometrics, very advanced undergraduate students, and researchers seeking to extend their knowledge of
Publikováno v:
The Economic Journal. 132:2615-2643
There is substantial uncertainty about the impact of quantitative easing on market liquidity. Identifying the impact is particularly challenging due to the potential for reverse causality, because liquidity considerations might affect quantitative ea
Publikováno v:
Journal of Econometrics.
Nonlinear dynamic modeling of spatio-temporal data is often a challenge, especially due to irregularly observed locations and location-wide nonstationarity. In this article we propose a semiparametric family of Dynamic Functional-coefficient Autoregr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a99b4a2992ccf239fe58c71c08c419d1
Autor:
OLIVER LINTON, Tom Auld
Publikováno v:
International Journal of Forecasting.
Autor:
Z. Merrick Li, Oliver Linton
Publikováno v:
Econometrica. 90:367-389
We introduce the Realized moMents of Disjoint Increments (ReMeDI) paradigm to measure microstructure noise (the deviation of the observed asset prices from the fundamental values caused by market imperfections). We propose consistent estimators of ar
Publikováno v:
Econometric Reviews. 40:709-727
We provide an estimator of the lower regression function and provide large sample properties for inference. We also propose a test of the hypothesis of positive expectation dependence and derive its limiting distribution under the null hypothesis and
Publikováno v:
Journal of Econometrics.
This paper studies a heterogeneous coefficient spatial factor model that separately addresses both common factor risks (strong cross-sectional dependence) and local dependency (weak cross-sectional dependence) in the equity returns. From the asset pr
Publikováno v:
Journal of Econometrics. 222:909-932
We study a class of nonparametric regression models that includes deterministic time trends and both stationary and nonstationary stochastic processes (whose shocks are allowed to be mutually correlated). We propose a unified approach to estimation b
Publikováno v:
Journal of Econometrics. 222:265-268