Anders Bredahl Kock
Names
| first: |
Anders |
| middle: |
Bredahl |
| last: |
Kock |
Identifer
Contact
Affiliations
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Aarhus Universitet
/ Institut for Økonomi
/ School of Economics and Management (weight: 5%)
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Oxford University
/ Department of Economics (weight: 90%)
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Aarhus Universitet
/ Institut for Økonomi
/ Center for Research in Econometric Analysis of Time Series (CREATES) (weight: 5%)
Research profile
author of:
- Forecasting with Universal Approximators and a Learning Algorithm (RePEc:aah:create:2009-18)
by Anders Bredahl Kock - Forecasting with nonlinear time series models (RePEc:aah:create:2010-01)
by Anders Bredahl Kock & Timo Teräsvirta - Oracle Efficient Variable Selection in Random and Fixed Effects Panel Data Models (RePEc:aah:create:2010-56)
by Anders Bredahl Kock - Forecasting Macroeconomic Variables using Neural Network Models and Three Automated Model Selection Techniques (RePEc:aah:create:2011-27)
by Anders Bredahl Kock & Timo Teräsvirta - Forecasting performance of three automated modelling techniques during the economic crisis 2007-2009 (RePEc:aah:create:2011-28)
by Anders Bredahl Kock & Timo Teräsvirta - On the Oracle Property of the Adaptive Lasso in Stationary and Nonstationary Autoregressions (RePEc:aah:create:2012-05)
by Anders Bredahl Kock - Oracle Inequalities for High Dimensional Vector Autoregressions (RePEc:aah:create:2012-16)
by Anders Bredahl Kock & Laurent A.F. Callot - Oracle Efficient Estimation and Forecasting with the Adaptive LASSO and the Adaptive Group LASSO in Vector Autoregressions (RePEc:aah:create:2012-38)
by Anders Bredahl Kock & Laurent A.F. Callot - Oracle inequalities for high-dimensional panel data models (RePEc:aah:create:2013-20)
by Anders Bredahl Kock - Lassoing the Determinants of Retirement (RePEc:aah:create:2013-21)
by Malene Kallestrup-Lamb & Anders Bredahl Kock & Johannes Tang Kristensen - Oracle Inequalities for Convex Loss Functions with Non-Linear Targets (RePEc:aah:create:2013-51)
by Mehmet Caner & Anders Bredahl Kock - Asymptotically Honest Confidence Regions for High Dimensional Parameters by the Desparsified Conservative Lasso (RePEc:aah:create:2014-36)
by Mehmet Caner & Anders Bredahl Kock - Estimation and Forecasting of Large Realized Covariance Matrices and Portfolio Choice (RePEc:aah:create:2014-42)
by Laurent A. F. Callot & Anders B. Kock & Marcelo C. Medeiros - Inference in High-dimensional Dynamic Panel Data Models (RePEc:aah:create:2014-58)
by Anders Bredahl Kock & Haihan Tang - Sharp Threshold Detection Based on Sup-norm Error rates in High-dimensional Models (RePEc:aah:create:2015-10)
by Laurent Callot & Mehmet Caner & Anders Bredahl Kock & Juan Andres Riquelme - Inference in partially identified models with many moment inequalities using Lasso (RePEc:aah:create:2016-12)
by Federico A. Bugni & Mehmet Caner & Anders Bredahl Kock & Soumendra Lahiri - Optimal sequential treatment allocation (RePEc:arx:papers:1705.09952)
by Anders Bredahl Kock & Martin Thyrsgaard - Functional Sequential Treatment Allocation (RePEc:arx:papers:1812.09408)
by Anders Bredahl Kock & David Preinerstorfer & Bezirgen Veliyev - Functional Sequential Treatment Allocation with Covariates (RePEc:arx:papers:2001.10996)
by Anders Bredahl Kock & David Preinerstorfer & Bezirgen Veliyev - Treatment recommendation with distributional targets (RePEc:arx:papers:2005.09717)
by Anders Bredahl Kock & David Preinerstorfer & Bezirgen Veliyev - Superconsistency of Tests in High Dimensions (RePEc:arx:papers:2106.03700)
by Anders Bredahl Kock & David Preinerstorfer - A Ridge-Regularised Jackknifed Anderson-Rubin Test (RePEc:arx:papers:2209.03259)
by Max-Sebastian Dov`i & Anders Bredahl Kock & Sophocles Mavroeidis - Moment-dependent phase transitions in high-dimensional Gaussian approximations (RePEc:arx:papers:2310.12863)
by Anders Bredahl Kock & David Preinerstorfer - Regularizing Discrimination in Optimal Policy Learning with Distributional Targets (RePEc:arx:papers:2401.17909)
by Anders Bredahl Kock & David Preinerstorfer - Forecasting with Universal Approximators and a Learning Algorithm (RePEc:bpj:jtsmet:v:3:y:2011:i:3:n:3)
by Kock Anders Bredahl - Oracle Efficient Variable Selection In Random And Fixed Effects Panel Data Models (RePEc:cup:etheor:v:29:y:2013:i:01:p:115-152_00)
by Kock, Anders Bredahl - Consistent And Conservative Model Selection With The Adaptive Lasso In Stationary And Nonstationary Autoregressions (RePEc:cup:etheor:v:32:y:2016:i:01:p:243-259_00)
by Kock, Anders Bredahl - Uniform Inference In High-Dimensional Dynamic Panel Data Models With Approximately Sparse Fixed Effects (RePEc:cup:etheor:v:35:y:2019:i:02:p:295-359_00)
by Kock, Anders Bredahl & Tang, Haihan - Power in High-dimensional testing Problems (RePEc:eca:wpaper:2013/260442)
by Anders Bredahl Kock & David Preinerstorfer - Oracle inequalities for high dimensional vector autoregressions (RePEc:eee:econom:v:186:y:2015:i:2:p:325-344)
by Kock, Anders Bredahl & Callot, Laurent - Oracle inequalities, variable selection and uniform inference in high-dimensional correlated random effects panel data models (RePEc:eee:econom:v:195:y:2016:i:1:p:71-85)
by Kock, Anders Bredahl - Asymptotically honest confidence regions for high dimensional parameters by the desparsified conservative Lasso (RePEc:eee:econom:v:203:y:2018:i:1:p:143-168)
by Caner, Mehmet & Kock, Anders Bredahl - Treatment recommendation with distributional targets (RePEc:eee:econom:v:234:y:2023:i:2:p:624-646)
by Kock, Anders Bredahl & Preinerstorfer, David & Veliyev, Bezirgen - Forecasting performances of three automated modelling techniques during the economic crisis 2007–2009 (RePEc:eee:intfor:v:30:y:2014:i:3:p:616-631)
by Kock, Anders Bredahl & Teräsvirta, Timo - Forecasting the Finnish Consumer Price Inflation Using Artificial Neural Network Models and Three Automated Model Selection Techniques (RePEc:fep:journl:v:26:y:2013:i:1:p:13-24)
by Anders Bredahl Kock & Timo Teräsvirta - Oracle Inequalities for Convex Loss Functions with Nonlinear Targets (RePEc:taf:emetrv:v:35:y:2016:i:8-10:p:1377-1411)
by Mehmet Caner & Anders Bredahl Kock - Lassoing the Determinants of Retirement (RePEc:taf:emetrv:v:35:y:2016:i:8-10:p:1522-1561)
by Malene Kallestrup-Lamb & Anders Bredahl Kock & Johannes Tang Kristensen - Forecasting Macroeconomic Variables Using Neural Network Models and Three Automated Model Selection Techniques (RePEc:taf:emetrv:v:35:y:2016:i:8-10:p:1753-1779)
by Anders Bredahl Kock & Timo Teräsvirta - Functional Sequential Treatment Allocation (RePEc:taf:jnlasa:v:117:y:2022:i:539:p:1311-1323)
by Anders Bredahl Kock & David Preinerstorfer & Bezirgen Veliyev - Sharp Threshold Detection Based on Sup-Norm Error Rates in High-Dimensional Models (RePEc:taf:jnlbes:v:35:y:2017:i:2:p:250-264)
by Laurent Callot & Mehmet Caner & Anders Bredahl Kock & Juan Andres Riquelme - Estimation and Forecasting of Large Realized Covariance Matrices and Portfolio Choice (RePEc:tin:wpaper:20140147)
by Laurent Callot & Anders B. Kock & Marcelo C. Medeiros - Sharp Threshold Detection based on Sup-Norm Error Rates in High-dimensional Models (RePEc:tin:wpaper:20150019)
by Laurent Callot & Mehmet Caner & Anders Bredahl Kock & Juan Andres Riquelme - Power in High‐Dimensional Testing Problems (RePEc:wly:emetrp:v:87:y:2019:i:3:p:1055-1069)
by Anders Bredahl Kock & David Preinerstorfer - Modeling and Forecasting Large Realized Covariance Matrices and Portfolio Choice (RePEc:wly:japmet:v:32:y:2017:i:1:p:140-158)
by Laurent A. F. Callot & Anders B. Kock & Marcelo C. Medeiros