Anders Bredahl Kock : Citation Profile

Are you Anders Bredahl Kock?

Oxford University (90% share)
Aarhus Universitet (5% share)
Aarhus Universitet (5% share)

7

H index

4

i10 index

148

Citations

RESEARCH PRODUCTION:

14

Articles

21

Papers

RESEARCH ACTIVITY:

   10 years (2009 - 2019). See details.
   Cites by year: 14
   Journals where Anders Bredahl Kock has often published
   Relations with other researchers
   Recent citing documents: 65.    Total self citations: 16 (9.76 %)

MORE DETAILS IN:
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   Permalink: http://citec.repec.org/pko276
   Updated: 2020-05-23    RAS profile: 2019-11-11    
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Relations with other researchers

Works with:

Caner, Mehmet (8)

Callot, Laurent (7)

Medeiros, Marcelo (3)

Teräsvirta, Timo (2)

Authors registered in RePEc who have co-authored more than one work in the last five years with Anders Bredahl Kock.

Is cited by:

Barigozzi, Matteo (10)

Audrino, Francesco (10)

Claveria, Oscar (10)

Smeekes, Stephan (7)

Camponovo, Lorenzo (7)

Medeiros, Marcelo (7)

Brownlees, Christian (4)

Hallin, Marc (4)

Mogliani, Matteo (4)

Chernozhukov, Victor (4)

LINTON, OLIVER (3)

Cites to:

Fan, Jianqing (22)

Chernozhukov, Victor (11)

Leeb, Hannes (10)

Pötscher, Benedikt (10)

Teräsvirta, Timo (8)

Tetenov, Aleksey (7)

Caner, Mehmet (7)

Hansen, Christian (7)

Hansen, Bruce (6)

Hallin, Marc (5)

Marcellino, Massimiliano (5)

Main data

Where Anders Bredahl Kock has published?

Journals with more than one article published# docs
Econometric Reviews3
Journal of Econometrics3
Econometric Theory2

Working Papers Series with more than one paper published# docs
Papers / arXiv.org2
Tinbergen Institute Discussion Papers / Tinbergen Institute2

Recent works citing Anders Bredahl Kock (2020 and 2019)

YearTitle of citing document
2017“Regional tourism demand forecasting with machine learning models: Gaussian process regression vs. neural network models in a multiple-input multiple-output setting”. (2017). Claveria, Oscar ; Monte, Enric ; Torra, Salvador. In: AQR Working Papers. RePEc:aqr:wpaper:201701.

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2020On LASSO for Predictive Regression. (2018). Lee, Ji Hyung ; Gao, Zhan ; Shi, Zhentao ; Hyung, JI. In: Papers. RePEc:arx:papers:1810.03140.

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2019Many Average Partial Effects: with An Application to Text Regression. (2019). CHIANG, HAROLD. In: Papers. RePEc:arx:papers:1812.09397.

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2019Granger Causality Testing in High-Dimensional VARs: a Post-Double-Selection Procedure. (2019). Smeekes, Stephan ; Margaritella, Luca ; Hecq, Alain. In: Papers. RePEc:arx:papers:1902.10991.

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2020Bayesian MIDAS Penalized Regressions: Estimation, Selection, and Prediction. (2019). Mogliani, Matteo. In: Papers. RePEc:arx:papers:1903.08025.

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2019Time series models for realized covariance matrices based on the matrix-F distribution. (2019). Zhu, Ke ; Li, Wai Keung ; Jiang, Feiyu ; Zhou, Jiayuan. In: Papers. RePEc:arx:papers:1903.12077.

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2019Exact Testing of Many Moment Inequalities Against Multiple Violations. (2019). Bekker, Paul ; Koning, Nick. In: Papers. RePEc:arx:papers:1904.12775.

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2019Forward-Selected Panel Data Approach for Program Evaluation. (2019). Huang, Jingyi ; Shi, Zhentao. In: Papers. RePEc:arx:papers:1908.05894.

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2019Boosting High Dimensional Predictive Regressions with Time Varying Parameters. (2019). Ng, Serena ; Yousuf, Kashif. In: Papers. RePEc:arx:papers:1910.03109.

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2020Data-driven covariance estimators for high-dimensional minimum-variance portfolios. (2019). Steinert, Rick ; Shivarova, Antoniya ; Husmann, Sven . In: Papers. RePEc:arx:papers:1910.13960.

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2020Adaptive Discrete Smoothing for High-Dimensional and Nonlinear Panel Data. (2020). Spindler, Martin ; Luo, YE ; Chen, XI. In: Papers. RePEc:arx:papers:1912.12867.

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2020Oracle Efficient Estimation of Structural Breaks in Cointegrating Regressions. (2020). Schweikert, Karsten. In: Papers. RePEc:arx:papers:2001.07949.

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2020Sharpe Ratio in High Dimensions: Cases of Maximum Out of Sample, Constrained Maximum, and Optimal Portfolio Choice. (2020). Vasconcelos, Gabriel ; Medeiros, Marcelo ; Caner, Mehmet. In: Papers. RePEc:arx:papers:2002.01800.

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2020Wild Bootstrap Inference for Penalized Quantile Regression for Longitudinal Data. (2020). Parker, Thomas ; Lamarche, Carlos. In: Papers. RePEc:arx:papers:2004.05127.

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2020A dynamic conditional approach to portfolio weights forecasting. (2020). Cipollini, Fabrizio ; Palandri, Alessandro ; Gallo, Giampiero M. In: Papers. RePEc:arx:papers:2004.12400.

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2019Bayesian MIDAS penalized regressions: estimation, selection, and prediction. (2019). Mogliani, Matteo. In: Working papers. RePEc:bfr:banfra:713.

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2017A network analysis of the volatility of high dimensional financial series. (2017). Hallin, Marc ; Barigozzi, Matteo. In: Journal of the Royal Statistical Society Series C. RePEc:bla:jorssc:v:66:y:2017:i:3:p:581-605.

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2017WHEN ARE WAVELETS USEFUL FORECASTERS?. (2017). Yazgan, Ege ; Gencay, Ramazan. In: Working Papers. RePEc:bli:wpaper:1704.

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2018LASSO-Driven Inference in Time and Space. (2018). Härdle, Wolfgang ; Chernozhukov, Victor ; Wang, W ; Huang, C ; Hardle, W K. In: Working Papers. RePEc:cty:dpaper:18/04.

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2017Sparse seasonal and periodic vector autoregressive modeling. (2017). Baek, Changryong ; Davis, Richard A ; Pipiras, Vladas. In: Computational Statistics & Data Analysis. RePEc:eee:csdana:v:106:y:2017:i:c:p:103-126.

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2018Testing moment inequalities: Selection versus recentering. (2018). Allen, Roy. In: Economics Letters. RePEc:eee:ecolet:v:162:y:2018:i:c:p:124-126.

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2017A varying-coefficient panel data model with fixed effects: Theory and an application to US commercial banks. (2017). GAO, Jiti ; Feng, Guohua ; Zhang, Xiaohui ; Peng, Bin. In: Journal of Econometrics. RePEc:eee:econom:v:196:y:2017:i:1:p:68-82.

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2019Determination of vector error correction models in high dimensions. (2019). Schienle, Melanie ; Liang, Chong. In: Journal of Econometrics. RePEc:eee:econom:v:208:y:2019:i:2:p:418-441.

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2019Generalized high-dimensional trace regression via nuclear norm regularization. (2019). Fan, Jianqing ; Gong, Wenyan ; Zhu, Ziwei. In: Journal of Econometrics. RePEc:eee:econom:v:212:y:2019:i:1:p:177-202.

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2019Oracle inequalities for sign constrained generalized linear models. (2019). Tanoue, Yuta ; Koike, Yuta . In: Econometrics and Statistics. RePEc:eee:ecosta:v:11:y:2019:i:c:p:145-157.

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2019Exponential smoothing of realized portfolio weights. (2019). Seifert, Miriam Isabel ; Gribisch, Bastian ; Golosnoy, Vasyl. In: Journal of Empirical Finance. RePEc:eee:empfin:v:53:y:2019:i:c:p:222-237.

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2020Factor state–space models for high-dimensional realized covariance matrices of asset returns. (2020). Gribisch, Bastian ; Liesenfeld, Roman ; Hartkopf, Jan Patrick. In: Journal of Empirical Finance. RePEc:eee:empfin:v:55:y:2020:i:c:p:1-20.

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2017VARX-L: Structured regularization for large vector autoregressions with exogenous variables. (2017). Nicholson, William B ; Bien, Jacob ; Matteson, David S. In: International Journal of Forecasting. RePEc:eee:intfor:v:33:y:2017:i:3:p:627-651.

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2018Macroeconomic forecasting using penalized regression methods. (2018). Smeekes, Stephan ; Wijler, Etienne. In: International Journal of Forecasting. RePEc:eee:intfor:v:34:y:2018:i:3:p:408-430.

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2019Bagged neural networks for forecasting Polish (low) inflation. (2019). Szafranek, Karol. In: International Journal of Forecasting. RePEc:eee:intfor:v:35:y:2019:i:3:p:1042-1059.

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2017A network analysis of the volatility of high-dimensionalfinancial series. (2017). Hallin, Marc ; Barigozzi, Matteo. In: LSE Research Online Documents on Economics. RePEc:ehl:lserod:67456.

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2018Nets: network estimation for time series. (2018). Barigozzi, Matteo ; Brownlees, Christian T. In: LSE Research Online Documents on Economics. RePEc:ehl:lserod:90493.

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2019Penalized Estimation of Panel Vector Autoregressive Models. (2019). Schnucker, A M. In: Econometric Institute Research Papers. RePEc:ems:eureir:122072.

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2019Modeling and Forecasting Realized Portfolio Diversification Benefits. (2019). Kohler, Steffen ; Hildebrandt, Benno ; Golosnoy, Vasyl. In: Journal of Risk and Financial Management. RePEc:gam:jjrfmx:v:12:y:2019:i:3:p:116-:d:247544.

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2019The de-biased group Lasso estimation for varying coefficient models. (2019). Honda, Toshio. In: Discussion Papers. RePEc:hit:econdp:2018-04.

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2019LASSO-Driven Inference in Time and Space. (2019). Härdle, Wolfgang ; Chernozhukov, Victor ; Wang, Weining ; Huang, Chen ; Hardle, Wolfgang. In: CeMMAP working papers. RePEc:ifs:cemmap:20/19.

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2019Generalized Instrumental Variable Models, Methods, and Applications. (2019). Rosen, Adam ; Chesher, Andrew. In: CeMMAP working papers. RePEc:ifs:cemmap:41/19.

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2018Generalized instrumental variable models, methods, and applications. (2018). Rosen, Adam ; Chesher, Andrew. In: CeMMAP working papers. RePEc:ifs:cemmap:43/18.

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2017Lasso Regressions and Forecasting Models in Applied Stress Testing. (2017). Chan-Lau, Jorge A. In: IMF Working Papers. RePEc:imf:imfwpa:17/108.

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2017“Regional tourism demand forecasting with machine learning models: Gaussian process regression vs. neural network models in a multiple-input multiple-output setting. (2017). Claveria, Oscar ; Monte, Enric ; Torra, Salvador. In: IREA Working Papers. RePEc:ira:wpaper:201701.

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2019Anatomy of a Sovereign Debt Crisis: CDS Spreads and Real-Time Macroeconomic Data. (2019). Savona, Roberto ; Balduzzi, Pierluigi ; Alessi, Lucia. In: Working Papers. RePEc:jrs:wpaper:201903.

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2019Do High-frequency-based Measures Improve Conditional Covariance Forecasts?. (2019). Dumitrescu, Elena Ivona ; Banulescu-Radu, Denisa. In: LEO Working Papers / DR LEO. RePEc:leo:wpaper:2709.

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2020A Bayesian Covariance Graph And Latent Position Model For Multivariate Financial Time Series. (2020). Ahelegbey, Daniel Felix ; Carvalho, Luis ; Kolaczyk, Eric D. In: DEM Working Papers Series. RePEc:pav:demwpp:demwp0181.

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2019Time series modeling and forecasting of the consumer price index in Japan. (2019). Nyoni, Thabani. In: MPRA Paper. RePEc:pra:mprapa:92409.

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2019Forecasting UK consumer price index using Box-Jenkins ARIMA models. (2019). Nyoni, Thabani. In: MPRA Paper. RePEc:pra:mprapa:92410.

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2019Forecasting consumer price index in Norway: An application of Box-Jenkins ARIMA models. (2019). Nyoni, Thabani. In: MPRA Paper. RePEc:pra:mprapa:92411.

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2019Forecasting Australian CPI using ARIMA models. (2019). Nyoni, Thabani. In: MPRA Paper. RePEc:pra:mprapa:92412.

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2019Predicting CPI in Singapore: An application of the Box-Jenkins methodology. (2019). Nyoni, Thabani. In: MPRA Paper. RePEc:pra:mprapa:92413.

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2019Understanding inflation trends in Israel: A univariate approach. (2019). Nyoni, Thabani. In: MPRA Paper. RePEc:pra:mprapa:92427.

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2019Modeling and forecasting inflation in Philippines using ARIMA models. (2019). Nyoni, Thabani. In: MPRA Paper. RePEc:pra:mprapa:92429.

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2019ARIMA modeling and forecasting of Consumer Price Index (CPI) in Germany. (2019). Nyoni, Thabani. In: MPRA Paper. RePEc:pra:mprapa:92442.

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2019Understanding inflation trends in Finland: A univariate approach. (2019). Nyoni, Thabani. In: MPRA Paper. RePEc:pra:mprapa:92448.

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2019Predicting inflation in the Kingdom of Bahrain using ARIMA models. (2019). Nyoni, Thabani. In: MPRA Paper. RePEc:pra:mprapa:92452.

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2019Modeling and forecasting inflation in Tanzania using ARIMA models. (2019). Nyoni, Thabani. In: MPRA Paper. RePEc:pra:mprapa:92458.

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2019Understanding inflation dynamics in the United States of America (USA): A univariate approach. (2019). Nyoni, Thabani. In: MPRA Paper. RePEc:pra:mprapa:92460.

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2018Representation, Estimation and Forecasting of the Multivariate Index-Augmented Autoregressive Model. (2018). Guardabascio, Barbara ; Cubadda, Gianluca. In: CEIS Research Paper. RePEc:rtv:ceisrp:397.

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2018A Thick ANN Model for Forecasting Inflation. (2018). Iqbal, Javed ; Hanif, Muhammad ; Mughal, Khurrum S. In: SBP Working Paper Series. RePEc:sbp:wpaper:99.

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2019On Hodges’ superefficiency and merits of oracle property in model selection. (2019). Zhou, Xian ; Wu, Xianyi. In: Annals of the Institute of Statistical Mathematics. RePEc:spr:aistmt:v:71:y:2019:i:5:d:10.1007_s10463-018-0670-0.

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2019Order selection for possibly infinite-order non-stationary time series. (2019). Yu, Shu-Hui ; Sin, Chor-yiu . In: AStA Advances in Statistical Analysis. RePEc:spr:alstar:v:103:y:2019:i:2:d:10.1007_s10182-018-00333-1.

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2019Variable Selection with Spatially Autoregressive Errors: A Generalized Moments LASSO Estimator. (2019). Bhattacharjee, Arnab ; Maiti, Taps ; Calantone, Roger ; Cai, Liqian. In: Sankhya B: The Indian Journal of Statistics. RePEc:spr:sankhb:v:81:y:2019:i:1:d:10.1007_s13571-018-0176-z.

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2018Encompassing tests for evaluating multi-step system forecasts invariant to linear transformations. (2018). Hungnes, HÃ¥vard. In: Discussion Papers. RePEc:ssb:dispap:871.

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2017Inference in high-dimensional linear regression models. (2017). Nibbering, Didier ; Boot, Tom. In: Tinbergen Institute Discussion Papers. RePEc:tin:wpaper:20170032.

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2018Boosting Non-linear Predictabilityof Macroeconomic Time SeriesComplexity and benefit take-up: Empirical evidence from the Finnish homecare allowance. (2018). Virtanen, Timo ; Kauppi, Heikki. In: Discussion Papers. RePEc:tkk:dpaper:dp124.

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2018Artificial neural network regression models: Predicting GDP growth. (2018). Jahn, Malte. In: HWWI Research Papers. RePEc:zbw:hwwirp:185.

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2019Determination of vector error correction models in high dimensions. (2019). Schienle, Melanie ; Liang, Chong. In: Working Paper Series in Economics. RePEc:zbw:kitwps:124.

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Works by Anders Bredahl Kock:

YearTitleTypeCited
2009Forecasting with Universal Approximators and a Learning Algorithm In: CREATES Research Papers.
[Full Text][Citation analysis]		paper2
2011Forecasting with Universal Approximators and a Learning Algorithm.(2011) In: Journal of Time Series Econometrics.
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This paper has another version. Agregated cites: 2		article
2010Forecasting with nonlinear time series models In: CREATES Research Papers.
[Full Text][Citation analysis]		paper14
2010Oracle Efficient Variable Selection in Random and Fixed Effects Panel Data Models In: CREATES Research Papers.
[Full Text][Citation analysis]		paper7
2013ORACLE EFFICIENT VARIABLE SELECTION IN RANDOM AND FIXED EFFECTS PANEL DATA MODELS.(2013) In: Econometric Theory.
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This paper has another version. Agregated cites: 7		article
2011Forecasting Macroeconomic Variables using Neural Network Models and Three Automated Model Selection Techniques In: CREATES Research Papers.
[Full Text][Citation analysis]		paper5
2016Forecasting Macroeconomic Variables Using Neural Network Models and Three Automated Model Selection Techniques.(2016) In: Econometric Reviews.
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This paper has another version. Agregated cites: 5		article
2011Forecasting performance of three automated modelling techniques during the economic crisis 2007-2009 In: CREATES Research Papers.
[Full Text][Citation analysis]		paper8
2014Forecasting performances of three automated modelling techniques during the economic crisis 2007–2009.(2014) In: International Journal of Forecasting.
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This paper has another version. Agregated cites: 8		article
2012On the Oracle Property of the Adaptive Lasso in Stationary and Nonstationary Autoregressions In: CREATES Research Papers.
[Full Text][Citation analysis]		paper8
2012Oracle Inequalities for High Dimensional Vector Autoregressions In: CREATES Research Papers.
[Full Text][Citation analysis]		paper44
2015Oracle inequalities for high dimensional vector autoregressions.(2015) In: Journal of Econometrics.
[Full Text][Citation analysis]
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2012Oracle Efficient Estimation and Forecasting with the Adaptive LASSO and the Adaptive Group LASSO in Vector Autoregressions In: CREATES Research Papers.
[Full Text][Citation analysis]		paper6
2013Oracle inequalities for high-dimensional panel data models In: CREATES Research Papers.
[Full Text][Citation analysis]		paper4
2013Lassoing the Determinants of Retirement In: CREATES Research Papers.
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2016Lassoing the Determinants of Retirement.(2016) In: Econometric Reviews.
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This paper has another version. Agregated cites: 0		article
2013Oracle Inequalities for Convex Loss Functions with Non-Linear Targets In: CREATES Research Papers.
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2016Oracle Inequalities for Convex Loss Functions with Nonlinear Targets.(2016) In: Econometric Reviews.
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This paper has another version. Agregated cites: 1		article
2014Asymptotically Honest Confidence Regions for High Dimensional Parameters by the Desparsified Conservative Lasso In: CREATES Research Papers.
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2018Asymptotically honest confidence regions for high dimensional parameters by the desparsified conservative Lasso.(2018) In: Journal of Econometrics.
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This paper has another version. Agregated cites: 4		article
2014Estimation and Forecasting of Large Realized Covariance Matrices and Portfolio Choice In: CREATES Research Papers.
[Full Text][Citation analysis]		paper2
2014Estimation and Forecasting of Large Realized Covariance Matrices and Portfolio Choice.(2014) In: Tinbergen Institute Discussion Papers.
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This paper has another version. Agregated cites: 2		paper
2014Inference in High-dimensional Dynamic Panel Data Models In: CREATES Research Papers.
[Full Text][Citation analysis]		paper3
2015Sharp Threshold Detection Based on Sup-norm Error rates in High-dimensional Models In: CREATES Research Papers.
[Full Text][Citation analysis]		paper1
2017Sharp Threshold Detection Based on Sup-Norm Error Rates in High-Dimensional Models.(2017) In: Journal of Business & Economic Statistics.
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This paper has another version. Agregated cites: 1		article
2015Sharp Threshold Detection based on Sup-Norm Error Rates in High-dimensional Models.(2015) In: Tinbergen Institute Discussion Papers.
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This paper has another version. Agregated cites: 1		paper
2016Inference in partially identified models with many moment inequalities using Lasso In: CREATES Research Papers.
[Full Text][Citation analysis]		paper4
2018Optimal sequential treatment allocation In: Papers.
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2020Functional Sequential Treatment Allocation In: Papers.
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2016CONSISTENT AND CONSERVATIVE MODEL SELECTION WITH THE ADAPTIVE LASSO IN STATIONARY AND NONSTATIONARY AUTOREGRESSIONS In: Econometric Theory.
[Full Text][Citation analysis]		article9
2017Power in High-dimensional testing Problems In: Working Papers ECARES.
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2019Power in High‐Dimensional Testing Problems.(2019) In: Econometrica.
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2016Oracle inequalities, variable selection and uniform inference in high-dimensional correlated random effects panel data models In: Journal of Econometrics.
[Full Text][Citation analysis]		article1
2013Forecasting the Finnish Consumer Price Inflation Using Artificial Neural Network Models and Three Automated Model Selection Techniques In: Finnish Economic Papers.
[Full Text][Citation analysis]		article14
2017Modeling and Forecasting Large Realized Covariance Matrices and Portfolio Choice In: Journal of Applied Econometrics.
[Full Text][Citation analysis]		article11

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