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Peter Exterkate

Personal Details

First Name:Peter
Middle Name:
Last Name:Exterkate
Suffix:
RePEc Short-ID:pex2
http://sydney.edu.au/arts/economics/staff/profiles/peter.exterkate.php

Affiliation

(99%) School of Economics
Faculty of Arts and Social Sciences
University of Sydney

Sydney, Australia
http://sydney.edu.au/arts/economics/

61 +2 9351 5055
61 +2 9351 4341
Sydney, NSW 2006
RePEc:edi:deusyau (more details at EDIRC)

(1%) Center for Research in Econometric Analysis of Time Series (CREATES)
Institut for Økonomi
Aarhus Universitet

Aarhus, Denmark
http://www.creates.au.dk/



Building 1322, DK-8000 Aarhus C
RePEc:edi:creaudk (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Knapik, Oskar & Exterkate, Peter, 2017. "A regime-switching stochastic volatility model for forecasting electricity prices," Working Papers 2017-02, University of Sydney, School of Economics.
  2. Peter Exterkate & Patrick J.F. Groenen & Christiaan Heij & Dick van Dijk, 2013. "Nonlinear Forecasting With Many Predictors Using Kernel Ridge Regression," CREATES Research Papers 2013-16, Department of Economics and Business Economics, Aarhus University.
  3. Peter Exterkate, 2012. "Model Selection in Kernel Ridge Regression," CREATES Research Papers 2012-10, Department of Economics and Business Economics, Aarhus University.
  4. Christophe Croux & Peter Exterkate, 2011. "Sparse and Robust Factor Modelling," Tinbergen Institute Discussion Papers 11-122/4, Tinbergen Institute.
  5. Peter Exterkate, 2011. "Modelling Issues in Kernel Ridge Regression," Tinbergen Institute Discussion Papers 11-138/4, Tinbergen Institute.
  6. Exterkate, P. & van Dijk, D.J.C. & Heij, C. & Groenen, P.J.F., 2010. "Forecasting the Yield Curve in a Data-Rich Environment using the Factor-Augmented Nelson-Siegel Model," Econometric Institute Research Papers EI 2010-06, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

Articles

  1. Exterkate, Peter & Groenen, Patrick J.F. & Heij, Christiaan & van Dijk, Dick, 2016. "Nonlinear forecasting with many predictors using kernel ridge regression," International Journal of Forecasting, Elsevier, vol. 32(3), pages 736-753.
  2. Petrevski, Goran & Exterkate, Peter & Tevdovski, Dragan & Bogoev, Jane, 2015. "The transmission of foreign shocks to South Eastern European economies: A Bayesian VAR approach," Economic Systems, Elsevier, vol. 39(4), pages 632-643.
  3. Peter Exterkate & Dick Van Dijk & Christiaan Heij & Patrick J. F. Groenen, 2013. "Forecasting the Yield Curve in a Data‐Rich Environment Using the Factor‐Augmented Nelson–Siegel Model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(3), pages 193-214, April.

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Blog mentions

As found by EconAcademics.org, the blog aggregator for Economics research:
  1. Peter Exterkate, 2011. "Modelling Issues in Kernel Ridge Regression," Tinbergen Institute Discussion Papers 11-138/4, Tinbergen Institute.

    Mentioned in:

    1. Kernel Ridge Regression – Example Computation I
      by Clive Jones in Business Forecasting on 2012-07-27 00:23:25
    2. Kernel Ridge Regression – A Toy Example
      by Clive Jones in Business Forecasting on 2014-03-02 03:10:25
  2. Peter Exterkate, 2012. "Model Selection in Kernel Ridge Regression," CREATES Research Papers 2012-10, Department of Economics and Business Economics, Aarhus University.

    Mentioned in:

    1. Kernel Ridge Regression – Example Computation I
      by Clive Jones in Business Forecasting on 2012-07-27 00:23:25
    2. Kernel Ridge Regression – A Toy Example
      by Clive Jones in Business Forecasting on 2014-03-02 03:10:25

Working papers

  1. Peter Exterkate & Patrick J.F. Groenen & Christiaan Heij & Dick van Dijk, 2013. "Nonlinear Forecasting With Many Predictors Using Kernel Ridge Regression," CREATES Research Papers 2013-16, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Daiki Maki & Yasushi Ota, 2019. "Robust tests for ARCH in the presence of the misspecified conditional mean: A comparison of nonparametric approches," Papers 1907.12752, arXiv.org, revised Sep 2019.
    2. Dalibor Stevanovic & Stéphane Surprenant & Philippe Goulet Coulombe, 2019. "How is Machine Learning Useful for Macroeconomic Forecasting?," CIRANO Working Papers 2019s-22, CIRANO.
    3. Alessandro Giovannelli, 2012. "Nonlinear Forecasting Using Large Datasets: Evidences on US and Euro Area Economies," CEIS Research Paper 255, Tor Vergata University, CEIS, revised 08 Nov 2012.
    4. Milan Fičura, 2019. "Forecasting Foreign Exchange Rate Movements with k-Nearest-Neighbour, Ridge Regression and Feed-Forward Neural Networks," FFA Working Papers 1.001, Prague University of Economics and Business, revised 24 Nov 2019.
    5. Cheng, Kai & Lu, Zhenzhou, 2018. "Sparse polynomial chaos expansion based on D-MORPH regression," Applied Mathematics and Computation, Elsevier, vol. 323(C), pages 17-30.
    6. A. Frenkel’ A. & N. Volkova N. & A. Surkov A. & E. Romanyuk I. & А. Френкель А. & Н. Волкова Н. & А. Сурков А. & Э. Романюк И., 2018. "Использование Методов Гребневой Регрессии При Объединении Прогнозов // The Application Of Ridge Regression Methods When Combining Forecasts," Финансы: теория и практика/Finance: Theory and Practice // Finance: Theory and Practice, ФГОБУВО Финансовый университет при Правительстве Российской Федерации // Financial University under The Government of Russian Federation, vol. 22(4), pages 6-17.
    7. Christophe Croux & Peter Exterkate, 2011. "Sparse and Robust Factor Modelling," Tinbergen Institute Discussion Papers 11-122/4, Tinbergen Institute.
    8. Xu Gong & Boqiang Lin, 2018. "Structural breaks and volatility forecasting in the copper futures market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(3), pages 290-339, March.
    9. Thierry Moudiki & Frédéric Planchet & Areski Cousin, 2018. "Multiple Time Series Forecasting Using Quasi-Randomized Functional Link Neural Networks," Risks, MDPI, Open Access Journal, vol. 6(1), pages 1-20, March.
    10. Wei, Yu & Liang, Chao & Li, Yan & Zhang, Xunhui & Wei, Guiwu, 2020. "Can CBOE gold and silver implied volatility help to forecast gold futures volatility in China? Evidence based on HAR and Ridge regression models," Finance Research Letters, Elsevier, vol. 35(C).
    11. Peter Exterkate, 2012. "Model Selection in Kernel Ridge Regression," CREATES Research Papers 2012-10, Department of Economics and Business Economics, Aarhus University.
    12. Peter Exterkate, 2011. "Modelling Issues in Kernel Ridge Regression," Tinbergen Institute Discussion Papers 11-138/4, Tinbergen Institute.

  2. Peter Exterkate, 2012. "Model Selection in Kernel Ridge Regression," CREATES Research Papers 2012-10, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Exterkate, Peter & Groenen, Patrick J.F. & Heij, Christiaan & van Dijk, Dick, 2016. "Nonlinear forecasting with many predictors using kernel ridge regression," International Journal of Forecasting, Elsevier, vol. 32(3), pages 736-753.

  3. Christophe Croux & Peter Exterkate, 2011. "Sparse and Robust Factor Modelling," Tinbergen Institute Discussion Papers 11-122/4, Tinbergen Institute.

    Cited by:

    1. Johannes Tang Kristensen, 2012. "Factor-Based Forecasting in the Presence of Outliers: Are Factors Better Selected and Estimated by the Median than by The Mean?," CREATES Research Papers 2012-28, Department of Economics and Business Economics, Aarhus University.
    2. Thomas Despois & Catherine Doz, 2020. "Another look into the factor model black box: factor interpretation and structural (in)stability," PSE Working Papers halshs-02235543, HAL.
    3. Thomas Despois & Catherine Doz, 2020. "Another look into the factor model black box: factor interpretation and structural (in)stability," Working Papers halshs-02235543, HAL.
    4. Smeekes, Stephan & Wijler, Etiënne, 2016. "Macroeconomic Forecasting Using Penalized Regression Methods," Research Memorandum 039, Maastricht University, Graduate School of Business and Economics (GSBE).
    5. Johannes Tang Kristensen, 2013. "Diffusion Indexes with Sparse Loadings," CREATES Research Papers 2013-22, Department of Economics and Business Economics, Aarhus University.

  4. Exterkate, P. & van Dijk, D.J.C. & Heij, C. & Groenen, P.J.F., 2010. "Forecasting the Yield Curve in a Data-Rich Environment using the Factor-Augmented Nelson-Siegel Model," Econometric Institute Research Papers EI 2010-06, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Minchul Shin & Molin Zhong, 2015. "Does Realized Volatility Help Bond Yield Density Prediction?," Finance and Economics Discussion Series 2015-115, Board of Governors of the Federal Reserve System (U.S.), revised 18 Dec 2015.
    2. Falk Brauning & Siem Jan Koopman, 2012. "Forecasting Macroeconomic Variables using Collapsed Dynamic Factor Analysis," Tinbergen Institute Discussion Papers 12-042/4, Tinbergen Institute.
    3. Vieira, Fausto & Fernandes, Marcelo & Chague, Fernando, 2017. "Forecasting the Brazilian yield curve using forward-looking variables," International Journal of Forecasting, Elsevier, vol. 33(1), pages 121-131.
    4. Massimo Guidolin & Daniel L. Thornton, 2010. "Predictions of short-term rates and the expectations hypothesis," Working Papers 2010-013, Federal Reserve Bank of St. Louis.
    5. Lorenčič Eva, 2016. "Testing the Performance of Cubic Splines and Nelson-Siegel Model for Estimating the Zero-coupon Yield Curve," Naše gospodarstvo/Our economy, Sciendo, vol. 62(2), pages 42-50, June.
    6. Dick Dijk & Siem Jan Koopman & Michel Wel & Jonathan H. Wright, 2014. "Forecasting interest rates with shifting endpoints," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(5), pages 693-712, August.
    7. Koopman, Siem Jan & van der Wel, Michel, 2013. "Forecasting the US term structure of interest rates using a macroeconomic smooth dynamic factor model," International Journal of Forecasting, Elsevier, vol. 29(4), pages 676-694.
    8. Adam Traczyk, 2013. "Financial integration and the term structure of interest rates," Empirical Economics, Springer, vol. 45(3), pages 1267-1305, December.
    9. Michele Manna & Emmanuela Bernardini & Mauro Bufano & Davide Dottori, 2013. "Modelling public debt strategies," Questioni di Economia e Finanza (Occasional Papers) 199, Bank of Italy, Economic Research and International Relations Area.
    10. Fausto Vieira & Fernando Chague, Marcelo Fernandes, 2016. "A dynamic Nelson-Siegel model with forward-looking indicators for the yield curve in the US," Working Papers, Department of Economics 2016_31, University of São Paulo (FEA-USP).
    11. Tu, Anthony H. & Chen, Cathy Yi-Hsuan, 2018. "A factor-based approach of bond portfolio value-at-risk: The informational roles of macroeconomic and financial stress factors," Journal of Empirical Finance, Elsevier, vol. 45(C), pages 243-268.
    12. Caio Almeida & Kym Ardison & Daniela Kubudi & Axel Simonsen & José Vicente, 2018. "Forecasting Bond Yields with Segmented Term Structure Models," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 16(1), pages 1-33.
    13. Eran Raviv, 2013. "Prediction Bias Correction for Dynamic Term Structure Models," Tinbergen Institute Discussion Papers 13-041/III, Tinbergen Institute.
    14. Norman R. Swanson & Weiqi Xiong & Xiye Yang, 2020. "Predicting interest rates using shrinkage methods, real‐time diffusion indexes, and model combinations," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(5), pages 587-613, August.
    15. Scott A. Brave & R. Andrew Butters & David Kelley, 2019. "A New “Big Data” Index of U.S. Economic Activity," Economic Perspectives, Federal Reserve Bank of Chicago, issue 1, pages 1-30.
    16. Anthony H. Tu & Cathy Yi-Hsuan Chen, 2016. "What Derives the Bond Portfolio Value-at-Risk: Information Roles of Macroeconomic and Financial Stress Factors," SFB 649 Discussion Papers SFB649DP2016-006, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    17. Koopman, Siem Jan & Lucas, André & Schwaab, Bernd, 2011. "Modeling frailty-correlated defaults using many macroeconomic covariates," Journal of Econometrics, Elsevier, vol. 162(2), pages 312-325, June.
    18. Oguzhan Cepni & Ibrahim Ethem Guney & Doruk Kucuksarac & Muhammed Hasan Yilmaz, 2018. "The Interaction between Yield Curve and Macroeconomic Factors," CBT Research Notes in Economics 1802, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    19. Fernandes, Marcelo & Vieira, Fausto, 2019. "A dynamic Nelson–Siegel model with forward-looking macroeconomic factors for the yield curve in the US," Journal of Economic Dynamics and Control, Elsevier, vol. 106(C), pages 1-1.

Articles

  1. Exterkate, Peter & Groenen, Patrick J.F. & Heij, Christiaan & van Dijk, Dick, 2016. "Nonlinear forecasting with many predictors using kernel ridge regression," International Journal of Forecasting, Elsevier, vol. 32(3), pages 736-753.
    See citations under working paper version above.
  2. Petrevski, Goran & Exterkate, Peter & Tevdovski, Dragan & Bogoev, Jane, 2015. "The transmission of foreign shocks to South Eastern European economies: A Bayesian VAR approach," Economic Systems, Elsevier, vol. 39(4), pages 632-643.

    Cited by:

    1. Isabella Moder, 2019. "Spillovers from the ECB's Non-standard Monetary Policy Measures on Southeastern Europe," International Journal of Central Banking, International Journal of Central Banking, vol. 15(4), pages 127-163, October.
    2. Berisha Edmond, 2017. "ECB Monetary Policy Actions and the Economic Conditions of a Non-Euro Member: The Case of Croatia," Global Economy Journal, De Gruyter, vol. 17(2), pages 1-10, June.
    3. Rafael Ravnik & Nikola Bokan, 2018. "Quarterly Projection Model for Croatia," Surveys 34, The Croatian National Bank, Croatia.

  3. Peter Exterkate & Dick Van Dijk & Christiaan Heij & Patrick J. F. Groenen, 2013. "Forecasting the Yield Curve in a Data‐Rich Environment Using the Factor‐Augmented Nelson–Siegel Model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(3), pages 193-214, April.
    See citations under working paper version above.

More information

Research fields, statistics, top rankings, if available.

Statistics

Access and download statistics for all items

Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 5 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-FOR: Forecasting (5) 2010-03-06 2012-05-02 2013-06-16 2017-02-19 2017-03-26. Author is listed
  2. NEP-ECM: Econometrics (2) 2012-05-02 2017-02-19
  3. NEP-ENE: Energy Economics (2) 2017-02-19 2017-03-26
  4. NEP-ETS: Econometric Time Series (2) 2013-06-16 2017-03-26
  5. NEP-ORE: Operations Research (2) 2013-06-16 2017-03-26
  6. NEP-CBA: Central Banking (1) 2010-03-06
  7. NEP-FMK: Financial Markets (1) 2010-03-06
  8. NEP-MST: Market Microstructure (1) 2017-02-19

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