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Michel van der Wel

Personal Details

First Name:Michel
Middle Name:
Last Name:van der Wel
Suffix:
RePEc Short-ID:pva361
http://personal.eur.nl/vanderwel

Affiliation

(97%) Econometrisch Instituut
Faculteit der Economische Wetenschappen
Erasmus Universiteit Rotterdam

Rotterdam, Netherlands
http://www.econometric-institute.org/

: 010 - 40 81278
010 - 40 89162
Burgemeester Oudlaan 50, 3062 PA Rotterdam
RePEc:edi:eieurnl (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)

(1%) Erasmus Research Institute of Management (ERIM)
Erasmus Universiteit Rotterdam

Rotterdam, Netherlands
http://www.erim.eur.nl/

: 31-10-408 1182
31-10-408 9020
RSM Erasmus University & Erasmus School of Economics, PoBox 1738, 3000 DR Rotterdam
RePEc:edi:erimanl (more details at EDIRC)

(1%) Tinbergen Instituut

Amsterdam, Netherlands
http://www.tinbergen.nl/

: +31 (0)20 598 4580

Gustav Mahlerplein 117, 1082 MS Amsterdam
RePEc:edi:tinbenl (more details at EDIRC)

Research output

as
Jump to: Working papers Articles Chapters

Working papers

  1. Didier Nibbering & Richard Paap & Michel van der Wel, 2016. "A Bayesian Infinite Hidden Markov Vector Autoregressive Model," Tinbergen Institute Discussion Papers 16-107/III, Tinbergen Institute, revised 13 Oct 2017.
  2. Michel van der Wel & Sait R. Ozturk & Dick van Dijk, 2015. "Dynamic Factor Models for the Volatility Surface," CREATES Research Papers 2015-13, Department of Economics and Business Economics, Aarhus University.
  3. Didier Nibbering & Richard Paap & Michel van der Wel, 2015. "What Do Professional Forecasters Actually Predict?," Tinbergen Institute Discussion Papers 15-095/III, Tinbergen Institute, revised 13 Oct 2017.
  4. Sait R. Ozturk & Michel van der Wel & Dick van Dijk, 2015. "Why do Pit-Hours outlive the Pit?," Tinbergen Institute Discussion Papers 15-082/III, Tinbergen Institute.
  5. Anne Opschoor & Dick van Dijk & Michel van der Wel, 2014. "Improving Density Forecasts and Value-at-Risk Estimates by Combining Densities," Tinbergen Institute Discussion Papers 14-090/III, Tinbergen Institute.
  6. Bent Jesper Christensen & Olaf Posch & Michel van der Wel, 2014. "Estimating Dynamic Equilibrium Models Using Mixed Frequency Macro and Financial Data," CESifo Working Paper Series 5030, CESifo Group Munich.
  7. Dick van Dijk & Robin L. Lumsdaine & Michel van der Wel, 2014. "Market Set-Up in Advance of Federal Reserve Policy Decisions," NBER Working Papers 19814, National Bureau of Economic Research, Inc.
  8. Sait Ozturk & Michel van der Wel, 2014. "Intraday Price Discovery in Fragmented Markets," Tinbergen Institute Discussion Papers 14-027/III, Tinbergen Institute.
  9. Dennis Karstanje & Elvira Sojli & Wing Wah Tham & Michel van der Wel, 2013. "Economic Valuation of Liquidity Timing," Tinbergen Institute Discussion Papers 13-156/IV/DSF64, Tinbergen Institute.
  10. Anne Opschoor & Dick van Dijk & Michel van der Wel, 2013. "Predicting Covariance Matrices with Financial Conditions Indexes," Tinbergen Institute Discussion Papers 13-113/III, Tinbergen Institute.
  11. Anne Opschoor & Michel van der Wel & Dick van Dijk & Nick Taylor, 2012. "On the Effects of Private Information on Volatility," CREATES Research Papers 2012-08, Department of Economics and Business Economics, Aarhus University.
  12. Dick van Dijk & Siem Jan Koopman & Michel van der Wel & Jonathan H. Wright, 2012. "Forecasting Interest Rates with Shifting Endpoints," Tinbergen Institute Discussion Papers 12-076/4, Tinbergen Institute.
  13. Lei Pan & Olaf Posch & Michel van der Wel, 2012. "Measuring Convergence using Dynamic Equilibrium Models: Evidence from Chinese Provinces," CREATES Research Papers 2012-26, Department of Economics and Business Economics, Aarhus University.
  14. B. Jungbacker & S.J. Koopman & M. Van Der Wel, 2011. "Maximum likelihood estimation for dynamic factor models with missing data," Post-Print hal-00828980, HAL.
  15. Siem Jan Koopman & Michel van der Wel, 2011. "Forecasting the U.S. Term Structure of Interest Rates using a Macroeconomic Smooth Dynamic Factor Model," Tinbergen Institute Discussion Papers 11-063/4, Tinbergen Institute.
  16. Bent Jesper Christensen & Olaf Posch & Michel van der Wel, 2011. "Estimating Dynamic Equilibrium Models using Macro and Financial Data," CREATES Research Papers 2011-21, Department of Economics and Business Economics, Aarhus University.
  17. Borus Jungbacker & Siem Jan Koopman & Michel van der Wel, 2009. "Smooth Dynamic Factor Analysis with an Application to the U.S. Term Structure of Interest Rates," CREATES Research Papers 2009-39, Department of Economics and Business Economics, Aarhus University.
  18. B. Jungbacker & S.J. Koopman & M. van der Wel, 2009. "Dynamic Factor Analysis in The Presence of Missing Data," Tinbergen Institute Discussion Papers 09-010/4, Tinbergen Institute, revised 11 Mar 2011.
  19. Michel Van der Wel & Albert J. Menkveld & Asani Sarkar, 2009. "Are market makers uninformed and passive? Signing trades in the absence of quotes," Staff Reports 395, Federal Reserve Bank of New York.
  20. Menkveld, Albert J. & Sarkar, Asani & van der Wel, Michel, 2008. "Customer flow, intermediaries, and the discovery of the equilibrium riskfree rate," CFS Working Paper Series 2008/47, Center for Financial Studies (CFS).
  21. Albert J. Menkveld & Asani Sarkar & Michel van der Wel, 2007. "Macro News, Riskfree Rates, and the Intermediary," Tinbergen Institute Discussion Papers 07-086/2, Tinbergen Institute.
  22. Albert J. Menkveld & Asani Sarkar & Michel Van der Wel, 2007. "Macro news, risk-free rates, and the intermediary: customer orders for thirty-year Treasury futures," Staff Reports 307, Federal Reserve Bank of New York.
  23. Siem Jan Koopman & Max I.P. Mallee & Michel van der Wel, 2007. "Analyzing the Term Structure of Interest Rates using the Dynamic Nelson-Siegel Model with Time-Varying Parameters," Tinbergen Institute Discussion Papers 07-095/4, Tinbergen Institute.
  24. Borus Jungbacker & Siem Jan Koopman & Michel van der Wel, 0000. "Dynamic Factor Models with Smooth Loadings for Analyzing the Term Structure of Interest Rates," Tinbergen Institute Discussion Papers 09-041/4, Tinbergen Institute, revised 17 Sep 2010.
  25. Bent Jesper Christensen & Michel van der Wel, "undated". "An Asset Pricing Approach to Testing General Term Structure Models including Heath-Jarrow-Morton Specifications and Affine Subclasses," CREATES Research Papers 2010-14, Department of Economics and Business Economics, Aarhus University.

Articles

  1. Nibbering, Didier & Paap, Richard & van der Wel, Michel, 2018. "What do professional forecasters actually predict?," International Journal of Forecasting, Elsevier, vol. 34(2), pages 288-311.
  2. Ozturk, Sait R. & van der Wel, Michel & van Dijk, Dick, 2017. "Intraday price discovery in fragmented markets," Journal of Financial Markets, Elsevier, vol. 32(C), pages 28-48.
  3. Dick van Dijk & Robin L. Lumsdaine & Michel van der Wel, 2016. "Market Set‐up in Advance of Federal Reserve Policy Rate Decisions," Economic Journal, Royal Economic Society, vol. 0(592), pages 618-653, May.
  4. Christensen, Bent Jesper & Posch, Olaf & van der Wel, Michel, 2016. "Estimating dynamic equilibrium models using mixed frequency macro and financial data," Journal of Econometrics, Elsevier, vol. 194(1), pages 116-137.
  5. Opschoor, Anne & van Dijk, Dick & van der Wel, Michel, 2014. "Predicting volatility and correlations with Financial Conditions Indexes," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 435-447.
  6. Opschoor, Anne & Taylor, Nick & van der Wel, Michel & van Dijk, Dick, 2014. "Order flow and volatility: An empirical investigation," Journal of Empirical Finance, Elsevier, vol. 28(C), pages 185-201.
  7. Karstanje, Dennis & Sojli, Elvira & Tham, Wing Wah & van der Wel, Michel, 2013. "Economic valuation of liquidity timing," Journal of Banking & Finance, Elsevier, vol. 37(12), pages 5073-5087.
  8. 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.
  9. Menkveld, Albert J. & Sarkar, Asani & Wel, Michel van der, 2012. "Customer Order Flow, Intermediaries, and Discovery of the Equilibrium Risk-Free Rate," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 47(04), pages 821-849, August.
  10. Jungbacker, B. & Koopman, S.J. & van der Wel, M., 2011. "Maximum likelihood estimation for dynamic factor models with missing data," Journal of Economic Dynamics and Control, Elsevier, vol. 35(8), pages 1358-1368, August.
  11. Koopman, Siem Jan & Mallee, Max I. P. & Van der Wel, Michel, 2010. "Analyzing the Term Structure of Interest Rates Using the Dynamic Nelson–Siegel Model With Time-Varying Parameters," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(3), pages 329-343.

Chapters

  1. Michel van der Wel & Sait R. Ozturk & Dick van Dijk, 2016. "Dynamic Factor Models for the Volatility Surface," Advances in Econometrics,in: Dynamic Factor Models, volume 35, pages 127-174 Emerald Publishing Ltd.

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.

Working papers

  1. Bent Jesper Christensen & Olaf Posch & Michel van der Wel, 2014. "Estimating Dynamic Equilibrium Models Using Mixed Frequency Macro and Financial Data," CESifo Working Paper Series 5030, CESifo Group Munich.

    Cited by:

    1. Bacchiocchi, Emanuele & Bastianin, Andrea & Missale, Alessandro & Rossi, Eduardo, 2016. "Structural analysis with mixed frequencies: monetary policy, uncertainty and gross capital flows," Working Papers 2016-04, Joint Research Centre, European Commission (Ispra site).

  2. Dick van Dijk & Robin L. Lumsdaine & Michel van der Wel, 2014. "Market Set-Up in Advance of Federal Reserve Policy Decisions," NBER Working Papers 19814, National Bureau of Economic Research, Inc.

    Cited by:

    1. Tim Bollerslev & Jia Li & Yuan Xue, 2016. "Volume, Volatility and Public News Announcements," CREATES Research Papers 2016-19, Department of Economics and Business Economics, Aarhus University.

  3. Sait Ozturk & Michel van der Wel, 2014. "Intraday Price Discovery in Fragmented Markets," Tinbergen Institute Discussion Papers 14-027/III, Tinbergen Institute.

    Cited by:

    1. Takaki Hayashi & Yuta Koike, 2017. "Multi-scale analysis of lead-lag relationships in high-frequency financial markets," Papers 1708.03992, arXiv.org, revised Feb 2018.
    2. Gustavo Fruet Dias & Marcelo Fernandes & Cristina M. Scherrer, 2016. "Component shares in continuous time," CREATES Research Papers 2016-25, Department of Economics and Business Economics, Aarhus University.
    3. Dias, Gustavo Fruet & Fernandes, Marcelo & Scherrer, Cristina Mabel, 2017. "Improving on daily measures of price discovery," Textos para discussão 444, FGV/EESP - Escola de Economia de São Paulo, Getulio Vargas Foundation (Brazil).

  4. Dennis Karstanje & Elvira Sojli & Wing Wah Tham & Michel van der Wel, 2013. "Economic Valuation of Liquidity Timing," Tinbergen Institute Discussion Papers 13-156/IV/DSF64, Tinbergen Institute.

    Cited by:

    1. Ripamonti, Alexandre, 2016. "Corwin-Schultz bid-ask spread estimator in the Brazilian stock market," MPRA Paper 79459, University Library of Munich, Germany.

  5. Anne Opschoor & Dick van Dijk & Michel van der Wel, 2013. "Predicting Covariance Matrices with Financial Conditions Indexes," Tinbergen Institute Discussion Papers 13-113/III, Tinbergen Institute.

    Cited by:

    1. Manamani SAHOO, 2017. "Financial conditions index (FCI), inflation and growth: Some evidence," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania - AGER, vol. 0(3(612), A), pages 147-172, Autumn.

  6. Anne Opschoor & Michel van der Wel & Dick van Dijk & Nick Taylor, 2012. "On the Effects of Private Information on Volatility," CREATES Research Papers 2012-08, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Heejoon Han & Dennis Kristensen, 2012. "Asymptotic Theory for the QMLE in GARCH-X Models with Stationary and Non-Stationary Covariates," CREATES Research Papers 2012-25, Department of Economics and Business Economics, Aarhus University.

  7. Dick van Dijk & Siem Jan Koopman & Michel van der Wel & Jonathan H. Wright, 2012. "Forecasting Interest Rates with Shifting Endpoints," Tinbergen Institute Discussion Papers 12-076/4, Tinbergen Institute.

    Cited by:

    1. Shin, Minchul & Zhong, Molin, 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.).
    2. Joseph P. Byrne & Shuo Cao. & Dimitris Korobilis., 2015. "Term Structure Dynamics, Macro-Finance Factors and Model Uncertainty," Working Papers 2015_08, Business School - Economics, University of Glasgow.
    3. Geiger, Felix & Schupp, Fabian, 2018. "With a little help from my friends: Survey-based derivation of euro area short rate expectations at the effective lower bound," Discussion Papers 27/2018, Deutsche Bundesbank.
    4. Malik, Sheheryar & Meldrum, Andrew, 2016. "Evaluating the robustness of UK term structure decompositions using linear regression methods," Journal of Banking & Finance, Elsevier, vol. 67(C), pages 85-102.
    5. Crump, Richard K. & Eusepi, Stefano & Moench, Emanuel, 2016. "The term structure of expectations and bond yields," Staff Reports 775, Federal Reserve Bank of New York, revised 01 Apr 2018.
    6. 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.
    7. Eran Raviv, 2013. "Prediction Bias Correction for Dynamic Term Structure Models," Tinbergen Institute Discussion Papers 13-041/III, Tinbergen Institute.
    8. Byrne, Joseph P. & Cao, Shuo & Korobilis, Dimitris, 2017. "Forecasting the term structure of government bond yields in unstable environments," Journal of Empirical Finance, Elsevier, vol. 44(C), pages 209-225.

  8. B. Jungbacker & S.J. Koopman & M. Van Der Wel, 2011. "Maximum likelihood estimation for dynamic factor models with missing data," Post-Print hal-00828980, HAL.

    Cited by:

    1. D'Agostino, Antonello & Giannone, Domenico & Lenza, Michele & Modugno, Michele, 2015. "Nowcasting Business Cycles: a Bayesian Approach to Dynamic Heterogeneous Factor Models," Finance and Economics Discussion Series 2015-66, Board of Governors of the Federal Reserve System (U.S.).
    2. Marcellino, Massimiliano & Sivec, Vasja, 2016. "Monetary, fiscal and oil shocks: Evidence based on mixed frequency structural FAVARs," Journal of Econometrics, Elsevier, vol. 193(2), pages 335-348.
    3. Ruiz, Esther & Poncela, Pilar, 2012. "More is not always better : back to the Kalman filter in dynamic factor models," DES - Working Papers. Statistics and Econometrics. WS ws122317, Universidad Carlos III de Madrid. Departamento de Estadística.
    4. Libero Monteforte & Valentina Raponi, 2018. "Short term forecasts of economic activity: are fortnightly factors useful?," Temi di discussione (Economic working papers) 1177, Bank of Italy, Economic Research and International Relations Area.
    5. Tommaso Proietti & Alessandra Luati, 2013. "Maximum likelihood estimation of time series models: the Kalman filter and beyond," Chapters,in: Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 15, pages 334-362 Edward Elgar Publishing.
    6. Zirogiannis, Nikolaos & Tripodis, Yorghos, 2013. "A Generalized Dynamic Factor Model for Panel Data: Estimation with a Two-Cycle Conditional Expectation-Maximization Algorithm," Working Paper Series 142752, University of Massachusetts, Amherst, Department of Resource Economics.
    7. Matteo Barigozzi & Matteo Luciani, 2017. "Common Factors, Trends, and Cycles in Large Datasets," Finance and Economics Discussion Series 2017-111, Board of Governors of the Federal Reserve System (U.S.).
    8. Brave, Scott & Butters, R. Andrew, 2014. "Nowcasting Using the Chicago Fed National Activity Index," Economic Perspectives, Federal Reserve Bank of Chicago, issue Q I, pages 19-37.
    9. Christopher Otrok & Panayiotis M. Pourpourides, 2011. "On the Cyclicality of Real Wages and Wage Differentials," Working Papers 2011-4, Central Bank of Cyprus.
    10. Jackson, Laura E. & Kose, M. Ayhan & Otrok, Christopher & Owyang, Michael T., 2015. "Specification and Estimation of Bayesian Dynamic Factor Models: A Monte Carlo Analysis with an Application to Global House Price Comovement," Working Papers 2015-31, Federal Reserve Bank of St. Louis.
    11. Hang Qian, 2014. "A Flexible State Space Model And Its Applications," Journal of Time Series Analysis, Wiley Blackwell, vol. 35(2), pages 79-88, March.
    12. Ledenyov, Dimitri O. & Ledenyov, Viktor O., 2015. "Wave function method to forecast foreign currencies exchange rates at ultra high frequency electronic trading in foreign currencies exchange markets," MPRA Paper 67470, University Library of Munich, Germany.
    13. Qian, Hang, 2012. "A Flexible State Space Model and its Applications," MPRA Paper 38455, University Library of Munich, Germany.
    14. Daniel Kaufmann & Rolf Scheufele, 2015. "Business tendency surveys and macroeconomic fluctuations," KOF Working papers 15-378, KOF Swiss Economic Institute, ETH Zurich.
    15. Poncela, Pilar & Ruiz, Esther, 2015. "Small versus big-data factor extraction in Dynamic Factor Models: An empirical assessment," DES - Working Papers. Statistics and Econometrics. WS ws1502, Universidad Carlos III de Madrid. Departamento de Estadística.
    16. Matteo Luciani & Madhavi Pundit & Arief Ramayandi & Giovanni Veronese, 2018. "Nowcasting Indonesia," Empirical Economics, Springer, vol. 55(2), pages 597-619, September.
    17. Geert Mesters & Siem Jan Koopman, 2012. "Generalized Dynamic Panel Data Models with Random Effects for Cross-Section and Time," Tinbergen Institute Discussion Papers 12-009/4, Tinbergen Institute, revised 18 Mar 2014.
    18. Hindrayanto, Irma & Koopman, Siem Jan & de Winter, Jasper, 2016. "Forecasting and nowcasting economic growth in the euro area using factor models," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1284-1305.
    19. Bragoli, Daniela, 2017. "Now-casting the Japanese economy," International Journal of Forecasting, Elsevier, vol. 33(2), pages 390-402.
    20. Ledenyov, Dimitri O. & Ledenyov, Viktor O., 2013. "On the Stratonovich – Kalman - Bucy filtering algorithm application for accurate characterization of financial time series with use of state-space model by central banks," MPRA Paper 50235, University Library of Munich, Germany.
    21. Modugno, Michele & Soybilgen, Barış & Yazgan, Ege, 2016. "Nowcasting Turkish GDP and news decomposition," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1369-1384.
    22. Alvarez, Rocio & Camacho, Maximo & Perez-Quiros, Gabriel, 2016. "Aggregate versus disaggregate information in dynamic factor models," International Journal of Forecasting, Elsevier, vol. 32(3), pages 680-694.
    23. Liebermann, Joelle, 2012. "Real-time forecasting in a data-rich environment," Research Technical Papers 07/RT/12, Central Bank of Ireland.
    24. M. Pilar Muñoz & Cristina Corchero & F.-Javier Heredia, 2013. "Improving Electricity Market Price Forecasting with Factor Models for the Optimal Generation Bid," International Statistical Review, International Statistical Institute, vol. 81(2), pages 289-306, August.
    25. Kihwan Kim & Norman Swanson, 2013. "Diffusion Index Model Specification and Estimation Using Mixed Frequency Datasets," Departmental Working Papers 201315, Rutgers University, Department of Economics.
    26. Stock, J.H. & Watson, M.W., 2016. "Dynamic Factor Models, Factor-Augmented Vector Autoregressions, and Structural Vector Autoregressions in Macroeconomics," Handbook of Macroeconomics, Elsevier.
    27. Nikolaos Zirogiannis & Yorghos Tripodis, 2013. "A Generalized Dynamic Factor Model for Panel Data: Estimation with a Two-Cycle Conditional Expectation-Maximization Algorithm," Working Papers 2013-1, University of Massachusetts Amherst, Department of Resource Economics.

  9. Siem Jan Koopman & Michel van der Wel, 2011. "Forecasting the U.S. Term Structure of Interest Rates using a Macroeconomic Smooth Dynamic Factor Model," Tinbergen Institute Discussion Papers 11-063/4, Tinbergen Institute.

    Cited by:

    1. GUO-FITOUSSI, Liang, 2013. "A Comparison of the Finite Sample Properties of Selection Rules of Factor Numbers in Large Datasets," MPRA Paper 50005, University Library of Munich, Germany.
    2. Poncela, Pilar & Ruiz, Esther, 2015. "Small versus big-data factor extraction in Dynamic Factor Models: An empirical assessment," DES - Working Papers. Statistics and Econometrics. WS ws1502, Universidad Carlos III de Madrid. Departamento de Estadística.
    3. Kuruppuarachchi, Duminda & Premachandra, I.M., 2016. "Information spillover dynamics of the energy futures market sector: A novel common factor approach," Energy Economics, Elsevier, vol. 57(C), pages 277-294.
    4. Caio Almeida & Axel Simonsen & José Vicente, 2012. "Forecasting Bond Yields with Segmented Term Structure Models," Working Papers Series 288, Central Bank of Brazil, Research Department.
    5. Wellmann, Dennis & Trück, Stefan, 2018. "Factors of the term structure of sovereign yield spreads," Journal of International Money and Finance, Elsevier, vol. 81(C), pages 56-75.
    6. Gregory R. Duffee, 2012. "Forecasting interest rates," Economics Working Paper Archive 599, The Johns Hopkins University,Department of Economics.
    7. Geert Mesters & Bernd Schwaab & Siem Jan Koopman, 2014. "A Dynamic Yield Curve Model with Stochastic Volatility and Non-Gaussian Interactions: An Empirical Study of Non-standard Monetary Policy in the Euro Area," Tinbergen Institute Discussion Papers 14-071/III, Tinbergen Institute.
    8. Duffee, Gregory, 2013. "Forecasting Interest Rates," Handbook of Economic Forecasting, Elsevier.

  10. Bent Jesper Christensen & Olaf Posch & Michel van der Wel, 2011. "Estimating Dynamic Equilibrium Models using Macro and Financial Data," CREATES Research Papers 2011-21, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Olaf Posch, 2018. "Resurrecting the New-Keynesian Model: (Un)conventional Policy and the Taylor Rule," CESifo Working Paper Series 6925, CESifo Group Munich.
    2. Giannone, Domenico & Monti, Francesca & Reichlin, Lucrezia, 2014. "Exploiting the monthly data-flow in structural forecasting," LSE Research Online Documents on Economics 57998, London School of Economics and Political Science, LSE Library.
    3. Claudia Foroni & Massimiliano Marcellino, 2013. "Mixed frequency structural models: estimation, and policy analysis," Working Paper 2013/15, Norges Bank.

  11. B. Jungbacker & S.J. Koopman & M. van der Wel, 2009. "Dynamic Factor Analysis in The Presence of Missing Data," Tinbergen Institute Discussion Papers 09-010/4, Tinbergen Institute, revised 11 Mar 2011.

    Cited by:

    1. Cecilia Frale & Stefano Grassi & Massimiliano Marcellino & Gianluigi Mazzi & Tommaso Proietti, 2013. "EuroMInd-C: a Disaggregate Monthly Indicator of Economic Activity for the Euro Area and member countries," CEIS Research Paper 287, Tor Vergata University, CEIS, revised 01 Oct 2013.

  12. Michel Van der Wel & Albert J. Menkveld & Asani Sarkar, 2009. "Are market makers uninformed and passive? Signing trades in the absence of quotes," Staff Reports 395, Federal Reserve Bank of New York.

    Cited by:

    1. Opschoor, Anne & Taylor, Nick & van der Wel, Michel & van Dijk, Dick, 2014. "Order flow and volatility: An empirical investigation," Journal of Empirical Finance, Elsevier, vol. 28(C), pages 185-201.

  13. Menkveld, Albert J. & Sarkar, Asani & van der Wel, Michel, 2008. "Customer flow, intermediaries, and the discovery of the equilibrium riskfree rate," CFS Working Paper Series 2008/47, Center for Financial Studies (CFS).

    Cited by:

    1. Fricke, Christoph & Menkhoff, Lukas, 2010. "Does the "Bund" dominate price discovery in Euro bond futures? Examining information shares," Hannover Economic Papers (HEP) dp-449, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.

  14. Siem Jan Koopman & Max I.P. Mallee & Michel van der Wel, 2007. "Analyzing the Term Structure of Interest Rates using the Dynamic Nelson-Siegel Model with Time-Varying Parameters," Tinbergen Institute Discussion Papers 07-095/4, Tinbergen Institute.

    Cited by:

    1. Borus Jungbacker & Siem Jan Koopman & Michel van der Wel, 2009. "Smooth Dynamic Factor Analysis with an Application to the U.S. Term Structure of Interest Rates," CREATES Research Papers 2009-39, Department of Economics and Business Economics, Aarhus University.

Articles

  1. Ozturk, Sait R. & van der Wel, Michel & van Dijk, Dick, 2017. "Intraday price discovery in fragmented markets," Journal of Financial Markets, Elsevier, vol. 32(C), pages 28-48.
    See citations under working paper version above.
  2. Christensen, Bent Jesper & Posch, Olaf & van der Wel, Michel, 2016. "Estimating dynamic equilibrium models using mixed frequency macro and financial data," Journal of Econometrics, Elsevier, vol. 194(1), pages 116-137.
    See citations under working paper version above.
  3. Opschoor, Anne & van Dijk, Dick & van der Wel, Michel, 2014. "Predicting volatility and correlations with Financial Conditions Indexes," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 435-447.

    Cited by:

    1. Cristina Amado & Annastiina Silvennoinen & Timo Teräsvirta, 2504. "Models with Multiplicative Decomposition of Conditional Variances and Correlations," CREATES Research Papers 2018-14, Department of Economics and Business Economics, Aarhus University.
    2. Lubberink, Martien, 2014. "Are banks’ below-par own debt repurchases a cause for prudential concern?," MPRA Paper 59475, University Library of Munich, Germany.
    3. P. Evans & David G. McMillan & Fiona J. McMillan, 2017. "Time-varying correlations and interrelations: Firm-level-based sector evidence," Journal of Asset Management, Palgrave Macmillan, vol. 18(3), pages 209-221, May.
    4. Nguyen, Duc Khuong & Walther, Thomas, 2017. "Modeling and forecasting commodity market volatility with long-term economic and financial variables," MPRA Paper 84464, University Library of Munich, Germany, revised Jan 2018.
    5. Stan Hurn & Peter C. B. Phillips & Shu-Ping Shi, 2016. ""Change Detection and the Causal Impact of the Yield Curve," Cowles Foundation Discussion Papers 2058, Cowles Foundation for Research in Economics, Yale University.
    6. Giovanni Bonaccolto & Massimiliano Caporin, 2016. "The Determinants of Equity Risk and Their Forecasting Implications: A Quantile Regression Perspective," Journal of Risk and Financial Management, MDPI, Open Access Journal, vol. 9(3), pages 1-25, July.
    7. Conrad, Christian & Schienle, Melanie, 2015. "Misspecification Testing in GARCH-MIDAS Models," Working Papers 0597, University of Heidelberg, Department of Economics.

  4. Opschoor, Anne & Taylor, Nick & van der Wel, Michel & van Dijk, Dick, 2014. "Order flow and volatility: An empirical investigation," Journal of Empirical Finance, Elsevier, vol. 28(C), pages 185-201.

    Cited by:

    1. Kim, Jae H. & Ji, Philip Inyeob, 2015. "Significance testing in empirical finance: A critical review and assessment," Journal of Empirical Finance, Elsevier, vol. 34(C), pages 1-14.
    2. Füss, Roland & Grabellus, Markus & Mager, Ferdinand & Stein, Michael, 2018. "Something in the air: Information density, news surprises, and price jumps," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 53(C), pages 50-75.
    3. Adam Clements & Joanne Fuller & Vasilios Papalexiou, 2015. "Public news flow in intraday component models for trading activity and volatility," NCER Working Paper Series 106, National Centre for Econometric Research.
    4. Conrad, Christian & Schienle, Melanie, 2015. "Misspecification Testing in GARCH-MIDAS Models," Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112919, Verein für Socialpolitik / German Economic Association.
    5. Chang, Ya-Ting & Gau, Yin-Feng & Hsu, Chih-Chiang, 2017. "Liquidity Commonality in Foreign Exchange Markets During the Global Financial Crisis and the Sovereign Debt Crisis: Effects of Macroeconomic and Quantitative Easing Announcements," The North American Journal of Economics and Finance, Elsevier, vol. 42(C), pages 172-192.

  5. Karstanje, Dennis & Sojli, Elvira & Tham, Wing Wah & van der Wel, Michel, 2013. "Economic valuation of liquidity timing," Journal of Banking & Finance, Elsevier, vol. 37(12), pages 5073-5087.
    See citations under working paper version above.
  6. 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. See citations under working paper version above.
  7. Menkveld, Albert J. & Sarkar, Asani & Wel, Michel van der, 2012. "Customer Order Flow, Intermediaries, and Discovery of the Equilibrium Risk-Free Rate," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 47(04), pages 821-849, August.

    Cited by:

    1. Valseth, Siri, 2013. "Price discovery in government bond markets," Journal of Financial Markets, Elsevier, vol. 16(1), pages 127-151.
    2. Piccotti, Louis R., 2018. "Jumps, cojumps, and efficiency in the spot foreign exchange market," Journal of Banking & Finance, Elsevier, vol. 87(C), pages 49-67.
    3. Wu, Lei & Liu, Chunlin & Meng, Qingbin & Zeng, Hongchao, 2018. "Price discovery in China's inter-bank bond market," Pacific-Basin Finance Journal, Elsevier, vol. 48(C), pages 84-98.
    4. Opschoor, Anne & Taylor, Nick & van der Wel, Michel & van Dijk, Dick, 2014. "Order flow and volatility: An empirical investigation," Journal of Empirical Finance, Elsevier, vol. 28(C), pages 185-201.
    5. Su, Fei & Zhang, Jingjing, 2018. "Global price discovery in the Australian dollar market and its determinants," Pacific-Basin Finance Journal, Elsevier, vol. 48(C), pages 35-55.

  8. Jungbacker, B. & Koopman, S.J. & van der Wel, M., 2011. "Maximum likelihood estimation for dynamic factor models with missing data," Journal of Economic Dynamics and Control, Elsevier, vol. 35(8), pages 1358-1368, August.
    See citations under working paper version above.
  9. Koopman, Siem Jan & Mallee, Max I. P. & Van der Wel, Michel, 2010. "Analyzing the Term Structure of Interest Rates Using the Dynamic Nelson–Siegel Model With Time-Varying Parameters," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(3), pages 329-343.

    Cited by:

    1. Hautsch, Nikolaus & Ou, Yangguoyi, 2009. "Analyzing interest rate risk: Stochastic volatility in the term structure of government bond yields," CFS Working Paper Series 2009/03, Center for Financial Studies (CFS).
    2. Shin, Minchul & Zhong, Molin, 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.).
    3. Molenaars, Tomas K. & Reinerink, Nick H. & Hemminga, Marcus A., 2013. "Forecasting the yield curve - Forecast performance of the dynamic Nelson-Siegel model from 1971 to 2008," MPRA Paper 61862, University Library of Munich, Germany.
    4. Joseph P. Byrne & Shuo Cao. & Dimitris Korobilis., 2015. "Term Structure Dynamics, Macro-Finance Factors and Model Uncertainty," Working Papers 2015_08, Business School - Economics, University of Glasgow.
    5. David Ardia & Lennart F. Hoogerheide, 2013. "Cross-Sectional Distribution of GARCH Coefficients across S&P 500 Constituents: Time-Variation over the Period 2000-2012," Cahiers de recherche 1313, CIRPEE.
    6. Delle Monache, Davide & Petrella, Ivan & Venditti, Fabrizio, 2016. "Adaptive state space models with applications to the business cycle and financial stress," CEPR Discussion Papers 11599, C.E.P.R. Discussion Papers.
    7. 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.
    8. Hautsch, Nikolaus & Yang, Fuyu, 2012. "Bayesian inference in a Stochastic Volatility Nelson–Siegel model," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3774-3792.
    9. Jens H. E. Christensen & Francis X. Diebold & Glenn D. Rudebusch, 2007. "The Affine Arbitrage-Free Class of Nelson-Siegel Term Structure Models," PIER Working Paper Archive 07-029, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    10. 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.
    11. Andrea Carriero & Sarah Mouabbi & Elisabetta Vangelista, 2015. "UK Term Structure Decompositions at the Zero Lower Bound," Working Papers 755, Queen Mary University of London, School of Economics and Finance.
    12. Davide Delle Monache & Ivan Petrella & Fabrizio Venditti, 2016. "Common Faith or Parting Ways? A Time Varying Parameters Factor Analysis of Euro-Area Inflation," Advances in Econometrics,in: Dynamic Factor Models, volume 35, pages 539-565 Emerald Publishing Ltd.
    13. Levant, Jared & Ma, Jun, 2017. "A dynamic Nelson-Siegel yield curve model with Markov switching," Economic Modelling, Elsevier, vol. 67(C), pages 73-87.
    14. João Caldeira & Guilherme Moura & André Santos, 2015. "Measuring Risk in Fixed Income Portfolios using Yield Curve Models," Computational Economics, Springer;Society for Computational Economics, vol. 46(1), pages 65-82, June.
    15. Byrne, Joseph P. & Cao, Shuo & Korobilis, Dimitris, 2015. "Co-Movement, Spillovers and Excess Returns in Global Bond Markets," SIRE Discussion Papers 2015-75, Scottish Institute for Research in Economics (SIRE).
    16. Siem Jan Koopman & Michel van der Wel, 2011. "Forecasting the U.S. Term Structure of Interest Rates using a Macroeconomic Smooth Dynamic Factor Model," Tinbergen Institute Discussion Papers 11-063/4, Tinbergen Institute.
    17. Martin Gonzalez-Rozada & Martin sola & Constantino Hevia & Fabio Spagnolo, 2012. "Estimating and Forecasting the Yield Curve Using a Markov Switching Dynamic Nelson and Siegel Model," Department of Economics Working Papers 2012-07, Universidad Torcuato Di Tella.
    18. Takamizawa, Hideyuki, 2015. "Impact of No-arbitrage on Interest Rate Dynamics," Working Paper Series G-1-5, Center for Financial Research, Graduate School of Commerce and Management, Hitotsubashi University.
    19. Dang-Nguyen, Stéphane & Le Caillec, Jean-Marc & Hillion, Alain, 2014. "The deterministic shift extension and the affine dynamic Nelson–Siegel model," The North American Journal of Economics and Finance, Elsevier, vol. 29(C), pages 402-417.
    20. Caio Almeida & Axel Simonsen & José Vicente, 2012. "Forecasting Bond Yields with Segmented Term Structure Models," Working Papers Series 288, Central Bank of Brazil, Research Department.
    21. Márcio Laurini, 2012. "A Hybrid Data Cloning Maximum Likelihood Estimator for Stochastic Volatility Models," IBMEC RJ Economics Discussion Papers 2012-02, Economics Research Group, IBMEC Business School - Rio de Janeiro.
    22. S. Mouabbi, 2014. "An arbitrage-free Nelson-Siegel term structure model with stochastic volatility for the determination of currency risk premia," Working papers 527, Banque de France.
    23. Lorenzo Boldrini & Eric Hillebrand, 2015. "The Forecasting Power of the Yield Curve, a Supervised Factor Model Approach," CREATES Research Papers 2015-39, Department of Economics and Business Economics, Aarhus University.
    24. Laurini, Márcio P. & Caldeira, João F., 2016. "A macro-finance term structure model with multivariate stochastic volatility," International Review of Economics & Finance, Elsevier, vol. 44(C), pages 68-90.
    25. Wali Ullah, 2017. "Term structure forecasting in affine framework with time-varying volatility," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 26(3), pages 453-483, August.
    26. Barnett, William & Ftiti, Zied & Jawadi, Fredj, 2018. "The Causal Relationships between Inflation and Inflation Uncertainty," MPRA Paper 86478, University Library of Munich, Germany.
    27. Caldeira, João F. & Laurini, Márcio P. & Portugal, Marcelo S., 2010. "Bayesian Inference Applied to Dynamic Nelson-Siegel Model with Stochastic Volatility," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 30(1), October.
    28. Borus Jungbacker & Siem Jan Koopman & Michel van der Wel, 0000. "Dynamic Factor Models with Smooth Loadings for Analyzing the Term Structure of Interest Rates," Tinbergen Institute Discussion Papers 09-041/4, Tinbergen Institute, revised 17 Sep 2010.
    29. Christensen, Jens H.E. & Lopez, Jose A. & Rudebusch, Glenn D., 2014. "Can Spanned Term Structure Factors Drive Stochastic Yield Volatility?," Working Paper Series 2014-3, Federal Reserve Bank of San Francisco.
    30. Eran Raviv, 2013. "Prediction Bias Correction for Dynamic Term Structure Models," Tinbergen Institute Discussion Papers 13-041/III, Tinbergen Institute.
    31. Niels S. Hansen & Asger Lunde, 2013. "Analyzing Oil Futures with a Dynamic Nelson-Siegel Model," CREATES Research Papers 2013-36, Department of Economics and Business Economics, Aarhus University.
    32. Geert Mesters & Bernd Schwaab & Siem Jan Koopman, 2014. "A Dynamic Yield Curve Model with Stochastic Volatility and Non-Gaussian Interactions: An Empirical Study of Non-standard Monetary Policy in the Euro Area," Tinbergen Institute Discussion Papers 14-071/III, Tinbergen Institute.
    33. Polychronis Manousopoulos & Michalis Michalopoulos, 2015. "Term structure of interest rates estimation using rational Chebyshev functions," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 38(2), pages 119-146, October.
    34. Alexey Akimov & Simon Stevenson & Maxim Zagonov, 2015. "Public Real Estate and the Term Structure of Interest Rates: A Cross-Country Study," The Journal of Real Estate Finance and Economics, Springer, vol. 51(4), pages 503-540, November.

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NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 13 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-ECM: Econometrics (8) 2008-02-23 2009-02-28 2009-09-19 2009-10-31 2011-06-25 2014-11-17 2015-04-25 2016-12-11. Author is listed
  2. NEP-FOR: Forecasting (6) 2011-04-23 2012-08-23 2014-11-17 2015-04-25 2015-08-25 2016-12-11. Author is listed
  3. NEP-MST: Market Microstructure (6) 2007-12-01 2009-07-03 2009-10-31 2012-03-14 2015-04-25 2015-07-11. Author is listed
  4. NEP-MAC: Macroeconomics (5) 2008-02-23 2008-02-23 2014-01-24 2015-04-25 2015-08-25. Author is listed
  5. NEP-ETS: Econometric Time Series (4) 2009-02-28 2009-09-19 2015-03-13 2016-12-11
  6. NEP-RMG: Risk Management (2) 2014-11-17 2015-04-25
  7. NEP-BAN: Banking (1) 2015-04-25
  8. NEP-CBA: Central Banking (1) 2011-06-25
  9. NEP-CTA: Contract Theory & Applications (1) 2012-03-14
  10. NEP-DGE: Dynamic General Equilibrium (1) 2012-06-13
  11. NEP-FMK: Financial Markets (1) 2015-04-25
  12. NEP-ICT: Information & Communication Technologies (1) 2012-03-14
  13. NEP-MON: Monetary Economics (1) 2014-01-24
  14. NEP-ORE: Operations Research (1) 2016-12-11
  15. NEP-TRA: Transition Economics (1) 2012-06-13

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