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Dan Christian Wunderli

Personal Details

First Name:Dan
Middle Name:Christian
Last Name:Wunderli
Suffix:
RePEc Short-ID:pwu147
[This author has chosen not to make the email address public]

Affiliation

Schweizerische Nationalbank (SNB)

Bern/Zürich, Switzerland
http://www.snb.ch/
RePEc:edi:snbgvch (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Dan Wunderli, 2012. "Controlling the danger of false discoveries in estimating multiple treatment effects," ECON - Working Papers 060, Department of Economics - University of Zurich.
  2. Michael Wolf & Dan Wunderli, 2012. "Bootstrap joint prediction regions," ECON - Working Papers 064, Department of Economics - University of Zurich, revised May 2013.
  3. Michael Wolf & Dan Wunderli, 2009. "Fund-of-funds construction by statistical multiple testing methods," IEW - Working Papers 445, Institute for Empirical Research in Economics - University of Zurich.

Articles

  1. Giuseppe Cavaliere & Dimitris N. Politis & Anders Rahbek & Michael Wolf & Dan Wunderli, 2015. "Recent developments in bootstrap methods for dependent data," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(3), pages 352-376, May.
  2. Larsen, Bradley J. & Oswald, Florian & Reich, Gregor & Wunderli, Dan, 2012. "A test of the extreme value type I assumption in the bus engine replacement model," Economics Letters, Elsevier, vol. 116(2), pages 213-216.

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. Michael Wolf & Dan Wunderli, 2012. "Bootstrap joint prediction regions," ECON - Working Papers 064, Department of Economics - University of Zurich, revised May 2013.

    Cited by:

    1. Anna Staszewska-Bystrova & Peter Winker, 2014. "Measuring Forecast Uncertainty of Corporate Bond Spreads by Bonferroni-Type Prediction Bands," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 6(2), pages 89-104, June.
    2. Fady Barsoum, 2015. "Point and Density Forecasts Using an Unrestricted Mixed-Frequency VAR Model," Working Paper Series of the Department of Economics, University of Konstanz 2015-19, Department of Economics, University of Konstanz.
    3. Régis Barnichon & Geert Mesters, 2020. "Optimal policy perturbations," Economics Working Papers 1716, Department of Economics and Business, Universitat Pompeu Fabra.
    4. Grabowski, Daniel & Staszewska-Bystrova, Anna, 2018. "Skewness-Adjusted Bootstrap Confidence Intervals and Confidence Bands for Impulse Response Functions," VfS Annual Conference 2018 (Freiburg, Breisgau): Digital Economy 181590, Verein für Socialpolitik / German Economic Association.
    5. Stefan Bruder, 2014. "Comparing several methods to compute joint prediction regions for path forecasts generated by vector autoregressions," ECON - Working Papers 181, Department of Economics - University of Zurich, revised Dec 2015.
    6. Maria Lucia Parrella & Giuseppina Albano & Cira Perna & Michele La Rocca, 2021. "Bootstrap joint prediction regions for sequences of missing values in spatio-temporal datasets," Computational Statistics, Springer, vol. 36(4), pages 2917-2938, December.
    7. Andrew Martinez, 2017. "Testing for Differences in Path Forecast Accuracy: Forecast-Error Dynamics Matter," Working Papers (Old Series) 1717, Federal Reserve Bank of Cleveland.
    8. Sílvia Gonçalves & Benoit Perron & Antoine Djogbenou, 2017. "Bootstrap Prediction Intervals for Factor Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(1), pages 53-69, January.
    9. Lütkepohl, Helmut & Staszewska-Bystrova, Anna & Winker, Peter, 2020. "Constructing joint confidence bands for impulse response functions of VAR models – A review," Econometrics and Statistics, Elsevier, vol. 13(C), pages 69-83.
    10. Pan, Li & Politis, Dimitris N., 2016. "Bootstrap prediction intervals for Markov processes," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 467-494.
    11. David Harris & Gael M. Martin & Indeewara Perera & Don S. Poskitt, 2017. "Construction and visualization of optimal confidence sets for frequentist distributional forecasts," Monash Econometrics and Business Statistics Working Papers 9/17, Monash University, Department of Econometrics and Business Statistics.
    12. Farooq Akram & Andrew Binning & Junior Maih, 2016. "Joint prediction bands for macroeconomic risk management," Working Paper 2016/7, Norges Bank.
    13. Pan, Li & Politis, Dimitris, 2014. "Bootstrap prediction intervals for Markov processes," University of California at San Diego, Economics Working Paper Series qt7555757g, Department of Economics, UC San Diego.
    14. Helmut Lütkepohl & Anna Staszewska-Bystrova & Peter Winker, 2014. "Confidence Bands for Impulse Responses: Bonferroni versus Wald," CESifo Working Paper Series 4634, CESifo.
    15. Marcellino, Massimiliano & Knüppel, Malte & Jordà , Òscar, 2010. "Empirical Simultaneous Confidence Regions for Path-Forecasts," CEPR Discussion Papers 7797, C.E.P.R. Discussion Papers.
    16. Régis Barnichon & Geert Mesters, 2022. "A Sufficient Statistics Approach for Macro Policy Evaluation," Working Paper Series 2022, Federal Reserve Bank of San Francisco.
    17. Antoniadis, Anestis & Brossat, Xavier & Cugliari, Jairo & Poggi, Jean-Michel, 2016. "A prediction interval for a function-valued forecast model: Application to load forecasting," International Journal of Forecasting, Elsevier, vol. 32(3), pages 939-947.
    18. Lütkepohl, Helmut & Staszewska-Bystrova, Anna & Winker, Peter, 2013. "Comparison of methods for constructing joint confidence bands for impulse response functions," SFB 649 Discussion Papers 2013-031, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    19. Fresoli, Diego Eduardo, 2014. "The uncertainty of conditional returns, volatilities and correlations in DCC models," DES - Working Papers. Statistics and Econometrics. WS ws140202, Universidad Carlos III de Madrid. Departamento de Estadística.
    20. Giovanni Fonseca & Federica Giummolè & Paolo Vidoni, 2021. "A note on simultaneous calibrated prediction intervals for time series," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(1), pages 317-330, March.
    21. Fresoli, Diego & Ruiz, Esther & Pascual, Lorenzo, 2015. "Bootstrap multi-step forecasts of non-Gaussian VAR models," International Journal of Forecasting, Elsevier, vol. 31(3), pages 834-848.
    22. Skrobotov, Anton (Скроботов, Антон) & Turuntseva, Marina (Турунцева, Марина), 2015. "Theoretical Aspects of Modeling of the SVAR [Теоретические Аспекты Моделирования Svar]," Published Papers mak8, Russian Presidential Academy of National Economy and Public Administration.
    23. Paolo Vidoni, 2017. "Improved multivariate prediction regions for Markov process models," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 26(1), pages 1-18, March.
    24. Òscar Jordà & Malte Knuppel & Massimiliano Marcellino, 2012. "Empirical simultaneous prediction regions for path-forecasts," Working Paper Series 2012-05, Federal Reserve Bank of San Francisco.

  2. Michael Wolf & Dan Wunderli, 2009. "Fund-of-funds construction by statistical multiple testing methods," IEW - Working Papers 445, Institute for Empirical Research in Economics - University of Zurich.

    Cited by:

    1. Enareta Kurtbegu & Juliana Caicedo-llano, 2014. "European equity fund managers: luck or skill?!," Economics Bulletin, AccessEcon, vol. 34(4), pages 2340-2350.
    2. Olivier Ledoit & Michael Wolf, 2019. "The power of (non-)linear shrinking: a review and guide to covariance matrix estimation," ECON - Working Papers 323, Department of Economics - University of Zurich, revised Feb 2020.
    3. McDowell, Shaun, 2018. "The benefits of international diversification with weight constraints: A cross-country examination," The Quarterly Review of Economics and Finance, Elsevier, vol. 69(C), pages 99-109.

Articles

  1. Giuseppe Cavaliere & Dimitris N. Politis & Anders Rahbek & Michael Wolf & Dan Wunderli, 2015. "Recent developments in bootstrap methods for dependent data," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(3), pages 352-376, May.

    Cited by:

    1. Germán Aneiros & Paula Raña & Philippe Vieu & Juan Vilar, 2018. "Bootstrap in semi-functional partial linear regression under dependence," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 27(3), pages 659-679, September.

  2. Larsen, Bradley J. & Oswald, Florian & Reich, Gregor & Wunderli, Dan, 2012. "A test of the extreme value type I assumption in the bus engine replacement model," Economics Letters, Elsevier, vol. 116(2), pages 213-216.

    Cited by:

    1. Christopher Ferrall, 2021. "Was Harold Zurcher Myopic After All? Replicating Rust's Engine Replacement Estimates," Working Paper 1467, Economics Department, Queen's University.

More information

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Statistics

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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 3 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 (3) 2009-10-03 2012-03-08 2012-07-29
  2. NEP-ETS: Econometric Time Series (1) 2012-03-08
  3. NEP-FOR: Forecasting (1) 2012-03-08

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