Publikationen

Arbeitspapiere

  • del Barrio Castro, T., Escribano, A., Sibbertsen, P. (2024): Modeling and Forecasting the Long Memory of Cyclical Trends in Poleoclimate Data | File |
  • Otto, P. and Sibbertsen, P. (2023): Spatial autoregressive fractionally integrated moving average model | File |
  • Less, V. and Sibbertsen, P. (2022): Estimation and Testing in a Perturbed Multivariate Long Memory Framework | File |

Referierte Fachzeitschriften

  • Dissanayake, P., Amft, J., Sibbertsen, P. (2024): Defining an exposure index along the Schleswig-Holstein Baltic Sea coast, Marine Geology, Volume 476, 107382
    DOI: https://doi.org/10.1016/j.margeo.2024.107382
  • Rodrigues, P. M. M., Sibbertsen, P. and Voges, M. (2024): The stability of government bond markets’ equilibrium and the interdependence of lending rates, Empirical Economics More info
    DOI: https://doi.org/10.1007/s00181-024-02623-x
  • Dierkes, M., Krupski, J., Schroen, S., Sibbertsen, P. (2023): Volatility-Dependent Probability Weighting and the Dynamics of the Pricing Kernel PuzzleReview of Derivatives Research
    DOI: https://doi.org/10.1007/s11147-023-09197-3
  • Dräger, L., Kolaiti, T. and Sibbertsen, P. (2023): Measuring Macroeconomic Convergence and Divergence within EMU Using Long MemoryEmpirical Economics
    DOI: https://doi.org/10.1007/s00181-023-02426-6
  • Mboya, M. and Sibbertsen, P. (2023): Optimal Forecasts in the Presence of Discrete Structural Breaks under Long MemoryJournal of Forecasting, Volume 42, Issue 7, 1889-1908
    DOI: http://doi.org/10.1002/for.2988
  • Afzal, A. and Sibbertsen, P. (2021): Modeling fractional cointegration between high and low stock prices in Asian countriesEmpirical Economics, 60 (2), 661 – 682 More info
    DOI: 10.1007/s00181-019-01784-4
  • Bertram, P., Flock, T., Ma, J. and Sibbertsen, P. (2021): Real Exchange Rates and Fundamentals in a new Markov-STAR Modelforthcoming in Oxford Bulletin of Economics and Statistics | File | More info
  • Dissanayake, P., Flock, T., Meier, J. und Sibbertsen, P. (2021): Modelling Short- and Long-Term Dependencies of Clustered High-Threshold Exceedances in Significant Wave HeightsMathematics 2021, 9(21), 2817 More info
  • Kampers, J., Gerhardt, E., Sibbertsen, P., Flock, T., Klapdor, R., Hertel, H., Jentschke, M. and Hillemanns, P. (2021): Protective operative techniques in radical hysterectomy in early cervical carcinoma and their influence on disease-free and overall survival: a systematic review and meta-analysis of risk groupsArchives of Gynecology and Obstetrics, 304, 577–587
    DOI: https://doi.org/10.1007/s00404-021-06082-y
  • Leschinski, C., Voges, M. and Sibbertsen, P. (2021): A Comparison of Semiparametric Tests for Fractional CointegrationStatistical Papers 62, 1997–2030
    DOI: https://doi.org/10.1007/s00362-020-01169-1
  • Leschinski, C., Voges, M. and Sibbertsen, P. (2021): Integration and Disintegration of EMU Government Bond MarketsEconometrics 2021, 9(1), 13 More info
    DOI: 10.3390/econometrics9010013
  • Voges, M. and Sibbertsen, P. (2021): Cyclical fractional cointegrationEconometrics and Statistics, Volume 19, 114-129 More info
    DOI: https://doi.org/10.1016/j.ecosta.2020.05.004
  • Voges, M. and Sibbertsen, P. (2021): Cyclical fractional cointegrationEconometrics and Statistics, Volume 19, 114-129 More info
    DOI: https://doi.org/10.1016/j.ecosta.2020.05.004
  • Jentschke, M., Kampers, J., Becker, J., Sibbertsen, P. and Hillemanns, P. (2020): Prophylactic HPV vaccination after conization: A systematic review and meta-analysisVaccine, Volume 38, Issue 41 | File |
    DOI: 10.1016/j.vaccine.2020.07.055
  • Wingert, S., Mboya, M. and Sibbertsen, P. (2020): Distinguishing between Breaks in the Mean and Breaks in Persistence under Long MemoryEconomics Letters, Volume 193, 109338 More info
    DOI: 10.1016/j.econlet.2020.109338
  • Becker, J., Hollstein, F., Prokopczuk, M. and Sibbertsen, P. (2019): The Memory of BetaJournal of Banking and Finance, Volume 124, 106026
    DOI: https://doi.org/10.2139/ssrn.3492931
  • Leschinski, C., Sibbertsen, P. (2019): Model Order Selection in Seasonal/Cyclical Long Memory ModelsEconometrics and Statistics, 1, 78-94
    DOI: https://doi.org/10.1016/j.ecosta.2017.11.002
  • Wegener, C., Basse, T., Sibbertsen, P. and Nguyen, D. K. (2019): Liquidity Risk and the Covered Bond Market in Times of Crisis: Empirical Evidence from GermanyAnnals of Operations Research 282, 407–426
    DOI: https://doi.org/10.1007/s10479-019-03326-8
  • Wenger, K., Fritzsch, B., Sibbertsen, P. and Ullmann, G. (2019): Can Google Trends improve Sales Forecasts on a Product Level?Applied Economics Letters, Volume 27, Issue 17
    DOI: 10.1080/13504851.2019.1686110
  • Wenger, K., Leschinski, C. and Sibbertsen, P. (2019): Change-in-Mean Tests in Long-memory Time Series: A Review of Recent DevelopmentsAdvances in Statistical Analysis, 103, 02/2019, 237-256. More info
  • Busch, M. and Sibbertsen, P. (2018): An Overview of Modified Semiparametric Memory Estimation MethodsEconometrics, 6(1), 13 More info
    DOI: 10.3390/econometrics6010013
  • Nguyen, D. B. B., Prokopczuk, M. and Sibbertsen, P. (2020) (2018): The Memory of Stock Return Volatility: Asset Pricing ImplicationsJournal of Financial Markets, Volume 47, 100487 More info
    DOI: 10.1016/j.finmar.2019.01.002
  • Sibbertsen, P., Leschinski, C., Busch, M. (2018): A Multivariate Test Against Spurious Long MemoryJournal of Econometrics | File | More info
  • Stöver, B. and Sibbertsen, P. (2018): Die räumliche Flexibilität von Studierenden - Gründe für das Wanderungsverhalten von Studienanfänger/-innen zwischen den BundesländernBeiträge zur Hochschulforschung, 03/2018, Heft 3, 8-33 More info
  • Wenger, K., Leschinski, C. and Sibbertsen, P. (2018): The Memory of VolatilityQuantitative Finance and Economics, 2(1), 137-159 More info
  • Wenger, K., Leschinski, C. and Sibbertsen, P. (2018): A Simple Test on Structural Change in Long-Memory Time SeriesEconomics Letters, 163, 02/2018, 90-94 More info
  • Demetrescu, M., Sibbertsen, P. (2016): Inference on the Long-Memory Properties of Time Series with Non-Stationary VolatilityEconomics Letters, 144, 07/2016, 80-84 More info
  • Rinke, S. and Sibbertsen, P. (2016): Information Criteria for Nonlinear Time Series ModelsStudies of Nonlinear Dynamics and Econometrics, 20(3), 325–341 More info
  • Bertram, P., Sibbertsen, P., Stahl, G. (2015): About the impact of Model Risk on Capital Reserves: A Quantitative AnalysisJournal of Risk, 17, 69-97 More info
  • Kaufmann, H., Heinen, F., Sibbertsen, P. (2014): The dynamics of real exchange rates - A reconsiderationJournal of Applied Econometrics, 29, 758 - 773 More info
  • Sibbertsen, P., Wegener, C. and Basse, T. (2014): Testing for a Break in the Persistence in Yield Spreads of EMU Government BondsJournal of Banking and Finance, 41, 109 - 118 More info
  • Bertram, P., Kruse, R. and Sibbertsen, P. (2013): Fractional integration versus level shifts: the case of realized correlationsStatistical Papers, 54, 977 - 991 More info
  • Heinen, F., Michael, S. and Sibbertsen, P. (2013): Weak identification in the ESTAR model and a new modelJournal of Time Series Analysis, 34, 238 - 261 More info
  • Kaufmann H., Kruse R. and Sibbertsen P. (2012): On tests for linearity against STAR models with deterministic trendsEconomics Letters, 117, 268 - 271 More info
  • Kruse, R., Frömmel, M., Menkhoff, L., Sibbertsen, P. (2012): What do we know about real exchange rate non-linearities?Empirical Economics, 43, 457 - 474 More info
  • Kruse, R., Sibbertsen, P. (2012): Long memory and changing persistenceEconomics Letters, 114, 268 - 272 More info
  • Sibbertsen, P., Willert, J. (2012): Testing for a break in persistence under long-range dependencies and mean shiftsStatistical Papers, 53, 357 - 370 More info
  • Davidson, J., Sibbertsen, P. (2009): Tests of Bias in Log-Periodogram RegressionEconomics Letters 102, 83-86 More info
  • Sibbertsen, P., Kruse, R. (2009): Testing for a break in persistence under long-range dependenciesJournal of Time Series Analysis 30, 263 - 285 More info
  • Sibbertsen, P., Stahl, G., Luedtke, C. (2008): Measuring model riskJournal of Risk Model Validation 2, 65 - 81 More info
  • Nordman, D., Sibbertsen, P., Lahiri, S. N. (2007): Empirical likelihood confidence intervals for the mean of a long-range dependent processJournal of Time Series Analysis 28, 576 - 599 More info
  • Rothe, C., Sibbertsen, P. (2006): Phillips - Perron - type unit root tests in the nonlinear ESTAR frameworkAllgemeines Statistisches Archiv 90, 439 - 456 More info
  • Sibbertsen, P., Krämer, W. (2006): The Power of the KPSS - Test for Cointegration when Residuals are Fractionally IntegratedEconomics Letters 91, 321 - 324 More info
  • Davidson, J., Sibbertsen, P. (2005): Generating schemes for long memory processesGenerating schemes for long memory processes More info
  • Halverscheid, S., Hiltawsky, K., Sibbertsen, P. (2004): SamstagsUni: Ein Konzept zwischen Schule, Lehrerbildung und HochschuleZeitschrift für Hochschuldidaktik September 2004, 1 - 12 More info
  • Sibbertsen, P. (2004): Long memory in volatilities of German stock returnsEmpirical Economics 29, 477 - 488 More info
  • Sibbertsen, P. (2004): Long-memory versus structural change: An overviewStatistical Papers 45, 465 - 515 More info
  • Beran, J., Ghosh, S., Sibbertsen, P. (2003): Nonparametric M-estimation with long-memory errorsJournal of Statistical Planning and Inference 117, 199 - 206 More info
  • Lohre, M., Sibbertsen, P., Könning, T. (2003): Modelling Water Flow of the Rhine River Using Seasonal Long MemoryWater Resources Research 39, 1132 - 1138 More info
  • Sibbertsen, P. (2003): Log-Periodogram estimation of the memory parameter of a long-memory process under trendStatistics and Probability Letters 61, 261 - 268 More info
  • Beran, J., Feng, Y., Ghosh, S., Sibbertsen, P. (2002): On robust local polynomial estimation with long-memory errorsInternational Journal of Forecasting 18, 227 - 241 More info
  • Krämer, W., Sibbertsen, P. (2002): Testing for structural change in the presence of long-memoryInternational Journal of Business and Economics 1, 235 - 243
  • Krämer, W., Sibbertsen, P., Kleiber, C. (2002): Long Memory versus Structural Change in Financial Time SeriesAllgemeines Statistisches Archiv 86, 83 - 96
  • Lohre, M., Sibbertsen, P. (2002): Persistenz und saisonale Abhängigkeiten in Abflüssen des RheinsHydrology and Water Resources Management 46, 166 - 174
  • Sibbertsen, P. (2001): S-estimation in the linear regression model with long- memory error terms under trendJournal of Time Series Analysis 22, 353 - 363 More info

Veröffentlichte Bücher und referierte Buchbeiträge

  • Voges, M., Leschinski, C. and Sibbertsen, P. (2018): Seasonal long memory in intraday volatility and trading volume of Dow Jones stocksAdvances in Applied Financial Econometrics More info
  • Grote, C., Sibbertsen, P. (2014): Testing for Cointegration in a Double-LSTR FrameworkBeran, Jan, Feng, Yuanhua and Hebbel, Hartmut: Empirical Economic and Financial Research - Theory, Methods and Practice, Springer, New York More info
  • Kaufmann, H., Kruse, R., Sibbertsen, P. (2014): A Simple procedures for specifying transition functions in persistent nonlinear time series modelsRecent Advances in Estimating Nonlinear Models, Springer, New York, 2014, XVI, 169 - 191. More info
  • Luedtke, C. , Sibbertsen, P. (2010): Model Risk in GARCH-Type Financial Time SeriesIn: Model Risk, Identification, Measurement and Management, D. Rösch and H. Schedule (editors), Risk books, 75 – 89.
  • Stahl, G., Sibbertsen, P., Bertram, P. (2010): Modellrisiko = Spezifikation + ValidierungIn: Handbuch Solvency II, C. Bennemann, L. Oehlenberg, and G. Stahl (editors), Schäffer-Poeschel-Verlag.
  • Peters, A., Sibbertsen, P. (2002): Tests on Fractional Cointegration. Comparison of a finite M- and ML-test on fractional cointegrationIn: Developments in Robust Statistics. Editors: R. Dutter, U. Gather, P. J. Rousseeuw and P. Filzmoser, 306 - 315.
  • Sibbertsen, P. (1999): Robuste Parameterschätzung im linearen Regressionsmodell.Verlag für Wissenschaft und Forschung, Berlin.
    ISBN: 978-3897000926