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Philipp Sibbertsen

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. Wenger, Kai & Leschinski, Christian & Sibbertsen, Philipp, 2017. "The Memory of Volatility," Hannover Economic Papers (HEP) dp-601, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.

    Mentioned in:

    1. Long Memory in Realized Volatility
      by Francis Diebold in No Hesitations on 2017-10-07 18:07:00

Wikipedia or ReplicationWiki mentions

(Only mentions on Wikipedia that link back to a page on a RePEc service)
  1. Hendrik Kaufmann & Florian Heinen & Philipp Sibbertsen, 2014. "The Dynamics Of Real Exchange Rates: A Reconsideration," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(5), pages 758-773, August.

    Mentioned in:

    1. The Dynamics Of Real Exchange Rates: A Reconsideration (Journal of Applied Econometrics 2014) in ReplicationWiki ()

Working papers

  1. Mboya, Mwasi & Sibbertsen, Philipp, 2022. "Optimal Forecasts in the Presence of Discrete Structural Breaks under Long Memory," Hannover Economic Papers (HEP) dp-705, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.

    Cited by:

    1. Kreye, Tom Jannik & Sibbertsen, Philipp, 2024. "Testing for a Forecast Accuracy Breakdown under Long Memory," Hannover Economic Papers (HEP) dp-729, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.

  2. Dräger, Lena & Nguyen, Duc Binh Benno & Prokopczuk, Marcel & Sibbertsen, Philipp, 2020. "The Long Memory of Equity Volatility and the Macroeconomy: International Evidence," Hannover Economic Papers (HEP) dp-667, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.

    Cited by:

    1. Guglielmo Maria Caporale & Luis A. Gil-Alana & Carlos Poza, 2021. "The Covid-19 Pandemic and the Degree of Persistence of US Stock Prices and Bond Yields," CESifo Working Paper Series 8976, CESifo.

  3. Leschinski, Christian & Voges, Michelle & Sibbertsen, Philipp, 2019. "A Comparison of Semiparametric Tests for Fractional Cointegration," Hannover Economic Papers (HEP) dp-651, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.

    Cited by:

    1. Christian Leschinski & Michelle Voges & Philipp Sibbertsen, 2021. "Integration and Disintegration of EMU Government Bond Markets," Econometrics, MDPI, vol. 9(1), pages 1-17, March.
    2. Dräger, Lena & Kolaiti, Theoplasti & Sibbertsen, Philipp, 2020. "Measuring Macroeconomic Convergence and Divergence within EMU Using Long Memory," Hannover Economic Papers (HEP) dp-675, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät, revised Feb 2021.
    3. Less, Vivien & Sibbertsen, Philipp, 2022. "Estimation and Testing in a Perturbed Multivariate Long Memory Framework," Hannover Economic Papers (HEP) dp-704, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    4. Theoplasti Kolaiti & Mwasi Mboya & Philipp Sibbertsen, 2020. "Volatility Transmission across Financial Markets: A Semiparametric Analysis," JRFM, MDPI, vol. 13(8), pages 1-13, July.

  4. Rodrigues, Paulo M.M. & Sibbertsen, Philipp & Voges, Michelle, 2019. "Testing for breaks in the cointegrating relationship: On the stability of government bond markets' equilibrium," Hannover Economic Papers (HEP) dp-656, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.

    Cited by:

    1. Luis F. Martins & Paulo M. M. Rodrigues, 2022. "Tests for segmented cointegration: an application to US governments budgets," Empirical Economics, Springer, vol. 63(2), pages 567-600, August.

  5. Busch, Marie & Sibbertsen, Philipp, 2018. "An Overview of Modified Semiparametric Memory Estimation Methods," Hannover Economic Papers (HEP) dp-628, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.

    Cited by:

    1. Alexander Boca Saravia & Gabriel Rodríguez, 2022. "Presidential approval in Peru: an empirical analysis using a fractionally cointegrated VAR," Economic Change and Restructuring, Springer, vol. 55(3), pages 1973-2010, August.

  6. Leschinski, Christian & Voges, Michelle & Sibbertsen, Philipp, 2018. "Integration and Disintegration of EMU Government Bond Markets," Hannover Economic Papers (HEP) dp-625, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.

    Cited by:

    1. Stoupos, Nikolaos & Kiohos, Apostolos, 2022. "Bond markets integration in the EU: New empirical evidence from the Eastern non-euro member-states," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
    2. Rodrigues, Paulo M.M. & Sibbertsen, Philipp & Voges, Michelle, 2019. "Testing for breaks in the cointegrating relationship: On the stability of government bond markets' equilibrium," Hannover Economic Papers (HEP) dp-656, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    3. Dräger, Lena & Kolaiti, Theoplasti & Sibbertsen, Philipp, 2020. "Measuring Macroeconomic Convergence and Divergence within EMU Using Long Memory," Hannover Economic Papers (HEP) dp-675, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät, revised Feb 2021.
    4. Yunus, Nafeesa, 2023. "Long-run and short-run impact of the U.S. economy on stock, bond and housing markets: An evaluation of U.S. and six major economies," The Quarterly Review of Economics and Finance, Elsevier, vol. 90(C), pages 211-232.
    5. Paulo M. M. Rodrigues & Philipp Sibbertsen & Michelle Voges, 2024. "The stability of government bond markets’ equilibrium and the interdependence of lending rates," Empirical Economics, Springer, vol. 67(6), pages 2503-2538, December.

  7. Wenger, Kai & Leschinski, Christian & Sibbertsen, Philipp, 2017. "The Memory of Volatility," Hannover Economic Papers (HEP) dp-601, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.

    Cited by:

    1. Busch, Marie & Sibbertsen, Philipp, 2018. "An Overview of Modified Semiparametric Memory Estimation Methods," Hannover Economic Papers (HEP) dp-628, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    2. Nguyen, Duc Binh Benno & Prokopczuk, Marcel & Sibbertsen, Philipp, 2017. "The Long Memory of Equity Volatility: International Evidence," Hannover Economic Papers (HEP) dp-614, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    3. Janis Becker & Christian Leschinski, 2021. "Estimating the volatility of asset pricing factors," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(2), pages 269-278, March.
    4. Hiroyuki Kawakatsu, 2021. "Information in daily data volatility measurements," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 1642-1656, April.
    5. Theoplasti Kolaiti & Mwasi Mboya & Philipp Sibbertsen, 2020. "Volatility Transmission across Financial Markets: A Semiparametric Analysis," JRFM, MDPI, vol. 13(8), pages 1-13, July.
    6. Stéphane Goutte & David Guerreiro & Bilel Sanhaji & Sophie Saglio & Julien Chevallier, 2019. "International Financial Markets," Post-Print halshs-02183053, HAL.

  8. Wenger, Kai & Leschinski, Christian & Sibbertsen, Philipp, 2017. "A Simple Test on Structural Change in Long-Memory Time Series," Hannover Economic Papers (HEP) dp-592, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.

    Cited by:

    1. Ata Assaf & Luis Alberiko Gil-Alana & Khaled Mokni, 2022. "True or spurious long memory in the cryptocurrency markets: evidence from a multivariate test and other Whittle estimation methods," Empirical Economics, Springer, vol. 63(3), pages 1543-1570, September.
    2. Kunal Saha & Vinodh Madhavan & Chandrashekhar G. R. & David McMillan, 2020. "Pitfalls in long memory research," Cogent Economics & Finance, Taylor & Francis Journals, vol. 8(1), pages 1733280-173, January.
    3. Wingert, Simon & Mboya, Mwasi Paza & Sibbertsen, Philipp, 2020. "Distinguishing between breaks in the mean and breaks in persistence under long memory," Economics Letters, Elsevier, vol. 193(C).
    4. Daiqing Xi & Tianxiao Pang, 2021. "Estimating multiple breaks in mean sequentially with fractionally integrated errors," Statistical Papers, Springer, vol. 62(1), pages 451-494, February.
    5. Richard T. Baillie & Fabio Calonaci & Dooyeon Cho & Seunghwa Rho, 2019. "Long Memory, Realized Volatility and HAR Models," Working Papers 881, Queen Mary University of London, School of Economics and Finance.
    6. Dooruj Rambaccussing & Murat Mazibas, 2020. "True versus Spurious Long Memory in Cryptocurrencies," JRFM, MDPI, vol. 13(9), pages 1-11, August.

  9. Nguyen, Duc Binh Benno & Prokopczuk, Marcel & Sibbertsen, Philipp, 2017. "The Long Memory of Equity Volatility: International Evidence," Hannover Economic Papers (HEP) dp-614, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.

    Cited by:

    1. Busch, Marie & Sibbertsen, Philipp, 2018. "An Overview of Modified Semiparametric Memory Estimation Methods," Hannover Economic Papers (HEP) dp-628, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.

  10. Nguyen, Duc Binh Benno & Prokopczuk, Marcel & Sibbertsen, Philipp, 2017. "The Memory of Stock Return Volatility: Asset Pricing Implications," Hannover Economic Papers (HEP) dp-613, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.

    Cited by:

    1. Massimiliano Giacalone & Demetrio Panarello, 2022. "A Nonparametric Approach for Testing Long Memory in Stock Returns’ Higher Moments," Mathematics, MDPI, vol. 10(5), pages 1-21, February.
    2. Busch, Marie & Sibbertsen, Philipp, 2018. "An Overview of Modified Semiparametric Memory Estimation Methods," Hannover Economic Papers (HEP) dp-628, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    3. Duan, Kun & Gao, Yang & Mishra, Tapas & Satchell, Stephen, 2023. "Efficiency dynamics across segmented Bitcoin Markets: Evidence from a decomposition strategy," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 83(C).
    4. Nguyen, Duc Binh Benno & Prokopczuk, Marcel & Sibbertsen, Philipp, 2017. "The Long Memory of Equity Volatility: International Evidence," Hannover Economic Papers (HEP) dp-614, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    5. Theoplasti Kolaiti & Mwasi Mboya & Philipp Sibbertsen, 2020. "Volatility Transmission across Financial Markets: A Semiparametric Analysis," JRFM, MDPI, vol. 13(8), pages 1-13, July.

  11. Wenger, Kai & Leschinski, Christian & Sibbertsen, Philipp, 2017. "Change-in-Mean Tests in Long-memory Time Series: A Review of Recent Developments," Hannover Economic Papers (HEP) dp-598, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.

    Cited by:

    1. Li, Zheng & Zeng, Jingjing & Hensher, David A., 2023. "An efficient approach to structural breaks and the case of automobile gasoline consumption in Australia," Transportation Research Part A: Policy and Practice, Elsevier, vol. 169(C).
    2. Ata Assaf & Luis Alberiko Gil-Alana & Khaled Mokni, 2022. "True or spurious long memory in the cryptocurrency markets: evidence from a multivariate test and other Whittle estimation methods," Empirical Economics, Springer, vol. 63(3), pages 1543-1570, September.
    3. Kunal Saha & Vinodh Madhavan & Chandrashekhar G. R. & David McMillan, 2020. "Pitfalls in long memory research," Cogent Economics & Finance, Taylor & Francis Journals, vol. 8(1), pages 1733280-173, January.
    4. Daiqing Xi & Tianxiao Pang, 2021. "Estimating multiple breaks in mean sequentially with fractionally integrated errors," Statistical Papers, Springer, vol. 62(1), pages 451-494, February.
    5. Sibbertsen, Philipp & Wenger, Kai & Wingert, Simon, 2020. "Testing for Multiple Structural Breaks in Multivariate Long Memory Time Series," Hannover Economic Papers (HEP) dp-676, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    6. Wenger, Kai & Less, Vivien, 2020. "A modified Wilcoxon test for change points in long-range dependent time series," Economics Letters, Elsevier, vol. 192(C).

  12. Sibbertsen, Philipp & Leschinski, Christian & Holzhausen, Marie, 2015. "A Multivariate Test Against Spurious Long Memory," Hannover Economic Papers (HEP) dp-547, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.

    Cited by:

    1. Ata Assaf & Luis Alberiko Gil-Alana & Khaled Mokni, 2022. "True or spurious long memory in the cryptocurrency markets: evidence from a multivariate test and other Whittle estimation methods," Empirical Economics, Springer, vol. 63(3), pages 1543-1570, September.
    2. Kunal Saha & Vinodh Madhavan & Chandrashekhar G. R. & David McMillan, 2020. "Pitfalls in long memory research," Cogent Economics & Finance, Taylor & Francis Journals, vol. 8(1), pages 1733280-173, January.
    3. Alia Afzal & Philipp Sibbertsen, 2023. "Long Memory, Spurious Memory: Persistence in Range-Based Volatility of Exchange Rates," Open Economies Review, Springer, vol. 34(4), pages 789-811, September.
    4. Wenger, Kai & Leschinski, Christian & Sibbertsen, Philipp, 2017. "The Memory of Volatility," Hannover Economic Papers (HEP) dp-601, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    5. Kai Wenger & Christian Leschinski & Philipp Sibbertsen, 2019. "Change-in-mean tests in long-memory time series: a review of recent developments," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 103(2), pages 237-256, June.
    6. Mboya, Mwasi & Sibbertsen, Philipp, 2022. "Optimal Forecasts in the Presence of Discrete Structural Breaks under Long Memory," Hannover Economic Papers (HEP) dp-705, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    7. Leschinski, Christian & Sibbertsen, Philipp, 2018. "The Periodogram of Spurious Long-Memory Processes," Hannover Economic Papers (HEP) dp-632, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    8. Assaf, Ata & Mokni, Khaled & Yousaf, Imran & Bhandari, Avishek, 2023. "Long memory in the high frequency cryptocurrency markets using fractal connectivity analysis: The impact of COVID-19," Research in International Business and Finance, Elsevier, vol. 64(C).
    9. Becker, Janis & Leschinski, Christian & Sibbertsen, Philipp, 2019. "Robust Multivariate Local Whittle Estimation and Spurious Fractional Cointegration," Hannover Economic Papers (HEP) dp-660, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    10. Lujia Bai & Weichi Wu, 2021. "Detecting long-range dependence for time-varying linear models," Papers 2110.08089, arXiv.org, revised Mar 2023.
    11. Dooruj Rambaccussing & Murat Mazibas, 2020. "True versus Spurious Long Memory in Cryptocurrencies," JRFM, MDPI, vol. 13(9), pages 1-11, August.
    12. Less, Vivien & Sibbertsen, Philipp, 2022. "Estimation and Testing in a Perturbed Multivariate Long Memory Framework," Hannover Economic Papers (HEP) dp-704, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    13. Sibbertsen, Philipp & Wenger, Kai & Wingert, Simon, 2020. "Testing for Multiple Structural Breaks in Multivariate Long Memory Time Series," Hannover Economic Papers (HEP) dp-676, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    14. Leschinski, Christian & Sibbertsen, Philipp, 2017. "Origins of Spurious Long Memory," Hannover Economic Papers (HEP) dp-595, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.

  13. Rinke, Saskia & Sibbertsen, Philipp, 2015. "Information Criteria for Nonlinear Time Series Models," Hannover Economic Papers (HEP) dp-548, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.

    Cited by:

    1. Hee-Young Kim & Christian H. Weiß & Tobias A. Möller, 2020. "Models for autoregressive processes of bounded counts: How different are they?," Computational Statistics, Springer, vol. 35(4), pages 1715-1736, December.
    2. Rinke, Saskia, 2016. "The Influence of Additive Outliers on the Performance of Information Criteria to Detect Nonlinearity," Hannover Economic Papers (HEP) dp-575, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    3. Francesco Giordano & Marcella Niglio & Cosimo Damiano Vitale, 2023. "Linear approximation of the Threshold AutoRegressive model: an application to order estimation," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 32(1), pages 27-56, March.
    4. Greta Goracci, 2021. "An empirical study on the parsimony and descriptive power of TARMA models," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(1), pages 109-137, March.

  14. Demetrescu, Matei & Sibbertsen, Philipp, 2014. "Inference on the Long-Memory Properties of Time Series with Non-Stationary Volatility," Hannover Economic Papers (HEP) dp-531, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.

    Cited by:

    1. Matei Demetrescu & Christoph Hanck & Robinson Kruse, 2016. "Fixed-b Inference in the Presence of Time-Varying Volatility," CREATES Research Papers 2016-01, Department of Economics and Business Economics, Aarhus University.
    2. Eroğlu, Burak Alparslan & Yiğit, Taner, 2016. "A nonparametric unit root test under nonstationary volatility," Economics Letters, Elsevier, vol. 140(C), pages 6-10.
    3. Hanck, Christoph & Demetrescu, Matei & Kruse, Robinson, 2015. "Fixed-b Asymptotics for t-Statistics in the Presence of Time-Varying Volatility," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112916, Verein für Socialpolitik / German Economic Association.

  15. Leschinski, Christian & Sibbertsen, Philipp, 2014. "Model Order Selection in Seasonal/Cyclical Long Memory Models," Hannover Economic Papers (HEP) dp-535, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.

    Cited by:

    1. Voges, Michelle & Leschinski, Christian & Sibbertsen, Philipp, 2017. "Seasonal long memory in intraday volatility and trading volume of Dow Jones stocks," Hannover Economic Papers (HEP) dp-599, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.

  16. Sibbertsen, Philipp & Wegener, Christoph & Basse, Tobias, 2013. "Testing for a Break in the Persistence in Yield Spreads of EMU Government Bonds," Hannover Economic Papers (HEP) dp-517, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.

    Cited by:

    1. Nguyen, Duc Binh Benno & Prokopczuk, Marcel & Sibbertsen, Philipp, 2017. "The Memory of Stock Return Volatility: Asset Pricing Implications," Hannover Economic Papers (HEP) dp-613, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    2. Christian Leschinski & Michelle Voges & Philipp Sibbertsen, 2021. "Integration and Disintegration of EMU Government Bond Markets," Econometrics, MDPI, vol. 9(1), pages 1-17, March.
    3. Kinateder, Harald & Campbell, Ross & Choudhury, Tonmoy, 2021. "Safe haven in GFC versus COVID-19: 100 turbulent days in the financial markets," Finance Research Letters, Elsevier, vol. 43(C).
    4. Tobias Basse & Robinson Kruse & Christoph Wegener, 2017. "The Walking Debt Crisis," CREATES Research Papers 2017-06, Department of Economics and Business Economics, Aarhus University.
    5. António Afonso & João Tovar Jalles, 2020. "Economic volatility and sovereign yields’ determinants: a time-varying approach," Empirical Economics, Springer, vol. 58(2), pages 427-451, February.
    6. Del Brio, Esther B. & Mora-Valencia, Andrés & Perote, Javier, 2017. "The kidnapping of Europe: High-order moments' transmission between developed and emerging markets," Emerging Markets Review, Elsevier, vol. 31(C), pages 96-115.
    7. Christoph Wegener & Tobias Basse & Philipp Sibbertsen & Duc Khuong Nguyen, 2019. "Liquidity risk and the covered bond market in times of crisis: empirical evidence from Germany," Annals of Operations Research, Springer, vol. 282(1), pages 407-426, November.
    8. Juan Carlos Cuestas & Luis A. Gil-Alana & Paulo José Regis, 2015. "The Sustainability of European External Debt: What have We Learned?," Review of International Economics, Wiley Blackwell, vol. 23(3), pages 445-468, August.
    9. Qin, Weiping & Cho, Sungjun & Hyde, Stuart, 2023. "Time-varying bond market integration and the impact of financial crises," International Review of Financial Analysis, Elsevier, vol. 90(C).
    10. Thomas Dimpfl & Tobias Langen, 2019. "How Unemployment Affects Bond Prices: A Mixed Frequency Google Nowcasting Approach," Computational Economics, Springer;Society for Computational Economics, vol. 54(2), pages 551-573, August.
    11. M. Frömmel & R. Kruse, 2009. "Interest rate convergence in the EMS prior to European Monetary Union," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 09/610, Ghent University, Faculty of Economics and Business Administration.
    12. Fang, Libing & Yu, Honghai & Li, Lei, 2017. "The effect of economic policy uncertainty on the long-term correlation between U.S. stock and bond markets," Economic Modelling, Elsevier, vol. 66(C), pages 139-145.
    13. Takumi Ito & Fumiko Takeda, 2022. "Do sentiment indices always improve the prediction accuracy of exchange rates?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(4), pages 840-852, July.
    14. Dimpfl, Thomas & Langen, Tobias, 2015. "A Cross-Country Analysis of Unemployment and Bonds with Long-Memory Relations," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112921, Verein für Socialpolitik / German Economic Association.
    15. Robinson Kruse & Christoph Wegener, 2019. "Explosive behaviour and long memory with an application to European bond yield spreads," Scottish Journal of Political Economy, Scottish Economic Society, vol. 66(1), pages 139-153, February.
    16. Antonakakis, Nikolaos & Christou, Christina & Cunado, Juncal & Gupta, Rangan, 2017. "Convergence patterns in sovereign bond yield spreads: Evidence from the Euro Area," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 49(C), pages 129-139.
    17. Wang, Qishu, 2023. "Herding behavior and the dynamics of ESG performance in the European banking industry," Finance Research Letters, Elsevier, vol. 58(PD).
    18. Ahmet Sensoy & Duc Khuong Nguyen & Erk Hacihasanoglu & Ahmed Rostom, 2018. "Dynamic Integration and Network Structure of the EMU Sovereign Bond Markets," Working Papers 2018-009, Department of Research, Ipag Business School.
    19. Badarau, Cristina & Huart, Florence & Sangaré, Ibrahima, 2021. "Macroeconomic and policy implications of eurobonds," International Review of Law and Economics, Elsevier, vol. 65(C).
    20. Sylwester Kozak, 2021. "The Impact of COVID-19 on Bank Equity and Performance: The Case of Central Eastern South European Countries," Sustainability, MDPI, vol. 13(19), pages 1-15, October.
    21. Christian Leschinski, Christian & Bertram, Philip, 2013. "Contagion Dynamics in EMU Government Bond Spreads," Hannover Economic Papers (HEP) dp-515, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    22. Banerjee, Ameet Kumar & Pradhan, H.K. & Akhtaruzzaman, Md & Sensoy, Ahmet & Dann, Susan, 2024. "Anatomy of sovereign yield behaviour using textual news," Research in International Business and Finance, Elsevier, vol. 71(C).
    23. Tholl, Johannes & Schwarzbach, Christoph & Pittalis, Sandro & von Mettenheim, Hans-Jörg, 2020. "Bank funding and the recent political development in Italy: What about redenomination risk?," International Review of Law and Economics, Elsevier, vol. 64(C).
    24. Ahmad, Wasim & Mishra, Anil V. & Daly, Kevin J., 2018. "Financial connectedness of BRICS and global sovereign bond markets," Emerging Markets Review, Elsevier, vol. 37(C), pages 1-16.
    25. Soon, Siew-Voon & Baharumshah, Ahmad Zubaidi & Mohamad Shariff, Nurul Sima, 2017. "The persistence in real interest rates: Does it solve the intertemporal consumption behavior puzzle?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 50(C), pages 36-51.
    26. Bessler, Wolfgang & Leonhardt, Alexander & Wolff, Dominik, 2016. "Analyzing hedging strategies for fixed income portfolios: A Bayesian approach for model selection," International Review of Financial Analysis, Elsevier, vol. 46(C), pages 239-256.
    27. Ekaterina Koroleva & Maxim Kopeykin, 2022. "Understanding of Macro Factors That Affect Yield of Government Bonds," Risks, MDPI, vol. 10(8), pages 1-10, August.
    28. Basse, Tobias, 2020. "Solvency II and sovereign credit risk: Additional empirical evidence and some thoughts about implications for regulators and lawmakers," International Review of Law and Economics, Elsevier, vol. 64(C).
    29. Kunze, Frederik & Wegener, Christoph & Bizer, Kilian & Spiwoks, Markus, 2017. "Forecasting European interest rates in times of financial crisis – What insights do we get from international survey forecasts?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 48(C), pages 192-205.
    30. Paulo M. M. Rodrigues & Philipp Sibbertsen & Michelle Voges, 2024. "The stability of government bond markets’ equilibrium and the interdependence of lending rates," Empirical Economics, Springer, vol. 67(6), pages 2503-2538, December.
    31. Leschinski, Christian & Bertram, Philip, 2017. "Time varying contagion in EMU government bond spreads," Journal of Financial Stability, Elsevier, vol. 29(C), pages 72-91.
    32. Yu Hsing, 2015. "Determinants of the Government Bond Yield in Spain: A Loanable Funds Model," IJFS, MDPI, vol. 3(3), pages 1-9, July.
    33. Christoph Wegener & Tobias Basse & Frederik Kunze & Hans-Jörg von Mettenheim, 2016. "Oil prices and sovereign credit risk of oil producing countries: an empirical investigation," Quantitative Finance, Taylor & Francis Journals, vol. 16(12), pages 1961-1968, December.
    34. Kerkemeier, Marco & Kruse-Becher, Robinson, 2022. "Join the club! Dynamics of global ESG indices convergence," Finance Research Letters, Elsevier, vol. 49(C).
    35. Sensoy, Ahmet & Hacihasanoglu, Erk & Rostom, Ahmed, 2015. "European economic and monetary union sovereign debt markets," Policy Research Working Paper Series 7149, The World Bank.

  17. Kaufmann, Hendrik & Kruse, Robinson & Sibbertsen, Philipp, 2012. "A simple specification procedure for the transition function in persistent nonlinear time series models," Hannover Economic Papers (HEP) dp-500, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.

    Cited by:

    1. Grote, Claudia & Sibbertsen, Philipp, 2013. "Testing for Cointegration in a Double-LSTR Framework," Hannover Economic Papers (HEP) dp-514, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    2. He, HongWen & Zhang, YongZhi & Xiong, Rui & Wang, Chun, 2015. "A novel Gaussian model based battery state estimation approach: State-of-Energy," Applied Energy, Elsevier, vol. 151(C), pages 41-48.

  18. Heinen, Florian & Kaufmann, Hendrik & Sibbertsen, Philipp, 2011. "The dynamics of real exchange rates - A reconsideration," Hannover Economic Papers (HEP) dp-463, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.

    Cited by:

    1. Bertram, Philip & Ma, Jun & Sibbertsen, Philipp, 2015. "Real exchange rates and economic fundamentals: An investigation based on a Markov-STAR model," Hannover Economic Papers (HEP) dp-565, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    2. Michael Curran & Adnan Velic, 2017. "Real Exchange Rate Persistence and Country Characteristics," Trinity Economics Papers tep0917, Trinity College Dublin, Department of Economics.
    3. Philip Bertram & Teresa Flock & Jun Ma & Philipp Sibbertsen, 2022. "Real Exchange Rates and Fundamentals in a new Markov‐STAR Model," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(2), pages 356-379, April.
    4. Goodness C. Aye & Mehmet Balcilar & Adél Bosch & Rangan Gupta & Francois Stofberg, 2013. "The out-of-sample forecasting performance of non-linear models of real exchange rate behaviour: The case of the South African Rand," European Journal of Comparative Economics, Cattaneo University (LIUC), vol. 10(1), pages 121-148, April.

  19. Robinson Kruse & Philipp Sibbertsen, 2010. "Long memory and changing persistence," CREATES Research Papers 2010-42, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Robinson Kruse & Daniel Ventosa-Santaulària & Antonio E. Noriega, 2013. "Changes in persistence, spurious regressions and the Fisher hypothesis," CREATES Research Papers 2013-11, Department of Economics and Business Economics, Aarhus University.
    2. Strohsal, Till & Winkelmann, Lars, 2012. "Assessing the anchoring of inflation expectations," SFB 649 Discussion Papers 2012-022, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    3. Chen, Zhanshou & Xing, Yuhong & Li, Fuxiao, 2016. "Sieve bootstrap monitoring for change from short to long memory," Economics Letters, Elsevier, vol. 140(C), pages 53-56.
    4. Canarella, Giorgio & Miller, Stephen M., 2017. "Inflation targeting and inflation persistence: New evidence from fractional integration and cointegration," Journal of Economics and Business, Elsevier, vol. 92(C), pages 45-62.

  20. Donauer, Stefanie & Heinen, Florian & Sibbertsen, Philipp, 2010. "Identification problems in ESTAR models and a new model," Hannover Economic Papers (HEP) dp-444, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.

    Cited by:

    1. Peter Martey Addo & Monica Billio & Dominique Guegan, 2014. "The univariate MT-STAR model and a new linearity and unit root test procedure," Post-Print hal-01310518, HAL.
    2. Mario Cerrato & Christian de Peretti & Rolf Larsson & Nicholas Sarantis, 2011. "A nonlinear panel unit root test under cross section dependence," Working Papers 2011_08, Business School - Economics, University of Glasgow.
    3. Peter Martey Addo & Monica Billio & Dominique Guegan, 2011. "A test for a new modelling: The Univariate MT-STAR Model," Documents de travail du Centre d'Economie de la Sorbonne 11083, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.

  21. Robinson Kruse & Michael Frömmel & Lukas Menkhoff & Philipp Sibbertsen, 2009. "What do we know about real exchange rate non-linearities?," CREATES Research Papers 2009-50, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Niels Haldrup & Robinson Kruse & Timo Teräsvirta & Rasmus T. Varneskov, 2012. "Unit roots, nonlinearities and structural breaks," CREATES Research Papers 2012-14, Department of Economics and Business Economics, Aarhus University.
    2. Hendrik Kaufmann & Robinson Kruse & Philipp Sibbertsen, 2012. "On tests for linearity against STAR models with deterministic trends," CREATES Research Papers 2012-20, Department of Economics and Business Economics, Aarhus University.
    3. Aloy, Marcel & Boutahar, Mohamed & Gente, Karine & Péguin-Feissolle, Anne, 2011. "Purchasing power parity and the long memory properties of real exchange rates: Does one size fit all?," Economic Modelling, Elsevier, vol. 28(3), pages 1279-1290, May.
    4. Beckmann, Joscha, 2011. "Nonlinear Adjustment, Purchasing Power Parity and the Role of Nominal Exchange Rates and Prices," Ruhr Economic Papers 272, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    5. Brian M. Lucey & Fergal A. O’Connor, 2013. "Do bubbles occur in the gold price? An investigation of gold lease rates and Markov Switching models," Borsa Istanbul Review, Research and Business Development Department, Borsa Istanbul, vol. 13(3), pages 53-63, September.
    6. Dinçer Afat & Michael Frömmel, 2020. "An Alternative Version of Purchasing Power Parity," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 25(4), pages 511-517, October.
    7. Burns, Kelly & Moosa, Imad A., 2015. "Enhancing the forecasting power of exchange rate models by introducing nonlinearity: Does it work?," Economic Modelling, Elsevier, vol. 50(C), pages 27-39.
    8. Aaron D. Smallwood, 2016. "A Monte Carlo Investigation of Unit Root Tests and Long Memory in Detecting Mean Reversion in I(0) Regime Switching, Structural Break, and Nonlinear Data," Econometric Reviews, Taylor & Francis Journals, vol. 35(6), pages 986-1012, June.
    9. Leandro Maciel & Rosangela Ballini, 2021. "Functional Fuzzy Rule-Based Modeling for Interval-Valued Data: An Empirical Application for Exchange Rates Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 57(2), pages 743-771, February.

  22. Sibbertsen, Philipp & Willert, Juliane, 2009. "Testing for a break in persistence under long-range dependencies and mean shifts," Hannover Economic Papers (HEP) dp-422, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.

    Cited by:

    1. Nguyen, Duc Binh Benno & Prokopczuk, Marcel & Sibbertsen, Philipp, 2017. "The Memory of Stock Return Volatility: Asset Pricing Implications," Hannover Economic Papers (HEP) dp-613, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    2. M. Frömmel & R. Kruse, 2011. "Testing for a rational bubble under long memory," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 11/722, Ghent University, Faculty of Economics and Business Administration.
    3. Assaf, Ata & Bhandari, Avishek & Charif, Husni & Demir, Ender, 2022. "Multivariate long memory structure in the cryptocurrency market: The impact of COVID-19," International Review of Financial Analysis, Elsevier, vol. 82(C).
    4. Robinson Kruse & Philipp Sibbertsen, 2010. "Long memory and changing persistence," CREATES Research Papers 2010-42, Department of Economics and Business Economics, Aarhus University.
    5. Lajos Horváth & Hemei Li & Zhenya Liu, 2021. "How to identify the different phases of stock market bubbles statistically?," Post-Print hal-03511435, HAL.
    6. Busch, Ulrike & Nautz, Dieter, 2009. "Controllability and persistence of money Market rates along the yield curve: Evidence from the Euro area," SFB 649 Discussion Papers 2009-029, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    7. Wingert, Simon & Mboya, Mwasi Paza & Sibbertsen, Philipp, 2020. "Distinguishing between breaks in the mean and breaks in persistence under long memory," Economics Letters, Elsevier, vol. 193(C).
    8. Paulo M.M. Rodrigues & Uwe Hassler, 2014. "Persistence in the Banking Industry: Fractional integration and breaks in memory," Working Papers w201406, Banco de Portugal, Economics and Research Department.
    9. Zhanshou Chen & Yanting Xiao & Fuxiao Li, 2021. "Monitoring memory parameter change-points in long-memory time series," Empirical Economics, Springer, vol. 60(5), pages 2365-2389, May.
    10. Christoph Wegener & Tobias Basse & Philipp Sibbertsen & Duc Khuong Nguyen, 2019. "Liquidity risk and the covered bond market in times of crisis: empirical evidence from Germany," Annals of Operations Research, Springer, vol. 282(1), pages 407-426, November.
    11. Juan Carlos Cuestas & Luis A. Gil-Alana & Paulo José Regis, 2015. "The Sustainability of European External Debt: What have We Learned?," Review of International Economics, Wiley Blackwell, vol. 23(3), pages 445-468, August.
    12. M. Frömmel & R. Kruse, 2009. "Interest rate convergence in the EMS prior to European Monetary Union," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 09/610, Ghent University, Faculty of Economics and Business Administration.
    13. Giorgio Canarella & Stephen M. Miller, 2016. "Inflation Persistence and Structural Breaks: The Experience of Inflation Targeting Countries and the US," Working papers 2016-11, University of Connecticut, Department of Economics.
    14. Katarzyna Lasak & Carlos Velasco, 2014. "Fractional Cointegration Rank Estimation," Tinbergen Institute Discussion Papers 14-021/III, Tinbergen Institute.
    15. Guglielmo Maria Caporale & Luis A. Gil-Alana, 2009. "Long Memory in US Real Output per Capita," Discussion Papers of DIW Berlin 891, DIW Berlin, German Institute for Economic Research.
    16. Chen, Zhanshou & Xing, Yuhong & Li, Fuxiao, 2016. "Sieve bootstrap monitoring for change from short to long memory," Economics Letters, Elsevier, vol. 140(C), pages 53-56.
    17. Sibbertsen, Philipp & Wegener, Christoph & Basse, Tobias, 2013. "Testing for a Break in the Persistence in Yield Spreads of EMU Government Bonds," Hannover Economic Papers (HEP) dp-517, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    18. Si Zhang & Hao Jin & Menglin Su, 2024. "Modified Block Bootstrap Testing for Persistence Change in Infinite Variance Observations," Mathematics, MDPI, vol. 12(2), pages 1-25, January.
    19. Assaf, Ata & Mokni, Khaled & Yousaf, Imran & Bhandari, Avishek, 2023. "Long memory in the high frequency cryptocurrency markets using fractal connectivity analysis: The impact of COVID-19," Research in International Business and Finance, Elsevier, vol. 64(C).
    20. Sibbertsen, Philipp & Willert, Juliane, 2009. "Testing for a break in persistence under long-range dependencies and mean shifts," Hannover Economic Papers (HEP) dp-422, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    21. Soon, Siew-Voon & Baharumshah, Ahmad Zubaidi & Mohamad Shariff, Nurul Sima, 2017. "The persistence in real interest rates: Does it solve the intertemporal consumption behavior puzzle?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 50(C), pages 36-51.
    22. Davide Delle Monache & Stefano Grassi & Paolo Santucci de Magistris, 2017. "Does the ARFIMA really shift?," CREATES Research Papers 2017-16, Department of Economics and Business Economics, Aarhus University.
    23. Erhard Reschenhofer & Werner Ploberger & Georg Lehecka, 2014. "Detecting fuzzy periodic patterns in futures spreads," Statistical Papers, Springer, vol. 55(2), pages 487-496, May.
    24. Luis F. Martins & Paulo M. M. Rodrigues, 2022. "Tests for segmented cointegration: an application to US governments budgets," Empirical Economics, Springer, vol. 63(2), pages 567-600, August.
    25. Chen, Zhanshou & Jin, Zi & Tian, Zheng & Qi, Peiyan, 2012. "Bootstrap testing multiple changes in persistence for a heavy-tailed sequence," Computational Statistics & Data Analysis, Elsevier, vol. 56(7), pages 2303-2316.
    26. Jorge M. L. Andraz & Raúl F. C. Guerreiro & Paulo M. M. Rodrigues, 2018. "Persistence of travel and leisure sector equity indices," Empirical Economics, Springer, vol. 54(4), pages 1801-1825, June.
    27. Aeneas Rooch & Ieva Zelo & Roland Fried, 2019. "Estimation methods for the LRD parameter under a change in the mean," Statistical Papers, Springer, vol. 60(1), pages 313-347, February.
    28. Zhuoheng Chen & Yijun Hu, 2017. "Cumulative sum estimator for change-point in panel data," Statistical Papers, Springer, vol. 58(3), pages 707-728, September.
    29. Guillermo Ferreira & Jorge Mateu & Jose A. Vilar & Joel Muñoz, 2021. "Bootstrapping regression models with locally stationary disturbances," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(2), pages 341-363, June.
    30. Canarella, Giorgio & Miller, Stephen M., 2017. "Inflation targeting and inflation persistence: New evidence from fractional integration and cointegration," Journal of Economics and Business, Elsevier, vol. 92(C), pages 45-62.
    31. Kunze, Frederik & Basse, Tobias & Wegener, Christoph & Spiwoks, Markus, 2018. "The emergence of the RMB: A "New Normal" for China's exchange rate system?," University of Göttingen Working Papers in Economics 348, University of Goettingen, Department of Economics.

  23. Florian Heinen & Philipp Sibbertsen & Robinson Kruse, 2009. "Forecasting long memory time series under a break in persistence," CREATES Research Papers 2009-53, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. M. Frömmel & R. Kruse, 2011. "Testing for a rational bubble under long memory," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 11/722, Ghent University, Faculty of Economics and Business Administration.
    2. Mboya, Mwasi & Sibbertsen, Philipp, 2022. "Optimal Forecasts in the Presence of Discrete Structural Breaks under Long Memory," Hannover Economic Papers (HEP) dp-705, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    3. Sibbertsen, Philipp & Wegener, Christoph & Basse, Tobias, 2013. "Testing for a Break in the Persistence in Yield Spreads of EMU Government Bonds," Hannover Economic Papers (HEP) dp-517, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    4. Heinen, Florian & Willert, Juliane, 2011. "Monitoring a change in persistence of a long range dependent time series," Hannover Economic Papers (HEP) dp-479, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.

  24. Kuswanto, Heri & Sibbertsen, Philipp, 2008. "A Study on "Spurious Long Memory in Nonlinear Time Series Models"," Hannover Economic Papers (HEP) dp-410, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.

    Cited by:

    1. Ata Assaf & Luis Alberiko Gil-Alana & Khaled Mokni, 2022. "True or spurious long memory in the cryptocurrency markets: evidence from a multivariate test and other Whittle estimation methods," Empirical Economics, Springer, vol. 63(3), pages 1543-1570, September.
    2. Abounoori, Abbas Ali & Naderi, Esmaeil & Gandali Alikhani, Nadiya & Amiri, Ashkan, 2013. "Financial Time Series Forecasting by Developing a Hybrid Intelligent System," MPRA Paper 45615, University Library of Munich, Germany.
    3. Kuswanto, Heri, 2009. "A New Simple Test Against Spurious Long Memory Using Temporal Aggregation," Hannover Economic Papers (HEP) dp-425, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    4. Guglielmo Maria Caporale & Luis A. Gil-Alana & Carlos Poza, 2020. "Inflation in the G7 Countries: Persistence and Structural Breaks," CESifo Working Paper Series 8349, CESifo.
    5. Nazarian, Rafik & Naderi, Esmaeil & Gandali Alikhani, Nadiya & Amiri, Ashkan, 2013. "Long Memory Analysis: An Empirical Investigation," MPRA Paper 45605, University Library of Munich, Germany.
    6. Gil-Alana, Luis A. & Infante, Juan & Martín-Valmayor, Miguel Angel, 2023. "Persistence and long run co-movements across stock market prices," The Quarterly Review of Economics and Finance, Elsevier, vol. 89(C), pages 347-357.
    7. Delavari, Majid & Gandali Alikhani, Nadiya & Naderi, Esmaeil, 2012. "Do Dynamic Neural Networks Stand a Better Chance in Fractionally Integrated Process Forecasting?," MPRA Paper 45977, University Library of Munich, Germany.
    8. Juan Carlos Cuestas & Luis A. Gil-Alana & María Malmierca, 2022. "Credit-to-GDP ratios – non-linear trends and persistence: evidence from 44 OECD economies," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 50(3), pages 448-463, March.

  25. Sibbertsen, Philipp & Stahl, Gerhard & Luedtke, Corinna, 2008. "Measuring Model Risk," Hannover Economic Papers (HEP) dp-409, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.

    Cited by:

    1. Schlegel, Friederike & Hakenes, Hendrik, 2013. "Model Risk - an Agency Theoretic Approach," VfS Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 79954, Verein für Socialpolitik / German Economic Association.
    2. Dannenberg, Henry, 2011. "The Importance of Estimation Uncertainty in a Multi-Rating Class Loan Portfolio," IWH Discussion Papers 11/2011, Halle Institute for Economic Research (IWH).
    3. Volker Stein & Arnd Wiedemann, 2016. "Risk governance: conceptualization, tasks, and research agenda," Journal of Business Economics, Springer, vol. 86(8), pages 813-836, November.
    4. Mariano González-Sánchez & Eva M. Ibáñez Jiménez & Ana I. Segovia San Juan, 2022. "Market and model risks: a feasible joint estimate methodology," Risk Management, Palgrave Macmillan, vol. 24(3), pages 187-213, September.
    5. Stahl, Gerhard & Sibbertsen, Philipp & Bertram, Philip, 2011. "Modellrisiko = Spezifikation + Validierung," Hannover Economic Papers (HEP) dp-468, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    6. Gourieroux, Christian & Tiomo, Andre, 2019. "The Evaluation of Model Risk for Probability of Default and Expected Loss," MPRA Paper 95795, University Library of Munich, Germany.

  26. James Davidson & Philipp Sibbertsen, 2008. "Tests of Bias in Log-Periodogram Regression," Discussion Papers 0805, University of Exeter, Department of Economics.

    Cited by:

    1. M. Frömmel & R. Kruse, 2011. "Testing for a rational bubble under long memory," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 11/722, Ghent University, Faculty of Economics and Business Administration.
    2. Robinson Kruse & Philipp Sibbertsen, 2010. "Long memory and changing persistence," CREATES Research Papers 2010-42, Department of Economics and Business Economics, Aarhus University.
    3. Bertram, Philip & Sibbertsen, Philipp & Stahl, Gerhard, 2011. "About the Impact of Model Risk on Capital Reserves: A Quantitative Analysis," Hannover Economic Papers (HEP) dp-469, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    4. Busch, Ulrike & Nautz, Dieter, 2009. "Controllability and persistence of money Market rates along the yield curve: Evidence from the Euro area," SFB 649 Discussion Papers 2009-029, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    5. Nordman, Dan Nordman & Sibbertsen, Philipp & Lahiri, Soumendra N., 2005. "Empirical likelihood confidence intervals for the mean of a long-range dependent process," Hannover Economic Papers (HEP) dp-327, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    6. Abderrazak Ben Maatoug & Rim Lamouchi & Russell Davidson & Ibrahim Fatnassi, 2018. "Modelling Foreign Exchange Realized Volatility Using High Frequency Data: Long Memory versus Structural Breaks," Post-Print hal-01982032, HAL.
    7. Benjamin R Auer, 2016. "Pure return persistence, Hurst exponents and hedge fund selection – A practical note," Journal of Asset Management, Palgrave Macmillan, vol. 17(5), pages 319-330, September.
    8. Walid Chkili, 2021. "Modeling Bitcoin price volatility: long memory vs Markov switching," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 11(3), pages 433-448, September.
    9. Philip Bertram & Robinson Kruse & Philipp Sibbertsen, 2013. "Fractional integration versus level shifts: the case of realized asset correlations," Statistical Papers, Springer, vol. 54(4), pages 977-991, November.
    10. Tapas Mishra & Bazoumana Ouattara & Mamata Parhi, 2011. "A Note on Shock Persistence in Total Factor Productivity Growth," Economics Bulletin, AccessEcon, vol. 31(2), pages 1869-1893.
    11. Auer, Benjamin R., 2016. "On the performance of simple trading rules derived from the fractal dynamics of gold and silver price fluctuations," Finance Research Letters, Elsevier, vol. 16(C), pages 255-267.
    12. Dooruj Rambaccussing & Murat Mazibas, 2020. "True versus Spurious Long Memory in Cryptocurrencies," JRFM, MDPI, vol. 13(9), pages 1-11, August.
    13. Auer, Benjamin R., 2016. "On time-varying predictability of emerging stock market returns," Emerging Markets Review, Elsevier, vol. 27(C), pages 1-13.
    14. Auer, Benjamin R. & Hoffmann, Andreas, 2016. "Do carry trade returns show signs of long memory?," The Quarterly Review of Economics and Finance, Elsevier, vol. 61(C), pages 201-208.

  27. Sibbertsen, Philipp & Kruse, Robinson, 2007. "Testing for a break in persistence under long-range dependencies," Hannover Economic Papers (HEP) dp-381, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.

    Cited by:

    1. Nguyen, Duc Binh Benno & Prokopczuk, Marcel & Sibbertsen, Philipp, 2017. "The Memory of Stock Return Volatility: Asset Pricing Implications," Hannover Economic Papers (HEP) dp-613, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    2. M. Frömmel & R. Kruse, 2011. "Testing for a rational bubble under long memory," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 11/722, Ghent University, Faculty of Economics and Business Administration.
    3. Assaf, Ata & Bhandari, Avishek & Charif, Husni & Demir, Ender, 2022. "Multivariate long memory structure in the cryptocurrency market: The impact of COVID-19," International Review of Financial Analysis, Elsevier, vol. 82(C).
    4. Uwe Hassler & Jan Scheithauer, 2011. "Detecting changes from short to long memory," Statistical Papers, Springer, vol. 52(4), pages 847-870, November.
    5. Robinson Kruse & Philipp Sibbertsen, 2010. "Long memory and changing persistence," CREATES Research Papers 2010-42, Department of Economics and Business Economics, Aarhus University.
    6. Lajos Horváth & Hemei Li & Zhenya Liu, 2021. "How to identify the different phases of stock market bubbles statistically?," Post-Print hal-03511435, HAL.
    7. Busch, Ulrike & Nautz, Dieter, 2009. "Controllability and persistence of money Market rates along the yield curve: Evidence from the Euro area," SFB 649 Discussion Papers 2009-029, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    8. Bond, Derek & Gallagher, Emer & Ramsey, Elaine, 2012. "A preliminary investigation of northern Ireland's housing market dynamics," MPRA Paper 39806, University Library of Munich, Germany.
    9. Kruse, Robinson, 2008. "Rational bubbles and fractional integration," Hannover Economic Papers (HEP) dp-394, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    10. Rodrigues, Paulo M.M. & Sibbertsen, Philipp & Voges, Michelle, 2019. "Testing for breaks in the cointegrating relationship: On the stability of government bond markets' equilibrium," Hannover Economic Papers (HEP) dp-656, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    11. Wingert, Simon & Mboya, Mwasi Paza & Sibbertsen, Philipp, 2020. "Distinguishing between breaks in the mean and breaks in persistence under long memory," Economics Letters, Elsevier, vol. 193(C).
    12. Paulo M.M. Rodrigues & Uwe Hassler, 2014. "Persistence in the Banking Industry: Fractional integration and breaks in memory," Working Papers w201406, Banco de Portugal, Economics and Research Department.
    13. Zhanshou Chen & Yanting Xiao & Fuxiao Li, 2021. "Monitoring memory parameter change-points in long-memory time series," Empirical Economics, Springer, vol. 60(5), pages 2365-2389, May.
    14. Christoph Wegener & Tobias Basse & Philipp Sibbertsen & Duc Khuong Nguyen, 2019. "Liquidity risk and the covered bond market in times of crisis: empirical evidence from Germany," Annals of Operations Research, Springer, vol. 282(1), pages 407-426, November.
    15. Juan Carlos Cuestas & Luis A. Gil-Alana & Paulo José Regis, 2015. "The Sustainability of European External Debt: What have We Learned?," Review of International Economics, Wiley Blackwell, vol. 23(3), pages 445-468, August.
    16. M. Frömmel & R. Kruse, 2009. "Interest rate convergence in the EMS prior to European Monetary Union," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 09/610, Ghent University, Faculty of Economics and Business Administration.
    17. Giorgio Canarella & Stephen M. Miller, 2016. "Inflation Persistence and Structural Breaks: The Experience of Inflation Targeting Countries and the US," Working papers 2016-11, University of Connecticut, Department of Economics.
    18. Robinson Kruse & Daniel Ventosa-Santaulària & Antonio E. Noriega, 2013. "Changes in persistence, spurious regressions and the Fisher hypothesis," CREATES Research Papers 2013-11, Department of Economics and Business Economics, Aarhus University.
    19. Katarzyna Lasak & Carlos Velasco, 2014. "Fractional Cointegration Rank Estimation," Tinbergen Institute Discussion Papers 14-021/III, Tinbergen Institute.
    20. Dominique Guégan, 2009. "A Meta-Distribution for Non-Stationary Samples," CREATES Research Papers 2009-24, Department of Economics and Business Economics, Aarhus University.
    21. Guglielmo Maria Caporale & Luis A. Gil-Alana, 2009. "Long Memory in US Real Output per Capita," Discussion Papers of DIW Berlin 891, DIW Berlin, German Institute for Economic Research.
    22. Martins, Luis F. & Rodrigues, Paulo M.M., 2014. "Testing for persistence change in fractionally integrated models: An application to world inflation rates," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 502-522.
    23. Uwe Hassler & Barbara Meller, 2014. "Detecting multiple breaks in long memory the case of U.S. inflation," Empirical Economics, Springer, vol. 46(2), pages 653-680, March.
    24. Florian Heinen & Philipp Sibbertsen & Robinson Kruse, 2009. "Forecasting long memory time series under a break in persistence," CREATES Research Papers 2009-53, Department of Economics and Business Economics, Aarhus University.
    25. Chen, Zhanshou & Xing, Yuhong & Li, Fuxiao, 2016. "Sieve bootstrap monitoring for change from short to long memory," Economics Letters, Elsevier, vol. 140(C), pages 53-56.
    26. Sibbertsen, Philipp & Wegener, Christoph & Basse, Tobias, 2013. "Testing for a Break in the Persistence in Yield Spreads of EMU Government Bonds," Hannover Economic Papers (HEP) dp-517, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    27. Assaf, Ata & Mokni, Khaled & Yousaf, Imran & Bhandari, Avishek, 2023. "Long memory in the high frequency cryptocurrency markets using fractal connectivity analysis: The impact of COVID-19," Research in International Business and Finance, Elsevier, vol. 64(C).
    28. Sibbertsen, Philipp & Willert, Juliane, 2009. "Testing for a break in persistence under long-range dependencies and mean shifts," Hannover Economic Papers (HEP) dp-422, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    29. Soon, Siew-Voon & Baharumshah, Ahmad Zubaidi & Mohamad Shariff, Nurul Sima, 2017. "The persistence in real interest rates: Does it solve the intertemporal consumption behavior puzzle?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 50(C), pages 36-51.
    30. Davide Delle Monache & Stefano Grassi & Paolo Santucci de Magistris, 2017. "Does the ARFIMA really shift?," CREATES Research Papers 2017-16, Department of Economics and Business Economics, Aarhus University.
    31. Grassi, Stefano & Santucci de Magistris, Paolo, 2014. "When long memory meets the Kalman filter: A comparative study," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 301-319.
    32. Luis F. Martins & Paulo M. M. Rodrigues, 2022. "Tests for segmented cointegration: an application to US governments budgets," Empirical Economics, Springer, vol. 63(2), pages 567-600, August.
    33. Chen, Zhanshou & Jin, Zi & Tian, Zheng & Qi, Peiyan, 2012. "Bootstrap testing multiple changes in persistence for a heavy-tailed sequence," Computational Statistics & Data Analysis, Elsevier, vol. 56(7), pages 2303-2316.
    34. Jorge M. L. Andraz & Raúl F. C. Guerreiro & Paulo M. M. Rodrigues, 2018. "Persistence of travel and leisure sector equity indices," Empirical Economics, Springer, vol. 54(4), pages 1801-1825, June.
    35. Heinen, Florian & Willert, Juliane, 2011. "Monitoring a change in persistence of a long range dependent time series," Hannover Economic Papers (HEP) dp-479, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    36. Guillermo Ferreira & Jorge Mateu & Jose A. Vilar & Joel Muñoz, 2021. "Bootstrapping regression models with locally stationary disturbances," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(2), pages 341-363, June.
    37. Canarella, Giorgio & Miller, Stephen M., 2017. "Inflation targeting and inflation persistence: New evidence from fractional integration and cointegration," Journal of Economics and Business, Elsevier, vol. 92(C), pages 45-62.
    38. Kunze, Frederik & Basse, Tobias & Wegener, Christoph & Spiwoks, Markus, 2018. "The emergence of the RMB: A "New Normal" for China's exchange rate system?," University of Göttingen Working Papers in Economics 348, University of Goettingen, Department of Economics.

  28. Kuswanto, Heri & Sibbertsen, Philipp, 2007. "Can we distinguish between common nonlinear time series models and long memory?," Hannover Economic Papers (HEP) dp-380, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.

    Cited by:

    1. Kuswanto, Heri & Sibbertsen, Philipp, 2008. "A Study on "Spurious Long Memory in Nonlinear Time Series Models"," Hannover Economic Papers (HEP) dp-410, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    2. Busch, Ulrike & Nautz, Dieter, 2009. "Controllability and persistence of money Market rates along the yield curve: Evidence from the Euro area," SFB 649 Discussion Papers 2009-029, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    3. Kuswanto, Heri, 2009. "A New Simple Test Against Spurious Long Memory Using Temporal Aggregation," Hannover Economic Papers (HEP) dp-425, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.

  29. Rothe, Christoph & Sibbertsen, Philipp, 2005. "Phillips-Perron-type unit root tests in the nonlinear ESTAR framework," Hannover Economic Papers (HEP) dp-315, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.

    Cited by:

    1. Rickard Sandberg, 2015. "M-estimator based unit root tests in the ESTAR framework," Statistical Papers, Springer, vol. 56(4), pages 1115-1135, November.
    2. Hepsag, Aycan, 2017. "New unit root tests with two smooth breaks and nonlinear adjustment," MPRA Paper 83353, University Library of Munich, Germany.
    3. Niels Haldrup & Robinson Kruse & Timo Teräsvirta & Rasmus T. Varneskov, 2012. "Unit roots, nonlinearities and structural breaks," CREATES Research Papers 2012-14, Department of Economics and Business Economics, Aarhus University.
    4. Chen, Shyh-Wei, 2014. "Smooth transition, non-linearity and current account sustainability: Evidence from the European countries," Economic Modelling, Elsevier, vol. 38(C), pages 541-554.
    5. Kuswanto, Heri & Sibbertsen, Philipp, 2009. "Testing for Long Memory Against ESTAR Nonlinearities," Hannover Economic Papers (HEP) dp-427, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    6. Ahmad, Yamin & Lo, Ming Chien & Mykhaylova, Olena, 2013. "Causes of nonlinearities in low-order models of the real exchange rate," Journal of International Economics, Elsevier, vol. 91(1), pages 128-141.
    7. Robinson Kruse, 2011. "A new unit root test against ESTAR based on a class of modified statistics," Statistical Papers, Springer, vol. 52(1), pages 71-85, February.
    8. Sandberg, Rickard, 2016. "Trends, unit roots, structural changes, and time-varying asymmetries in U.S. macroeconomic data: the Stock and Watson data re-examined," Economic Modelling, Elsevier, vol. 52(PB), pages 699-713.
    9. Onsurang Norrbin & Aaron D. Smallwood, 2011. "Mean Reversion in the Real Interest Rate and the Effects of Calculating Expected Inflation," Southern Economic Journal, John Wiley & Sons, vol. 78(1), pages 107-130, July.
    10. Rehim Kılıç, 2016. "Tests for Linearity in Star Models: Supwald and Lm-Type Tests," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(5), pages 660-674, September.
    11. Shyh-Wei Chen & Chi-Sheng Hsu & Cyun-Jhen Pen, 2016. "Are Inflation Rates Mean-reverting Processes? Evidence from Six Asian Countries," Journal of Economics and Management, College of Business, Feng Chia University, Taiwan, vol. 12(1), pages 119-155, February.
    12. Dilem Yildirim & Ralf Becker & Denise R Osborn, 2009. "Bootstrap Unit Root Tests for Nonlinear Threshold Models," Economics Discussion Paper Series 0915, Economics, The University of Manchester.
    13. Chen, Shyh-Wei & Hsu, Chi-Sheng, 2016. "Threshold, smooth transition and mean reversion in inflation: New evidence from European countries," Economic Modelling, Elsevier, vol. 53(C), pages 23-36.

  30. Nordman, Dan Nordman & Sibbertsen, Philipp & Lahiri, Soumendra N., 2005. "Empirical likelihood confidence intervals for the mean of a long-range dependent process," Hannover Economic Papers (HEP) dp-327, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.

    Cited by:

    1. Gong, Yun & Peng, Liang & Qi, Yongcheng, 2010. "Smoothed jackknife empirical likelihood method for ROC curve," Journal of Multivariate Analysis, Elsevier, vol. 101(6), pages 1520-1531, July.
    2. Gianfranco Adimari & Annamaria Guolo, 2010. "A note on the asymptotic behaviour of empirical likelihood statistics," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 19(4), pages 463-476, November.
    3. Wu, Rongning & Cao, Jiguo, 2011. "Blockwise empirical likelihood for time series of counts," Journal of Multivariate Analysis, Elsevier, vol. 102(3), pages 661-673, March.
    4. Feifan Jiang & Lihong Wang, 2018. "Adjusted blockwise empirical likelihood for long memory time series models," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 27(2), pages 319-332, June.
    5. Chioneso S. Marange & Yongsong Qin & Raymond T. Chiruka & Jesca M. Batidzirai, 2023. "A Blockwise Empirical Likelihood Test for Gaussianity in Stationary Autoregressive Processes," Mathematics, MDPI, vol. 11(4), pages 1-20, February.
    6. Li, Minqiang & Peng, Liang & Qi, Yongcheng, 2011. "Reduce computation in profile empirical likelihood method," MPRA Paper 33744, University Library of Munich, Germany.

  31. Sibbertsen, Philipp & Weißbach, Rafael, 2004. "The cost for the default of a loan : Linking theory and practice," Technical Reports 2004,33, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.

    Cited by:

    1. Weißbach, Rafael, 2004. "A rule of thumb for the economic capital of a large credit portfolio," Technical Reports 2004,58, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.

  32. Herzberg, Markus & Sibbertsen, Philipp, 2004. "Pricing of options under different volatility models," Technical Reports 2004,62, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.

    Cited by:

    1. Härdle, Wolfgang Karl & Mungo, Julius, 2008. "Value-at-risk and expected shortfall when there is long range dependence," SFB 649 Discussion Papers 2008-006, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    2. Christian Conrad, 2007. "Non-negativity Conditions for the Hyperbolic GARCH Model," KOF Working papers 07-162, KOF Swiss Economic Institute, ETH Zurich.
    3. Härdle, Wolfgang Karl & Mungo, Julius, 2007. "Long memory persistence in the factor of Implied volatility dynamics," SFB 649 Discussion Papers 2007-027, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

  33. Sibbertsen, Philipp & Venetis, Ioannis, 2003. "Distinguishing between long-range dependence and deterministic trends," Technical Reports 2003,16, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.

    Cited by:

    1. Zhongjun Qu, 2010. "A Test Against Spurious Long Memory," Boston University - Department of Economics - Working Papers Series WP2010-051, Boston University - Department of Economics.
    2. Cassola, Nuno & Morana, Claudio, 2010. "Comovements in volatility in the euro money market," Journal of International Money and Finance, Elsevier, vol. 29(3), pages 525-539, April.
    3. Morana, Claudio, 2006. "A small scale macroeconometric model for the Euro-12 area," Economic Modelling, Elsevier, vol. 23(3), pages 391-426, May.
    4. Laura Mayoral, 2005. "Is the observed persistence spurious? A test for fractional integration versus short memory and structural breaks," Economics Working Papers 956, Department of Economics and Business, Universitat Pompeu Fabra.
    5. Juan J. Dolado & Jesús Gonzalo & Laura Mayoral, 2005. "What is What? A Simple Time-Domain Test of Long-memory vs. Structural Breaks," Working Papers 258, Barcelona School of Economics.
    6. Laura Mayoral, 2005. "Further evidence on the statistical properties of real GNP," Economics Working Papers 955, Department of Economics and Business, Universitat Pompeu Fabra, revised Feb 2006.

  34. Davidson, James & Sibbertsen, Philipp, 2002. "Generating schemes for long memory processes: Regimes, aggregation and linearity," Technical Reports 2002,46, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.

    Cited by:

    1. Guillaume Chevillon & Alain Hecq & Sébastien Laurent, 2018. "Generating Univariate Fractional Integration within a Large VAR(1)," AMSE Working Papers 1844, Aix-Marseille School of Economics, France.
    2. Kuswanto, Heri & Sibbertsen, Philipp, 2008. "A Study on "Spurious Long Memory in Nonlinear Time Series Models"," Hannover Economic Papers (HEP) dp-410, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    3. Davidson, James & Hashimzade, Nigar, 2009. "Type I and type II fractional Brownian motions: A reconsideration," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2089-2106, April.
    4. J. Coulon & Y. Malevergne, 2011. "Heterogeneous expectations and long-range correlation of the volatility of asset returns," Quantitative Finance, Taylor & Francis Journals, vol. 11(9), pages 1329-1356, November.
    5. Ulrich K. Müller & Mark W. Watson, 2008. "Testing Models of Low-Frequency Variability," Econometrica, Econometric Society, vol. 76(5), pages 979-1016, September.
    6. Chevillon, Guillaume & Mavroeidis, Sophocles, 2011. "Learning generates Long Memory," ESSEC Working Papers WP1113, ESSEC Research Center, ESSEC Business School.
    7. Leipus, Remigijus & Paulauskas, Vygantas & Surgailis, Donatas, 2005. "Renewal regime switching and stable limit laws," Journal of Econometrics, Elsevier, vol. 129(1-2), pages 299-327.
    8. Arturo Leccadito & Omar Rachedi & Giovanni Urga, 2015. "True Versus Spurious Long Memory: Some Theoretical Results and a Monte Carlo Comparison," Econometric Reviews, Taylor & Francis Journals, vol. 34(4), pages 452-479, April.
    9. Matei Demetrescu & Mehdi Hosseinkouchack, 2022. "Autoregressive spectral estimates under ignored changes in the mean," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(2), pages 329-340, March.
    10. Laura Mayoral, 2005. "Is the observed persistence spurious? A test for fractional integration versus short memory and structural breaks," Economics Working Papers 956, Department of Economics and Business, Universitat Pompeu Fabra.
    11. Richard T. Baillie & Fabio Calonaci & Dooyeon Cho & Seunghwa Rho, 2019. "Long Memory, Realized Volatility and HAR Models," Working Papers 881, Queen Mary University of London, School of Economics and Finance.
    12. Juan J. Dolado & Jesús Gonzalo & Laura Mayoral, 2005. "What is What? A Simple Time-Domain Test of Long-memory vs. Structural Breaks," Working Papers 258, Barcelona School of Economics.
    13. Kuswanto, Heri & Sibbertsen, Philipp, 2009. "Testing for Long Memory Against ESTAR Nonlinearities," Hannover Economic Papers (HEP) dp-427, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    14. McAleer, Michael & Medeiros, Marcelo C., 2008. "A multiple regime smooth transition Heterogeneous Autoregressive model for long memory and asymmetries," Journal of Econometrics, Elsevier, vol. 147(1), pages 104-119, November.
    15. Davidson, James & Sibbertsen, Philipp, 2005. "Tests of Bias in Log-Periodogram Regression," Hannover Economic Papers (HEP) dp-317, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    16. Chevillon, G. & Hecq, A.W. & Laurent, S.F.J.A., 2015. "Long memory through marginalization of large systems and hidden cross-section dependence," Research Memorandum 014, Maastricht University, Graduate School of Business and Economics (GSBE).
    17. Javier Haulde & Morten Ørregaard Nielsen, 2022. "Fractional integration and cointegration," CREATES Research Papers 2022-02, Department of Economics and Business Economics, Aarhus University.
    18. Susanne M. Schennach, 2013. "Long memory via networking," CeMMAP working papers CWP13/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    19. Avishek Bhandari & Bandi Kamaiah, 2021. "Long Memory and Fractality Among Global Equity Markets: a Multivariate Wavelet Approach," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 23-37, March.
    20. Haldrup, Niels & Vera Valdés, J. Eduardo, 2017. "Long memory, fractional integration, and cross-sectional aggregation," Journal of Econometrics, Elsevier, vol. 199(1), pages 1-11.
    21. Tommaso Proietti & Federico Maddanu, 2021. "Modelling Cycles in Climate Series: the Fractional Sinusoidal Waveform Process," CEIS Research Paper 518, Tor Vergata University, CEIS, revised 19 Oct 2021.
    22. Richard T. Baillie & Dooyeon Cho & Seunghwa Rho, 2023. "Approximating long-memory processes with low-order autoregressions: Implications for modeling realized volatility," Empirical Economics, Springer, vol. 64(6), pages 2911-2937, June.
    23. Onsurang Norrbin & Aaron D. Smallwood, 2011. "Mean Reversion in the Real Interest Rate and the Effects of Calculating Expected Inflation," Southern Economic Journal, John Wiley & Sons, vol. 78(1), pages 107-130, July.
    24. Leschinski, Christian & Sibbertsen, Philipp, 2018. "The Periodogram of Spurious Long-Memory Processes," Hannover Economic Papers (HEP) dp-632, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    25. Kapetanios, George, 2006. "Nonlinear autoregressive models and long memory," Economics Letters, Elsevier, vol. 91(3), pages 360-368, June.
    26. Samet Günay, 2016. "Performance of the Multifractal Model of Asset Returns (MMAR): Evidence from Emerging Stock Markets," IJFS, MDPI, vol. 4(2), pages 1-17, May.
    27. Jan Beran & Haiyan Liu & Sucharita Ghosh, 2020. "On aggregation of strongly dependent time series," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 47(3), pages 690-710, September.
    28. Chevillon, Guillaume & Mavroeidis, Sophocles, 2017. "Learning can generate long memory," Journal of Econometrics, Elsevier, vol. 198(1), pages 1-9.
    29. Chatzikonstanti, Vasiliki & Venetis, Ioannis A., 2015. "Long memory in log-range series: Do structural breaks matter?," Journal of Empirical Finance, Elsevier, vol. 33(C), pages 104-113.
    30. Mihaela Craioveanu & Eric Hillebrand, 2012. "Level changes in volatility models," Annals of Finance, Springer, vol. 8(2), pages 277-308, May.
    31. Al-Shboul, Mohammad & Anwar, Sajid, 2016. "Fractional integration in daily stock market indices at Jordan's Amman stock exchange," The North American Journal of Economics and Finance, Elsevier, vol. 37(C), pages 16-37.
    32. Laura Mayoral, 2005. "Further evidence on the statistical properties of real GNP," Economics Working Papers 955, Department of Economics and Business, Universitat Pompeu Fabra, revised Feb 2006.
    33. Shikta Sing & Supun Chandrasena & Yue Shi & Abdullah Alhussain & Claude DIEBOLT & Martin Enilov & Tapas Mishra, 2024. "A Learning Model with Memory in the Financial Markets," Working Papers 06-24, Association Française de Cliométrie (AFC).
    34. Jan Beran & Britta Steffens & Sucharita Ghosh, 2022. "On nonparametric regression for bivariate circular long-memory time series," Statistical Papers, Springer, vol. 63(1), pages 29-52, February.
    35. Luis Alberiko & OlaOluwa S. Yaya & Olarenwaju I. Shittu, 2015. "Fractional integration and asymmetric volatility in european, asian and american bull and bear markets. Applications to high frequency stock data," NCID Working Papers 07/2015, Navarra Center for International Development, University of Navarra.
    36. Aaron D. Smallwood, 2016. "A Monte Carlo Investigation of Unit Root Tests and Long Memory in Detecting Mean Reversion in I(0) Regime Switching, Structural Break, and Nonlinear Data," Econometric Reviews, Taylor & Francis Journals, vol. 35(6), pages 986-1012, June.
    37. Eric Hillebrand & Marcelo Cunha Medeiros, 2010. "Asymmetries, breaks, and long-range dependence: An estimation framework for daily realized volatility," Textos para discussão 578, Department of Economics PUC-Rio (Brazil).
    38. Laura Mayoral, 2003. "Further Evidence on the Uncertain (Fractional) Unit Root in Real GNP," Working Papers 82, Barcelona School of Economics.
    39. Bhandari, Avishek, 2020. "Long memory and fractality among global equity markets: A multivariate wavelet approach," MPRA Paper 99653, University Library of Munich, Germany.
    40. Leschinski, Christian & Sibbertsen, Philipp, 2017. "Origins of Spurious Long Memory," Hannover Economic Papers (HEP) dp-595, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.

  35. Krämer, Walter & Sibbertsen, Philipp & Kleiber, Christian, 2001. "Long memory vs. structural change in financial time series," Technical Reports 2001,37, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.

    Cited by:

    1. Walter Kramer & Philipp Sibbertsen, 2002. "Testing for Structural Changes in the Presence of Long Memory," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 1(3), pages 235-242, December.
    2. Philip Bertram & Robinson Kruse & Philipp Sibbertsen, 2013. "Fractional integration versus level shifts: the case of realized asset correlations," Statistical Papers, Springer, vol. 54(4), pages 977-991, November.
    3. Matei Demetrescu, 2009. "Panel unit root testing and the martingale difference hypothesis for German stocks," Economics Bulletin, AccessEcon, vol. 29(3), pages 1749-1759.
    4. Philipp Sibbertsen, 2004. "Long memory in volatilities of German stock returns," Empirical Economics, Springer, vol. 29(3), pages 477-488, September.
    5. Sibbertsen, Philipp & Venetis, Ioannis, 2003. "Distinguishing between long-range dependence and deterministic trends," Technical Reports 2003,16, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.

  36. Sibbertsen, Philipp, 2001. "Log-periodogram estimation of the memory parameter of a long-memory process under trend," Technical Reports 2001,39, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.

    Cited by:

    1. Jussi Tolvi, 2003. "Long memory in a small stock market," Economics Bulletin, AccessEcon, vol. 7(3), pages 1-13.
    2. Surgailis, Donatas & Teyssière, Gilles & Vaiciulis, Marijus, 2008. "The increment ratio statistic," Journal of Multivariate Analysis, Elsevier, vol. 99(3), pages 510-541, March.
    3. Philipp Sibbertsen, 2004. "Long memory versus structural breaks: An overview," Statistical Papers, Springer, vol. 45(4), pages 465-515, October.
    4. Kang, Sang Hoon & Cheong, Chongcheul & Yoon, Seong-Min, 2010. "Long memory volatility in Chinese stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(7), pages 1425-1433.
    5. Philipp Sibbertsen, 2004. "Long memory in volatilities of German stock returns," Empirical Economics, Springer, vol. 29(3), pages 477-488, September.
    6. Sibbertsen, Philipp & Venetis, Ioannis, 2003. "Distinguishing between long-range dependence and deterministic trends," Technical Reports 2003,16, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    7. Canarella, Giorgio & Miller, Stephen M., 2017. "Inflation targeting and inflation persistence: New evidence from fractional integration and cointegration," Journal of Economics and Business, Elsevier, vol. 92(C), pages 45-62.

  37. Sibbertsen, Philipp, 2001. "Long-memory versus structural breaks: An overview," Technical Reports 2001,28, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.

    Cited by:

    1. Luisa Bisaglia & Matteo Grigoletto, 2018. "A new time-varying model for forecasting long-memory series," Papers 1812.07295, arXiv.org.
    2. Uwe Hassler & Jan Scheithauer, 2011. "Detecting changes from short to long memory," Statistical Papers, Springer, vol. 52(4), pages 847-870, November.
    3. Juan Carlos Cuestas & Luis A. Gil-Alana, 2022. "Unemployment hysteresis by sex and education attainment in the EU," Working Papers 2022/06, Economics Department, Universitat Jaume I, Castellón (Spain).
    4. Aikins Abakah, Emmanuel Joel & Gil-Alana, Luis A. & Tripathy, Trilochan, 2022. "Stochastic structure of metal prices: Evidence from fractional integration non-linearities and breaks," Resources Policy, Elsevier, vol. 78(C).
    5. Caporale, Guglielmo Maria & Gil-Alana, Luis A. & Poza, Carlos, 2020. "Persistence, non-linearities and structural breaks in European stock market indices," The Quarterly Review of Economics and Finance, Elsevier, vol. 77(C), pages 50-61.
    6. Sibbertsen, Philipp, 2001. "Log-periodogram estimation of the memory parameter of a long-memory process under trend," Technical Reports 2001,39, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    7. Choi, Kyongwook & Zivot, Eric, 2007. "Long memory and structural changes in the forward discount: An empirical investigation," Journal of International Money and Finance, Elsevier, vol. 26(3), pages 342-363, April.
    8. Kunal Saha & Vinodh Madhavan & Chandrashekhar G. R. & David McMillan, 2020. "Pitfalls in long memory research," Cogent Economics & Finance, Taylor & Francis Journals, vol. 8(1), pages 1733280-173, January.
    9. Beran, Jan, 2007. "On parameter estimation for locally stationary long-memory processes," CoFE Discussion Papers 07/13, University of Konstanz, Center of Finance and Econometrics (CoFE).
    10. Luisa Bisaglia & Matteo Grigoletto, 2021. "A new time-varying model for forecasting long-memory series," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(1), pages 139-155, March.
    11. Rea, William & Reale, Marco & Brown, Jennifer & Oxley, Les, 2011. "Long memory or shifting means in geophysical time series?," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 81(7), pages 1441-1453.
    12. Luis A. Gil-Alana & Zeynel Abidin Ozdemir & Aysit Tansel, 2017. "Long Memory in Turkish Unemployment Rates," ERC Working Papers 1709, ERC - Economic Research Center, Middle East Technical University, revised Sep 2017.
    13. Beran, Jan & Shumeyko, Yevgen, 2012. "Bootstrap testing for discontinuities under long-range dependence," Journal of Multivariate Analysis, Elsevier, vol. 105(1), pages 322-347.
    14. Richard T. Baillie & Fabio Calonaci & Dooyeon Cho & Seunghwa Rho, 2019. "Long Memory, Realized Volatility and HAR Models," Working Papers 881, Queen Mary University of London, School of Economics and Finance.
    15. William Rea & Marco Reale & Jennifer Brown, 2011. "Long memory in temperature reconstructions," Climatic Change, Springer, vol. 107(3), pages 247-265, August.
    16. Les Oxley & Chris Price & William Rea & Marco Reale, 2008. "A New Procedure to Test for H Self-Similarity," Working Papers in Economics 08/16, University of Canterbury, Department of Economics and Finance.
    17. Uwe Hassler & Barbara Meller, 2014. "Detecting multiple breaks in long memory the case of U.S. inflation," Empirical Economics, Springer, vol. 46(2), pages 653-680, March.
    18. Harry Haupt & Markus Fritsch, 2022. "Quantile Trend Regression and Its Application to Central England Temperature," Mathematics, MDPI, vol. 10(3), pages 1-20, January.
    19. Giorgio Canarella & Luis A. Gil-Alana & Rangan Gupta & Stephen M. Miller, 2018. "Persistence and Cyclical Dynamics of US and UK House Prices: Evidence from Over 150 Years of Data," Working Papers 201838, University of Pretoria, Department of Economics.
    20. Willert, Juliane, 2010. "Mean Shift detection under long-range dependencies with ART," Hannover Economic Papers (HEP) dp-437, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    21. Raquel Ayestarán & Juan Infante & Juan José Tenorio & Luis Alberiko Gil-Alana, 2023. "Evidence of Inflation Using Harmonized Consumer Price Indices in Some Euro Countries: France, Germany, Italy, and Spain, along with the Euro Zone," Mathematics, MDPI, vol. 11(10), pages 1-12, May.
    22. Kuswanto, Heri, 2009. "A New Simple Test Against Spurious Long Memory Using Temporal Aggregation," Hannover Economic Papers (HEP) dp-425, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    23. Richard T. Baillie & Dooyeon Cho & Seunghwa Rho, 2023. "Approximating long-memory processes with low-order autoregressions: Implications for modeling realized volatility," Empirical Economics, Springer, vol. 64(6), pages 2911-2937, June.
    24. Baillie, Richard T. & Cho, Dooyeon & Rho, Seunghwa, 2024. "Combining Long and Short Memory in Time Series Models: the Role of Asymptotic Correlations of the MLEs," Econometrics and Statistics, Elsevier, vol. 29(C), pages 88-112.
    25. Lihong Wang, 2020. "Lack of fit test for long memory regression models," Statistical Papers, Springer, vol. 61(3), pages 1043-1067, June.
    26. Taro Ikeda, 2017. "Fractal analysis revisited: The case of the US industrial sector stocks," Economics Bulletin, AccessEcon, vol. 37(2), pages 666-674.
    27. Kyongwook Choi & Eric Zivot, 2003. "Long Memory and Structural Changes in the Forward Discount: An Empirical Investigation," EERI Research Paper Series EERI_RP_2003_02, Economics and Econometrics Research Institute (EERI), Brussels.
    28. Sibbertsen, Philipp & Willert, Juliane, 2009. "Testing for a break in persistence under long-range dependencies and mean shifts," Hannover Economic Papers (HEP) dp-422, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    29. Long Hai Vo & Duc Hong Vo, 2020. "Modelling Australian Dollar Volatility at Multiple Horizons with High-Frequency Data," Risks, MDPI, vol. 8(3), pages 1-16, August.
    30. Mawuli Segnon & Manuel Stapper, 2019. "Long Memory Conditional Heteroscedasticity in Count Data," CQE Working Papers 8219, Center for Quantitative Economics (CQE), University of Muenster.
    31. Hassler, Uwe & Nautz, Dieter, 2008. "On the persistence of the Eonia spread," Economics Letters, Elsevier, vol. 101(3), pages 184-187, December.
    32. Karanasos, Menelaos & Paraskevopoulos, Alexandros & Magdalinos, Anastasios & Canepa, Alessandra, 2024. "A Unified Theory for Arma Models with Varying Coefficients: One Solution Fits All," Department of Economics and Statistics Cognetti de Martiis. Working Papers 202413, University of Turin.
    33. Hwang, Eunju & Shin, Dong Wan, 2013. "A CUSUM test for a long memory heterogeneous autoregressive model," Economics Letters, Elsevier, vol. 121(3), pages 379-383.
    34. Caporale, Guglielmo Maria & Gil-Alana, Luis A. & Poza, Carlos, 2020. "High and low prices and the range in the European stock markets: A long-memory approach," Research in International Business and Finance, Elsevier, vol. 52(C).
    35. Aeneas Rooch & Ieva Zelo & Roland Fried, 2019. "Estimation methods for the LRD parameter under a change in the mean," Statistical Papers, Springer, vol. 60(1), pages 313-347, February.
    36. Giorgio Canarella & Stephen M. Miller, 2016. "Inflation Targeting: New Evidence from Fractional Integration and Cointegration," Working papers 2016-08, University of Connecticut, Department of Economics.
    37. Apergis, Nicholas & Carmona-González, Nieves & Gil-Alana, Luis Alberiko, 2020. "Persistence in silver prices and the influence of solar energy," Resources Policy, Elsevier, vol. 69(C).
    38. Philipp Sibbertsen, 2004. "Long memory in volatilities of German stock returns," Empirical Economics, Springer, vol. 29(3), pages 477-488, September.
    39. Wali, Muammer & Chan, Felix & Manzur, Meher, 2017. "Nonlinear dependence in exchange rate returns: How do emerging Asian currencies compare with major currencies?," Journal of Asian Economics, Elsevier, vol. 50(C), pages 62-72.
    40. Sibbertsen, Philipp & Venetis, Ioannis, 2003. "Distinguishing between long-range dependence and deterministic trends," Technical Reports 2003,16, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    41. Canarella, Giorgio & Miller, Stephen M., 2017. "Inflation targeting and inflation persistence: New evidence from fractional integration and cointegration," Journal of Economics and Business, Elsevier, vol. 92(C), pages 45-62.

  38. Sibbertsen, Philipp, 2001. "Long-memory in volatilities of German stock returns," Technical Reports 2001,42, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.

    Cited by:

    1. J. Cuñado & L. Gil-Alana & F. Gracia, 2009. "US stock market volatility persistence: evidence before and after the burst of the IT bubble," Review of Quantitative Finance and Accounting, Springer, vol. 33(3), pages 233-252, October.
    2. Ngene, Geoffrey & Tah, Kenneth A. & Darrat, Ali F., 2017. "Long memory or structural breaks: Some evidence for African stock markets," Review of Financial Economics, Elsevier, vol. 34(C), pages 61-73.
    3. Ranjit Kumar Paul & Bishal Gurung & Sandipan Samanta, 2015. "Analyzing the Effect of Dual Long Memory Process in Forecasting Agricultural Prices in Different Markets of India," International Journal of Empirical Finance, Research Academy of Social Sciences, vol. 4(4), pages 235-249.
    4. Guglielmo Maria Caporale & Luis A. Gil-Alana, 2011. "Long Memory and Fractional Integration in High-Frequency British Pound / Dollar Spot Exchange Rates," Faculty Working Papers 02/11, School of Economics and Business Administration, University of Navarra.
    5. Herzberg, Markus & Sibbertsen, Philipp, 2004. "Pricing of options under different volatility models," Technical Reports 2004,62, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    6. Gil-Alana, Luis A. & Mudida, Robert & Yaya, OlaOluwa S & Osuolale, Kazeem & Ogbonna, Ephraim A, 2019. "Influence of US Presidential Terms on S&P500 Index Using a Time Series Analysis Approach," MPRA Paper 93941, University Library of Munich, Germany.
    7. Elie Bouri & Luis A. Gil-Alana & Rangan Gupta & David Roubaud, 2016. "Modelling Long Memory Volatility in the Bitcoin Market: Evidence of Persistence and Structural Breaks," Working Papers 201654, University of Pretoria, Department of Economics.
    8. Guglielmo Maria Caporale & Luis A. Gil-Alana, 2013. "Long Memory and Fractional Integration in High Frequency Data on the US Dollar / British Pound Spot Exchange Rate," Discussion Papers of DIW Berlin 1294, DIW Berlin, German Institute for Economic Research.
    9. Luis Alberiko Gil-Alaña & Olanrewaju L. Shittu & OlaOluwa S. Yaya, 2013. "On the persistence and volatility in European, American and Asian stocks bull and bear markets," NCID Working Papers 12/2013, Navarra Center for International Development, University of Navarra.
    10. Leïla Nouira & Mohamed Boutahar & Vêlayoudom Marimoutou, 2009. "The effect of tapering on the semiparametric estimators for nonstationary long memory processes," Statistical Papers, Springer, vol. 50(2), pages 225-248, March.
    11. Robinson Kruse & Christoph Wegener, 2019. "Explosive behaviour and long memory with an application to European bond yield spreads," Scottish Journal of Political Economy, Scottish Economic Society, vol. 66(1), pages 139-153, February.
    12. Kuswanto, Heri, 2009. "A New Simple Test Against Spurious Long Memory Using Temporal Aggregation," Hannover Economic Papers (HEP) dp-425, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    13. Kang, Sang Hoon & Cheong, Chongcheul & Yoon, Seong-Min, 2010. "Long memory volatility in Chinese stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(7), pages 1425-1433.
    14. Yalama, Abdullah & Celik, Sibel, 2013. "Real or spurious long memory characteristics of volatility: Empirical evidence from an emerging market," Economic Modelling, Elsevier, vol. 30(C), pages 67-72.
    15. Monge, Manuel & Gil-Alana, Luis A. & Pérez de Gracia, Fernando, 2017. "Crude oil price behaviour before and after military conflicts and geopolitical events," Energy, Elsevier, vol. 120(C), pages 79-91.
    16. Guglielmo Maria Caporale & Luis A. Gil-Alana, 2011. "Long Memory and Volatility Dynamics in the US Dollar Exchange Rate," Faculty Working Papers 04/11, School of Economics and Business Administration, University of Navarra.
    17. Härdle, Wolfgang Karl & Mungo, Julius, 2007. "Long memory persistence in the factor of Implied volatility dynamics," SFB 649 Discussion Papers 2007-027, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    18. Yuanhua Feng & Thomas Gries & Sebastian Letmathe, 2023. "FIEGARCH, modulus asymmetric FILog-GARCH and trend-stationary dual long memory time series," Working Papers CIE 156, Paderborn University, CIE Center for International Economics.
    19. Leandro Maciel, 2020. "Technical analysis based on high and low stock prices forecasts: evidence for Brazil using a fractionally cointegrated VAR model," Empirical Economics, Springer, vol. 58(4), pages 1513-1540, April.
    20. Geoffrey Ngene & Kenneth A. Tah & Ali F. Darrat, 2017. "Long memory or structural breaks: Some evidence for African stock markets," Review of Financial Economics, John Wiley & Sons, vol. 34(1), pages 61-73, September.
    21. Luis A. Gil‐Alana & Robert Mudida & OlaOluwa S. Yaya & Kazeem A. Osuolale & Ahamuefula E. Ogbonna, 2021. "Mapping US presidential terms with S&P500 index: Time series analysis approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 1938-1954, April.
    22. Alia Afzal & Philipp Sibbertsen, 2021. "Modeling fractional cointegration between high and low stock prices in Asian countries," Empirical Economics, Springer, vol. 60(2), pages 661-682, February.
    23. Luis A. Gil-Alana & Yun Cao, 2011. "Stock market prices in China. Efficiency, mean reversion, long memory volatility and other implicit dynamics," Faculty Working Papers 12/11, School of Economics and Business Administration, University of Navarra.
    24. Ibrahim M. Awad & Abdel-Rahman Al-Ewesat, 2017. "Volatility Persistence in Palestine Exchange Bulls and Bears: An Econometric Analysis of Time Series Data," Review of Economics & Finance, Better Advances Press, Canada, vol. 9, pages 83-97, August.
    25. Luis Alberiko & OlaOluwa S. Yaya & Olarenwaju I. Shittu, 2015. "Fractional integration and asymmetric volatility in european, asian and american bull and bear markets. Applications to high frequency stock data," NCID Working Papers 07/2015, Navarra Center for International Development, University of Navarra.
    26. Sibbertsen, Philipp & Venetis, Ioannis, 2003. "Distinguishing between long-range dependence and deterministic trends," Technical Reports 2003,16, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.

  39. Peters, Andrea & Sibbertsen, Philipp, 2001. "Robust tests on fractional cointegration," Technical Reports 2001,29, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.

    Cited by:

    1. Banerjee, Anindya & Urga, Giovanni, 2005. "Modelling structural breaks, long memory and stock market volatility: an overview," Journal of Econometrics, Elsevier, vol. 129(1-2), pages 1-34.

  40. Beran, Jan & Gosh, Sucharita & Sibbertsen, Philipp, 2000. "Nonparametric M-Estimation with Long-Memory Errors," CoFE Discussion Papers 00/19, University of Konstanz, Center of Finance and Econometrics (CoFE).

    Cited by:

    1. Beran, Jan & Feng, Yuanhua & Ghosh, Sucharita & Sibbertsen, Philipp, 2002. "On robust local polynomial estimation with long-memory errors," International Journal of Forecasting, Elsevier, vol. 18(2), pages 227-241.
    2. Philipp Sibbertsen, 2004. "Long memory versus structural breaks: An overview," Statistical Papers, Springer, vol. 45(4), pages 465-515, October.

  41. Beran, Jan & Feng, Yuanhua & Gosh, Sucharita & Sibbertsen, Philipp, 2000. "On robust local polynomial estimation with long-memory errors," CoFE Discussion Papers 00/18, University of Konstanz, Center of Finance and Econometrics (CoFE).

    Cited by:

    1. Heni Boubaker & Nadia Sghaier, 2014. "Semiparametric Generalized Long Memory Modelling of GCC Stock Market Returns: A Wavelet Approach," Working Papers 2014-66, Department of Research, Ipag Business School.
    2. Beran, Jan & Shumeyko, Yevgen, 2012. "Bootstrap testing for discontinuities under long-range dependence," Journal of Multivariate Analysis, Elsevier, vol. 105(1), pages 322-347.
    3. Beran, Jan & Feng, Yuanhua, 2002. "Recent Developments in Non- and Semiparametric Regression with Fractional Time Series Errors," CoFE Discussion Papers 02/13, University of Konstanz, Center of Finance and Econometrics (CoFE).
    4. De Gooijer, Jan G. & Hyndman, Rob J., 2006. "25 years of time series forecasting," International Journal of Forecasting, Elsevier, vol. 22(3), pages 443-473.
    5. Philipp Sibbertsen, 2004. "Long memory versus structural breaks: An overview," Statistical Papers, Springer, vol. 45(4), pages 465-515, October.
    6. Jan G. De Gooijer & Rob J. Hyndman, 2005. "25 Years of IIF Time Series Forecasting: A Selective Review," Monash Econometrics and Business Statistics Working Papers 12/05, Monash University, Department of Econometrics and Business Statistics.
    7. Quande Qin & Huangda He & Li Li & Ling-Yun He, 2020. "A Novel Decomposition-Ensemble Based Carbon Price Forecasting Model Integrated with Local Polynomial Prediction," Computational Economics, Springer;Society for Computational Economics, vol. 55(4), pages 1249-1273, April.
    8. Boubaker, Heni & Sghaier, Nadia, 2015. "Semiparametric generalized long-memory modeling of some mena stock market returns: A wavelet approach," Economic Modelling, Elsevier, vol. 50(C), pages 254-265.

  42. Krämer, Walter & Sibbertsen, Philipp, 2000. "Testing for structural change in the presence of long memory," Technical Reports 2000,31, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.

    Cited by:

    1. Luis Alberiko Gil-Alaña & Olanrewaju L. Shittu & OlaOluwa S. Yaya, 2011. "Long memory, strcutural breaks and mean shifts in the inflation rates in Nigeria," NCID Working Papers 04/2011, Navarra Center for International Development, University of Navarra.
    2. Theologos Dergiades & Lefteris Tsoulfidis, 2011. "Revisiting residential demand for electricity in Greece: new evidence from the ARDL approach to cointegration analysis," Empirical Economics, Springer, vol. 41(2), pages 511-531, October.
    3. Krämer, Walter & Sibbertsen, Philipp & Kleiber, Christian, 2001. "Long memory vs. structural change in financial time series," Technical Reports 2001,37, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    4. Laura Mayoral, 2005. "The persistence of inflation in OECD countries: A fractionally integrated approach," Economics Working Papers 958, Department of Economics and Business, Universitat Pompeu Fabra, revised Oct 2005.
    5. Bond, Derek & Harrison, Michael J & O’Brien, Edward J., 2006. "Testing for Long Memory and Nonlinear Time Series: A Demand for Money Study," Research Technical Papers 2/RT/06, Central Bank of Ireland.
    6. Rinke, Saskia & Busch, Marie & Leschinski, Christian, 2017. "Long Memory, Breaks, and Trends: On the Sources of Persistence in Inflation Rates," Hannover Economic Papers (HEP) dp-584, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    7. Zeynel Abidin Ozdemir & Mehmet Balcilar & Aysit Tansel, 2011. "International Labour Force Participation Rates by Gender: Unit Root or Structural Breaks?," ERC Working Papers 1105, ERC - Economic Research Center, Middle East Technical University, revised Oct 2011.
    8. Luis A. Gil-Alana & Antonio Moreno & Seonghoon Cho, 2009. "The Deaton paradox in a long memory context with structural breaks," Faculty Working Papers 03/09, School of Economics and Business Administration, University of Navarra.
    9. Smallwood, Aaron D., 2008. "Measuring the persistence of deviations from purchasing power parity with a fractionally integrated STAR model," Journal of International Money and Finance, Elsevier, vol. 27(7), pages 1161-1176, November.
    10. Beran, Jan & Shumeyko, Yevgen, 2012. "Bootstrap testing for discontinuities under long-range dependence," Journal of Multivariate Analysis, Elsevier, vol. 105(1), pages 322-347.
    11. Laura Mayoral, 2005. "Is the observed persistence spurious? A test for fractional integration versus short memory and structural breaks," Economics Working Papers 956, Department of Economics and Business, Universitat Pompeu Fabra.
    12. Derek Bond & Michael J. Harrison & Edward J. O'Brien, 2006. "Purchasing Power Parity: The Irish Experience Re-visited," Trinity Economics Papers tep200615, Trinity College Dublin, Department of Economics.
    13. Johnson, Paul & Papageorgiou, Chris, 2018. "What Remains of Cross-Country Convergence?," MPRA Paper 89355, University Library of Munich, Germany.
    14. Philip Bertram & Robinson Kruse & Philipp Sibbertsen, 2013. "Fractional integration versus level shifts: the case of realized asset correlations," Statistical Papers, Springer, vol. 54(4), pages 977-991, November.
    15. Gilles Dufrénot & Valérie Mignon & Théo Naccache, 2009. "The slow convergence of per capita income between the developing countries: “growth resistance” and sometimes “growth tragedy”," Discussion Papers 09/03, University of Nottingham, CREDIT.
    16. Bond, Derek & Harrison, Michael J & Hession, Niall & O’Brien, Edward J., 2006. "Some Empirical Observations on the Forward Exchange Rate Anomaly," Research Technical Papers 3/RT/06, Central Bank of Ireland.
    17. Zhichao Guo & Yuanhua Feng & Xiangyong Tan, 2010. "Short- and long-term impact of remarkable economic events on the growth causes of China-Germany trade in agri-food products," Working Papers CIE 32, Paderborn University, CIE Center for International Economics.
    18. Philipp Sibbertsen, 2004. "Long memory versus structural breaks: An overview," Statistical Papers, Springer, vol. 45(4), pages 465-515, October.
    19. Zhichao Guo & Yuanhua Feng & Thomas Gries, 2015. "Changes of China’s agri-food exports to Germany caused by its accession to WTO and the 2008 financial crisis," China Agricultural Economic Review, Emerald Group Publishing Limited, vol. 7(2), pages 262-279, May.
    20. Kai Wenger & Christian Leschinski & Philipp Sibbertsen, 2019. "Change-in-mean tests in long-memory time series: a review of recent developments," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 103(2), pages 237-256, June.
    21. Wenger, Kai & Leschinski, Christian & Sibbertsen, Philipp, 2018. "A simple test on structural change in long-memory time series," Economics Letters, Elsevier, vol. 163(C), pages 90-94.
    22. Kyongwook Choi & Eric Zivot, 2003. "Long Memory and Structural Changes in the Forward Discount: An Empirical Investigation," EERI Research Paper Series EERI_RP_2003_02, Economics and Econometrics Research Institute (EERI), Brussels.
    23. Pestana Barros, Carlos & Gil-Alana, Luis A. & Payne, James E., 2012. "Evidence of long memory behavior in U.S. renewable energy consumption," Energy Policy, Elsevier, vol. 41(C), pages 822-826.
    24. Krämer Walter, 2002. "Statistische Besonderheiten von Finanzzeitreihen / Statistical Properties of Financial Time Series," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 222(2), pages 210-229, April.
    25. Seong Yeon Chang & Pierre Perron, 2017. "Fractional Unit Root Tests Allowing for a Structural Change in Trend under Both the Null and Alternative Hypotheses," Econometrics, MDPI, vol. 5(1), pages 1-26, January.
    26. Sanghamitra Bandyopadhyay, 2016. "The persistence of inequality across Indian states," CSAE Working Paper Series 2016-26, Centre for the Study of African Economies, University of Oxford.
    27. Lee, Oesook, 2014. "The functional central limit theorem and structural change test for the HAR(∞) model," Economics Letters, Elsevier, vol. 124(3), pages 370-373.
    28. Laura Mayoral, 2005. "Further evidence on the statistical properties of real GNP," Economics Working Papers 955, Department of Economics and Business, Universitat Pompeu Fabra, revised Feb 2006.
    29. Hwang, Eunju & Shin, Dong Wan, 2013. "A CUSUM test for a long memory heterogeneous autoregressive model," Economics Letters, Elsevier, vol. 121(3), pages 379-383.
    30. Philipp Sibbertsen, 2004. "Long memory in volatilities of German stock returns," Empirical Economics, Springer, vol. 29(3), pages 477-488, September.
    31. Derek Bond & Michael J. Harrison & Edward J. O'Brien, 2007. "Demand for Money: A Study in Testing Time Series for Long Memory and Nonlinearity," The Economic and Social Review, Economic and Social Studies, vol. 38(1), pages 1-24.
    32. Banerjee, Anindya & Urga, Giovanni, 2005. "Modelling structural breaks, long memory and stock market volatility: an overview," Journal of Econometrics, Elsevier, vol. 129(1-2), pages 1-34.
    33. Sibbertsen, Philipp & Venetis, Ioannis, 2003. "Distinguishing between long-range dependence and deterministic trends," Technical Reports 2003,16, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.

  43. Sibbertsen, Philipp, 2000. "Robust CUSUM-M test in the presence of long-memory disturbances," Technical Reports 2000,19, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.

    Cited by:

    1. Walter Kramer & Philipp Sibbertsen, 2002. "Testing for Structural Changes in the Presence of Long Memory," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 1(3), pages 235-242, December.
    2. Philipp Sibbertsen, 2004. "Long memory versus structural breaks: An overview," Statistical Papers, Springer, vol. 45(4), pages 465-515, October.
    3. Krämer Walter, 2002. "Statistische Besonderheiten von Finanzzeitreihen / Statistical Properties of Financial Time Series," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 222(2), pages 210-229, April.

  44. Philipp Sibbertsen, 1999. "S-Estimation in the Linear Regression Model with Long-Memory Error Terms," Computing in Economics and Finance 1999 512, Society for Computational Economics.

    Cited by:

    1. Sibbertsen, Philipp & Stahl, Gerhard & Luedtke, Corinna, 2008. "Measuring Model Risk," Hannover Economic Papers (HEP) dp-409, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    2. Sibbertsen, Philipp, 2000. "Robust CUSUM-M test in the presence of long-memory disturbances," Technical Reports 2000,19, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    3. PREMINGER, Arie & SAKATA, Shinichi, 2005. "A model selection method for S-estimation," LIDAM Discussion Papers CORE 2005073, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

  45. Sibbertsen, Philipp, 1999. "S-estimation in the nonlinear regression model with long-memory error terms," Technical Reports 1999,36, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.

    Cited by:

    1. Krämer Walter, 2002. "Statistische Besonderheiten von Finanzzeitreihen / Statistical Properties of Financial Time Series," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 222(2), pages 210-229, April.
    2. PREMINGER, Arie & SAKATA, Shinichi, 2005. "A model selection method for S-estimation," LIDAM Discussion Papers CORE 2005073, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

Articles

  1. Mwasi Paza Mboya & Philipp Sibbertsen, 2023. "Optimal forecasts in the presence of discrete structural breaks under long memory," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(7), pages 1889-1908, November.
    See citations under working paper version above.
  2. Becker, Janis & Hollstein, Fabian & Prokopczuk, Marcel & Sibbertsen, Philipp, 2021. "The memory of beta," Journal of Banking & Finance, Elsevier, vol. 124(C).

    Cited by:

    1. Mehmet Balcilar & Riza Demirer & Festus V. Bekun, 2021. "Flexible Time-Varying Betas in a Novel Mixture Innovation Factor Model with Latent Threshold," Mathematics, MDPI, vol. 9(8), pages 1-20, April.

  3. Voges, Michelle & Sibbertsen, Philipp, 2021. "Cyclical fractional cointegration," Econometrics and Statistics, Elsevier, vol. 19(C), pages 114-129.

    Cited by:

    1. Tommaso Proietti & Diego J. Pedregal, 2021. "Seasonality in High Frequency Time Series," CEIS Research Paper 508, Tor Vergata University, CEIS, revised 11 Mar 2021.
    2. Webel, Karsten, 2022. "A review of some recent developments in the modelling and seasonal adjustment of infra-monthly time series," Discussion Papers 31/2022, Deutsche Bundesbank.

  4. Christian Leschinski & Michelle Voges & Philipp Sibbertsen, 2021. "A comparison of semiparametric tests for fractional cointegration," Statistical Papers, Springer, vol. 62(4), pages 1997-2030, August.
    See citations under working paper version above.
  5. Christian Leschinski & Michelle Voges & Philipp Sibbertsen, 2021. "Integration and Disintegration of EMU Government Bond Markets," Econometrics, MDPI, vol. 9(1), pages 1-17, March.
    See citations under working paper version above.
  6. Benjamin Fritzsch & Kai Wenger & Philipp Sibbertsen & Georg Ullmann, 2020. "Can google trends improve sales forecasts on a product level?," Applied Economics Letters, Taylor & Francis Journals, vol. 27(17), pages 1409-1414, October.

    Cited by:

    1. Lash, Michael T. & Sajeesh, S. & Araz, Ozgur M., 2023. "Predicting mobility using limited data during early stages of a pandemic," Journal of Business Research, Elsevier, vol. 157(C).

  7. Nguyen, Duc Binh Benno & Prokopczuk, Marcel & Sibbertsen, Philipp, 2020. "The memory of stock return volatility: Asset pricing implications," Journal of Financial Markets, Elsevier, vol. 47(C).
    See citations under working paper version above.
  8. Wingert, Simon & Mboya, Mwasi Paza & Sibbertsen, Philipp, 2020. "Distinguishing between breaks in the mean and breaks in persistence under long memory," Economics Letters, Elsevier, vol. 193(C).

    Cited by:

    1. Assaf, Ata & Bhandari, Avishek & Charif, Husni & Demir, Ender, 2022. "Multivariate long memory structure in the cryptocurrency market: The impact of COVID-19," International Review of Financial Analysis, Elsevier, vol. 82(C).
    2. Assaf, Ata & Mokni, Khaled & Yousaf, Imran & Bhandari, Avishek, 2023. "Long memory in the high frequency cryptocurrency markets using fractal connectivity analysis: The impact of COVID-19," Research in International Business and Finance, Elsevier, vol. 64(C).

  9. Christoph Wegener & Tobias Basse & Philipp Sibbertsen & Duc Khuong Nguyen, 2019. "Liquidity risk and the covered bond market in times of crisis: empirical evidence from Germany," Annals of Operations Research, Springer, vol. 282(1), pages 407-426, November.

    Cited by:

    1. Afonso, António & Jalles, João Tovar & Kazemi, Mina, 2020. "The effects of macroeconomic, fiscal and monetary policy announcements on sovereign bond spreads," International Review of Law and Economics, Elsevier, vol. 63(C).
    2. Fauß, Tobias Friedrich, 2022. "Analysis of Green Bonds," Junior Management Science (JUMS), Junior Management Science e. V., vol. 7(3), pages 668-689.
    3. Guohua He & Zirun Hu, 2023. "Precautionary Saving and Liquidity Shortage," Sustainability, MDPI, vol. 15(3), pages 1-15, January.
    4. Xu, Guoquan & Lu, Nuotian & Tong, Yan, 2022. "Greenwashing and credit spread: Evidence from the Chinese green bond market," Finance Research Letters, Elsevier, vol. 48(C).
    5. Nikolas Stege & Christoph Wegener & Tobias Basse & Frederik Kunze, 2021. "Mapping swap rate projections on bond yields considering cointegration: an example for the use of neural networks in stress testing exercises," Annals of Operations Research, Springer, vol. 297(1), pages 309-321, February.

  10. Kai Wenger & Christian Leschinski & Philipp Sibbertsen, 2019. "Change-in-mean tests in long-memory time series: a review of recent developments," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 103(2), pages 237-256, June.
    See citations under working paper version above.
  11. Leschinski, Christian & Sibbertsen, Philipp, 2019. "Model order selection in periodic long memory models," Econometrics and Statistics, Elsevier, vol. 9(C), pages 78-94.

    Cited by:

    1. Paul M. Beaumont & Aaron D. Smallwood, 2024. "Conditional sum of squares estimation of k-factor GARMA models," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 108(3), pages 501-543, September.
    2. Tommaso Proietti & Diego J. Pedregal, 2021. "Seasonality in High Frequency Time Series," CEIS Research Paper 508, Tor Vergata University, CEIS, revised 11 Mar 2021.
    3. Federico Maddanu, 2022. "A harmonically weighted filter for cyclical long memory processes," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 106(1), pages 49-78, March.
    4. del Barrio Castro, Tomas & Escribano, Alvaro & Sibbertsen, Philipp, 2024. "Modeling and Forecasting the Long Memory of Cyclical Trends in Paleoclimate Data," Hannover Economic Papers (HEP) dp-722, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    5. Beaumont, Paul & Smallwood, Aaron, 2019. "Inference for likelihood-based estimators of generalized long-memory processes," MPRA Paper 96313, University Library of Munich, Germany.
    6. Webel, Karsten, 2022. "A review of some recent developments in the modelling and seasonal adjustment of infra-monthly time series," Discussion Papers 31/2022, Deutsche Bundesbank.
    7. Tommaso Proietti & Federico Maddanu, 2021. "Modelling Cycles in Climate Series: the Fractional Sinusoidal Waveform Process," CEIS Research Paper 518, Tor Vergata University, CEIS, revised 19 Oct 2021.
    8. Baillie, Richard T. & Cho, Dooyeon & Rho, Seunghwa, 2024. "Combining Long and Short Memory in Time Series Models: the Role of Asymptotic Correlations of the MLEs," Econometrics and Statistics, Elsevier, vol. 29(C), pages 88-112.
    9. Voges, Michelle & Sibbertsen, Philipp, 2021. "Cyclical fractional cointegration," Econometrics and Statistics, Elsevier, vol. 19(C), pages 114-129.
    10. Cantoni, Eva & Jacot, Nadège & Ghisletta, Paolo, 2024. "Review and comparison of measures of explained variation and model selection in linear mixed-effects models," Econometrics and Statistics, Elsevier, vol. 29(C), pages 150-168.
    11. Beaumont, Paul & Smallwood, Aaron, 2019. "Conditional Sum of Squares Estimation of Multiple Frequency Long Memory Models," MPRA Paper 96314, University Library of Munich, Germany.
    12. Stéphane Goutte & David Guerreiro & Bilel Sanhaji & Sophie Saglio & Julien Chevallier, 2019. "International Financial Markets," Post-Print halshs-02183053, HAL.
    13. Jan Beran & Jeremy Näscher & Fabian Pietsch & Stephan Walterspacher, 2024. "Testing for periodicity at an unknown frequency under cyclic long memory, with applications to respiratory muscle training," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 108(4), pages 705-731, December.

  12. Wenger, Kai & Leschinski, Christian & Sibbertsen, Philipp, 2018. "A simple test on structural change in long-memory time series," Economics Letters, Elsevier, vol. 163(C), pages 90-94.
    See citations under working paper version above.
  13. Sibbertsen, Philipp & Leschinski, Christian & Busch, Marie, 2018. "A multivariate test against spurious long memory," Journal of Econometrics, Elsevier, vol. 203(1), pages 33-49.
    See citations under working paper version above.
  14. Marie Busch & Philipp Sibbertsen, 2018. "An Overview of Modified Semiparametric Memory Estimation Methods," Econometrics, MDPI, vol. 6(1), pages 1-21, March.
    See citations under working paper version above.
  15. Demetrescu, Matei & Sibbertsen, Philipp, 2016. "Inference on the long-memory properties of time series with non-stationary volatility," Economics Letters, Elsevier, vol. 144(C), pages 80-84.
    See citations under working paper version above.
  16. Rinke Saskia & Sibbertsen Philipp, 2016. "Information criteria for nonlinear time series models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(3), pages 325-341, June.
    See citations under working paper version above.
  17. Hendrik Kaufmann & Florian Heinen & Philipp Sibbertsen, 2014. "The Dynamics Of Real Exchange Rates: A Reconsideration," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(5), pages 758-773, August.
    See citations under working paper version above.
  18. Sibbertsen, Philipp & Wegener, Christoph & Basse, Tobias, 2014. "Testing for a break in the persistence in yield spreads of EMU government bonds," Journal of Banking & Finance, Elsevier, vol. 41(C), pages 109-118.
    See citations under working paper version above.
  19. Philip Bertram & Robinson Kruse & Philipp Sibbertsen, 2013. "Fractional integration versus level shifts: the case of realized asset correlations," Statistical Papers, Springer, vol. 54(4), pages 977-991, November.

    Cited by:

    1. Dennis Alvaro & Ángel Guillén & Gabriel Rodríguez, 2017. "Modelling the volatility of commodities prices using a stochastic volatility model with random level shifts," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 153(1), pages 71-103, February.
    2. Lihong Wang, 2020. "Lack of fit test for long memory regression models," Statistical Papers, Springer, vol. 61(3), pages 1043-1067, June.
    3. Becker, Janis & Leschinski, Christian & Sibbertsen, Philipp, 2019. "Robust Multivariate Local Whittle Estimation and Spurious Fractional Cointegration," Hannover Economic Papers (HEP) dp-660, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    4. Audrino, Francesco & Camponovo, Lorenzo & Roth, Constantin, 2015. "Testing the lag structure of assets’ realized volatility dynamics," Economics Working Paper Series 1501, University of St. Gallen, School of Economics and Political Science.
    5. Jan Beran & Yuanhua Feng & Sucharita Ghosh, 2015. "Modelling long-range dependence and trends in duration series: an approach based on EFARIMA and ESEMIFAR models," Statistical Papers, Springer, vol. 56(2), pages 431-451, May.
    6. Lihong Wang, 2020. "Nearest neighbors estimation for long memory functional data," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 29(4), pages 709-725, December.
    7. Vasyl Golosnoy, 2018. "Sequential monitoring of portfolio betas," Statistical Papers, Springer, vol. 59(2), pages 663-684, June.

  20. Robinson Kruse & Michael Frömmel & Lukas Menkhoff & Philipp Sibbertsen, 2012. "What do we know about real exchange rate nonlinearities?," Empirical Economics, Springer, vol. 43(2), pages 457-474, October.
    See citations under working paper version above.
  21. Philipp Sibbertsen & Juliane Willert, 2012. "Testing for a break in persistence under long-range dependencies and mean shifts," Statistical Papers, Springer, vol. 53(2), pages 357-370, May.
    See citations under working paper version above.
  22. Kruse, Robinson & Sibbertsen, Philipp, 2012. "Long memory and changing persistence," Economics Letters, Elsevier, vol. 114(3), pages 268-272.
    See citations under working paper version above.
  23. Philipp Sibbertsen & Robinson Kruse, 2009. "Testing for a break in persistence under long‐range dependencies," Journal of Time Series Analysis, Wiley Blackwell, vol. 30(3), pages 263-285, May.
    See citations under working paper version above.
  24. Davidson, James & Sibbertsen, Philipp, 2009. "Tests of bias in log-periodogram regression," Economics Letters, Elsevier, vol. 102(2), pages 83-86, February.
    See citations under working paper version above.
  25. Daniel J. Nordman & Philipp Sibbertsen & Soumendra N. Lahiri, 2007. "Empirical likelihood confidence intervals for the mean of a long‐range dependent process," Journal of Time Series Analysis, Wiley Blackwell, vol. 28(4), pages 576-599, July.
    See citations under working paper version above.
  26. Christoph Rothe & Philipp Sibbertsen, 2006. "Phillips-Perron-type unit root tests in the nonlinear ESTAR framework," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 90(3), pages 439-456, September.
    See citations under working paper version above.
  27. Davidson, James & Sibbertsen, Philipp, 2005. "Generating schemes for long memory processes: regimes, aggregation and linearity," Journal of Econometrics, Elsevier, vol. 128(2), pages 253-282, October.
    See citations under working paper version above.
  28. Philipp Sibbertsen, 2004. "Long memory versus structural breaks: An overview," Statistical Papers, Springer, vol. 45(4), pages 465-515, October.
    See citations under working paper version above.
  29. Philipp Sibbertsen, 2004. "Long memory in volatilities of German stock returns," Empirical Economics, Springer, vol. 29(3), pages 477-488, September.
    See citations under working paper version above.
  30. Sibbertsen, Philipp, 2003. "Log-periodogram estimation of the memory parameter of a long-memory process under trend," Statistics & Probability Letters, Elsevier, vol. 61(3), pages 261-268, February.
    See citations under working paper version above.
  31. Beran, Jan & Feng, Yuanhua & Ghosh, Sucharita & Sibbertsen, Philipp, 2002. "On robust local polynomial estimation with long-memory errors," International Journal of Forecasting, Elsevier, vol. 18(2), pages 227-241.
    See citations under working paper version above.
  32. Walter Kramer & Philipp Sibbertsen, 2002. "Testing for Structural Changes in the Presence of Long Memory," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 1(3), pages 235-242, December.
    See citations under working paper version above.

Books

  1. Stefan Helber & Michael Breitner & Daniel Rösch & Cornelia Schön & Johann-Matthias Graf von der Schu (ed.), 2014. "Operations Research Proceedings 2012," Operations Research Proceedings, Springer, edition 127, number 978-3-319-00795-3, March.

    Cited by:

    1. Schwarz, Hannes & Bertsch, Valentin & Fichtner, Wolf, 2015. "Two-stage stochastic, large-scale optimization of a decentralized energy system - a residential quarter as case study," Working Paper Series in Production and Energy 10, Karlsruhe Institute of Technology (KIT), Institute for Industrial Production (IIP).
    2. Bertsch, Valentin & Geldermann, Jutta & Lühn, Tobias, 2017. "What drives the profitability of household PV investments, self-consumption and self-sufficiency?," MPRA Paper 78644, University Library of Munich, Germany.
    3. Goeke, Dominik, 2019. "Granular tabu search for the pickup and delivery problem with time windows and electric vehicles," European Journal of Operational Research, Elsevier, vol. 278(3), pages 821-836.
    4. Esther Mohr & Robert Dochow, 2017. "Risk management strategies for finding universal portfolios," Annals of Operations Research, Springer, vol. 256(1), pages 129-147, September.
    5. Bierwirth, Christian & Meisel, Frank, 2015. "A follow-up survey of berth allocation and quay crane scheduling problems in container terminals," European Journal of Operational Research, Elsevier, vol. 244(3), pages 675-689.
    6. Goeke, D. & Schneider, M., 2015. "Routing a Mixed Fleet of Electric and Conventional Vehicles," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 65939, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    7. Goeke, Dominik & Schneider, Michael, 2015. "Routing a mixed fleet of electric and conventional vehicles," European Journal of Operational Research, Elsevier, vol. 245(1), pages 81-99.
    8. Pelletier, Samuel & Jabali, Ola & Laporte, Gilbert & Veneroni, Marco, 2017. "Battery degradation and behaviour for electric vehicles: Review and numerical analyses of several models," Transportation Research Part B: Methodological, Elsevier, vol. 103(C), pages 158-187.
    9. Dahlbeck, Mirko, 2021. "A mixed-integer linear programming approach for the T-row and the multi-bay facility layout problem," European Journal of Operational Research, Elsevier, vol. 295(2), pages 443-462.

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