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A Test Against Spurious Long Memory

Citations

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Cited by:

  1. 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).
  2. 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.
  3. Janus, Paweł & Koopman, Siem Jan & Lucas, André, 2014. "Long memory dynamics for multivariate dependence under heavy tails," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 187-206.
  4. Adam McCloskey, 2013. "Estimation of the long-memory stochastic volatility model parameters that is robust to level shifts and deterministic trends," Journal of Time Series Analysis, Wiley Blackwell, vol. 34(3), pages 285-301, May.
  5. 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.
  6. Mccloskey, Adam & Perron, Pierre, 2013. "Memory Parameter Estimation In The Presence Of Level Shifts And Deterministic Trends," Econometric Theory, Cambridge University Press, vol. 29(6), pages 1196-1237, December.
  7. de Truchis, Gilles & Keddad, Benjamin, 2016. "On the risk comovements between the crude oil market and U.S. dollar exchange rates," Economic Modelling, Elsevier, vol. 52(PA), pages 206-215.
  8. M. A. Limam & V. Terraza & M. Terraza, 2017. "Hedge Fund Return Dynamics: Long Memory and Regime Switching," International Journal of Financial Research, International Journal of Financial Research, Sciedu Press, vol. 8(4), pages 148-166, October.
  9. Marcel Aloy & Gilles Truchis, 2016. "Optimal Estimation Strategies for Bivariate Fractional Cointegration Systems and the Co-persistence Analysis of Stock Market Realized Volatilities," Computational Economics, Springer;Society for Computational Economics, vol. 48(1), pages 83-104, June.
  10. Klaus Grobys & Sami Vähämaa, 0. "Another look at value and momentum: volatility spillovers," Review of Quantitative Finance and Accounting, Springer, vol. 0, pages 1-21.
  11. 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.
  12. 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.
  13. Juneja, Januj A., 2016. "Financial crises and estimation bias in international bond markets," Research in International Business and Finance, Elsevier, vol. 38(C), pages 593-607.
  14. Davide Delle Monache & Stefano Grassi & Paolo Santucci, 2015. "Testing for Level Shifts in Fractionally Integrated Processes: a State Space Approach," Studies in Economics 1511, School of Economics, University of Kent.
  15. Rossi, Eduardo & Santucci de Magistris, Paolo, 2013. "Long memory and tail dependence in trading volume and volatility," Journal of Empirical Finance, Elsevier, vol. 22(C), pages 94-112.
  16. Kruse, Robinson & Leschinski, Christian & Will, Michael, 2016. "Comparing Predictive Accuracy under Long Memory - With an Application to Volatility Forecasting," Hannover Economic Papers (HEP) dp-571, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
  17. Alessandro Casini & Pierre Perron, 2018. "Structural Breaks in Time Series," Papers 1805.03807, arXiv.org.
  18. 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.
  19. Hou, Jie & Perron, Pierre, 2014. "Modified local Whittle estimator for long memory processes in the presence of low frequency (and other) contaminations," Journal of Econometrics, Elsevier, vol. 182(2), pages 309-328.
  20. Fabrizio Iacone & Stephen J. Leybourne & A. M. Robert Taylor, 2014. "A FIXED- b TEST FOR A BREAK IN LEVEL AT AN UNKNOWN TIME UNDER FRACTIONAL INTEGRATION," Journal of Time Series Analysis, Wiley Blackwell, vol. 35(1), pages 40-54, January.
  21. Javier Haulde & Morten Ørregaard Nielsen, 2022. "Fractional integration and cointegration," CREATES Research Papers 2022-02, Department of Economics and Business Economics, Aarhus University.
  22. Marie Busch & Philipp Sibbertsen, 2018. "An Overview of Modified Semiparametric Memory Estimation Methods," Econometrics, MDPI, vol. 6(1), pages 1-21, March.
  23. Sibbertsen, Philipp & Leschinski, Christian & Busch, Marie, 2018. "A multivariate test against spurious long memory," Journal of Econometrics, Elsevier, vol. 203(1), pages 33-49.
  24. Kruse, Robinson, 2015. "A modified test against spurious long memory," Economics Letters, Elsevier, vol. 135(C), pages 34-38.
  25. 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.
  26. Papailias, Fotis & Fruet Dias, Gustavo, 2015. "Forecasting long memory series subject to structural change: A two-stage approach," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1056-1066.
  27. 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.
  28. Rodríguez, Gabriel, 2017. "Modeling Latin-American stock and Forex markets volatility: Empirical application of a model with random level shifts and genuine long memory," The North American Journal of Economics and Finance, Elsevier, vol. 42(C), pages 393-420.
  29. Iacone Fabrizio & Leybourne Stephen J. & Robert Taylor A.M., 2017. "Testing for a Change in Mean under Fractional Integration," Journal of Time Series Econometrics, De Gruyter, vol. 9(1), pages 1-8, January.
  30. Christensen, Bent Jesper & Varneskov, Rasmus Tangsgaard, 2017. "Medium band least squares estimation of fractional cointegration in the presence of low-frequency contamination," Journal of Econometrics, Elsevier, vol. 197(2), pages 218-244.
  31. 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.
  32. Rasmus T. Varneskov & Pierre Perron, 2018. "Combining long memory and level shifts in modelling and forecasting the volatility of asset returns," Quantitative Finance, Taylor & Francis Journals, vol. 18(3), pages 371-393, March.
  33. Chen, Cathy Yi-Hsuan & Chiang, Thomas C. & Härdle, Wolfgang Karl, 2018. "Downside risk and stock returns in the G7 countries: An empirical analysis of their long-run and short-run dynamics," Journal of Banking & Finance, Elsevier, vol. 93(C), pages 21-32.
  34. Gabriel Rodríguez, 2016. "Modeling Latin-American Stock and Forex Markets Volatility: Empirical Application of a Model with Random Level Shifts and Genuine Long Memory [Modelando la volatilidad de los mercados bursátiles y cam," Documentos de Trabajo / Working Papers 2016-416, Departamento de Economía - Pontificia Universidad Católica del Perú.
  35. Lujia Bai & Weichi Wu, 2021. "Detecting long-range dependence for time-varying linear models," Papers 2110.08089, arXiv.org, revised Mar 2023.
  36. Carina Gerstenberger, 2021. "Robust discrimination between long‐range dependence and a change in mean," Journal of Time Series Analysis, Wiley Blackwell, vol. 42(1), pages 34-62, January.
  37. Dark, Jonathan, 2024. "An adaptive long memory conditional correlation model," Journal of Empirical Finance, Elsevier, vol. 75(C).
  38. 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.
  39. Dark, Jonathan, 2015. "Futures hedging with Markov switching vector error correction FIEGARCH and FIAPARCH," Journal of Banking & Finance, Elsevier, vol. 61(S2), pages 269-285.
  40. 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.
  41. 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.
  42. 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.
  43. Dalla, Violetta, 2015. "Power transformations of absolute returns and long memory estimation," Journal of Empirical Finance, Elsevier, vol. 33(C), pages 1-18.
  44. Charfeddine, Lanouar & Maouchi, Youcef, 2019. "Are shocks on the returns and volatility of cryptocurrencies really persistent?," Finance Research Letters, Elsevier, vol. 28(C), pages 423-430.
  45. Yohei Yamamoto & Pierre Perron, 2013. "Estimating and testing multiple structural changes in linear models using band spectral regressions," Econometrics Journal, Royal Economic Society, vol. 16(3), pages 400-429, October.
  46. Andrea Cipollini & Iolanda Lo Cascio & Silvia Muzzioli, 2015. "Financial connectedness among European volatility risk premia," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 15112, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
  47. Cipollini, Andrea & Lo Cascio, Iolanda & Muzzioli, Silvia, 2018. "Risk aversion connectedness in five European countries," Economic Modelling, Elsevier, vol. 71(C), pages 68-79.
  48. 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.
  49. 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.
  50. Kellard, Neil M. & Jiang, Ying & Wohar, Mark, 2015. "Spurious long memory, uncommon breaks and the implied–realized volatility puzzle," Journal of International Money and Finance, Elsevier, vol. 56(C), pages 36-54.
  51. Hassler, Uwe & Rodrigues, Paulo M.M. & Rubia, Antonio, 2014. "Persistence in the banking industry: Fractional integration and breaks in memory," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 95-112.
  52. Niels Haldrup & Robinson Kruse, 2014. "Discriminating between fractional integration and spurious long memory," CREATES Research Papers 2014-19, Department of Economics and Business Economics, Aarhus University.
  53. 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.
  54. 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.
  55. Gilles Truchis & Benjamin Keddad, 2016. "Long-Run Comovements in East Asian Stock Market Volatility," Open Economies Review, Springer, vol. 27(5), pages 969-986, November.
  56. Andrés Herrera Aramburú & Gabriel Rodríguez, 2016. "Volatility of stock market and exchange rate returns in Peru: Long memory or short memory with level shifts?," International Journal of Monetary Economics and Finance, Inderscience Enterprises Ltd, vol. 9(1), pages 45-66.
  57. Gabriel Rodríguez & Junior A. Ojeda Cunya & José Carlos Gonzáles Tanaka, 2019. "An empirical note about estimation and forecasting Latin American Forex returns volatility: the role of long memory and random level shifts components," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 18(2), pages 107-123, June.
  58. Dooruj Rambaccussing & Murat Mazibas, 2020. "True versus Spurious Long Memory in Cryptocurrencies," JRFM, MDPI, vol. 13(9), pages 1-11, August.
  59. OlaOluwa S. Yaya & Xuan Vinh Vo & Ahamuefula E. Ogbonna & Adeolu O. Adewuyi, 2022. "Modelling cryptocurrency high–low prices using fractional cointegrating VAR," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 489-505, January.
  60. 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.
  61. Wenger, Kai & Leschinski, Christian & Sibbertsen, Philipp, 2017. "The Memory of Volatility," Hannover Economic Papers (HEP) dp-601, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
  62. 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.
  63. Januj Juneja, 2018. "Empirical performance of Gaussian affine dynamic term structure models in the presence of autocorrelation misspecification bias," Review of Quantitative Finance and Accounting, Springer, vol. 50(3), pages 695-715, April.
  64. Jorge Barrientos Marin & Laura Marquez Marulanda & Fernando Villada Duque, 2023. "Analyzing Electricity Demand in Colombia: A Functional Time Series Approach," International Journal of Energy Economics and Policy, Econjournals, vol. 13(1), pages 75-84, January.
  65. Andersen, Torben G. & Varneskov, Rasmus T., 2021. "Consistent inference for predictive regressions in persistent economic systems," Journal of Econometrics, Elsevier, vol. 224(1), pages 215-244.
  66. Dark, Jonathan, 2018. "Multivariate models with long memory dependence in conditional correlation and volatility," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 162-180.
  67. Klaus Grobys & Sami Vähämaa, 2020. "Another look at value and momentum: volatility spillovers," Review of Quantitative Finance and Accounting, Springer, vol. 55(4), pages 1459-1479, November.
  68. Gao, Guangyuan & Ho, Kin-Yip & Shi, Yanlin, 2020. "Long memory or regime switching in volatility? Evidence from high-frequency returns on the U.S. stock indices," Pacific-Basin Finance Journal, Elsevier, vol. 61(C).
  69. 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.
  70. Renzo Pardo Figueroa & Gabriel Rodríguez, 2014. "Distinguishing between True and Spurious Long Memory in the Volatility of Stock Market Returns in Latin America," Documentos de Trabajo / Working Papers 2014-395, Departamento de Economía - Pontificia Universidad Católica del Perú.
  71. 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.
  72. Francisco Estrada & Pierre Perron, "undated". "Detection and attribution of climate change through econometric methods," Boston University - Department of Economics - Working Papers Series 2013-015, Boston University - Department of Economics.
  73. Jiawen Xu & Pierre Perron, 2013. "Robust testing of time trend and mean with unknown integration order errors Frequency (and Other) Contaminations," Boston University - Department of Economics - Working Papers Series 2013-006, Boston University - Department of Economics.
  74. Ye Li & Pierre Perron & Jiawen Xu, 2017. "Modelling exchange rate volatility with random level shifts," Applied Economics, Taylor & Francis Journals, vol. 49(26), pages 2579-2589, June.
  75. Berna Kirkulak-Uludag & Zorikto Lkhamazhapov, 2017. "Volatility Dynamics of Precious Metals: Evidence from Russia," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 67(4), pages 300-317, August.
  76. 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.
  77. Andrea Cipollini & Iolanda Lo Cascio & Silvia Muzzioli, 2015. "Financial connectedness among European volatility risk premia," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 0058, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
  78. 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.
  79. repec:hum:wpaper:sfb649dp2016-001 is not listed on IDEAS
  80. Chen, Cathy Yi-Hsuan & Chiang, Thomas C. & Härdle, Wolfgang Karl, 2016. "Downside risk and stock returns: An empirical analysis of the long-run and short-run dynamics from the G-7 Countries," SFB 649 Discussion Papers 2016-001, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
  81. 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.
  82. Andrea Cipollini & Iolanda Lo Cascio & Silvia Muzzioli, 2014. "Volatility risk premia and financial connectedness," Department of Economics 0047, University of Modena and Reggio E., Faculty of Economics "Marco Biagi".
  83. Andrea Cipollini & Iolanda Lo Cascio & Silvia Muzzioli, 2014. "Volatility risk premia and financial connectedness," Center for Economic Research (RECent) 109, University of Modena and Reggio E., Dept. of Economics "Marco Biagi".
  84. Tan, Zhengxun & Xiao, Binuo & Huang, Yilong & Zhou, Li, 2021. "Value at risk and return in Chinese and the US stock markets: Double long memory and fractional cointegration," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).
  85. Jonathan Dark & Xin Gao & Thijs van der Heijden & Federico Nardari, 2022. "Forecasting variance swap payoffs," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(12), pages 2135-2164, December.
  86. Assaf, Ata & Demir, Ender & Mokni, Khaled, 2024. "Exploring connectedness among cryptocurrency, technology communication, and FinTech through dynamic and fractal analysis," Finance Research Letters, Elsevier, vol. 63(C).
  87. Leschinski, Christian & Sibbertsen, Philipp, 2017. "Origins of Spurious Long Memory," Hannover Economic Papers (HEP) dp-595, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
  88. Leschinski, Christian & Sibbertsen, Philipp, 2018. "The Periodogram of Spurious Long-Memory Processes," Hannover Economic Papers (HEP) dp-632, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
  89. 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).
  90. Lovcha, Yuliya & Pérez Laborda, Àlex, 2018. "Volatility Spillovers in a Long-Memory VAR: an Application to Energy Futures Returns," Working Papers 2072/307362, Universitat Rovira i Virgili, Department of Economics.
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