IDEAS home Printed from https://ideas.repec.org/r/cup/etheor/v16y2000i06p835-854_16.html

Monitoring Structural Changes With The Generalized Fluctuation Test

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Torben G. Andersen & Viktor Todorov & Bo Zhou, 2025. "Real‐time detection of local no‐arbitrage violations," Quantitative Economics, Econometric Society, vol. 16(2), pages 459-495, May.
  2. William Kengne & Isidore S. Ngongo, 2022. "Inference for nonstationary time series of counts with application to change-point problems," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 74(4), pages 801-835, August.
  3. Mengrui Zhu & Hua Xu & Xingyu Gao & Minggang Wang & André L. M. Vilela & Lixin Tian, 2022. "Identification of Breakpoints in Carbon Market Based on Probability Density Recurrence Network," Energies, MDPI, vol. 15(15), pages 1-18, July.
  4. Harvey, David I. & Leybourne, Stephen J. & Taylor, A.M. Robert, 2010. "Robust methods for detecting multiple level breaks in autocorrelated time series," Journal of Econometrics, Elsevier, vol. 157(2), pages 342-358, August.
  5. Christis Katsouris, 2023. "Break-Point Date Estimation for Nonstationary Autoregressive and Predictive Regression Models," Papers 2308.13915, arXiv.org.
  6. Jana Eklund & George Kapetanios & Simon Price, 2013. "Robust Forecast Methods and Monitoring during Structural Change," Manchester School, University of Manchester, vol. 81, pages 3-27, October.
  7. Šárka Hudecová & Marie Hušková & Simos G. Meintanis, 2017. "Tests for Structural Changes in Time Series of Counts," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 44(4), pages 843-865, December.
  8. Bernales, Alejandro & Chen, Louisa & Valenzuela, Marcela, 2017. "Learning and forecasts about option returns through the volatility risk premium," Journal of Economic Dynamics and Control, Elsevier, vol. 82(C), pages 312-330.
  9. Bardet, Jean-Marc & Kengne, William, 2014. "Monitoring procedure for parameter change in causal time series," Journal of Multivariate Analysis, Elsevier, vol. 125(C), pages 204-221.
  10. Lee, Sangyeol & Park, Siyun, 2009. "The monitoring test for the stability of regression models with nonstationary regressors," Economics Letters, Elsevier, vol. 105(3), pages 250-252, December.
  11. Mikkel Bennedsen, 2020. "Designing a sequential testing procedure for verifying global CO2 emissions," CREATES Research Papers 2020-01, Department of Economics and Business Economics, Aarhus University.
  12. Andreou, Elena & Ghysels, Eric, 2006. "Monitoring disruptions in financial markets," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 77-124.
  13. Tatsuru Kikuchi & Toranosuke Onishi & Kenichi Ueda, 2021. "Price Stability of Cryptocurrencies as a Medium of Exchange," CARF F-Series CARF-F-526, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
  14. Jana Eklund & George Kapetanios & Simon Price, 2010. "Forecasting in the presence of recent structural change," Bank of England working papers 406, Bank of England.
  15. Kurt Hornik & Friedrich Leisch & Christian Kleiber & Achim Zeileis, 2005. "Monitoring structural change in dynamic econometric models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(1), pages 99-121.
  16. Yudong Chen & Tengyao Wang & Richard J. Samworth, 2022. "High‐dimensional, multiscale online changepoint detection," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(1), pages 234-266, February.
  17. Pouliot, William, 2016. "Robust tests for change in intercept and slope in linear regression models with application to manager performance in the mutual fund industry," Economic Modelling, Elsevier, vol. 58(C), pages 523-534.
  18. Alexander Aue & Lajos Horváth & Piotr Kokoszka & Josef Steinebach, 2008. "Monitoring shifts in mean: Asymptotic normality of stopping times," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 17(3), pages 515-530, November.
  19. Czinkota, Thomas, 2012. "Das Halteproblem bei Strukturbrüchen in Finanzmarktzeitreihen [The Halting Problem applied to Structural Breaks in Financial Time Series]," MPRA Paper 37072, University Library of Munich, Germany.
  20. Hsu, Chih-Chiang, 2007. "The MOSUM of squares test for monitoring variance changes," Finance Research Letters, Elsevier, vol. 4(4), pages 254-260, December.
  21. Abhijit Sharma & Kelvin G Balcombe & Iain M Fraser, 2009. "Non-renewable resource prices: Structural breaks and long term trends," Economics Bulletin, AccessEcon, vol. 29(2), pages 805-819.
  22. Alberto Cazzola & Aurora Angeli & Lucia Pasquini, 2016. "The relationship between unemployment and fertility in Italy," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 34(1), pages 1-38.
  23. Otto, Sven & Breitung, Jörg, 2020. "Backward CUSUM for Testing and Monitoring Structural Change," VfS Annual Conference 2020 (Virtual Conference): Gender Economics 224533, Verein für Socialpolitik / German Economic Association.
  24. KUROZUMI, Eiji & 黒住, 英司, 2016. "Monitoring Parameter Constancy with Endogenous Regressors," Discussion Papers 2016-01, Graduate School of Economics, Hitotsubashi University.
  25. Anatolyev, Stanislav, 2009. "Nonparametric Retrospection and Monitoring of Predictability of Financial Returns," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(2), pages 149-160.
  26. Aue, Alexander & Horváth, Lajos & Reimherr, Matthew L., 2009. "Delay times of sequential procedures for multiple time series regression models," Journal of Econometrics, Elsevier, vol. 149(2), pages 174-190, April.
  27. Jan Verbesselt & Achim Zeileis & Martin Herold, 2011. "Near Real-Time Disturbance Detection in Terrestrial Ecosystems Using Satellite Image Time Series: Drought Detection in Somalia," Working Papers 2011-18, Faculty of Economics and Statistics, Universität Innsbruck.
  28. Bock, David, 2007. "Consequences of using the probability of a false alarm as the false alarm measure," Research Reports 2007:3, University of Gothenburg, Statistical Research Unit, School of Business, Economics and Law.
  29. Gabriela Ciuperca, 2022. "Real-time detection of a change-point in a linear expectile model," Statistical Papers, Springer, vol. 63(4), pages 1323-1367, August.
  30. Christis Katsouris, 2023. "Structural Break Detection in Quantile Predictive Regression Models with Persistent Covariates," Papers 2302.05193, arXiv.org.
  31. Choi, Hanbok & Eom, Young Ho & Jang, Woon Wook & Kim, Don H., 2017. "Covered interest parity deviation and counterparty default risk: U.S. Dollar/Korean Won FX swap market," Pacific-Basin Finance Journal, Elsevier, vol. 44(C), pages 47-63.
  32. Olmo Jose & Pouliot William, 2011. "Early Detection Techniques for Market Risk Failure," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 15(4), pages 1-55, September.
  33. Chen, Yudong & Wang, Tengyao & Samworth, Richard J., 2022. "High-dimensional, multiscale online changepoint detection," LSE Research Online Documents on Economics 113665, London School of Economics and Political Science, LSE Library.
  34. Jan J. J. Groen & George Kapetanios & Simon Price, 2013. "Multivariate Methods For Monitoring Structural Change," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(2), pages 250-274, March.
  35. Anton Skrobotov, 2020. "Survey on structural breaks and unit root tests," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 58, pages 96-141.
  36. Mamadou Lamine Diop & William Kengne, 2022. "Poisson QMLE for change-point detection in general integer-valued time series models," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 85(3), pages 373-403, April.
  37. Sven Otto & Jorg Breitung, 2020. "Backward CUSUM for Testing and Monitoring Structural Change with an Application to COVID-19 Pandemic Data," Papers 2003.02682, arXiv.org, revised Mar 2022.
  38. Carsten J. Crede, 2019. "A Structural Break Cartel Screen for Dating and Detecting Collusion," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 54(3), pages 543-574, May.
  39. Jan J. J. Groen & George Kapetanios & Simon Price, 2013. "Multivariate Methods For Monitoring Structural Change," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(2), pages 250-274, March.
  40. Josua Gösmann & Tobias Kley & Holger Dette, 2021. "A new approach for open‐end sequential change point monitoring," Journal of Time Series Analysis, Wiley Blackwell, vol. 42(1), pages 63-84, January.
  41. Carsten J. Crede, 2015. "A structural break cartel screen for dating and detecting collusion," Working Paper series, University of East Anglia, Centre for Competition Policy (CCP) 2015-11, Centre for Competition Policy, University of East Anglia, Norwich, UK..
  42. Bernales, Alejandro & Guidolin, Massimo, 2015. "Learning to smile: Can rational learning explain predictable dynamics in the implied volatility surface?," Journal of Financial Markets, Elsevier, vol. 26(C), pages 1-37.
  43. Andreou, Elena & Ghysels, Eric, 2008. "Quality control for structural credit risk models," Journal of Econometrics, Elsevier, vol. 146(2), pages 364-375, October.
  44. David I. Harvey & Stephen J. Leybourne & A. M. Robert Taylor, 2009. "Robust methods for detecting multiple level breaks in autocorrelated time series [Revised to become No. 10/01 above]," Discussion Papers 09/01, University of Nottingham, Granger Centre for Time Series Econometrics.
  45. Chevallier, Julien, 2011. "Detecting instability in the volatility of carbon prices," Energy Economics, Elsevier, vol. 33(1), pages 99-110, January.
  46. Okyoung Na & Youngmi Lee & Sangyeol Lee, 2011. "Monitoring parameter change in time series models," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 20(2), pages 171-199, June.
  47. Haitham A. Al-Zoubi & Aktham Maghyereh, 2007. "Stationary Component in Stock Prices: A Reappraisal of Empirical Findings," Multinational Finance Journal, Multinational Finance Journal, vol. 11(3-4), pages 287-322, September.
  48. 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.
  49. Anatolyev Stanislav & Kosenok Grigory, 2018. "Sequential Testing with Uniformly Distributed Size," Journal of Time Series Econometrics, De Gruyter, vol. 10(2), pages 1-22, July.
  50. Elena Andreou & Eric Ghysels, 2004. "Monitoring for Disruptions in Financial Markets," CIRANO Working Papers 2004s-26, CIRANO.
  51. Pierre Perron & Eduardo Zorita & Eiji Kurozumi, 2017. "Monitoring Parameter Constancy with Endogenous Regressors," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(5), pages 791-805, September.
  52. Christis Katsouris, 2022. "Partial Sum Processes of Residual-Based and Wald-type Break-Point Statistics in Time Series Regression Models," Papers 2202.00141, arXiv.org, revised Feb 2022.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.