IDEAS home Printed from https://ideas.repec.org/r/bla/jtsera/v1y1980i1p47-71.html
   My bibliography  Save this item

State‐Dependent Models: A General Approach To Non‐Linear Time Series Analysis

Citations

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


Cited by:

  1. Chen, Song Xi & Lei, Lihua & Tu, Yundong, 2014. "Functional Coefficient Moving Average Model with Applications to forecasting Chinese CPI," MPRA Paper 67074, University Library of Munich, Germany, revised 2015.
  2. Andrada-Félix, Julián & Fernández-Rodríguez, Fernando & Fuertes, Ana-Maria, 2016. "Combining nearest neighbor predictions and model-based predictions of realized variance: Does it pay?," International Journal of Forecasting, Elsevier, vol. 32(3), pages 695-715.
  3. Bai, Zhidong & Hui, Yongchang & Wong, Wing-Keung, 2012. "New Non-Linearity Test to Circumvent the Limitation of Volterra Expansion," MPRA Paper 41872, University Library of Munich, Germany.
  4. LeBaron, Blake, 2003. "Non-Linear Time Series Models in Empirical Finance,: Philip Hans Franses and Dick van Dijk, Cambridge University Press, Cambridge, 2000, 296 pp., Paperback, ISBN 0-521-77965-0, $33, [UK pound]22.95, [," International Journal of Forecasting, Elsevier, vol. 19(4), pages 751-752.
  5. Hai‐Bin Wang, 2008. "Nonlinear ARMA models with functional MA coefficients," Journal of Time Series Analysis, Wiley Blackwell, vol. 29(6), pages 1032-1056, November.
  6. David E. Runkle & Peter C. Young, 1989. "Recursive estimation and modelling of nonstationary and nonlinear time series," Discussion Paper / Institute for Empirical Macroeconomics 7, Federal Reserve Bank of Minneapolis.
  7. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521770415.
  8. Giorgio Busetti & Matteo Manera, 2003. "STAR-GARCH Models for Stock Market Interactions in the Pacific Basin Region, Japan and US," Working Papers 2003.43, Fondazione Eni Enrico Mattei.
  9. Sio Chong U & Jacky So & Deng Ding & Lihong Liu, 2016. "An efficient Fourier expansion method for the calculation of value-at-risk: Contributions of extra-ordinary risks," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 3(01), pages 1-27, March.
  10. Chung-Shu Wu & Ruey S. Tsay, 2003. "Forecasting with leading indicators revisited," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 22(8), pages 603-617.
  11. Ihle, Rico & von Cramon-Taubadel, Stephan, 2008. "A Comparison of Threshold Cointegration and Markov-Switching Vector Error Correction Models in Price Transmission Analysis," 2008 Conference, April 21-22, 2008, St. Louis, Missouri 37603, NCCC-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
  12. Giampiero M. Gallo & Yongmiao Hong & Tae-Why Lee, 2001. "Modelling the Impact of Overnight Surprises on Intra-daily Stock Returns," Econometrics Working Papers Archive wp2001_03, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
  13. Bruno, Giancarlo, 2009. "Non-linear relation between industrial production and business surveys data," MPRA Paper 42337, University Library of Munich, Germany.
  14. Cross, Philip & Ma, Xiandong, 2014. "Nonlinear system identification for model-based condition monitoring of wind turbines," Renewable Energy, Elsevier, vol. 71(C), pages 166-175.
  15. S. Heravi & J. Easaw & R. Golinelli, 2016. "Generalized State-Dependent Models: A Multivariate Approach," Working Papers wp1067, Dipartimento Scienze Economiche, Universita' di Bologna.
  16. T.P. Koirala Ph.D., 2012. "Inflation Persistence in Nepal: A TAR Representation," NRB Working Paper 11/2012, Nepal Rastra Bank, Research Department.
  17. Alexandros Agapitos & Anthony Brabazon & Michael O’Neill, 2017. "Regularised gradient boosting for financial time-series modelling," Computational Management Science, Springer, vol. 14(3), pages 367-391, July.
  18. Yamei Liu & Walter Enders, 2003. "Out‐of‐Sample Forecasts and Nonlinear Model Selection with an Example of the Term Structure of Interest Rates," Southern Economic Journal, John Wiley & Sons, vol. 69(3), pages 520-540, January.
  19. Mira, Santiago & Escribano, Álvaro, 1995. "Nonlinear time series models: consistency and asymptotic normality of nls under new conditions," DES - Working Papers. Statistics and Econometrics. WS 6202, Universidad Carlos III de Madrid. Departamento de Estadística.
  20. Hui, Yongchang & Wong, Wing-Keung & Bai, Zhidong & Zhu, Zhenzhen, 2016. "A New Nonlinearity Test to Circumvent the Limitation of Volterra Expansion with Applications," MPRA Paper 75216, University Library of Munich, Germany.
  21. Bekiros, Stelios D., 2009. "A robust algorithm for parameter estimation in smooth transition autoregressive models," Economics Letters, Elsevier, vol. 103(1), pages 36-38, April.
  22. Donya Rahmani & Saeed Heravi & Hossein Hassani & Mansi Ghodsi, 2016. "Forecasting time series with structural breaks with Singular Spectrum Analysis, using a general form of recurrent formula," Papers 1605.02188, arXiv.org.
  23. Bovas Abraham & A. Thavaneswaran, 1991. "A nonlinear time series model and estimation of missing observations," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 43(3), pages 493-504, September.
  24. Guan, Bo & Silva, Emmanuel Sirimal & Hassani, Hossein & Heravi, Saeed, 2022. "Forecasting tourism growth with State-Dependent Models," Annals of Tourism Research, Elsevier, vol. 94(C).
  25. Philip Rothman, "undated". "Higher-Order Residual Analysis for Simple Bilinear and Threshold Autoregressive Models with the TR Test," Working Papers 9813, East Carolina University, Department of Economics.
  26. G. Boero & E. Marrocu, 1999. "Modelli non lineari per i tassi di cambio: un confronto previsivo," Working Paper CRENoS 199914, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
  27. Martín González-Rozada & Luis Pereiro, 2013. "Forecasting Prices in Regime-Switching Markets," Department of Economics Working Papers 2013_2, Universidad Torcuato Di Tella.
  28. Muhammad Akram GILAL* & Muhammad AJMAIR** & Sohail FAROOQ***, 2019. "Structural Changes And Economic Growth In Pakistan," Pakistan Journal of Applied Economics, Applied Economics Research Centre, vol. 29(1), pages 35-51.
  29. Ip, Wai-Cheung & Wong, Heung & Li, Yuan & Xie, Zhongjie, 1999. "Threshold variable selection by wavelets in open-loop threshold autoregressive models," Statistics & Probability Letters, Elsevier, vol. 42(4), pages 375-392, May.
  30. G. Boero & E. Marrocu, 2000. "La performance di modelli non lineari per i tassi di cambio: un'applicazione con dati a diversa frequenza," Working Paper CRENoS 200014, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
  31. Lee, Oesook, 2000. "On probabilistic properties of nonlinear ARMA(p,q) models," Statistics & Probability Letters, Elsevier, vol. 46(2), pages 121-131, January.
  32. Zhou, Yihong & Zhang, Xiao & Ding, Feng, 2022. "Partially-coupled nonlinear parameter optimization algorithm for a class of multivariate hybrid models," Applied Mathematics and Computation, Elsevier, vol. 414(C).
  33. Huang, Alex YiHou & Hu, Wen-Cheng, 2012. "Regime switching dynamics in credit default swaps: Evidence from smooth transition autoregressive model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(4), pages 1497-1508.
  34. Jeff B. Cromwell & Michael J. Hannan, 1993. "The Utility of Impulse Response Functions in Regional Analysis: Some Critical Issues," International Regional Science Review, , vol. 15(2), pages 199-222, August.
  35. Donya Rahmani & Damien Fay, 2022. "A state‐dependent linear recurrent formula with application to time series with structural breaks," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(1), pages 43-63, January.
  36. Liu, Yamei, 2000. "Overfitting and forecasting: linear versus non-linear time series models," ISU General Staff Papers 2000010108000014914, Iowa State University, Department of Economics.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.