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Threshold Autoregressive Modeling In Finance: The Price Differences Of Equivalent Assets1

Citations

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Cited by:

  1. Dick van Dijk & Timo Terasvirta & Philip Hans Franses, 2002. "Smooth Transition Autoregressive Models — A Survey Of Recent Developments," Econometric Reviews, Taylor & Francis Journals, vol. 21(1), pages 1-47.
  2. van Dijk, D.J.C. & Franses, Ph.H.B.F., 1997. "Nonlinear Error-Correction Models for Interest Rates in The Netherlands," Econometric Institute Research Papers EI 9704-/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  3. Canto, Bea & Kräussl, Roman, 2007. "Electronic trading systems and intraday non-linear dynamics: An examination of the FTSE 100 cash and futures returns," CFS Working Paper Series 2007/20, Center for Financial Studies (CFS).
  4. Antoine Lejay & Paolo Pigato, 2017. "A threshold model for local volatility: evidence of leverage and mean reversion effects on historical data," Working Papers hal-01669082, HAL.
  5. Li, Ming-Yuan Leon, 2008. "Clarifying the dynamics of the relationship between option and stock markets using the threshold vector error correction model," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(3), pages 511-520.
  6. Erik Theissen, 2012. "Price discovery in spot and futures markets: a reconsideration," The European Journal of Finance, Taylor & Francis Journals, vol. 18(10), pages 969-987, November.
  7. Tse, Yiuman, 2001. "Index arbitrage with heterogeneous investors: A smooth transition error correction analysis," Journal of Banking & Finance, Elsevier, vol. 25(10), pages 1829-1855, October.
  8. repec:ntu:ntugeo:vol2-iss1-14-042 is not listed on IDEAS
  9. Jürgen Gaul & Erik Theissen, 2015. "A Partially Linear Approach to Modeling the Dynamics of Spot and Futures Prices," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 35(4), pages 371-384, April.
  10. Lucio Sarno & Giorgio Valente, 2005. "Modelling and forecasting stock returns: exploiting the futures market, regime shifts and international spillovers," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(3), pages 345-376, March.
  11. Laurence Copeland, 2007. "Arbitrage Bounds and the Time Series Properties of the Discount on UK Closed‐End Mutual Funds," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 34(1‐2), pages 313-330, January.
  12. Kim, Bong-Han & Chun, Sun-Eae & Min, Hong-Ghi, 2010. "Nonlinear dynamics in arbitrage of the S&P 500 index and futures: A threshold error-correction model," Economic Modelling, Elsevier, vol. 27(2), pages 566-573, March.
  13. Pavlidis Efthymios G & Paya Ivan & Peel David A, 2010. "Specifying Smooth Transition Regression Models in the Presence of Conditional Heteroskedasticity of Unknown Form," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(3), pages 1-40, May.
  14. Ledenyov, Dimitri O. & Ledenyov, Viktor O., 2015. "Wave function method to forecast foreign currencies exchange rates at ultra high frequency electronic trading in foreign currencies exchange markets," MPRA Paper 67470, University Library of Munich, Germany.
  15. Conlin Lizieri & Steven Satchell & Elaine Worzala & Roberto Dacco', 1998. "Real Interest Regimes and Real Estate Performance: A Comparison of UK and US Markets," Journal of Real Estate Research, American Real Estate Society, vol. 16(3), pages 339-356.
  16. Galyna Grynkiv & Lars Stentoft, 2018. "Stationary Threshold Vector Autoregressive Models," JRFM, MDPI, vol. 11(3), pages 1-23, August.
  17. Zhang, Qi & Cai, Charlie X. & Keasey, Kevin, 2013. "Market reaction to earnings news: A unified test of information risk and transaction costs," Journal of Accounting and Economics, Elsevier, vol. 56(2), pages 251-266.
  18. Man-Wai Ng & Wai-Sum Chan, 2004. "Robustness of alternative non-linearity tests for SETAR models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(3), pages 215-231.
  19. Antoine Lejay & Paolo Pigato, 2019. "A Threshold Model For Local Volatility: Evidence Of Leverage And Mean Reversion Effects On Historical Data," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 22(04), pages 1-24, June.
  20. Antoine Lejay & Paolo Pigato, 2020. "Maximum likelihood drift estimation for a threshold diffusion," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 47(3), pages 609-637, September.
  21. Geoffrey F. Loudon & Wing H. Watt & Pradeep K. Yadav, 2000. "An empirical analysis of alternative parametric ARCH models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(2), pages 117-136.
  22. Li, Johnny Siu-Hang & Ng, Andrew C.Y. & Chan, Wai-Sum, 2015. "Managing financial risk in Chinese stock markets: Option pricing and modeling under a multivariate threshold autoregression," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 217-230.
  23. McMillan, David G. & Philip, Dennis, 2012. "Short-sale constraints and efficiency of the spot–futures dynamics," International Review of Financial Analysis, Elsevier, vol. 24(C), pages 129-136.
  24. Christos Ioannidis & David A. Peel & Michael J. Peel, 2003. "The Time Series Properties of Financial Ratios: Lev Revisited," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 30(5‐6), pages 699-714, June.
  25. Charlie X. Cai & Robert Faff & Yongcheol Shin, 2018. "Noise Momentum Around the World," Abacus, Accounting Foundation, University of Sydney, vol. 54(1), pages 79-104, March.
  26. Kuck, Konstantin & Schweikert, Karsten, 2023. "Price discovery in equity markets: A state-dependent analysis of spot and futures markets," Journal of Banking & Finance, Elsevier, vol. 149(C).
  27. Chan, W.S. & Cheung, S.H., 2005. "A bivariate threshold time series model for analyzing Australian interest rates," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 68(5), pages 429-437.
  28. Adrian Cantemir Calin & Tiberiu Diaconescu & Oana – Cristina Popovici, 2014. "Nonlinear Models for Economic Forecasting Applications: An Evolutionary Discussion," Computational Methods in Social Sciences (CMSS), "Nicolae Titulescu" University of Bucharest, Faculty of Economic Sciences, vol. 2(1), pages 42-47, June.
  29. Siu, Tak Kuen, 2016. "A self-exciting threshold jump–diffusion model for option valuation," Insurance: Mathematics and Economics, Elsevier, vol. 69(C), pages 168-193.
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