IDEAS home Printed from https://ideas.repec.org/p/cdl/ucsdec/qt31f8500p.html
   My bibliography  Save this paper

Time irreversible copula-based Markov Models

Author

Listed:
  • Beare, Brendan K.
  • Seo, Juwon

Abstract

Economic and financial time series frequently exhibit time irreversible dynamics. For instance, there is considerable evidence of asymmetric fluctuations in many macroeconomic and financial variables, and certain game theoretic models of price determination predict asymmetric cycles in price series. In this paper we make two primary contributions to the econometric literature on time reversibility. First, we propose a new test of time reversibility, applicable to stationary Markov chains. Compared to existing tests, our test has the advantage of being consistent against arbitrary violations of reversibility. Second, we explain how a circulation density function may be used to characterize the nature of time irreversibility when it is present. We propose a copula-based estimator of the circulation density, and verify that it is well behaved asymptotically under suitable regularity conditions. We illustrate the use of our time reversibility test and circulation density estimator by applying them to five years of Canadian gasoline price markup data.

Suggested Citation

  • Beare, Brendan K. & Seo, Juwon, 2012. "Time irreversible copula-based Markov Models," University of California at San Diego, Economics Working Paper Series qt31f8500p, Department of Economics, UC San Diego.
  • Handle: RePEc:cdl:ucsdec:qt31f8500p
    as

    Download full text from publisher

    File URL: https://www.escholarship.org/uc/item/31f8500p.pdf;origin=repeccitec
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Chen, Xiaohong & Fan, Yanqin, 2006. "Estimation of copula-based semiparametric time series models," Journal of Econometrics, Elsevier, vol. 130(2), pages 307-335, February.
    2. Eric Bouye & Mark Salmon, 2009. "Dynamic copula quantile regressions and tail area dynamic dependence in Forex markets," The European Journal of Finance, Taylor & Francis Journals, vol. 15(7-8), pages 721-750.
    3. Xiaohong Chen & Wei Biao Wu & Yanping Yi, 2009. "Efficient Estimation of Copula-based Semiparametric Markov Models," Cowles Foundation Discussion Papers 1691, Cowles Foundation for Research in Economics, Yale University, revised Mar 2009.
    4. Michael D. Noel, 2008. "Edgeworth Price Cycles and Focal Prices: Computational Dynamic Markov Equilibria," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 17(2), pages 345-377, June.
    5. Racine, Jeffrey S. & Maasoumi, Esfandiar, 2007. "A versatile and robust metric entropy test of time-reversibility, and other hypotheses," Journal of Econometrics, Elsevier, vol. 138(2), pages 547-567, June.
    6. Jean-David FERMANIAN & Olivier SCAILLET, 2003. "Nonparametric Estimation of Copulas for Time Series," FAME Research Paper Series rp57, International Center for Financial Asset Management and Engineering.
    7. Beare, Brendan K., 2012. "Archimedean Copulas And Temporal Dependence," Econometric Theory, Cambridge University Press, vol. 28(6), pages 1165-1185, December.
    8. Michael D. Noel, 2007. "Edgeworth Price Cycles, Cost-Based Pricing, and Sticky Pricing in Retail Gasoline Markets," The Review of Economics and Statistics, MIT Press, vol. 89(2), pages 324-334, May.
    9. Roger Nelsen, 2007. "Extremes of nonexchangeability," Statistical Papers, Springer, vol. 48(4), pages 695-695, October.
    10. Paparoditis, Efstathios & Politis, Dimitris N., 2001. "A Markovian Local Resampling Scheme For Nonparametric Estimators In Time Series Analysis," Econometric Theory, Cambridge University Press, vol. 17(3), pages 540-566, June.
    11. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    12. Darolles, Serge & Florens, Jean-Pierre & Gourieroux, Christian, 2004. "Kernel-based nonlinear canonical analysis and time reversibility," Journal of Econometrics, Elsevier, vol. 119(2), pages 323-353, April.
    13. P. Gagliardini & C. Gourieroux, 2008. "Duration time‐series models with proportional hazard," Journal of Time Series Analysis, Wiley Blackwell, vol. 29(1), pages 74-124, January.
    14. Yi-Ting Chen & Chung-Ming Kuan, 2002. "Time irreversibility and EGARCH effects in US stock index returns," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 565-578.
    15. Xiaohong Chen & Roger Koenker & Zhijie Xiao, 2009. "Copula-based nonlinear quantile autoregression," Econometrics Journal, Royal Economic Society, vol. 12(s1), pages 50-67, January.
    16. Ibragimov, Rustam, 2009. "Copula-Based Characterizations For Higher Order Markov Processes," Econometric Theory, Cambridge University Press, vol. 25(3), pages 819-846, June.
    17. Chen, Yi-Ting & Chou, Ray Y. & Kuan, Chung-Ming, 2000. "Testing time reversibility without moment restrictions," Journal of Econometrics, Elsevier, vol. 95(1), pages 199-218, March.
    18. Brendan K. Beare, 2010. "Copulas and Temporal Dependence," Econometrica, Econometric Society, vol. 78(1), pages 395-410, January.
    19. Ramsey, James B & Rothman, Philip, 1996. "Time Irreversibility and Business Cycle Asymmetry," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 28(1), pages 1-21, February.
    20. Cason, Timothy N. & Friedman, Daniel & Wagener, Florian, 2005. "The dynamics of price dispersion, or Edgeworth variations," Journal of Economic Dynamics and Control, Elsevier, vol. 29(4), pages 801-822, April.
    21. Rothman, Philip, 1991. "Further evidence on the asymmetric behavior of unemployment rates over the business cycle," Journal of Macroeconomics, Elsevier, vol. 13(2), pages 291-298.
    22. J. T. Chang & D. Pollard, 1997. "Conditioning as disintegration," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 51(3), pages 287-317, November.
    23. Serge Darolles & Jean-Pierre Florens & Christian Gourieroux, 2004. "Kernel-based nonlinear canonical analysis and time reversibility," Post-Print halshs-00678062, HAL.
    24. Matthew Lewis & Michael Noel, 2011. "The Speed of Gasoline Price Response in Markets with and without Edgeworth Cycles," The Review of Economics and Statistics, MIT Press, vol. 93(2), pages 672-682, May.
    25. Mariano Tappata, 2009. "Rockets and feathers: Understanding asymmetric pricing," RAND Journal of Economics, RAND Corporation, vol. 40(4), pages 673-687, December.
    26. McCausland, William J., 2007. "Time reversibility of stationary regular finite-state Markov chains," Journal of Econometrics, Elsevier, vol. 136(1), pages 303-318, January.
    27. Hinich , Melvin J. & Rothman, Philip, 1998. "Frequency-Domain Test Of Time Reversibility," Macroeconomic Dynamics, Cambridge University Press, vol. 2(1), pages 72-88, March.
    28. Sam Peltzman, 2000. "Prices Rise Faster than They Fall," Journal of Political Economy, University of Chicago Press, vol. 108(3), pages 466-502, June.
    29. Maskin, Eric & Tirole, Jean, 1988. "A Theory of Dynamic Oligopoly, II: Price Competition, Kinked Demand Curves, and Edgeworth Cycles," Econometrica, Econometric Society, vol. 56(3), pages 571-599, May.
    30. Chen Yi-Ting, 2003. "Testing Serial Independence against Time Irreversibility," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 7(3), pages 1-30, October.
    31. P. M. Robinson, 1983. "Nonparametric Estimators For Time Series," Journal of Time Series Analysis, Wiley Blackwell, vol. 4(3), pages 185-207, May.
    32. Zhongmin Wang, 2009. "(Mixed) Strategy in Oligopoly Pricing: Evidence from Gasoline Price Cycles Before and Under a Timing Regulation," Journal of Political Economy, University of Chicago Press, vol. 117(6), pages 987-1030, December.
    33. Eckert, Andrew, 2003. "Retail price cycles and the presence of small firms," International Journal of Industrial Organization, Elsevier, vol. 21(2), pages 151-170, February.
    34. Michael D. Noel, 2011. "Edgeworth price cycles," The New Palgrave Dictionary of Economics,, Palgrave Macmillan.
    35. Andrew Eckert, 2002. "Retail price cycles and response asymmetry," Canadian Journal of Economics, Canadian Economics Association, vol. 35(1), pages 52-77, February.
    36. Neftci, Salih N, 1984. "Are Economic Time Series Asymmetric over the Business Cycle?," Journal of Political Economy, University of Chicago Press, vol. 92(2), pages 307-328, April.
    37. Zacharias Psaradakis, 2008. "Assessing Time‐Reversibility Under Minimal Assumptions," Journal of Time Series Analysis, Wiley Blackwell, vol. 29(5), pages 881-905, September.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Bastianin, Andrea & Manera, Matteo, 2021. "A test of symmetry based on L-moments with an application to the business cycles of the G7 economies," Economics Letters, Elsevier, vol. 198(C).
    2. Tommaso Proietti, 2023. "Peaks, gaps, and time‐reversibility of economic time series," Journal of Time Series Analysis, Wiley Blackwell, vol. 44(1), pages 43-68, January.
    3. Yuichi Goto & Tobias Kley & Ria Van Hecke & Stanislav Volgushev & Holger Dette & Marc Hallin, 2021. "The Integrated Copula Spectrum," Working Papers ECARES 2021-29, ULB -- Universite Libre de Bruxelles.
    4. Beare, Brendan K. & Seo, Juwon, 2020. "Randomization Tests Of Copula Symmetry," Econometric Theory, Cambridge University Press, vol. 36(6), pages 1025-1063, December.
    5. Brendan K. Beare & Juwon Seo, 2015. "Vine Copula Specifications for Stationary Multivariate Markov Chains," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(2), pages 228-246, March.
    6. Shibin Zhang, 2023. "A copula spectral test for pairwise time reversibility," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 75(5), pages 705-729, October.
    7. Fang, Jun & Jiang, Fan & Liu, Yong & Yang, Jingping, 2020. "Copula-based Markov process," Insurance: Mathematics and Economics, Elsevier, vol. 91(C), pages 166-187.
    8. Patton, Andrew J., 2012. "A review of copula models for economic time series," Journal of Multivariate Analysis, Elsevier, vol. 110(C), pages 4-18.
    9. Juwon Seo, 2018. "Randomization Tests for Equality in Dependence Structure," Papers 1811.02105, arXiv.org.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Shibin Zhang, 2023. "A copula spectral test for pairwise time reversibility," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 75(5), pages 705-729, October.
    2. Patton, Andrew J., 2012. "A review of copula models for economic time series," Journal of Multivariate Analysis, Elsevier, vol. 110(C), pages 4-18.
    3. Noel, Michael D., 2015. "Do Edgeworth price cycles lead to higher or lower prices?," International Journal of Industrial Organization, Elsevier, vol. 42(C), pages 81-93.
    4. McCausland, William J., 2007. "Time reversibility of stationary regular finite-state Markov chains," Journal of Econometrics, Elsevier, vol. 136(1), pages 303-318, January.
    5. David P. Byrne, Gordon W. Leslie, and Roger Ware, 2015. "How do Consumers Respond to Gasoline Price Cycles?," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1).
    6. Seaton, Jonathan S. & Waterson, Michael, 2013. "Identifying and characterising price leadership in British supermarkets," International Journal of Industrial Organization, Elsevier, vol. 31(5), pages 392-403.
    7. Noel, Michael D., 2012. "Edgeworth Price Cycles and intertemporal price discrimination," Energy Economics, Elsevier, vol. 34(4), pages 942-954.
    8. Noel, Michael D. & Chu, Lanlan, 2015. "Forecasting gasoline prices in the presence of Edgeworth Price Cycles," Energy Economics, Elsevier, vol. 51(C), pages 204-214.
    9. Andreoli-Versbach, Patrick & Franck, Jens-Uwe, 2015. "Endogenous price commitment, sticky and leadership pricing: Evidence from the Italian petrol market," International Journal of Industrial Organization, Elsevier, vol. 40(C), pages 32-48.
    10. Beare, Brendan K., 2012. "Archimedean Copulas And Temporal Dependence," Econometric Theory, Cambridge University Press, vol. 28(6), pages 1165-1185, December.
    11. Paul Zimmerman & John Yun & Christopher Taylor, 2013. "Edgeworth Price Cycles in Gasoline: Evidence from the United States," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 42(3), pages 297-320, May.
    12. Patton, Andrew, 2013. "Copula Methods for Forecasting Multivariate Time Series," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 899-960, Elsevier.
    13. Michael D. Noel, 2019. "Calendar synchronization of gasoline price increases," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 28(2), pages 355-370, April.
    14. Isakower, Sean & Wang, Zhongmin, 2014. "A comparison of regular price cycles in gasoline and liquefied petroleum gas," Energy Economics, Elsevier, vol. 45(C), pages 445-454.
    15. Arezoo Ghazanfari & Armin Razmjoo, 2022. "The Effect of Market Isolation on Competitive Behavior in Retail Petrol Markets," Sustainability, MDPI, vol. 14(13), pages 1-33, July.
    16. Elliott, Robert & Sun, Puyang & Zhu, Tong, 2020. "Shell shocked: The impact of foreign entry on the gasoline retail market in China," Energy Economics, Elsevier, vol. 86(C).
    17. Michael Noel, 2009. "Do retail gasoline prices respond asymmetrically to cost shocks? The influence of Edgeworth Cycles," RAND Journal of Economics, RAND Corporation, vol. 40(3), pages 582-595, September.
    18. Heijnen, Pim & Soetevent, Adriaan R., 2018. "Price competition on graphs," Journal of Economic Behavior & Organization, Elsevier, vol. 146(C), pages 161-179.
    19. Justus Haucap & Ulrich Heimeshoff & Manuel Siekmann, 2017. "Fuel Prices and Station Heterogeneity on Retail Gasoline Markets," The Energy Journal, , vol. 38(6), pages 81-104, November.
    20. Alexander J. McNeil, 2020. "Modelling volatile time series with v-transforms and copulas," Papers 2002.10135, arXiv.org, revised Jan 2021.

    More about this item

    Keywords

    Social and Behavioral Sciences; Markov chains; time irreversible dynamics; economic time series;
    All these keywords.

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:cdl:ucsdec:qt31f8500p. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Lisa Schiff (email available below). General contact details of provider: https://edirc.repec.org/data/deucsus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.