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Bayesian Arbitrage Threshold Analysis

Author

Listed:
  • Forbes, Catherine S
  • Kalb, Guyonne R J
  • Kofman, Paul

Abstract

A Bayesian estimation procedure is developed for estimating multiple-regime (multiple-threshold) error-correction models appropriate for deviations from financial arbitrage relationships. This approach has clear advantages over classical stepwise threshold autoregressive analysis. Unlike many other applications of threshold models, the knowledge of some costs involved in setting up arbitrage positions allows the authors to specify an informative prior. To illustrate the Bayesian procedure, they estimate a no-arbitrage band within which index futures arbitrage is not profitable despite (persistent) deviations from parity.

Suggested Citation

  • Forbes, Catherine S & Kalb, Guyonne R J & Kofman, Paul, 1999. "Bayesian Arbitrage Threshold Analysis," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(3), pages 364-372, July.
  • Handle: RePEc:bes:jnlbes:v:17:y:1999:i:3:p:364-72
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    Cited by:

    1. Kristyna Ters & Jörg Urban, 2018. "Estimating unknown arbitrage costs: evidence from a three-regime threshold vector error correction model," BIS Working Papers 689, Bank for International Settlements.
    2. Greb, Friederike & Krivobokova, Tatyana & von Cramon-Taubadel, Stephan & Munk, Axel, 2011. "On threshold estimation in threshold vector error correction models," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 114599, European Association of Agricultural Economists.
    3. 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.
    4. Robles-Fernandez M. Dolores & Nieto Luisa & Fernandez M. Angeles, 2004. "Nonlinear Intraday Dynamics in Eurostoxx50 Index Markets," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 8(4), pages 1-28, December.
    5. Lee, Jaeram & Kang, Jangkoo & Ryu, Doojin, 2015. "Common deviation and regime-dependent dynamics in the index derivatives markets," Pacific-Basin Finance Journal, Elsevier, vol. 33(C), pages 1-22.
    6. Bajo-Rubio, Oscar & Diaz-Roldan, Carmen & Esteve, Vicente, 2006. "Is the budget deficit sustainable when fiscal policy is non-linear? The case of Spain," Journal of Macroeconomics, Elsevier, vol. 28(3), pages 596-608, September.
    7. Byeongseon Seo, 2004. "Testing for Nonlinear Adjustment in Smooth Transition Vector Error Correction Models," Econometric Society 2004 Far Eastern Meetings 749, Econometric Society.
    8. Alexakis, Christos, 2010. "Long-run relations among equity indices under different market conditions: Implications on the implementation of statistical arbitrage strategies," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 20(4), pages 389-403, October.
    9. Goldman Elena & Nam Jouahn & Tsurumi Hiroki & Wang Jun, 2013. "Regimes and long memory in realized volatility," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(5), pages 521-549, December.
    10. 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.
    11. Jaeram Lee & Doojin Ryu, 2016. "Asymmetric Mispricing and Regime-dependent Dynamics in Futures and Options Markets," Asian Economic Journal, East Asian Economic Association, vol. 30(1), pages 47-65, March.
    12. Hu, Jin-Li & Lin, Cheng-Hsun, 2008. "Disaggregated energy consumption and GDP in Taiwan: A threshold co-integration analysis," Energy Economics, Elsevier, vol. 30(5), pages 2342-2358, September.
    13. Shively, Philip A., 2003. "The nonlinear dynamics of stock prices," The Quarterly Review of Economics and Finance, Elsevier, vol. 43(3), pages 505-517.

    More about this item

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing

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