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Bayesian Arbitrage Threshold Analysis

Author

Listed:
  • Forbes, C.S.
  • Kalb, G.R.J.
  • Kofman, P.
Abstract
A Bayesian estimation procedure is developed for estimating multiple regime vector autoregressive models appropriate for deviations from financial arbitrage relationships. This approach has clear advantages over classical stepwise threshold autoregressive analysis.

Suggested Citation

  • Forbes, C.S. & Kalb, G.R.J. & Kofman, P., 1997. "Bayesian Arbitrage Threshold Analysis," Monash Econometrics and Business Statistics Working Papers 3/97, Monash University, Department of Econometrics and Business Statistics.
    • Handle: RePEc:msh:ebswps:1997-3
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    Citations

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    Cited by:

    1. Ters, Kristyna & Urban, Jörg, 2020. "Estimating unknown arbitrage costs: Evidence from a 3-regime threshold vector error correction model," Journal of Financial Markets, Elsevier, vol. 47(C).
    2. 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.
    3. 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.
    4. Emmanouil Mavrakis & Christos Alexakis, 2018. "Statistical Arbitrage Strategies under Different Market Conditions: The Case of the Greek Banking Sector," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 17(2), pages 159-185, August.
    5. 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.
    6. 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.
    7. Martin Bruns & Michele Piffer, 2021. "Monetary policy shocks over the business cycle: Extending the Smooth Transition framework," University of East Anglia School of Economics Working Paper Series 2021-07, School of Economics, University of East Anglia, Norwich, UK..
    8. Liu, Xialu & Chen, Rong, 2020. "Threshold factor models for high-dimensional time series," Journal of Econometrics, Elsevier, vol. 216(1), pages 53-70.
    9. Huber, Florian & Zörner, Thomas O., 2019. "Threshold cointegration in international exchange rates:A Bayesian approach," International Journal of Forecasting, Elsevier, vol. 35(2), pages 458-473.
    10. Nicholas Taylor, 2007. "A New Econometric Model of Index Arbitrage," European Financial Management, European Financial Management Association, vol. 13(1), pages 159-183, January.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. Shively, Philip A., 2003. "The nonlinear dynamics of stock prices," The Quarterly Review of Economics and Finance, Elsevier, vol. 43(3), pages 505-517.
    17. 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.
    18. Byeongseon Seo, 2004. "Testing for Nonlinear Adjustment in Smooth Transition Vector Error Correction Models," Econometric Society 2004 Far Eastern Meetings 749, Econometric Society.
    19. 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.

    More about this item

    Keywords

    STATISTICS ; PRICING ; FINANCIAL MARKET;
    All these keywords.

    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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