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Identifying Statistical Arbitrage in Interest Rate Markets: A Genetic Algorithm Approach


  • J. C. Arismendi-Zambrano

    (Department of Economics, Finance and Accounting, Maynooth University, Ireland & ICMA Centre, Henley Business School, University of Reading, Whiteknights, Reading, United Kingdom.)

  • T. Ramos-Almeida

    () (Federal University of Bahia, UFBA, Salvador, Brazil.)

  • J. C. Reboredo

    () (Department of Economics, University of Santiago de Compostela, Santiago de Compostela, Spain.)

  • M. A. Rivera-Castro

    () (University of Salvador (UNIFACS), Salvador, Brazil. Department of Applied Social Sciences, State University of Feira de Santana, Feira de Santana, Brazil.)


In this paper a multidimensional term structure model is used to find statistical arbitrage opportunities in the interest rates derivatives market. The implied volatility of the model is calibrated by using a genetic algorithm optimization method. Two different options over the same underlying interest rate asset are tested, using data from a weak efficient economy market - Brazilian derivatives market. The results show that there is no systematic mispricing between these two options, but temporary arbitrage opportunities perceptible to the average informed trader are possible.

Suggested Citation

  • J. C. Arismendi-Zambrano & T. Ramos-Almeida & J. C. Reboredo & M. A. Rivera-Castro, 2020. "Identifying Statistical Arbitrage in Interest Rate Markets: A Genetic Algorithm Approach," Economics, Finance and Accounting Department Working Paper Series n305-20.pdf, Department of Economics, Finance and Accounting, National University of Ireland - Maynooth.
  • Handle: RePEc:may:mayecw:n305-20.pdf

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    References listed on IDEAS

    1. Al-Khazali, Osamah & Mirzaei, Ali, 2017. "Stock market anomalies, market efficiency and the adaptive market hypothesis: Evidence from Islamic stock indices," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 51(C), pages 190-208.
    2. Bueno-Guerrero, Alberto & Moreno, Manuel & Navas, Javier F., 2016. "The stochastic string model as a unifying theory of the term structure of interest rates," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 461(C), pages 217-237.
    3. Backus, David & Foresi, Silverio & Zin, Stanley, 1998. "Arbitrage Opportunities in Arbitrage-Free Models of Bond Pricing," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(1), pages 13-26, January.
    4. Ansotegui, Carmen & Bassiouny, Aliaa & Tooma, Eskandar, 2013. "The proof is in the pudding: Arbitrage is possible in limited emerging markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 23(C), pages 342-357.
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    9. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
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    11. Black, Fischer, 1976. "The pricing of commodity contracts," Journal of Financial Economics, Elsevier, vol. 3(1-2), pages 167-179.
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    More about this item


    Interest Rates Derivatives; Financial Economics; Arbitrage; Swaption-Cap Puzzle;

    JEL classification:

    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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