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

J. C. Arismendi-Zambrano, T. Ramos-Almeida (), Juan Reboredo () and M. A. Rivera-Castro ()
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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.
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.

Authors registered in the RePEc Author Service: Juan Carlos Arismendi Zambrano ()

Economics Department Working Paper Series from Department of Economics, National University of Ireland - Maynooth

Abstract: 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.

Keywords: Interest Rates Derivatives; Financial Economics; Arbitrage; Swaption-Cap Puzzle (search for similar items in EconPapers)
JEL-codes: G13 C51 C52 C63 (search for similar items in EconPapers)
Pages: 40 pages
Date: 2020
New Economics Papers: this item is included in nep-ore
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