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The Impact Of The Exchange Rate In Option Pricing In Brazil €“ A Comparative Analysis Between A Neural Network Model And The Black & Scholes Model

Author

Listed:
  • Carlos Alberto Aragón de Planas

    (Bovespa)

  • Léo da Rocha Ferreira

    (Universidade Estadual do Rio de Janeiro (Uerj))

  • Gerson Lachtermacher

    (Universidade Estadual do Rio de Janeiro (Uerj))

Abstract

The main goal of this paper is to evaluate the impact of the exchange rate volatility in price prediction of derivative securities in the Brazilian capital markets using an artificial neural network technique, given the Black & Scho­les Model limitations. For this purpose a multiplayer, feedforward neural ne­twork, trained by the backpropagation algorithm model, to perform the pre­diction of the Telemar option prices was developed. The model results show that price estimates are close to the real values, mainly when appended to the exchange rate, confirming that the performance of neural network is superior to other results. The inclusion of the exchange rate in neural networks techni­que results in a better price forecasting for the options, because the volatility in the price of the underlying asset is caused by temporary arbitrage of quotes among the national and foreign stock markets where the company is listed.

Suggested Citation

  • Carlos Alberto Aragón de Planas & Léo da Rocha Ferreira & Gerson Lachtermacher, 2009. "The Impact Of The Exchange Rate In Option Pricing In Brazil €“ A Comparative Analysis Between A Neural Network Model And The Black & Scholes Model," Revista de Economia Mackenzie (REM), Mackenzie Presbyterian University, Social and Applied Sciences Center, vol. 7(2), pages 138-181, may-augus.
    • Handle: RePEc:aft:journl:v:7:2:2009:may:aug:p:138-181
    DOI: -
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