Most viewed recipes tagged "laplace" and "computational_finance" but not "numerical"http://code.activestate.com/recipes/tags/laplace-numerical+computational_finance/views/2009-11-13T01:28:24-08:00ActiveState Code RecipesPricing Asian options using mpmath (Python)
2009-11-13T01:28:24-08:00Fernando Nieuwveldthttp://code.activestate.com/recipes/users/4172088/http://code.activestate.com/recipes/576954-pricing-asian-options-using-mpmath/
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Python
recipe 576954
by <a href="/recipes/users/4172088/">Fernando Nieuwveldt</a>
(<a href="/recipes/tags/computational_finance/">computational_finance</a>, <a href="/recipes/tags/laplace/">laplace</a>, <a href="/recipes/tags/mpmath/">mpmath</a>).
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<p>I present a numerical method for pricing Asian options. The method is based on the numerical inversion of the Laplace transform. The inversion method that is used is based on Talbot contours. It is known that Geman and Yor's formula is computational expensive for low volatility cases. By using Talbots method we can reduce the timing for the low volatility cases, at least to \sigma ~ 0.05. Afterwards the method start to converge slowly. In the literature for \sigma = 0.1 the Geman and Yor formula converges slowly.</p>