Learning short-option valuation in the presence of rare events

Details Learning short-option valuation in the presence of rare events Learning short-option valuation in the presence of rare events

2000-01-18

arxiv.org/abs/cond-mat/0001253v1

International Journal of Theoretical and Applied Finance 3, 563-564 (2000)

Physics

Condensed Matter

Statistical Mechanics

details and related works in http://www.econophysics.org

Scientific paper

10.1142/S0219024900000590

We present a neural-network valuation of financial derivatives in the case of fat-tailed underlying asset returns. A two-layer perceptron is trained on simulated prices taking into account the well-known effect of volatility smile. The prices of the underlier are generated using fractional calculus algorithms, and option prices are computed by means of the Bouchaud-Potters formula. This learning scheme is tested on market data; the results show a very good agreement between perceptron option prices and real market ones.

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