Abstract
The paper outlines the use of an alternative option pricing scheme to perform statistical arbitrage in derivative markets. The method links a binomial tree to an innovative stochastic volatility model that is based on wavelets and artificial neural networks. Wavelets provide a convenient signal/noise decomposition of volatility in a non-linear feature space. Neural networks are used to infer future volatility levels from the wavelets feature space in an iterative manner. The bootstrap method provides 95% confidence intervals for the option prices. When used to set up delta-hedged arbitrage trades in the US equity options market, the proposed approach generates substantial profits.
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