An adaptive averaging binomial method for option valuation

We introduce efficient accurate binomial methods for option pricing. The standard binomial approximation converges to continuous Black-Scholes values with the saw-tooth pattern in the error as the number of time steps increases. When we introduce local averages of payoffs at expiry, the saw-tooth pattern in the error has been reduced and the approximation becomes reliable. Furthermore, we employ adaptive meshes around non-smooth regions for efficiency. Numerical experiments illustrate that the proposed method gives more accurate values with less computational work compared to other methods.