The ImpliedBinomialTree(, r, d, v, G) command constructs an implied binomial tree based on the given and implied volatility term structure. This is an implementation of an algorithm proposed by E. Derman and I. Kani (1994) in which the state space of the implied binomial tree is decided by any method for building constant volatility binomial trees (we use the CRR binomial tree). Once we have already fixed the state space of the implied binomial tree, we use induction to infer the transition probabilities and local volatilities.

The ImpliedBinomialTree(, r, d, v, T, N) calling sequence is similar except that in this case a uniform time grid with time step  is used.

The ImpliedBinomialTree(, r, d, v, p, c, G) and ImpliedBinomialTree(, r, d, v, p, c, T, N) calling sequences construct an implied binomial tree given two pricing functions: p, which, given a strike price and time to maturity, computes the price of a European put option for the underlying asset; and c, which computes the price of a European call option.

The Finance[ImpliedBinomialTree] command was introduced in Maple 15.

For more information on Maple 15 changes, see Updates in Maple 15.

Cizek, P., and Komorad, K., Implied Trinomial Trees, SFB 649 Economic Risk, Berlin, 2005-07.

Derman, E., and Kani, I., The Volatility Smile and Its Implied Tree, Goldman Sachs Quantitative Strategies Research Notes, January 1994.

Derman, E., Kani, I., Chriss, N., Implied Trinomial Trees of the Volatility Smile, Goldman Sachs Quantitative Strategies Research Notes, February 1996.

Glasserman, P., Monte Carlo Methods in Financial Engineering, New York: Springer-Verlag, 2004.

Hull, J., Options, Futures, and Other Derivatives, 5th. edition. Upper Saddle River, New Jersey: Prentice Hall, 2003.

Jackwerth, J.C., Option-Implied Risk-Neutral Distributions and Implied Binomial Trees: A Literature Review, 1999.

Rubinstein, M., Implied binomial trees, J. Finance, 49 ,1994, pp. 771--818.