The Journal of Computational Finance · 1997 · 201 citations · 0 references
BusinessFinanceMathematicsDiscrete MathematicsDynamical SystemsFinancial EconomicsFinite Difference MethodsNumerical Methods In FinanceOption PricingOption Pricing ModelsStock OptionsVolatility ModelingBinomial Tree PricingConvergenceFinite Difference SchemesForward InductionImplied Volatility SmileOption Pricing AlgorithmsSpace PartitioningVolatility Smile Modeling
ABSTRACT This paper illustrates how to construct an unconditionally stable finite-difference lattice consistent with the equity option volatility smile. In particular, the paper shows how to extend the method of forward induction on Arrow-Debreu securities to generate local instantaneous volatilities in implicit and semi-implicit (Crank-Nicholson) lattices. The technique developed in the paper provides a highly accurate fit to the entire volatility smile and offers excellent convergence properties and high flexibility of asset- and time-space partitioning. Contrary to standard algorithms based on binomial trees, our approach is well suited to price options with discontinuous payouts (e.g. knock-out and barrier options) and does not suffer from problems arising from negative branching probabilities.