An efficient and accurate lattice for pricing derivatives under a jump-diffusion process

Tian-Shyr Dai*, Chuan Ju Wang, Yuh Dauh Lyuu, Yen Chun Liu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

7 Scopus citations


Derivatives are popular financial instruments whose values depend on other more fundamental financial assets (called the underlying assets). As they play essential roles in financial markets, evaluating them efficiently and accurately is critical. Most derivatives have no simple valuation formulas; as a result, they must be priced by numerical methods such as lattice methods. In a lattice, the prices of the derivatives converge to theoretical values when the number of time steps increases. Unfortunately, the nonlinearity error introduced by the nonlinearity of the option value function may cause the pricing results to converge slowly or even oscillate significantly. The lognormal diffusion process, which has been widely used to model the underlying asset's price dynamics, does not capture the empirical findings satisfactorily. Therefore, many alternative processes have been proposed, and a very popular one is the jump-diffusion process. This paper proposes an accurate and efficient lattice for the jump-diffusion process. Our lattice is accurate because its structure can suit the derivatives' specifications so that the pricing results converge smoothly. To our knowledge, no other lattices for the jump-diffusion process have successfully solved the oscillation problem. In addition, the time complexity of our lattice is lower than those of existing lattice methods by at least half an order. Numerous numerical calculations confirm the superior performance of our lattice to existing methods in terms of accuracy, speed, and generality.

Original languageEnglish
Pages (from-to)3174-3189
Number of pages16
JournalApplied Mathematics and Computation
Issue number7
StatePublished - 1 Dec 2010


  • Complexity
  • Jump-diffusion process
  • Lattice construction
  • Numerical method
  • Option pricing


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