Revealing the implied risk-neutral MGF from options: The wavelet method

Emmanuel Haven, Xiaoquan Liu, Chenghu Ma, Liya Shen

Research output: Journal PublicationArticlepeer-review

13 Citations (Scopus)


Options are believed to contain unique information on the risk-neutral moment generating function (MGF) or the risk-neutral probability density function (PDF) of the underlying asset. This paper applies the wavelet method to approximate the implied risk-neutral MGF from option prices. Monte Carlo simulations are carried out to show how the risk-neutral MGF can be obtained using the wavelet method. With the Black-Scholes model as the benchmark, we offer a novel method to reveal the implied MGF, and to price in-sample options and forecast out-of-sample option prices with the estimated MGF.

Original languageEnglish
Pages (from-to)692-709
Number of pages18
JournalJournal of Economic Dynamics and Control
Issue number3
Publication statusPublished - Mar 2009
Externally publishedYes


  • Laplace transform
  • Option pricing
  • Wavelet analysis

ASJC Scopus subject areas

  • Economics and Econometrics
  • Control and Optimization
  • Applied Mathematics


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