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Maximum penalized quasi-likelihood estimation of the diffusion function

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  • Jeff Hamrick
  • Yifei Huang
  • Constantinos Kardaras
  • Murad Taqqu

Abstract

We develop a maximum penalized quasi-likelihood estimator for estimating in a non-parametric way the diffusion function of a diffusion process, as an alternative to more traditional kernel-based estimators. After developing a numerical scheme for computing the maximizer of the penalized maximum quasi-likelihood function, we study the asymptotic properties of our estimator by way of simulation. Under the assumption that overnight London Interbank Offered Rates (LIBOR), the USD/EUR, USD/GBP, JPY/USD, and EUR/USD nominal exchange rates, and the 1-month, 3-month Treasury bill yields, and 30-year Treasury bond yields are generated by diffusion processes, we use our numerical scheme to estimate the diffusion function.

Suggested Citation

  • Jeff Hamrick & Yifei Huang & Constantinos Kardaras & Murad Taqqu, 2011. "Maximum penalized quasi-likelihood estimation of the diffusion function," Quantitative Finance, Taylor & Francis Journals, vol. 11(11), pages 1675-1684.
    • Handle: RePEc:taf:quantf:v:11:y:2011:i:11:p:1675-1684
    DOI: 10.1080/14697688.2011.615212
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    Cited by:

    1. Ignatieva, Katja & Platen, Eckhard, 2012. "Estimating the diffusion coefficient function for a diversified world stock index," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 1333-1349.

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