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Reports (Research Report) Year : 2004

Functional quantization for pricing derivatives

Gilles Pagès


We investigate in this paper the numerical performances of quadratic functional quantization and their applications to Finance. We emphasize the rôle played by the so-called product quantizers and the Karhunen-Loève expansion of Gaussian processes. Numerical experiments are carried out on two classical pricing problems: Asian options in a Black-Scholes model and vanilla options in a stochastic volatility Heston model. Pricing based on ``crude" functional quantization is very fast and produce accurate deterministic results. When combined with a Romberg $\log$-extrapolation, it always outperforms Monte Carlo simulation for usual accuracy levels.
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Dates and versions

inria-00070611 , version 1 (19-05-2006)


  • HAL Id : inria-00070611 , version 1


Gilles Pagès, Jacques Printems. Functional quantization for pricing derivatives. [Research Report] RR-5392, INRIA. 2004, pp.53. ⟨inria-00070611⟩
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