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Pricing American options: RNMs-constrained entropic least-squares approach

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  • Yu, Xisheng
  • Xie, Xiaoke

Abstract

Recently the entropy-based valuation of European options (Stutzer, 1996) has been extended to American option pricing. In this paper, we improve the pricing accuracy by incorporating informative risk-neutral moments (RNMs), which are recovered from a set of market-available option data, as constraints into the entropy framework. With these RNMs, an appropriate risk-neutral measure close enough to the correct one is achieved. An adjusted least-squares algorithm is then utilized to determine the optimal exercising strategy. The results based on simulations and empirical analysis demonstrate that our method can price American options rather accurately and significantly outperforms the benchmark methods.

Suggested Citation

  • Yu, Xisheng & Xie, Xiaoke, 2015. "Pricing American options: RNMs-constrained entropic least-squares approach," The North American Journal of Economics and Finance, Elsevier, vol. 31(C), pages 155-173.
    • Handle: RePEc:eee:ecofin:v:31:y:2015:i:c:p:155-173
    DOI: 10.1016/j.najef.2014.10.009
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    Cited by:

    1. Yu, Xisheng, 2021. "A unified entropic pricing framework of option: Using Cressie-Read family of divergences," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    2. Chan, Tat Lung (Ron), 2020. "Hedging and pricing early-exercise options with complex fourier series expansion," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).

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    More about this item

    Keywords

    Risk-neutral moments; Maximum entropy; Least-squares; American option valuation;
    All these keywords.

    JEL classification:

    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing

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