Higher order asymptotic option valuation for non-Gaussian dependent returns

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    7 Citations (Scopus)

    Abstract

    This paper discusses the option pricing problems using statistical series expansion for the price process of an underlying asset. We derive the Edgeworth expansion for the stock log return via extracting dynamics structure of time series. Using this result, we investigate influences of the non-Gaussianity and the dependency of log return processes for option pricing. Numerical studies show some interesting features of them.

    Original languageEnglish
    Pages (from-to)1043-1058
    Number of pages16
    JournalJournal of Statistical Planning and Inference
    Volume137
    Issue number3
    DOIs
    Publication statusPublished - 2007 Mar 1

    Fingerprint

    Option Valuation
    Higher-order Asymptotics
    Option Pricing
    Edgeworth Expansion
    Dependent
    Series Expansion
    Costs
    Time series
    Numerical Study
    Option pricing
    Option valuation
    Influence
    Edgeworth expansion
    Assets

    Keywords

    • Black and Scholes model
    • Edgeworth expansion
    • Non-Gaussian stationary process
    • Option pricing

    ASJC Scopus subject areas

    • Statistics, Probability and Uncertainty
    • Applied Mathematics
    • Statistics and Probability

    Cite this

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    abstract = "This paper discusses the option pricing problems using statistical series expansion for the price process of an underlying asset. We derive the Edgeworth expansion for the stock log return via extracting dynamics structure of time series. Using this result, we investigate influences of the non-Gaussianity and the dependency of log return processes for option pricing. Numerical studies show some interesting features of them.",
    keywords = "Black and Scholes model, Edgeworth expansion, Non-Gaussian stationary process, Option pricing",
    author = "Kenichiro Tamaki and Masanobu Taniguchi",
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    AU - Taniguchi, Masanobu

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    KW - Non-Gaussian stationary process

    KW - Option pricing

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