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    Extending and simulating the quantum binomial options pricing model

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    THESIS.pdf (2.293Mb)
    Date
    2009-04-23
    Author
    Meyer, Keith
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    Abstract
    Pricing options quickly and accurately is a well known problem in finance. Quantum computing is being researched with the hope that quantum computers will be able to price options more efficiently than classical computers. This research extends the quantum binomial option pricing model proposed by Zeqian Chen to European put options and to Barrier options and develops a quantum algorithm to price them. This research produced three key results. First, when Maxwell-Boltzmann statistics are assumed, the quantum binomial model option prices are equivalent to the classical binomial model. Second, options can be priced efficiently on a quantum computer after the circuit has been built. The time complexity is O((N − τ)log(N − τ)) and it is in the BQP quantum computational complexity class. Finally, challenges extending the quantum binomial model to American, Asian and Bermudan options exist as the quantum binomial model does not take early exercise into account.
    URI
    http://hdl.handle.net/1993/3154
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    • FGS - Electronic Theses and Practica [25494]

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