Extending and simulating the quantum binomial options pricing model
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Date
2009-04-23T13:27:17Z
Authors
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.
Description
http://orcid.org/0000-0002-1641-5388
Keywords
Quantum, Options, Binomial, No-arbitrage, Risk-neutral, Computing, Stock, Black-Scholes, Cox-Ross-Rubinstein, Pricing, Model, European, American, Bermudan, Barrier, Volatility