Option pricing applications of the nonparametric kernel estimator

Macksey, Aaron. (2001). Option pricing applications of the nonparametric kernel estimator Honours Thesis, School of Business, The University of Queensland.

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Author Macksey, Aaron.
Thesis Title Option pricing applications of the nonparametric kernel estimator
School, Centre or Institute School of Business
Institution The University of Queensland
Publication date 2001
Thesis type Honours Thesis
Total pages 110
Language eng
Subjects 15 Commerce, Management, Tourism and Services
Formatted abstract
The prices of traded financial assets incorporate a rich information set regarding payoffs and investor risk preferences in equilibrium. Arrow-Debreu prices, or in continuous states, the state price density (SPD) summarise this information. This study applies a nonparametric kernel regression technique that estimates an option pricing function from observed data. Inferred from the estimated pricing function is the nonparametric SPD estimator. From a pricing perspective the SPD is a 'sufficient' statistic. The SPD estimator is applied to the pricing of European 'exotic' options. The existing literature is extended by outlining a method of incorporating the important data features of the nonparametric estimator into a trinomial tree for the purpose of pricing path dependent derivatives. These data features encompass negative skewness in stock price returns and implied volatility 'smiles' from option prices, that are observed in the sample of common stock options. Monte Carlo analysis and a bootstrap statistical test provide evidence of the nonparametric model's robustness and the SPD estimator's deviation from the Black-Scholes lognormal.

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Created: Tue, 09 Nov 2010, 15:57:16 EST by Muhammad Noman Ali on behalf of The University of Queensland Library