Lattice-based pricing of S&P/ASX 200 index options under a GARCH framework

McPhee, Alana. (2004). Lattice-based pricing of S&P/ASX 200 index options under a GARCH framework Honours Thesis, School of Business, The University of Queensland.

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Author McPhee, Alana.
Thesis Title Lattice-based pricing of S&P/ASX 200 index options under a GARCH framework
School, Centre or Institute School of Business
Institution The University of Queensland
Publication date 2004
Thesis type Honours Thesis
Total pages 99
Language eng
Subjects 15 Commerce, Management, Tourism and Services
Formatted abstract
GARCH models of financial time series are popular because they are flexible and able to explain volatility clustering and the skewness and kurtosis of asset price returns. Pricing options when the underlying asset follows a GARCH process is challenging. Monte Carlo methods are slow, and lattice methods tend to explode due to the path-dependency of the volatility process. Ritchken & Trevor (RT) (1999) have proposed an efficient lattice that can price American and European style options, for a number of different underlying GARCH specifications. This thesis explores the RT algorithm by examining its convergence properties and speed of estimation, showing a clear relationship between the computation time and accuracy of the model. It demonstrates that computation time is an issue for longer-dated options (of 60 days or greater). Its out-of-sample pricing ability is examined using the S&P/ASX 200 index between 1999 and 2002. The RT algorithm is demonstrated to have a lower bias and MAE for in-the-money options, however it struggles for short maturity out-of-the-money options. Relative to the BS model, the RT algorithm has a lower MAE for call options, however the BS model dominates the RT algorithm for put options. Increasing the number of computations in the lattice is found to improve overall performance, however computational constraints limit the ability for accurate prices to be found in a reasonable time.

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Created: Fri, 19 Nov 2010, 13:01:11 EST by Muhammad Noman Ali on behalf of The University of Queensland Library