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A stochastic dynamic programming approach for pricing options on stock-index futures

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Show simple item record Kirillov, Tymur 2012-03-21T18:03:38Z 2012-03-21T18:03:38Z 2012-03-21
dc.description.abstract The aim of this thesis is to price options on equity index futures with an application to standard options on S&P 500 futures traded on the Chicago Mercantile Exchange. Our methodology is based on stochastic dynamic programming, which can accommodate European as well as American options. The model accommodates dividends from the underlying asset. It also captures the optimal exercise strategy and the fair value of the option. This approach is an alternative to available numerical pricing methods such as binomial trees, finite differences, and ad-hoc numerical approximation techniques. Our numerical and empirical investigations demonstrate convergence, robustness, and efficiency. We use this methodology to value exchange-listed options. The European option premiums thus obtained are compared to Black's closed-form formula. They are accurate to four digits. The American option premiums also have a similar level of accuracy compared to premiums obtained using finite differences and binomial trees with a large number of time steps. The proposed model accounts for deterministic, seasonally varying dividend yield. In pricing futures options, we discover that what matters is the sum of the dividend yields over the life of the futures contract and not their distribution. en_US
dc.subject Stocks en_US
dc.subject Stocks -- Rate of return en_US
dc.subject Commodity exchanges -- Illinois -- Chicago en_US
dc.subject Stochastic programming en_US
dc.title A stochastic dynamic programming approach for pricing options on stock-index futures en_US M.Sc. Management en_US Masters en_US
dc.contributor.department Faculty of Business Programs en_US Faculty of Business en_US

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