First Advisor

Richard Tymerski

Term of Graduation

Fall 2020

Date of Publication


Document Type


Degree Name

Master of Science (M.S.) in Computer Science


Computer Science




Mathematical optimization, Options (Finance)



Physical Description

1 online resource (vi, 71 pages)


Obtaining an edge in financial markets has been the objective of many hedge funds, investors, and market participants. Even with today's abundance of data and computing power, few individuals achieve a consistent edge over an extended time. To obtain this edge, investors usually use options strategies. The Broken Wing Butterfly (BWB) is an options strategy that has increased in popularity among traders. Profit is generated primarily by exploiting option value time decay. In this thesis, the selection of entry and exit BWB parameters, such as profit and loss targets, are optimized for an in-sample period. Afterward, they are used to assess profitability during an out-of-sample period. The optimization takes place for over a decade of historical options data of the S&P exchange-traded fund (symbol: SPY). The importance of selecting an optimal strike mapping method is emphasized. Of the three mapping methods considered, the normalized strike mapping method was found to be superior. The optimization of the parameters was performed with a differential evolution (DE) evolutionary algorithm. The objective function to optimize took into consideration the strategy's cumulative profits and maximum equity drawdown. The out-of-sample trades' performance shows that information from past trades can be used to trade in the future successfully.


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Persistent Identifier

Available for download on Monday, January 31, 2022