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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Ucar, I. Ozbayoglu, A.M. Ucar, M. |
| Copyright Year | 2015 |
| Description | Author affiliation: TOBB Univ. of Econ. & Technol., Ankara, Turkey (Ucar, I.; Ozbayoglu, A.M.; Ucar, M.) |
| Abstract | In this study, a two level options trading strategy is modelled and optimized with Genetic Algorithms and Particle Swarm Optimization for profit maximization. In the first level, the trend is found and in the second level, options trading strategies for the particular trend are determined. The strike prices and expiration dates of the traded options are optimized and tested on 5 different Exchange Traded Funds (ETFs) (DIA, IWM, SPY, XLE, XLF). The performance of the proposed model is compared with Buy and Hold and commonly used technical analysis indicators and the results indicate using optimized options increased the overall profit with less drawdown risk. |
| Starting Page | 2526 |
| Ending Page | 2531 |
| File Size | 417250 |
| Page Count | 6 |
| File Format | |
| e-ISBN | 9781479974924 |
| DOI | 10.1109/CEC.2015.7257199 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2015-05-25 |
| Publisher Place | Japan |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Market research Genetic algorithms Biological cells Particle swarm optimization Portfolios Optimization Training |
| Content Type | Text |
| Resource Type | Article |
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