Statistical analysis of correlated fossil fuel securities
Thesis (S.B.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2011.
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| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2012
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| Online Access: | http://hdl.handle.net/1721.1/69516 |
| _version_ | 1811086344544321536 |
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| author | Li, Derek Z |
| author2 | Paul D. Sclavounos. |
| author_facet | Paul D. Sclavounos. Li, Derek Z |
| author_sort | Li, Derek Z |
| collection | MIT |
| description | Thesis (S.B.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2011. |
| first_indexed | 2024-09-23T13:24:38Z |
| format | Thesis |
| id | mit-1721.1/69516 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T13:24:38Z |
| publishDate | 2012 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/695162019-04-12T10:24:30Z Statistical analysis of correlated fossil fuel securities Li, Derek Z Paul D. Sclavounos. Massachusetts Institute of Technology. Dept. of Mechanical Engineering. Massachusetts Institute of Technology. Dept. of Mechanical Engineering. Mechanical Engineering. Thesis (S.B.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2011. Cataloged from PDF version of thesis. Includes bibliographical references (p. 36). Forecasting the future prices or returns of a security is extraordinarily difficult if not impossible. However, statistical analysis of a basket of highly correlated securities offering a cross-sectional representation of a particular sector can yield information that is potentially tradable. Securities related to the fossil fuels industry are used as the basis of a practical application to two distinct forecasting techniques. The first method, forecasting using conditional multivariate Gaussian statistics, was shown to yield, in a relative sense, the best results for those securities which exhibited a high correlation with the rest of the basket. For the second method, principal component analysis was done on a basket of commodity futures to reveal a small number of dominant factors governing the movements of the portfolio. Autoregressive models were then applied to both the factors and futures, but results showed both to be essentially Markov processes. by Derek Z. Li. S.B. 2012-02-29T18:22:55Z 2012-02-29T18:22:55Z 2011 2011 Thesis http://hdl.handle.net/1721.1/69516 775781166 eng M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 36 p. application/pdf Massachusetts Institute of Technology |
| spellingShingle | Mechanical Engineering. Li, Derek Z Statistical analysis of correlated fossil fuel securities |
| title | Statistical analysis of correlated fossil fuel securities |
| title_full | Statistical analysis of correlated fossil fuel securities |
| title_fullStr | Statistical analysis of correlated fossil fuel securities |
| title_full_unstemmed | Statistical analysis of correlated fossil fuel securities |
| title_short | Statistical analysis of correlated fossil fuel securities |
| title_sort | statistical analysis of correlated fossil fuel securities |
| topic | Mechanical Engineering. |
| url | http://hdl.handle.net/1721.1/69516 |
| work_keys_str_mv | AT liderekz statisticalanalysisofcorrelatedfossilfuelsecurities |