An information-theoretic approach to estimating risk premia
Thesis: S.M. in Management Research, Massachusetts Institute of Technology, Sloan School of Management, 2018.
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| Other Authors: | |
| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2018
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| Online Access: | http://hdl.handle.net/1721.1/118003 |
| _version_ | 1811093701422743552 |
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| author | Kazemi, Maziar Mahdavi |
| author2 | Hui Chen. |
| author_facet | Hui Chen. Kazemi, Maziar Mahdavi |
| author_sort | Kazemi, Maziar Mahdavi |
| collection | MIT |
| description | Thesis: S.M. in Management Research, Massachusetts Institute of Technology, Sloan School of Management, 2018. |
| first_indexed | 2024-09-23T15:49:16Z |
| format | Thesis |
| id | mit-1721.1/118003 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T15:49:16Z |
| publishDate | 2018 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/1180032023-07-13T12:52:27Z An information-theoretic approach to estimating risk premia Kazemi, Maziar Mahdavi Hui Chen. Sloan School of Management. Sloan School of Management Sloan School of Management. Thesis: S.M. in Management Research, Massachusetts Institute of Technology, Sloan School of Management, 2018. Cataloged from PDF version of thesis. Includes bibliographical references (pages 31-35). Evaluation of linear factor models in asset pricing requires estimation of two unknown quantities: the factor loadings and the factor risk premia. Using relative entropy minimization, this paper estimates factor risk premia with only no-arbitrage economic assumptions and without needing to estimate the factor loadings. The method proposed here is particularly useful when the factor model suffers from omitted variable bias, rendering classic Fama-MacBeth/GMM estimation infeasible. Asymptotics are derived and simulation exercises show that the accuracy of the method is comparable to, and frequently is higher than, leading techniques, even those designed explicitly to deal with omitted variables. Empirically, we find estimates of risk premia that are closer to those expected by financial economic theory, relative to estimates from classical estimation techniques. For example, we find that the risk premia on size, book-to-market, and momentum sorted portfolios are very close to the observed average excess returns of these portfolios. An exciting application of our methodology is to performance evaluation for active fund managers. We show that we are able to estimate a manager's "alpha" without specifying the manager's factor exposures. by Maziar M. Kazemi. S.M. in Management Research 2018-09-17T15:53:24Z 2018-09-17T15:53:24Z 2018 2018 Thesis http://hdl.handle.net/1721.1/118003 1051300223 eng MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission. http://dspace.mit.edu/handle/1721.1/7582 40 pages application/pdf Massachusetts Institute of Technology |
| spellingShingle | Sloan School of Management. Kazemi, Maziar Mahdavi An information-theoretic approach to estimating risk premia |
| title | An information-theoretic approach to estimating risk premia |
| title_full | An information-theoretic approach to estimating risk premia |
| title_fullStr | An information-theoretic approach to estimating risk premia |
| title_full_unstemmed | An information-theoretic approach to estimating risk premia |
| title_short | An information-theoretic approach to estimating risk premia |
| title_sort | information theoretic approach to estimating risk premia |
| topic | Sloan School of Management. |
| url | http://hdl.handle.net/1721.1/118003 |
| work_keys_str_mv | AT kazemimaziarmahdavi aninformationtheoreticapproachtoestimatingriskpremia AT kazemimaziarmahdavi informationtheoreticapproachtoestimatingriskpremia |