Thesis (Ph.D.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2000. / Includes bibliographical references (leaves 95-102). / Survivorship bias influences statistical inference in Finance. Through a series of Monte Carlo simulations in the style of Brown, Goetzmann, Ibbotson, and Ross {1992), we study the sampling distribution of the mean return, standard deviation, beta, Fama & MacBeth {1973) t-statistic, and Jegadeesh & Titman (1993) momentum strategy return in progressively truncated datasets. Survivor-biased datasets have higher mean returns, lower return standard deviations and lower betas than the full sample. Beta has no explanatory power even when the CAPM is true, a finding virtually unaffected by survivorship bias. Returns to a momentum strategy are positive even when stock idiosyncratic returns are serially and cross-sectionally uncorrelated, but survivorship bias overestimates the returns and underestimates the beta of the strategy. / by Jonathan David Taylor. / Ph.D.
| Identifer | oai:union.ndltd.org:MIT/oai:dspace.mit.edu:1721.1/9043 |
| Date | January 2000 |
| Creators | Taylor, Jonathan David, 1969- |
| Contributors | Andrew W. Lo., Massachusetts Institute of Technology. Operations Research Center., Massachusetts Institute of Technology. Operations Research Center. |
| Publisher | Massachusetts Institute of Technology |
| Source Sets | M.I.T. Theses and Dissertation |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | 102 leaves, 8194842 bytes, 8194602 bytes, application/pdf, application/pdf, application/pdf |
| Rights | 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 |
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