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dc.contributor.advisorAndrew W. Lo.en_US
dc.contributor.authorKaminski, Kathryn Margareten_US
dc.contributor.otherMassachusetts Institute of Technology. Operations Research Center.en_US
dc.date.accessioned2008-02-27T22:18:19Z
dc.date.available2008-02-27T22:18:19Z
dc.date.copyright2007en_US
dc.date.issued2007en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/40384
dc.descriptionThesis (Ph. D.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2007.en_US
dc.descriptionIncludes bibliographical references (p. 139-150).en_US
dc.description.abstractInvestors commonly use stopping rules to help them get in and out of their investment positions. Despite their widespread use and support from behavioral finance, there has been little discussion of their impact on portfolio performance in classic portfolio choice theory. In this thesis, I remedy this situation by discussing the performance impact of stopping rules, highlighting the stop-loss rule. Stop-loss rules-predetermined policies that reduce a portfolio's exposure after reaching a certain threshold of cumulative losses-are commonly used by retail and institutional investors to manage the risks of their investments, but have also been viewed with some skepticism by critics who question their efficacy. I develop a simple framework for measuring the impact of stop-loss rules on the expected return and volatility of an arbitrary portfolio strategy, and derive conditions under which stop-loss rules add or subtract value to that portfolio strategy. I show that under the Random Walk Hypothesis, simple 0/1 stop-loss rules always decrease a strategy's expected return, but in the presence of momentum, stop-loss rules can add value. To illustrate the practical relevance of this framework,en_US
dc.description.abstract(cont.) I provide an empirical analysis of a stop-loss policy applied to a buy-and-hold strategy in U.S. equities, where the stop-loss asset is U.S. long-term government bonds. Using monthly returns data from January 1950 to December 2004, I find that certain stop-loss rules add 50 to 100 basis points per month to the buy-and-hold portfolio during stop-out periods. By computing performance measures for several price processes, including a new regime-switching model that implies periodic "flights-to-quality," I provide a possible explanation for our empirical results and connections to the behavioral finance literature. Consistent with the traditional investor's problem, I discuss a generalization of this approach to general stopping rules, which are superimposed on arbitrary portfolio strategies. I define a stopping utility premium and discuss how uncertainty about the true stochastic process can explain a potential value added or value lost by the use of stopping rules in practice.en_US
dc.description.statementofresponsibilityby Kathryn Margaret Kaminski.en_US
dc.format.extent150 p.en_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.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.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582
dc.subjectOperations Research Center.en_US
dc.titleGeneral superposition strategies and asset allocationen_US
dc.typeThesisen_US
dc.description.degreePh.D.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Operations Research Center
dc.contributor.departmentSloan School of Management
dc.identifier.oclc191106918en_US


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