Portfolio optimization using stochastic programming with market trend forecast

dc.contributor.advisorBard, Jonathan F.
dc.contributor.advisorLasdon, Leon S., 1939-
dc.creatorYang, Yutian, active 21st centuryen
dc.date.accessioned2014-10-02T21:10:44Zen
dc.date.issued2014-08en
dc.date.submittedAugust 2014en
dc.date.updated2014-10-02T21:10:44Zen
dc.descriptiontexten
dc.description.abstractThis report discusses a multi-stage stochastic programming model that maximizes expected ending time profit assuming investors can forecast a bull or bear market trend. If an investor can always predict the market trend correctly and pick the optimal stochastic strategy that matches the real market trend, intuitively his return will beat the market performance. For investors with different levels of prediction accuracy, our analytical results support their decision of selecting the highest return strategy. Real stock prices of 154 stocks on 73 trading days are collected. The computational results verify that accurate prediction helps to exceed market return while portfolio profit drops if investors partially predict or forecast incorrectly part of the time. A sensitivity analysis shows how risk control requirements affect the investor's decision on selecting stochastic strategies under the same prediction accuracy.en
dc.description.departmentMechanical Engineeringen
dc.format.mimetypeapplication/pdfen
dc.identifier.urihttp://hdl.handle.net/2152/26248en
dc.language.isoenen
dc.subjectPortfolio optimizationen
dc.subjectStochastic programmingen
dc.subjectMarket trend predictionen
dc.titlePortfolio optimization using stochastic programming with market trend forecasten
dc.typeThesisen
thesis.degree.departmentMechanical Engineeringen
thesis.degree.disciplineOperations Research & Industrial Engineeringen
thesis.degree.grantorThe University of Texas at Austinen
thesis.degree.levelMastersen
thesis.degree.nameMaster of Science in Engineeringen

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