Stability of deterministic signals in stochastic financial stock price data

dc.contributor.authorHilder, Charles
dc.date.accessioned2026-04-27T15:04:25Z
dc.date.available2026-04-27T15:04:25Z
dc.date.issued2026
dc.description.abstractThe focus of this project is to quantify the persistence of deterministic trends within stock price paths from the S&P500. We start by considering "synthetic assets" – linear combinations of held and shorted stocks, which are designed based on underlying financial theory to exhibit predictable behaviour. We then model the synthetic assets out of sample by mapping their price paths to a non euclidean space, where their evolution can be described approximately linearly using a best fit Koopman operator (K). Then using this linear approximation, we asses the persistence of the fitted operator K by the use of spectral analysis and a stochastic adaptation of Lyapunov stability theory.
dc.description.reviewstatusReviewed
dc.description.scholarlevelUndergraduate
dc.description.sponsorshipJamie Cassels Undergraduate Research Awards (JCURA)
dc.identifier.urihttps://hdl.handle.net/1828/23729
dc.language.isoen
dc.publisherUniversity of Victoria
dc.subjectmath
dc.subjectstatistics
dc.subjectfinance
dc.subjectmodelling
dc.subjectdynamic-systems
dc.subjectJamie Cassels Undergraduate Research Awards (JCURA)
dc.subject.departmentDepartment of Mathematics and Statistics
dc.titleStability of deterministic signals in stochastic financial stock price data
dc.typePoster

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