Detecting Bubbles in the USD-JPY Exchange Rate by Sequential Monte Carlo Methods

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dc.contributor.advisorLockwood, Pamela
dc.creatorRizcallah, John
dc.creator.orcid0000-0002-5635-5199
dc.date.accessioned2021-02-15T21:46:35Z
dc.date.available2021-02-15T21:46:35Z
dc.date.created2020-12
dc.date.issued2021-02-12
dc.date.submittedDecember 2020
dc.date.updated2021-02-15T21:46:36Z
dc.description.abstractThis paper uses recently developed Bayesian techniques in the analysis of stochastic bubbles in the USD-JPY exchange rate. After the fundamental value of the price series is removed, the exchange rate is subject to two regimes. The first regime follows a mean-reverting process around a longterm moving average. The second regime is an autoregressive process with an explosive root. The SMC2 particle filter jointly estimates the hidden state and model parameters in real time. This method can readily deal with changes in market behavior and provides a measure of parameter uncertainty. Significant evidence of bubbles in the USD-JPY exchange rate were found. Furthermore, two trading strategies are devised and tested. Both strategies produce higher Sharpe ratios than a directional-trading benchmark.
dc.format.mimetypeapplication/pdf
dc.identifier.urihttps://hdl.handle.net/11310/396
dc.language.isoen_US
dc.subjectParticle filter
dc.subjectMCMC
dc.subjectSMC
dc.subjectMonte Carlo
dc.subjectExchange Rate
dc.subjectTrading
dc.subjectFinance
dc.subjectFOREX
dc.subjectBubble
dc.subject
dc.titleDetecting Bubbles in the USD-JPY Exchange Rate by Sequential Monte Carlo Methods
dc.typeThesis
dc.type.materialtext
thesis.degree.departmentMathematics, Chemistry & Physics
thesis.degree.disciplineMathematics
thesis.degree.grantorWest Texas A&M University
thesis.degree.levelMasters
thesis.degree.nameM. S.

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