Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.270822
Title: A fully Bayesian approach to financial forecasting and portfolio selection
Author: Simpson, Andrew
Awarding Body: Newcastle University
Current Institution: University of Newcastle upon Tyne
Date of Award: 2002
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Abstract:
The movements of share prices has long been of interest to both academic researchers as well as market practitioners. The statistical research in this field dates back to the work of Bachelier (1900) and there have been many approaches adopted subsequently. This thesis considers a Bayesian approach to multivariate forecasting of financial time series based on dynamic linear models. We will also consider the forecasting of the returns distribution using stochastic volatility models. We will then look at combining these two model structures. We will also demonstrate how the posterior forecast distribution can be simulated and how this may be used directly in order to implement a fully Bayesian decision theoretic approach to selection of optimal stock portfolios. These methods are first illustrated on simulated data and then applied to real data for selected shares from the Standard and Poor 500.
Supervisor: Not available Sponsor: University of Newcastle upon Tyne
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.270822  DOI: Not available
Keywords: Banking Finance Taxation Mathematical statistics Operations research
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