| Abstract : | We examine a different approach to the portfolio optimizationproblem. We employ stochastic dominance as our tool of optimizationunder uncertainty. Before proceeding to describe the model, itsapplication and our results we include some chapters guiding thereader through concepts that should be known and understood tocomprehend the work we are attempting and the reasons behind it.We employ a first and second degree of stochastic dominanceefficiency test on our data, to optimize our portfolio consisted of thirtyshares listed on S&P500 and we use the index as our benchmark. Weprovide proof of concept for our portfolio outperforming the index.We will apply five portfolio performance measures to appraiseour results and reach a conclusion regarding the viability andprofitability of a stochastically optimized portfolio.As we will demonstrate in the closing chapter of this thesis, sucha portfolio exists and truly achieves, as an out-of-sample test, showedhigher than market returns most of the time.
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