Tid: 15 juni 2018 kl 12.45.

Föredragshållare: Aidine Ahsant och Elisabeth Hakim

Title: Quantitative portfolio construction using stochastic programming

Abstract: In this study within quantitative portfolio optimization, stochastic program- ming is investigated as an investment decision tool. This research takes the direction of scenario based Mean-Absolute Deviation and is compared with the traditional Mean-Variance model and widely used Risk Parity portfolio. Furthermore, this thesis is done in collaboration with the First Swedish National Pension Fund, AP1, and the implemented multi-asset portfolios are thus tailored to match their investment style. The models are evaluated on two different fund management levels, in order to study if the portfolio performance benefits from a more restricted feasible domain. This research concludes that stochastic programming over the investigated time period is inferior to Risk Parity, but outperforms the Mean-Variance Model. The biggest flaw of the model is its poor performance during periods of market stress. However, the model showed superior results during normal market conditions.

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