Browsing by Author "Palmelind, Sheida"

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    Reducing the Carbon Footprint of Equity Portfolios
    (2017-07-26) Jonsdottir, Harpa Sif; Palmelind, Sheida; University of Gothenburg/Graduate School; Göteborgs universitet/Graduate School
    This paper investigates the e ect of reducing the carbon footprint of Swedish equity portfolios. In order to decrease CO2e emission of investments, the constituents of the portfolios are re-weighted with regards to their carbon footprint, while minimizing the tracking error against a benchmark portfolio. The study provides insight to whether it is possible to construct portfolios with lower CO2e in a limited investment environment. Our ndings show that we can decrease carbon footprint by 25% without altering the portfolios' sector exposure or su ering loss of returns. The optimization incorporates a recently proposed Swedish national standard for calculating portfolio footprint as well as a calculation of how much an investor contributes to emission when investing 1000 SEK a month for ten years in each of the portfolios.
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    Value-at-Risk and Expected Shortfall - Managing risk for an equity portfolio
    (2014-06-24) Emmoth, Stefan; Palmelind, Sheida; University of Gothenburg/Department of Economics; Göteborgs universitet/Institutionen för nationalekonomi med statistik
    This thesis intends to examine a risk measure used for estimating a potential future loss. The risk measure Value-at-Risk, is widely used throughout the world of financial risk management. We will examine different approaches to computing Value-at-Risk for two equity portfolios, one univariate portfolio and one multivariate portfolio. We assume that portfolio losses have a certain distribution. Even though Value-at-Risk is widely used and accepted within financial management, Value-at-Risk is not a coherent risk measure. We will therefore include another risk measure in our thesis, the so-called Expected Shortfall. What we find is that our assumption considering portfolio losses are not valid for all methods of computing Value-at-Risk. Methods investigated in this thesis are not suitable for capturing more extreme losses that occur during periods of market turbulences.