The Fourth Swedish National Pension Fund (AP4), as well as many other large investors, has noted deficiencies the Mean-Variance framework for portfolio management of asset with non-normal characteristics. The main problem apparent in the Mean-Variance framework, when investing in alternative assets such as hedge funds, is the lacking systematic control of the balance between the measurements of risk due normal variation and tail-risk. Hedge funds constitute an asset class distinguished by non-normal characteristics such as negative skewness and heavy excess kurtosis, which suggests normality should not be assumed when optimizing a portfolio of hedge funds. Certain hedge fund strategies aim to be uncorrelated to other hedge funds and the major asset markets and are thus expected to have the capacity to hedge against extreme market events. Hedge fund performance during historically volatile market periods, including heavy losses and liquidations, has however proved this untrue. Outcomes in the tail of hedge fund distributions rather appear to occur in conjunction with increased correlation toward external indicators such as the equity stock market. With the aim to consider tail events in a portfolio of hedge funds and index futures, an optimization model intending to capture the asymmetric covariance between hedge fund assets and the equity market is developed and evaluated. The theory of copulas is applied to estimate the multivariate distribution by separating assumptions regarding univariate characteristics and dependence between assets. The estimated multivariate distribution is thereafter utilized in a scenario-based optimization model applying the Conditional Value at Risk (CVaR) measure as a risk measure, to capture events in the left tail of the portfolio distribution. The proposed GARCH-C-Vine-Mean-CVaR model is presented and evaluated against two reference models, a GARCH-C-Vine-Mean-Variance model, and a model assuming a multivariate normal distribution, EWMA-Mean-Variance. The ability to capture realized outcomes is analyzed for all three models, where the proposed GARCH-C-Vine-Mean-CVaR as well as the GARCH-C-Vine-Mean-Variance model show to capture realized outcomes to a further extent than the model assuming a multivariate normal distribution. Further, applying the risk measure CVaR has in this study shown to capture the realized outcomes to the same extent as applying variance as the risk measure. In conclusion, the proposed model manages to capture tail-events in the data analyzed in this study, to a further extent than if assuming multivariate normality. The lack of regulations and bias that denote hedge fund reporting, does however prevent a conclusion on whether the proposed model captures actual realized tail-events of hedge fund returns.

Load calculation wing, aileron, flaps, tail unit of Parrot Aircraft according to specification ASTM F 2245-04. Stress analysis coat, stem, flange, rivet and point.

African clawed frogs (Xenopus) represent an ideal model organism for study of regeneration mechanisms. In frogs, complete regeneration occurs in the tadpole stage. In later stages the regeneration capacity is lost. The Laboratory of Developmental biology was successful in establishment of cell culture called Xenopus tropicalis immature Sertoli cells (XtiSCs) derived from X. tropicalis testes. These cells are common progenitors of Sertoli cells and peritubular myoid cells. XtiSCs show similar characteristics as mesenchymal stem cells. MSCs hold interest of scientists for their immunomodulatory properties and multipotent differential and regeneration potential. In this thesis, we studied regeneration and migration potential of XtiSCs after X. tropicalis tadpole's tail amputation in developmental stage 47 - 50. Transgenic XtiSCs culture expressing RFP was prepared to facilitate transplantation experiments. Transplantation experiments showed preferential migration of XtiSCs into the site of injury. XtiSCs transplantations in X. laevis tadpoles with downregulated NO synthases eNOS and nNOS revealed their migratory dependence on nitric oxide signalization. Imunocytochemical staining of XtiSCs in vitro showed positive iNOS, nNOS and Pax7 expression. Imunohistochemical staining of tadpole's tail vibratome...

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Mitochondria carry out several important functions in eukaryotic cells such as energy metabolism, iron-sulfur cluster assembly, apoptosis, signaling pathways, protein quality control etc. Most mitochondrial proteins are synthesized on the cytosolic ribosomes and transported to the organelles by the cytosolic chaperones and mitochondrial protein import machinery based on specific targeting signals. Although, the basic principles of protein import have been explained, many questions remain unanswered, particularly for highly modified mitochondria such as hydrogenosomes. The aim of the study was to investigate protein translocation into hydrogenosomes of a human parasite, Trichomonas vaginalis (Tv) with a focus on the composition, function and structure of protein translocases and the role of targeting signals. The translocase of the outer membrane (TOM) is responsible for the import of most proteins into the organelle. Even though, the presence of a TOM complex in trichomonad hydrogenosomes was predicted, its components were not known. Moreover, the generic structure of the mitochondrial TOM complex was not resolved. This study showed that the TvTOM complex is highly divergent consisting of two modified core subunits - channel- forming TvTom40 isoforms and a Tom22-like protein, and two...

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This thesis examines the dependence structures between commodity futures and corresponding commodity producer equity indices in bearish, bullish and normal market conditions. We study commodity futures and producer indices in the energy, precious metals, gold and agriculture commodity markets using daily return data that ranges from 16 December 2005 to 28 June 2019. We employ the cross-quantilogram approach developed by Han et al. (2016) to examine dependence structures in the full quantile range, which represents different market states. Furthermore, we control for different lag structures, uncertainties and time-varying dependence structures. From our results we conclude the following: 1) There are time-varying asymmetric and symmetric dependencies in different commodity markets. There is asymmetric dependence between commodity futures and producer indices in the precious metals, gold and agricultural markets. In the oil market, the relationship is symmetrical. No relationship is found in the natural gas market. 2) Heterogenous dependence structures are identified in the gold, precious metals and agricultural commodity markets. The oil market uncovers homogenous dependence structures. 3) The observed spillover in all markets occur in the very short run, at one day, and dissipates after a week and additionally after a month. Our results provide new information regarding commodity diversification attributes which can be useful to investors. Our results also provide important policy implications: Since volatility spillovers between commodity futures and producer indices may deter investors from including commodities in their portfolios, as they might lose their diversifier qualities, it is important to enforce policies that will prevent the spillovers between the assets. Further, regulations of the commodity futures markets could be an alternative to reduce the spillovers.

Abstract This thesis project is divided in two parts. The first part examines the possibility that correlation matrix estimates based on an outlier sample would contain information about extreme events. According to my findings, such methods do not perform better than simple shrinkage methods where robust shrinkage targets are used. The method tested is especially outperformed when it comes to the extreme events, where a shrinkage of the correlation matrix towards the identity matrix seems to give the best result. The second part is about valuation of skewness in marginal distributions and the penalizing of heavy tails. I argue that it is reasonable to use a degrees of freedom parameter instead of kurtosis and a certain regression parameter, that I develop, instead of skewness due to robustness issues. When minimizing the one period draw-down is our target, the "value" of skewness seems to have a linear relationship with expected returns. Re-valuing of expected returns, in terms of skewness, in the standard Markowitz framework will tend to lower expected shortfall (ES), increase skewness and lower the realized portfolio variance. Penalizing of heavy tails will most times in the same way lower ES, lower kurtosis and realized portfolio variance. The results indicate that the parameters representing higher order moments in some way characterize the assets and also reflect their future behavior. These properties can be used in a simple optimization framework and seem to have a positive impact even on portfolio level

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