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Portfolio selection involves a trade-off between maximizing expected return and minimizing risk. In practice, useful formulations also include various costs and constraints that regularize the problem and reduce the risk due to estimation errors, resulting in solutions that depend on a number of hyperparameters. As the number of hyperparameters grows, selecting their value becomes increasingly imp

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We compare Value at Risk estimates from an AR(1)-GARCH(1,1) model with t- or normally distributed innovations, to estimates from an AR(1)-GARCH(1,1) model where the Peak-Over-Threshold method is applied to the tails of the innovations. Using the Christoffersen backtest, we find that the performance of the second type of model is superior to the first, particularly at high confidence levels for the

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Title: Critical success factors that influence the corporate venturing process Seminar date: 2013-05-02 Course: ENTN39 Internship and Degree Project Authors: Martin Zündorf & Marcus Holgersson Advisor/s: Joakim Winborg Purpose: We investigated the influence of different factors on the corporate venturing process. Therefore we combined several factors from the organizational level with cha