Contributions in Merlin

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We present and estimate a model of competition in a two-sided market: the market for magazine readership and advertising. Using data on magazines in Germany, we find evidence that magazines have properties of two-sided markets. The results are consistent with the perception that prices for readers are ‘subsidized’ and that magazines make all their money from advertisers. Consistent with advertisers valuing readers more than readers value advertisements, our results imply that higher demand on the reader side increases ad rates, but that higher demand on the advertising side decreases cover prices.

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We consider optimization problems for minimizing conditional value-at-risk (CVaR) from a computational point of view, with an emphasis on financial applications. As a general solution approach, we suggest to reformulate these CVaR optimization problems as two-stage recourse problems of stochastic programming. Specializing the L-shaped method leads to a new algorithm for minimizing conditional value-at-risk. We implemented the algorithm as the solver CVaRMin. For illustrating the performance of this algorithm, we present some comparative computational results with two kinds of test problems. Firstly, we consider portfolio optimization problems with 5 random variables. Such problems involving conditional value at risk play an important role in financial risk management. Therefore, besides testing the performance of the proposed algorithm, we also present computational results of interest in finance. Secondly, with the explicit aim of testing algorithm performance, we also present comparative computational results with randomly generated test problems involving 50 random variables. In all our tests, the experimental solver, based on the new approach, outperformed by at least one order of magnitude all general-purpose solvers, with an accuracy of solution being in the same range as that with the LP solvers.

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