This paper examines a new approach for credit risk optimization. The model is based on the Conditional Value-at-Risk (CVaR) risk measure, the expected loss exceeding Value-at-Risk. CVaR is also known as Mean Excess, Mean Shortfall, or Tail VaR. This model can simultaneously adjust all positions in a portfolio of financial instruments in order to minimize CVaR subject to trading and return constraints. The credit risk distribution is generated by Monte Carlo simulations and the optimization problem is solved effectively by linear programming. The algorithm is very efficient; it can handle hundreds of instruments and thousands of scenarios in reasonable computer time. The approach is demonstrated with a portfolio of emerging market bonds.F. Andersson: Ementor,

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HipSpec is a system for automatically deriving and proving properties about functional programs. It uses a novel approach, combining theory exploration, counterexample testing and inductive theorem proving. HipSpec automatically generates a set of equational theorems about the available recursive functions of a program. These equational properties make up an algebraic specification for the program and can in addition be used as a background theory for proving additional user-stated properties. Experimental results are encouraging: HipSpec compares favourably to other inductive theorem provers and theory exploration systems.

M5T 2C6managing, as opposed to simply monitoring, a portfolio's Value-at-Risk (VaR). These tools include the calculation of VaR contribution, marginal VaR and trade risk profiles. We first review the parametric, or delta-normal, versions of these tools and then extend them to the simulationbased, or non-parametric, case. We analyze two sample portfolios: one, consisting of foreign exchange contracts, is well-suited for parametric analysis while the other, which contains European options, is best addressed with simulation-based methods. The limitations of the simulation-based approach, due to the potential effects of sampling error, are also discussed.

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