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This thesis aims to examine an efficient asset and liability management method under Solvency II regulations, and to find an optimization framework that takes complex interactions between assets and liabilities into account. The investigated approach consists of a least-squares Monte Carlo method, where least-squares regression is used to obtain a proxy function for future net asset values. A fair
