Asset and Liability Management: Optimization using Least-Squares Monte Carlo
Detta examensarbete ämnar undersöka en effektiv Asset and Liability Management (ALM) metod under Solvency II direktiv, med m˚alsättningen att etablera ett optimeringsramverk som hanterar komplexa interaktioner mellan tillg˚ang- och skuldsida. En stokastisk simuleringsmetod kallad least-squares Monte Carlo (LSMC) implementeras för att skatta en proxy funktion för framtida nettotillg˚angsvärden. LSMThis 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
