Fuzzy Asset-liability Portfolio Optimization Model with Investors' Mental Accounts

In reality, investors are often influenced by mental account when they manage assets and liabilities at the same time. Therefore, an asset-liability portfolio optimization problem is considered with investors' mental accounts and debt-paying behavior in fuzzy environment. First, we assume that the return rates of assets and the growth rate of liability are LR-fuzzy numbers, with the objectives of maximizing the possibilistic mean of the net wealth and minimizing its lower semi-absolute deviation, a fuzzy asset-liability portfolio optimization model considering investors' mental accounts is proposed. Second, a novel hybrid intelligent algorithm is designed based on Particle Swarm Optimization and Simulated Annealing to solve it. Finally, based on real stock data, a numerical example is conducted to analyze the model and the solving algorithm. The results show that different mental accounts will have different investment strategies, the proposed model can describe investors' mental account characteristics and provide decision support for actual investment activities.