年度	2023
計畫類別	研究計畫
計畫名稱	基於碎形布朗運動之多目標投資組合最佳化
參與人	陳耀宗
職稱/擔任之工作	主持人
計畫期間	2023.08 ~ 2024.07
補助/委託或合作機構	國家科學及技術委員會
摘要	Multi-objective optimization algorithms have been used in portfolio optimization for many years. However, when the optimized portfolio is tested in out-sample, the risk measured by the variance of return is not always optimal. That maybe because the assumption of a normal distribution of return on assets may be problematic. The return distribution simulated by the Fractal Brownian Motion (fBm) with long-term memory has a greater variance than the normal distribution, which is more suitable for capturing extreme return changes in the future. Therefore, if the return distribution simulated by the fBm is used as training data, the portfolio optimized by algorithms should better reflect the extreme changes in the financial market, which can make the theory of portfolio optimization and its function of guiding investment direction more reliable.
語言	中文