블랙리터만과 모멘텀을 결합한 적극적 자산배분 전략 연구

In this study, we propose a new proactive asset allocation model that combines the Black-Litterman model with a momentum strategy. The Black- Litterman model effectively addresses the corner solution problem of the mean- variance model by incorporating investor market views into the implied expected returns of the market equilibrium portfolio. However, it heavily relies on the subjectivity of market views, relying on expert knowledge and experience. In this paper, we suggest a quantitative momentum score using recent time series data to create a market outlook method that can adapt to market changes. Additionally, we integrate the relative and absolute momentum strategies, as criteria for asset selection in portfolio construction. This combination allows for achieving higher expected returns and lower risk. The proposed model demonstrates superior performance in terms of returns and portfolio evaluation metrics such as volatility and Maximum Drawdown(MDD) compared to the Black-Litterman model without market views, mean-variance considerations, or fixed weights portfolio. This model, designed to respond to market changes without predicting the market, is notable for its simplicity and intuitiveness, making it easily understandable. The significance lies in its potential application in automated solutions such as robo-advisors, where data-driven interventions without human involvement are preferred.