Greedy Strategies with Multiobjective Optimization for Investment Portfolio Problem Modeling.

The ultimate purpose of portfolio investment is to reduce investment risk and improve total return on the premise of ensuring reasonable allocation of capital. In this paper, we build a quantitative model to advise on trading based on the price movement of Bitcoin and gold between 2016 and 2021; our goal is to maximize profit while minimizing risk. We mainly use greedy strategies with multiobjective optimization models. For the purpose of obtaining the correct price trend, some popular trend indicator strategies are referred to predict the future price trend in the medium and long term. In addition, we also consider people with different trading preferences and divided them into aggressive, advanced, balanced, and cautious and provided trading strategies for each of these four groups. This gives our model scalability. Finally, we analyze the sensitivity of the model and discuss the impact of trading commission costs on the model results. The model can be applicable to various investment situations.