Abstract
Along with the development of the times, bitcoin and gold obtained more and more people’s hot pursuit. However, the frequent price changes, especially for the rapid price changes of bitcoin, cause great suffering to the traders’ investments. Therefore, making the appropriate trading strategy to maximize the trader’s profits is a significant problem. To make the best trading strategy, we model the prices of bitcoin and gold, the typical symbol of instability and stability in quantitative investment, to maximize profits while minimizing risk.In this work, We establish the Counterfactual Regret Minimizing (CFR) model and the Topological Sorting based Longest Multiplicative Path (TSLMP) model to help traders make strategy under low risk or high risk accordingly. To dynamically adjust the weight of the two models according to the feedback of real price change, we propose the Dynamic Weight Update (DWU) Method. The experimental results show that our Model is useful.
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