Quantitative Investment Decision Model Based on PPO Algorithm

Abstract

Bitcoin is sometimes called the new gold, replacing gold as a hedge against inflation, and research on the relationship between bitcoin and gold has important practical implications. This paper first calculates the correlation between bitcoin and gold. By introducing the calculation of dynamic penalty coefficient, the double stock portfolio investment problem is transformed into the single stock purchase investment problem, which greatly reduces the difficulty of feature engineering and model application. In terms of decision model, deep reinforcement learning (PPO algorithm) is used to make quantitative investment decisions, and the expected data in SLTM is taken as the input data of deep reinforcement learning, which is combined with deep reinforcement learning. Compared with machine learning quantitative investment decisions, after a period of learning, the accuracy rate and returns have been substantially improved.