Mathematical processing of trading strategy based on long short-term memory neural network model

【Author】 Wang, Han-Yang; Li, An-Qi; Tie, Chao-Chen; Wang, Chao-Jun; Xu, Yun-Hua

【Source】FRONTIERS IN COMPUTATIONAL NEUROSCIENCE

【影响因子】3.387

【Abstract】At present, gold and bitcoin have become mainstream assets in market transactions. Due to the volatility of gold and bitcoin prices, we can buy and sell assets like gold and bitcoin the same way we buy and sell stocks. The research goal of this article is to develop an optimal trading strategy that maximizes our post-trade returns. By studying the relationship between the two, on the one hand, it supplements and enriches the theoretical research on the rate of return of gold and Bitcoin, on the other hand, it provides a certain reference for investors to construct investment strategies. The research on the cointegration relationship between them has important practical significance. At the same time, it has important practical significance for the research on the cointegration relationship between bitcoin and gold.

【Keywords】gold; Bitcoin; long short-term memory network model; trading strategy; mathematical processing

【发表时间】2022 28-Nov

【收录时间】2023-01-06

【文献类型】实证数据

【主题类别】

区块链治理-市场治理-价格预测