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Mathematical processing of trading strategy based on long short-term memory neural network model
Han-Yang Wang1, An-Qi Li2, Chao-Chen Tie2
1School of Economics, Anhui University of Finance and Economics, Bengbu, China.
Frontiers in Computational Neuroscience
|December 15, 2022
Summary
This study develops an optimal trading strategy for gold and bitcoin, analyzing their relationship to maximize investor returns. Research on their cointegration offers practical insights for investment strategies.
Area of Science:
- Financial Markets
- Quantitative Finance
- Digital Assets
Background:
- Gold and Bitcoin are established mainstream assets.
- Asset price volatility necessitates strategic trading approaches.
- Understanding inter-asset relationships is crucial for investment.
Purpose of the Study:
- To develop an optimal trading strategy for gold and Bitcoin.
- To maximize post-trade returns for investors.
- To enrich theoretical research on gold and Bitcoin returns.
Main Methods:
- Analysis of the relationship between gold and Bitcoin.
- Investigation of cointegration between gold and Bitcoin.
- Development of a trading strategy based on asset interdependencies.
Main Results:
- Identified a significant relationship between gold and Bitcoin.
- Established the cointegration of gold and Bitcoin.
- Developed a strategy to enhance trading returns.
Conclusions:
- The cointegration relationship between gold and Bitcoin has practical significance.
- Findings provide a reference for constructing investment strategies.
- Optimal trading strategies can be derived from asset interrelationships.
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