JACIII Vol.27 No.1 pp. 105-118
doi: 10.20965/jaciii.2023.p0105

Research Paper:

Optimization Trading Strategy Model for Gold and Bitcoin Based on Market Fluctuation

Hong-Xia Xie*, Yan Feng**,†, Xue-Yong Yu*, and Yu-Ning Hu*

*School of Computer and Computing Science, Zhejiang University City College
P. O. Box 94, No.51 Huzhou Street, Gongshu District, Hangzhou, Zhejiang 310015, China

**Zhejiang Metals and Materials Co.
78 Fengqi Road, Hangzhou City, Zhejiang 310003, China

Corresponding author

March 17, 2022
September 27, 2022
January 20, 2023
CNN-machine learning algorithm, ant colony algorithm, single-object optimal model, Markov-switching copula model, index GARCH model

As a new type of digital currency, Bitcoin is considered as “future gold” by various scholars. Therefore, this study considers Bitcoin and gold as a group of hedging assets to conduct investment research and it also discusses the investment rules between Bitcoin and gold: prediction of the rise and fall of Bitcoin, comparison of the characteristics of Bitcoin and gold, and the impact of the transaction procedures of Bitcoin and gold on the final trading results, and formulates trading strategies through optimization algorithms. Then, four machine learning algorithms, i.e., LSTM, BP neural network, Adaboost, and Bagging, are introduced to predict the rise and fall of gold and Bitcoin the next day, and then, the entropy weight method is used to synthesize four predicted results to ensure the robustness of the predicted results. To establish the optimal trading strategy, this study considers the maximum expected return as the goal to develop a single-objective optimization model and historical five-day price volatility as a risk factor. In this study, ant colony, simulated annealing, and genetic algorithms are used to solve the single-objective optimization model. Finally, we conclude that Bitcoin, similar to other financial assets, e.g., gold, is sensitive to shocks and volatile and possesses a relatively quiet cycle. When Bitcoin has an asymmetric impact, Bitcoin and gold can equally treat transactions.

Rise and fall prediction of gold and bitcoin based on LSTM, BP neural network, Adaboost, and Bagging

Rise and fall prediction of gold and bitcoin based on LSTM, BP neural network, Adaboost, and Bagging

Cite this article as:
H. Xie, Y. Feng, X. Yu, and Y. Hu, “Optimization Trading Strategy Model for Gold and Bitcoin Based on Market Fluctuation,” J. Adv. Comput. Intell. Intell. Inform., Vol.27 No.1, pp. 105-118, 2023.
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Last updated on Jul. 12, 2024