Academic Journal of Computing & Information Science, 2022, 5(4); doi: 10.25236/AJCIS.2022.050407.
Yage Ren, Jiangxue Li
Xuchang University, Xuchang, Henan, 461000, China
Trading strategies based on the technical analysis are widely employed in the fifinancial markets in order to maximize the total return of market traders. This paper proposes an optimization model for gold and bitcoin investment that gives the best daily trading strategy by analyzing the price data. We employed time series ARIMA model, and BP neural network to forecast the closing price. With the help of MATLAB and SPSS software, the respective forecast values and model evaluation indexes are calculated. The errors of the corresponding models are analyzed, and the predicted value of BP neural network is the closest to the true value through comprehensive analysis.
BP neural network; Greedy algorithm; Control variable method; Optimization model of gold and bitcoin investment
Yage Ren, Jiangxue Li. Optimization Model for Gold and Bitcoin Value Based on Neural Network and Greedy Algorithm. Academic Journal of Computing & Information Science (2022), Vol. 5, Issue 4: 41-45. https://doi.org/10.25236/AJCIS.2022.050407.
 Cha Bo, A study on the optimization problem of venture capital contracts under the behavior of changing capital use of startups [J]. Systems Engineering, 2021: 1-13.
 Xu Rui, Han Feng Xia. Research progress and application of BP neural network for predicting property prices along subway lines [J]. Sichuan building materials, 2021, 47(12): 172-175+177.
 Liu Zhiqian. Markov chain-based stock price volatility prediction [J]. Cooperative Economics and Technology, 2021, (24): 64-67.
 Zeng Ni, Chen Junhao, Fu Qingxin. A dynamic planning strategy based on greedy algorithm [J]. Computer Knowledge and Technology, 2021, 17(20): 141-143+152.
 Guo Qiansheng, Li Dong, Zhang Lei, Wei Chuyuan. A time series prediction model based on point-in-time process [J]. Computer Engineering and Science, 2021, 43(07): 1299-1307.