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.

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.

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