Analysis of the best trading strategies based on neural networks

: This article build a prediction model based on the historical trading volume of gold and Bitcoin, then establish an investment return maximization model to maximize the return amount, and finally propose a feasible trading strategy to traders based on the model results. First, this article will process the data visualization after missing values to analyze the trend of bitcoin and gold trading volume, yield, risk and volatility respectively. Second, This article combine the ARIMA model and the LSTM model to establish an ensemble learning model, and use the critic method to combine the two series of predictions with appropriate weights to predict the asset price of gold and bitcoin for each trading day during the period from 2016 to 2021, again, According to the ensemble learning prediction results, the optimal average cost method (DCA) (DCA) is used to solve the prediction curve and verify the optimality, and it is concluded that there is a maximum benefit when k=19% and p=54%. Finally, based on the above predictive analysis results, this article explain to traders the model building process and the results it presents, and propose feasible investment decisions about gold and bitcoin from the aspects of trading behavior and trading psychology.