Assets Trading Strategy Based on ALG Evaluation and Prediction Integrated Model

Abstract

With the rapid development of economy and the maturity of financial markets, more and more people choose to invest in stocks to achieve property appreciation, so the study of stock investment decision-making is increasingly important. In this topic, in order to maximize the interests of investors, our team not only needs to accurately predict the future trend of gold and bitcoin, but also needs to make the most reasonable strategy according to the future trend of gold and bitcoin. Therefore, our team reads a large number of papers, refer to the current model of stock trend prediction and decision-making and combine with the data given by the topic to establish our model. According to the stock trend, this paper designs an ALG (Apriori algorithm - Attentional BiLSTM neural network - GARCH model) evaluation and prediction integrated model, and makes a time series chart of daily return rate related to gold and bitcoin, finally predicts the daily return rate. This paper compares the daily yield predicted by ALG model with that predicted by grey model, which shows that the yield predicted by ALG model is much higher than that predicted by grey prediction model.