Abstract
Gold and bitcoin are the hottest investment products today. In this wave of investment, a large number of investors swarmed in, trying to obtain huge profits. Therefore, it is very important to establish mathematical models to help traders make decisions. In order to explore the best trading strategy to maximize revenue, we need to solve prediction problems to help carry out quantitative trading. Based on the time series given in the question, we use the LSTM long-term and short-term memory neural network model to build the network layer, and set the training time to predict the gold and bitcoin prices on the trading day. We use quantitative trading investment method, combined with turtle strategy and prediction data to obtain the daily transaction types of gold and bitcoin, and then combined with alpha hedging strategy and LB ladder rule to obtain the daily transaction quantity of both, and then combined with the Commission of each transaction to obtain the daily total account value model.
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