Research on gold and bitcoin trading strategy based on XGBoost and zero-one programming

Abstract

In the actual trading process, investors can only give the best daily trading strategy based on the past price data of gold and bitcoin, then they need to predict and evaluate the trend of the investment items in the coming period and plan out the trading scheme in advance. We also draw on data from many investment questionnaires on websites such as Stock Market Analysis & Tools for Investors to give specific trading strategies. We choose the XGBoost regression price prediction model and enable the genetic algorithm to find the best learning rate parameters. The first 100 trading days of gold and bitcoin data are taken separately for learning training tests, and then the first 20 data are used to predict the price trend for the next five days, which is repeated every day. It provides more accurate prediction results based on the latest prices. An optimization model is established to increase the final investment value by judging the buying and selling indexes by whether the expected return exceeds the purchased commission.