Application of supervised learning models in the Chinese futures market

Global financial systems have seen considerable growth in size, concentration, and complexity over the past few decades, the complexity of financial systems exceeds the modelling capabilities of traditional quantitative methods. In addition, some very useful data sets, such as satellite images, voice recordings or news sentiment, are beyond the reach of econometrics[2]. In recent years, many hedge funds have started experimenting with machine learning (ML) methods. ML is a subset of artificial intelligence, where machines are used to learn from previous experience[3]. Unlike traditional programming, where developers need to predict every potential condition to program, ML's solution can effectively tailor the output to the data.