1. Collect relevant historical data first. These data can come from the trading market or other professional institutions, and the important data points are cotton price, volume, position, profit and loss, etc.

2. After collecting the data, analyze and process it. Through statistical methods and various data mining techniques, some useful information and laws can be obtained. We can analyze the historical price fluctuation, find out the trend and periodicity of price fluctuation, and understand the market trend and demand change.

3. According to the collected data and analysis results, we can choose a suitable mathematical model to describe the price trend of cotton futures. Commonly used models include linear regression model, time series model and support vector machine model. When establishing a model, we should pay attention to model assumptions, data processing methods, model parameters and optimization methods.