With the implementation of the innovation-driven development strategy, increasing technical innovations are patented by the individuals or the companies. As a form of intellectual properties, the patent has attracted attention from individuals and companies. Although there are some researches on the economic function of patent, few quantitative researches discuss on whether patents can work on the company stock market. To discover the relations between the company patents and the stock market, we explore a method to analyze the influence of patent activity on the company stock market. We collect the patent data and the stock data of listed companies, from which patent and market activities are extracted. By the recursive discrete wavelet transform, the patent and market activities are decomposed into multi-scale wavelets. These wavelets are fed into a patent and market activity based stock market trend prediction model, in which the influences of patent activity are analyzed. We compare our model with the state-of-the-art model on 4 measurements for 3 manufacturing datasets. The experimental results show that the patent activities have positive effect on market trend prediction in about 30% manufacturing listed companies and that the measurements of Shanghai/Shenzhen Stock Exchange often outperform that of USA in years 2016–2019 for the manufacturing listed companies.