The Impact of Patent Activities on Stock Dynamics in the High-Tech Sector

Patent data has been used for generating patent-based indicators for tracking the technology development of high-tech companies. In this paper, we further show the promises of exploiting patent data for the analysis and prospecting of high-tech companies in the stock market. Specifically, we aim at investigating the relationship between the patent activities of high-tech companies and the dynamics of their stock price movement. While stock forecasting is a topic of general interest and has been studied extensively in the literature, the most popular forecasting models do not facilitate the discovery of the patent-activity impact all essential characteristics of the market performance of a given stock. To this end, we propose a new approach to analyze the relationships between patent activities and the statistical characteristics of stock prices. To the best of our knowledge, we are the first to propose a model of this nature, relating patent data mining and financial modeling. Also, we demonstrate the relationships of the market-adjusted stock returns and the number of patent applications as well as the diversity of the corresponding patent categories. Moreover, we establish relationships between the monthly drift and volatility of the market-adjusted stock returns and those patent activity indicators. Here, we exploit a widely accepted diffusion model of the stock returns and estimate its parameters. By adopting the moving window technique, we create fitted models by introducing various lagged terms of patent activity characteristics. For each company, we consider the coefficients of each significant term over the entire time horizon and perform further statistical testing on the overall significance of the corresponding indicator. The analysis has been performed on real-world stock trading data as well as patent data. The results confirm the significant impact of patent activity on stock movement and on its essential statistical characteristics of drift and volatility.