Analysis of the Effectiveness of Alpha Strategy for Optimized Multi-Factor Models

Abstract

The emergence of ChatGPT signifies the advent of a new artificial intelligence revolution. Generative AI technologies, represented by ChatGPT, will profoundly afferct the research paradigm in finance and the systemic ecosystem of the financial industry. This study primarily focuses on the stocks within the ChatGPT concept sector of China's A-share market and investigates the effectiveness of a multi-factor Alpha stock selection strategy in this sector. Firstly, the research optimizes the Fama-French three-factor model and establishes a four-factor model. Using this optimized four-factor model, stock selection is performed within the ChatGPT concept sector, resulting in the formation of an investment portfolio. Based on backtesting, the strategy is found to be highly effective, though it requires a certain level of risk tolerance from investors. These results represent a proactive attempt to apply the Alpha strategy to the ChatGPT concept sector of China's A-share market, providing a preliminary examination of its performance characteristics and offering valuable insights for further research by subsequent scholars.