On the evening of April 14th, Magic Square Quantitative announced that the company would concentrate resources and efforts to establish a new independent research organization to explore the essence of AGI. This makes people curious. As one of the "Four Heavenly Kings" of quantification, Magic Square Quantification needs to prepare for "AI stock trading"? The so-called AGI is Artistic

The abbreviation of general intelligence specifically refers to general artificial intelligence, which mainly focuses on developing machines that think like humans and engage in multiple purposes like humans.

What would be the stock market trading scenario when investing with AI? Investing in AI is not mysterious. Data display. Since 2017, investment giants have systematically incorporated machine learning and deep learning technologies, successfully applying artificial intelligence technology to the financial market. The core three elements of artificial intelligence (data, algorithms, and computing power) are all crucial in quantitative investment. The synergy of these three elements helps to continuously and efficiently iterate quantitative investment strategies. If a certain element has obvious shortcomings, it may lead to missed opportunities for high-speed development. However, market participants do not believe that AI can become a fund manager. According to the latest interviews published by American media, Wall Street fund managers who are passionate about AI stocks do not seem to believe that there will be stronger "stock trading AI" than humans in the foreseeable future. Wall Street is also very enthusiastic about industries that use new technologies, including investment processes such as placing orders and risk control, which have already been handed over to algorithms for resolution. Jim Simmons, the founder of the Renaissance Technology Fund and a mathematician, began researching "algorithmic stock trading" 40 years ago. After years of effort, they finally realized the use of machine learning to identify patterns of past market trends and generate profitable trading strategies.

What new insights does the emergence of ChatGPT have for quantitative investment? ChatGPT itself cannot be directly applied to quantitative investment at present, but its NLP (natural language processing) direction needs continuous research and trial. You can use it to help capture some specific information, improve the efficiency of information collection, and reduce learning costs. Language models are closely related to data processing in the early stages of quantitative investment, as multimodal data includes text, images, and speech, and all data needs to be translated into a form that machines can understand. Such technologies can better assist teams in understanding textual information. Many prediction models and algorithms used by large companies in research and application are similar to ChatGPT in terms of underlying performance. ChatGPT's significant performance improvement represents a significant potential for this technology in the field of quantification. The company is currently researching the reasons why this technology can make such significant progress and integrating it into the application scenarios of quantitative investment. When using ChatGPT and other technologies for quantitative investment, private equity managers need to have highly automated data processing capabilities and computer computing power, as well as complete data pipelines, data storage, and data security measures.