Can ai predict stock price in market?
Recently, OpenAI launched its first video generation model “Sora”, which quickly became popular around the world. Since OpenAI launched ChatGPT in late 2022, AI has been conquering one area of human society after another. So can ai replace humans in stock trading?
Current applications of AI for trading
In fact, since the application of computer technology in the field of investment, the internal algorithm that constitutes AI has been constantly applied by investors in the financial market, in order to obtain higher returns. These people who use mathematical models to analyze the financial market to make investment decisions call themselves “quant”. The most famous is Renaissance Technologies, led by Jim Simons. According to market watchers, the company’s Medallion fund has returned 71.8 percent on an annualized basis, beating Warren Buffett. It’s just that these algorithms may initially be used more as statistical models in investing than as “world-aware” artificial intelligence, as it’s now known.
James Simons Speech at MIT
Just a few months ago, the AI core team of two sigma, another well-known company in the field of Quantitative investment, held an online discussion entitled Deep Learning for Sequences in Quantitative Finance. Team leader Professor David kriegman, at the meeting, shed light on how Two Sigma researchers are applying sequential deep learning to quantitative investing. Deep learning is an important part of current AI technology.
AI stock trading is not far away
From the perspective of many quantitative investment companies emphasizing that their key forecasting basis is data and models, the realization of true ai stock trading is not far away.
Firstly, from the perspective of data, the advent of ChatGPT has undoubtedly broadened the data sources available to quantitative investment companies. Many news and public comments have been processed to form a new basis for investment decisions.
Secondly, from the perspective of the model, the analytical ability of the GPT model itself and its internal composition algorithm provide quantitative researchers with new tools, which not only greatly improve the work efficiency of researchers, but also constitute a new modeling idea and improve the existing investment model.
Third, from the perspective of hardware, with the development of chip technology and the continuous expansion of social computing power, it is more and more efficient to process larger and more complex data.
All of these provide basic support for the application of ai technology in the investment field, and as the application of these technologies continues to accumulate, a general ai investor is likely to become more and more mature. AI’s prediction of stock price is likely to become a new trend.