2022/02/03 by Yun‐Cheng Tsai, Fu-Min Szu, Tsai, Yun-Cheng +5
Decision Sciences · #Artificial Intelligence (cs.AI) #Computational Engineering #FOS: Computer and information sciences #Finance #Machine Learning (cs.LG) #Stock Market Forecasting Methods #and Science (cs.CE)
paper · pdf · doi:10.48550/arxiv.2202.04115
openalex publication_date 2022/02/03 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Recent advances in artificial intelligence (AI) for quantitative trading have led to its general superhuman performance in significant trading performance. However, the potential risk of AI trading is a "black box" decision. Some AI computing mechanisms are complex and challenging to understand. If we use AI without proper supervision, AI may lead to wrong choices and make huge losses. Hence, we need to ask about the AI "black box", including why did AI decide to do this or not? Why can people trust AI or not? How can people fix their mistakes? These problems also highlight the challenges that AI technology can explain in the trading field.