论文标题
基于财务视觉的强化学习交易策略
Financial Vision Based Reinforcement Learning Trading Strategy
论文作者
论文摘要
定量交易的人工智能（AI）的最新进展导致其在重大交易绩效方面的一般超人表现。但是，AI交易的潜在风险是“黑匣子”决定。某些AI计算机制很复杂且具有挑战性。如果我们在没有适当监督的情况下使用AI，AI可能会导致错误的选择并造成巨大的损失。因此，我们需要询问AI“黑匣子”，包括AI为什么决定这样做？人们为什么信任AI？人们如何解决错误？这些问题还强调了AI技术可以在交易领域解释的挑战。
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.
