At MDT, we’ve been a big believer in AI and machine learning for a long time, and we have long integrated machine learning into our investment process. Our decision trees can be a powerful way to produce alpha forecasts while enabling us to understand and explain the rationale behind every trade. We believe that in making forecasts that drive investment decisions, the emphasis should be on this kind of transparency and accountability.
Today there’s a lot of excitement around generative AI models and large language models (LLMs), but off-the-shelf versions of those models face some challenges when applied to investing. They can be limited in context, produce unreliable answers, and lack transparency. It can be hard to understand how they arrive at their conclusions and recommendations. We think those are serious issues.
We look at AI as a toolbox, and we can selectively adopt the most relevant ideas and tools from the field as it evolves. That lets us preserve our model’s accountability and transparency while benefiting from the groundbreaking innovations happening in AI.
The pace of AI innovation has been remarkable, and we continuously evaluate new advances to cherry-pick the best ideas for enhancing our investment process, which can lead to new alpha factors and new insights. We’re very excited to see where that will take us.
