With the evolution of LLM and natural language processing, there is a closer connection between the discretionary and quantitative world, yet the two are not perfectly linked. There is uncertainty in both worlds. For the quant, there is model and parameter uncertainty. For the discretionary trader or non-quant, the problem is the precision in words. What you say may not be precise by you as the sender and by the receiver.
We have discussed this issue of precision in language in the past, yet most investors still seem to be at risk from word uncertainty. Just think of all the Twitter words and Substack posts driven by language. Are these words given any quality control? If you look at the research, the answer is no. If you look at the range of meaning for these words of estimative probability, you will have to agree that there is ambiguity concerning the words often used by any decision-maker. Ask for specifics. Ask for the actual probabilities. Close the range of uncertainty.
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