, and the prices at which those trades might have executed. And crucially, you want to be able to align with data from other market participants. And this is where you start getting into the realm of not just having these tools but maybe also building the tools that potentially relate to prediction markets or tools that help you make decisions about how to quote this order and what kind of research you might continue to do based off this initial hypothesis. And in addition, you might want to have some kind of testing ground to test out your different ways of providing quotes. And again, here this is where the tools can rapid iterate to help find the best way of providing this execution for the client. And I would characterize the final stage of a research project as being more akin to a softer skill, but just as important, which is understanding the domain that you’re playing in. So you have the data that says maybe you can predict a little bit better when this client is going to be active in the market, but there’s going to be a lot of uncertainty as to whether you can actually move the market at that time or those kinds of trades are going to make sense for the ity of the basis, and so having an understanding of the real-time simulator
https://signalsandthreads.com/finding-signal-in-the-noise/