Glad you like it! Overall, we're working on adding more education and tools to help you with these set of questions. You're asking the right questions.
One of the hard things about algo writing is that there is no straightforward "do these 3 steps and you're done" from here. What I'd suggest you do first is think about your alpha factor and these results. Sometimes one can come up with an alpha factor, it looks great, but then when you do performance attribution you find out you simply rediscovered the momentum factor. When that happens you just have to throw it out and start over. It looks like you have high exposure to a couple of styles - do you understand why? Do you think your factor is intrinsically linked to them? Or do you think you can remove those common factors and still hang on to your alpha?
For instance, it looks like you're pretty long the size factor. Can bin your universe into some high-cap, mid-cap, and small-cap stocks and then apply the alpha property to each bin, thereby smoothing out your size bias? Or is your alpha directly linked to the size of the stocks?
Then, you should do pretty much what you're thinking of. Add the risk model to your optimizer and see if you can constrain it away. For some algos that will work, for others it will constrain away the alpha, too, and then you're stuck. Note - we're working at adding API improvements so you can add the risk model directly into your simulation.
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