Check it out here: papers.ssrn.com/sol3/papers....

We hope this sparks fresh ideas for researchers, practitioners, and especially students, and generally lowers any barriers to using natural language data in your work.

We also highlight real-world applications: measuring financial constraints, uncovering product-market synergies, tracking investor sentiment, mapping climate risk, and more.

From word lists and anchor-phrase queries to embeddings and Generative AI, our paper surveys the full spectrum of NLP methods. We explain when each approach excels, and how to choose the right tool for your research objective.

I recognize though, that I know much more about generating natural language than I know about generating power, so maybe this is also not as big a deal ...

Abolish the CPA/CFA?

Congratulations!

I was joking of course. I think some of the papers it generated have clear formatting problems (though real submitted papers sometimes have those too). But the tech will keep improving so you are clearly pointing to a real issue.

Cool paper. Why not take the extra step and see if they are credible enough to pass peer review?

The machines are still producing mostly convex combinations of human writing and ideas.

If you put an exponential growth curve on it then sure, they'll be super intelligent around the corner, but until then, still human civilization.

Thanks for making our paper much more fun than we ever could.

Getting a journal pub is nice, but in my circles, a feature in Money Stuff is on a higher level.

Achievement unlocked ;)

Don't know about CF, but in AP I would consider estimates of:
1. relative risk aversion
2. intertemporal elasticity of substitution
3. equity premium