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Tl;dr markets are hard to beat, but it's not impossible. Case in point, there is probably alpha in understanding AI's impact but it's very hard to time and finance the associated bets

I would call it a tie:

 

  • Since 1972, the Nasdaq 100 has experienced slightly higher annual returns (10.8%) than the S&P 500 (10.5%), but it has also experienced much higher volatility. 
  • During the bull markets, the Nasdaq 100 has crushed the S&P 500 (the 1990s and the post-2008 market).
  • However, during bear markets, the S&P 500 has performed much better than the Nasdaq 100 (1973-1974, early 2000s, the 2008 financial crisis).
  • The Nasdaq 100 beat the S&P 500 in 25 out of these 46 years (54% of years).

To play devil's advocate, would you have said the same thing about computers and the internet (improving productivity in a lot of things)? If so, would you expect it to impact GDP? Because it's not clear that it did.  https://fred.stlouisfed.org/graph/fredgraph.png?width=880&height=440&id=RTFPNAUSA632NRUG

Stock market feels like one of the last places that modern AI will have a huge impact on (beyond the basics that are already in use).  All the breakthroughs seems to be coming in the form of models which are really bad at non-stationarity and extremely high noise.  Could be interesting to build a stack of LLMs that ingests 10K's and macro econ data and tries to infer causal models, but I'm skeptical it'll be better than humans at this for a long while. I think you're safe for now :)

Those titles should link to explanations, or did you mean something more specific?

I'm working towards more content, of course. I wasn't aware CFAR workbook was public and they wanted their stuff shared more broadly, in which case I will definitely add those.