All of Gary Basin's Comments + Replies

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).
2James Dao1y
The wiki page says the Nasdaq-100 started in 1985? Where are you getting your 1972 data from?
3James Dao1y
Coincidentally, I made an app to do exactly these types of historical comparisons of returns, with much greater fidelity. Input ^NDX and ^GSPC (Nasdaq-100 and S&P500 respectively) as the input tickers. These are Yahoo Finance's codes for those respective indices. Alternatively, you can input QQQ and SPY, which are ETFs that track those indices but there will be less historical data since ETFs come after indices.

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.

I don't think one can easily unpack the impact from either computers or internet (which I'm honestly not sure really has significantly increased productivity) impacts on aggregate productivity just by looking and a graph. GDP is nominal prices basically so technology changes that might well increase output or increase output quality while also working to lower or hold prices constant will be masked in simple GDP traces. I think you'd need to look at some older models, perhaps like Solow's Growth Model, that include a technology term and see how that is moving around. Total productivity seems like it would be driven by labor, capital and technology state. If one assumes human productivity is pretty constant and the installed capital base is likewise pretty set then innovation like computers, internet and AI should show up in the technology component of the model.
Independent of effects on GDP, the internet (nasdaq100) has still strongly outperformed the overall US stock market (sp500).

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.

Yeah, it's totally un-intuitive that the titles are also links. I guess even with better formatting (underlines) it wouldn't be much better. I have some experience with our internal wiki where this was an issue for many people too. Never make titles links.
it's not public but there is the unofficial cfar cannon. I missed that they were links because of the formatting here.