There's a lot of the talk on WSO about HF fundamentalists needing to learn how to code. However, most of the coding that is discussed is about web scraping and model making. Should fundamentalists also learn machine learning to provide insighs?
| +95 | Best SM seats in 2024? | 70 | 21m | |
| +84 | If and when to move to a pod? | 19 | 2h | |
| +69 | Pod Shop Regret | 24 | 1d | |
| +24 | Intellectual Caliber of People in HF | 15 | 5h | |
| +23 | Understanding pod shop leverage & cash usage | 2 | 2d | |
| +16 | Are you making money these days? | 9 | 4d | |
| +12 | Mid to Low Frequency Quantamental | 1 | 6d | |
| +9 | Suggestions for market structure analysis & better trades | 1 | 5d | |
| +8 | What discount rate do you use if you don't believe in those damodaran beta crap? | 17 | 17m | |
| +8 | Opinions on Yipit and/or Mscience? | 11 | 5d |
Career Resources
Get instant access to lessons taught by experienced private equity pros and bulge bracket investment bankers including financial statement modeling, DCF, M&A, LBO, Comps and Excel Modeling.
Yeah, that's (hopefully) what all smart investors do. You look at the data, try to figure out what the data says about how the world works, apply that understanding to make money, if possible. Reminds me of a convo I heard by Fama. Guy greatly moved forward EMH but was completely open to other hypotheses if the data showed different. Too many people shape data to fit beliefs rather than let beliefs be shaped by data. Aight time for me to go move around some logos
The correct process is to
1) Form a hypothesis 2) Determine if the data supports your hypothesis 3) If your hypothesis is supported than implement it into your process
Step 2 requires a great level of discipline to ensure that you don't squeeze the data to fit your hypothesis. But having an ex-ante hypothesis is a part of this. Digging around the data to find your thesis is not correct. It will lead you to find patterns that are random/not persistent.
few clarifying comments about how ive seen ML used at $4b+ fundamental shop:
so while fundamental analysts will likely stay fundamental, the rest of the infrastructure is going to use best practices, including ML for whatever their function
I think the answer is you use exactly zero of these skills at a fundamental hedge fund on average.
I actually work as a well respected quant fund now after working at a pretty prestigious hf and we STILL don’t use machine learning. If you are pussyfooting around with overly complex models, you’re probably going to miss a lot of opportunities.
Do I believe hedge funds tell their LPs they use machine learning? Absolutely. LPs might on average be slightly dumber than people on this forum so it makes sense they’d say that. The “data scientists” at hedge funds are marketing spend. You buy them for the same reason you buy nice office furniture.