Alternative Data at Hedge Funds Stories
What are some interesting stories of alt data that people have used or have seen their colleagues use/create at hedge funds?
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It's not as useful as you think or really adding too much edge, everyone is using the similar credit card data, phone location data, email receipts, satellite imagery, etc
Is the ability for someone to go from a data provider to an HF a possibility? Do HFs still hire these data guys even though the edge is gone?
Possible, but unlikely. I've interviewed people from these firms. They usually fall into one of two buckets: either they're academic statisticians who spent the last three years over-engineering their company's models (and thus not pragmatic enough to work at a discretionary equities fund), or they're too junior and don't have strong enough coding abilities to keep up with HF pace.
Without knowing your personal situation, your best bet would be if you're a very strong data analyst or junior data scientist.
Alt data vendors are typically the first place recruiters look at when trying to fill an in-house DS/DA seat. Unfortunately the environment at most vendors either a) don't provide enough technical sophistication/training or b) does not encourage the DS team to think like an investor.
If you want to do alt data in HF, best bet would be to join a data team at a MM (these are always hiring for SDA) then branch out to a specific sub-sector/fund.
No trade secrets for you.
There were a ton of teams using credit card data for a while to trade consumer stocks. Apparently easy enough to monetize the data with a recent college grad data scientist, but I've heard that all the alpha is gone now
Agree in the sense that it’s now table stakes. Major funds all have the same data and markets react quickly to new data.
I’ve also seen predictive models at major funds NAIL revenue vs the street (I.e., huge beat or miss) and stock goes the other way on something else - guide, incrementals/decrementals, idio news, etc.
"It's all priced in."
Side question: all I've seen in alt data is for equities. Is there a use case for credit, macro, FX, commodities etc?
Ethanol traders using satellite and helicopter imagery at terminals to look at things like mold to gauge ho full storage is.
I actually know guys that are former construction engineers specializing in refineries and petrochemical plants that make their living do flybys on helicopters and sell their observations on the speed a relevant project is coming along since a plant startup/delay naturally has huge implications on the market.
Are alt data teams in HFs paid the same as investment teams? Or how are they viewed?
It depends on the fund/team. There are funds out there where a senior data analyst/scientist can move into a concurrent sub-PM role. Some funds firmly place alt data as back office (where comp/bonus is much lower). I would like to think that most shops classify alt data individuals as investment professionals and comp them the same. The ones that don't typically have a hard time retaining good talent.
On the last point, while there is a lot of people interested in this space, for firms who are picky (think non-MM SDAs) it can take well over a year to fill an alt data analyst seat.
98% of real creative/alpha producing use cases will never be shared outside the fund. The people who say there is no edge to be had aren’t doing it right or need to caveat ‘in my particular strategy’. There’s plenty of edge to be had. There’s limited scalability and almost no barriers beyond discovering a dataset. It would be bad business to tell anyone about it unless you’re marketing or it’s no longer useful. Hell you don’t even want the provider to know it’s useful or they’ll go sell it all your competitors. The satellite / oil tank story thing and private jet tracking things are examples where a creative use case was disclosed and now they’re completely commoditized or useless. Stuff that is obviously useful like credit card data is always bound to become commoditized. Early movers and creative application of data are real edges and should be a principle of funds today.
Spot on from what I've seen. The context I've always seen it as the more people know about it, that alternative data signal goes from alpha source -> risk factor to hedge out over its life cycle. A good way to see this is to look at how major alt data vendor's publications change tone over the years.
What if a vendor restricts the dataset to X users?
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