Takeaways from Eagle Alpha London 2024

Over the years the number of datasets which have come to the market have increased significantly. How do data buyers in the buy and sell side find such data? One way has been to approach individual sources of data, whether it is data vendors or corporates, ie. through outbound requests, often as a result of specific questions from the business whether that is data scientists or portfolio managers. The flipside, inbound requests, where data vendors seek to find data buyers has also been another approach.

Data conferences seek to bring together both data buyers and sellers in one place to make this whole process efficient, most notably the Eagle Alpha conference in London, which I recently spoke at and attended. In this article, I'll look to write some of main takeaways from the Eagle Alpha conference. Whilst, I can't cover every session, I'll try to give a flavour of some of the discussions.

The supply of data and the market

Niall Hurley gave the keynote address at the conference discussing how their Eagle Alpha platform has around 2000 datasets on it, alongside due diligence documentation. The idea of the platform is to allow data buyers to quickly browse what's out there instead of having to separately approach many data vendors themselves, which can take a lot of time. He noted how we are now in a post covid era for alternative data. One thing that been said to me many times, was that it became very apparent during covid was that alternative data could plug gaps in more traditional datasets because of publication lag. Despite the view that everything has normalised, I still believe there is tremendous value in alternative data not purely from the perspective of plugging that publication lag, but also in terms of giving your different insights. Hurley also made a parallel between the shale gas revolution and the falling costs of extraction with that in terms of getting new datasets to market. Supply of data from corporate environments could be one of the new stories.

Also on the topic of supply data there was a discussion with Mark Fleming-Williams (CFM) and also the presenter of the fantastic Alt Data Podcast and Connor Emmel (Apptopia) discussing the data market. Given the session was a closed session purely for data vendors, I won’t discuss the specifics of the discussion. However, it was very useful from my perspective, despite being in the alt data space for quite a long time. The session went over some of the aspects of the whole data selling cycle. I think my key takeaway is that clients can be very different, and also based on my own experience of being at Turnleaf Analytics. For example, a discretionary fund will have a very different approach to data compared to a systematic fund, and vendors need to be cognoscente of this. This is of course is not the only difference between data buyers, but it is perhaps one of the clearest differentiating factors.

Macro, inflation, data and point-in-time

I appeared on a panel on macro and inflation (thanks James Munro for the above photo!), which was moderated by Brendon Furlong (Eagle Alpha), alongside panelists Lasse Simonsen (JPMorgan/MacroSynergy) and Meghna Shah (Macrobond). Typically, when people think of alternative data, it is mostly related to data for individual companies most suited to equities investors. Indeed, whilst there are still more equity based datasets, macro datasets in alt space are growing. One the complexities of using macro data is that trying to map it to an asset can require more domain knowledge knowledge.

If we think more broadly about macroeconomic data it is also different to market data. One difference is that you can have many timestamps associated with the same point....

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