Criteria to judge datasets

There are McDonalds everywhere. It’s probably the most ubiquitous fast food joint. If you want a burger, and want it quickly, it not a bad choice (double negative intended). Is it the best choice for a burger? My uncontroversial response would be, no. I doubt many readers would find an issue with my answer. There are many other burger joints which have much better burgers. It all comes at a cost however, not just financially but also in terms of time. You want a great burger, you’ll have to wait for it to be cooked, and it’ll cost more than a Big Mac. My point is that ubiquity and low cost aren’t always the only criteria you’d use to judge a burger.

Data, like burgers, is ubiquitous in our society. It drives the largest companies such as Google, and how you use data is not purely a question for tech firms. For investors, data has always been a key part of the investment process. Today there are more datasets available for investors. Some of course are traditional, such as market data and economic fundamental data. However, there had been a huge increase in alternative data, datasets which haven’t traditionally been used in finance. These can range from machine readable news to satellite imagery.

When it comes to buying data, what are investors looking for? If you want to know more about this, in The Book of Alternative Data, which Alexander Denev and I are coauthoring (available for preorder on Amazon), we seek to answer this question in a lot of detail. Here, we’ll try to summarise a few of the major points however...

To read the rest of the article on the Cuemacro website, please click here!