Geolocation and COVID-19: What to Expect
With the COVID-19 outbreak Eagle Alpha has seen a surge in requests for geolocation data. This article addresses methods of data collection and detailed advice on selecting a GDS provider.
With the COVID-19 outbreak Eagle Alpha has seen a surge in requests for geolocation data. This article addresses methods of data collection and detailed advice on selecting a GDS provider.
Google search data can be used for conducting competitive analysis, measure traction of new products, or to build signals on revenue growth/same-store sales
The new iOS 14 will allow consumers to limit how much location information they have to share and provides users with more options to restrict what information they have to share on apps.
Lucena's Analysts Consensus Retrained (ACR) has enjoyed a year-to-date return of 39.2% – approximately 48% higher than the S&P 500 (its benchmark) for the same period. What’s more important is that it was able to achieve this with significantly reduced volatility and sustained growth.
When it comes to trading strategies, we develop models that are approximations of the reality of the market. We choose specific datasets or factors to incorporate into a model. Trying to incorporate every nuance of the market into a single model isn’t feasible.
The following examples show various types of alt data that can be applied to Match Group.
The following examples show various types of alt data that can be applied to Fever Tree.
There is a wide variety of alternative data that can be applied to the automotive sector to obtain granular fundamental insights.
FISD Alternative Data Council/Greenwich Report: A Guide to Alternative Data
The following examples show various types of alt data that can be applied to gaming related stocks. Sample Companies that the data can be applied to are Ubisoft, Electronic Arts, Activision, Take Two.
We summarized expert responses to the question: "Is AWS the best cloud solution for working with alternative data, or are Azure and GCP viable alternatives?”
In increasingly efficient markets, the challenge for investment professionals to generate value beyond commoditized smart beta factors has intensified. This has put a spotlight on creating alternative datasets from big data and extracting value not already reflected in the market.