The growth of technology-influenced investing that utilizes algorithms and other quantitative methods has led to a mismatch between the skills of traditional investors and the tasks they are now required to carry out.
On May 15th, 2018, Eagle Alpha organized an online meeting attended by twenty-one asset management firms to discuss the topic of testing alternative datasets for quality.
The purpose of this report (attached) is to provide data owners with advice on how to sell their data to asset managers. This report is the first in a series of reports published by Eagle Alpha.
Sixteen asset management firms joined this meeting held on April 24th 2018 in New York City. Most vendors of alternative datasets do not currently map their datasets to financial instruments.
Thirteen asset management firms joined this online meeting held on April 10th 2018.
The attached paper was prepared by researchers working at the Monetary Department of the Riksbank, the central bank of Sweden.
This webinar was prepared by Dr. Derek Greene, Eagle Alpha's advisor on data science strategy.
This webinar was prepared by Dr. Derek Greene, Eagle Alpha's advisor on data science strategy.
To back-test data, a dataset is divided into a training portion and a testing portion. The typical split of the data is 50/50 or 66/33. A model is built using the training data.
At Eagle Alpha, our analysts are always conscious of the tradeoff between improving the collection technique for a data source while still maintaining the integrity of the signal derived from that source.
Eagle Alpha’s Search Signals product consists of a series of company revenue indicators constructed using Google search volumes for a company’s product offering.
The science of artificial intelligence and alternative data isn’t fiction anymore.
