Testing showed that firms with lower employee turnover systematically outperformed those with higher turnover rates.
Completely unique in the industry, the job listing dataset only indexes jobs directly from employer websites.
Accelerating growth in active job listings and Google search data were used to correctly call improving momentum for Palo Alto Networks.
Accelerating growth in active job listings and Google search data were used to correctly call improving momentum for HubSpot.
Negative growth in active job listings and Google search data were used to correctly call worsening momentum for Chipotle.
Testing shows that there is alpha in the data, with the “Jobs Active” variable producing the highest and most consistent returns (6-8% yearly).
Analyzing job listings data, from an Eagle Alpha data partner, can reveal insights on company fundamentals.
Eagle Alpha analysts have spent over three years finding the best way to use online search data to predict economic indicators. Eagle Alpha has devised its own proprietary methodology that leverages all relevant academic research, as well as accepted best practices in the field.
Asset managers constantly ask Eagle Alpha for case studies that demonstrate how alternative data can add value to their investment process. In response to this demand Eagle Alpha will regularly publish a compilation of case studies. This document is the first in this series.
Starting with macro-related alternative data, we investigate the appeal of web search data to predict macroeconomic indicators which in academic literature shows some promising results.
his article highlights some of the most actionable research reports that Eagle Alpha published in 2015.
