June 14, 2024
Researchers used RavenPack Job Analytics to predict future company performance and stock returns.
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Wolfe Research, a prominent financial research firm, has introduced a novel stock selection model that leverages job data. Their study, titled "Alpha Insights from Global Job Postings Data", utilizes a comprehensive daily database provided by RavenPack, offering insights into global job postings since 2007.
The data extends beyond traditional job numbers: it incorporates the skills mentioned and locations specified in job postings, providing a detailed picture of a company's talent needs and geographic focus.
The Wolfe Research team constructed hundreds of potential stock selection signals based on this data, focusing on job postings, the specific skills mentioned, and locations. Their analysis revealed a correlation between a company's hiring trends and its future stock performance.
“Firms only engage in hiring when they are confident that the increase in labor costs can be offset by subsequent demand for their products and improvement in revenue, suggesting that hiring decisions can be forward-looking indicators of firm fundamentals and stock performance” note the authors in their research motivation. “However, high and persistent hiring could also signal potential managerial overconfidence or misalignment with shareholder interests, such as empire-building, which might negatively impact shareholder value.”
Firms only engage in hiring when they are confident that the increase in labor costs can be offset by subsequent demand for their products and improvement in revenue, suggesting that hiring decisions can be forward-looking indicators of firm fundamentals and stock performance.
The study goes beyond simply analyzing overall hiring trends. By employing Natural Language Processing (NLP) techniques, the researchers were able to dissect the technical skills mentioned in job postings. This provided insights into a company's adoption of new technologies, potentially signaling future areas of growth.
The research also examined the geographic scope of hiring activity. The analysis suggests that growth in existing locations and developed markets is viewed most favorably by the market, likely due to the lower associated uncertainty.
High and persistent hiring could also signal potential managerial overconfidence or misalignment with shareholder interests, such as empire-building, which might negatively impact shareholder value.
To translate these findings into a practical tool, the Wolfe Research team developed the JSL model (Jobs, Skills, and Locations). This stock-selection model leverages the insights gleaned from job posting data to identify promising stocks for investment.
According to the paper, the JSL model demonstrates:
the model offers data for nearly 4,000 companies across major markets including the US, Canada, Europe, and Asia.
the model identifies investment opportunities with returns that are independent of broader market trends in most regions.
Sharpe ratios surpass industry benchmarks by a factor of 1.2 to 1.5.
This research contributes to the growing body of evidence highlighting the value of job analytics in financial analysis.
If you'd like to learn more, you can get in touch with Wolfe Research to access the full paper as well as explore other studies on the value of job analytics:
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