Finding value in supply chain data

In an era when a vast amount of real-time or near real-time data about companies is available, investors are seeking an edge using information that ranges beyond earnings calls, quarterly reports, and the classic fundamental measures of corporate performance.

Data on the global supply chains of large international firms help investors study the web of interactions between companies, their suppliers, and their customers. This information can help analysts glean insights on a company’s current performance and future prospects in the global marketplace.

A quantamental approach with supply chain insights

The use of supply chain data as part of a conjoined fundamental-quantitative research framework, often referred to as a “quantamental” approach, may help investors avoid some of the drawbacks of the standard top-down methods for stock screening and selection. In pure fundamental analysis, analysts face the problem of selecting a small set of investments subject to unknown idiosyncratic risk. At the other end of the spectrum, the surge of passive strategies and factor investing have led to investment across very broad sets of names, where the risk centers on exposure to systemic factors.

Examination of a company’s relationships across the supply chain can inform analysis of historical data, firm shocks, and operational performance. It can reflect and highlight the depth and breadth of global business relationships for firms both large and small. In doing so, it can drive compelling analysis of individual firms, their customers and suppliers, their industry sectors, and even activity within specific geographic regions.

Testing a customer momentum factor

Bloomberg’s Quant Research team evaluated the efficacy using information on supplier company’s customers as a factor in investment decision-making. The research utilized the Bloomberg supply chain dataset, an extensive resource with coverage of 23,000 public companies, 100,000 private companies and more than 800,000 supplier-customer relationships.

The research built on classic factor models with the addition of quantitative metrics for customer momentum. Supply chain data makes it possible to show how much revenue is generated by a given customer and express it as a percentage of the supplier’s total revenue stream. Taken further, it enables a quantification of aggregated customer momentum, across various time horizons and calculated by region.

This added customer momentum factor can be back-tested to provide insight on its efficacy, with a multi-step process to maximize the value of the data in developing new strategies. This analysis was conducted comparatively over three global regions, represented in the U.S. by the S&P 500 and Russell 3000 indices, in Europe by the STOXX 600 and in Japan by the TPX. Time horizons considered for constructing the momentum factor ranged from one day to twelve months

Simple quintile long/short portfolios were used to demonstrate the performance characteristics of the strategy. The new factor analysis was examined against other factor portfolios, including the Fama-French 3-factor framework and the Carhart 4-factor framework.

Demonstrating the potential of supply chain data

In certain regions and over specific horizons, supply chain customer momentum is a significant driver of supplier returns, and it behaves differently than conventional Fama-French and momentum factors. This research shows the deep wealth of potential possibilities in supply chain data for investment firms that take a rigorous approach to its application.

Download the white paper to learn more about the research and the full conclusions.