Leveraging New Technology to Improve the Fundamental Investment Process

The Chartered Alternative Investment Analysts Association (CAIA) has published an article, entitled "Including Investment Process Technologies within Operational Due Diligence", by Dana Lambert and Rayne Gaisford. The EDS Intelligent Search technology is featured, and we are including highlights from the article: 

 

"The tools and processes below help enable more process-centric techniques for a manager’s fundamental investment program. These approaches complement a comprehensive and repeatable due diligence methodology effectively, and therefore help enhance alpha generation when weaved effectively into a firm’s behavior. 

 

There are tools the “Big 4” data vendors (Bloomberg, FactSet, Thomson Financial and Capital IQ) offer that represent an initial layer to this type of screening, but often they lack the ease or dimensions needed to give this process repeatability and scale. This is where platforms like Equity Data Science (EDS) can play an appropriate role, in assuring all historical and projected valuation, fundamental, trading, and other relationships make for the most compelling research ideas. EDS’s “quantamental” platform has helped its users identify inefficiencies in the broader universe where, as a starting point, favorable data point to the greatest ROIs on one’s research time. The notion is to present instances where there is a statistical alignment of stars, so to speak.

 

This might imply for a particular stock an analyst is evaluating for the long side of the book, for example:

 

  • A low relative valuation (and versus companies with similar financial profiles outside the specific sector in question);

  • Improving fundamentals (sales, EPS, ROIC, etc);

  • Upside revisions in earnings estimates.

  • Margins with upside potential relative to historical levels;

  • Declining short interest; 

  • Low relative crowdedness;

  • The beginning of a shift from value holders to growth investors;

  • Improving sector fundamentals;

  • Positive correlation to a market-based factor that is coming into favor, such as a certain market cap levels or interest rate sensitivity, etc.;

  • Sell-side ratings that imply room for numerous upgrades;

 

EDS can show all of these kinds of measures on one screen, with graphical illustrations and color-coded and Z-score-derived quintiles for appropriate quantifications. In so doing, the platform provides an abundantly clear picture that helps users identify the increasingly rare inefficiencies in the broader universe. This means users can quickly see where as a starting point, favorable data point to the greatest ROIs on one’s research time. 

 

The EDS platform has been in development since 2013, and currently has multiple customers. Where the system is in use at its current clients, it effectively replaces a dedicated data analyst and rudimentary, non-database linked screening tools (most often Bloomberg data pumped into Excel).

 

While all the fundamental and market-centric data that analysts and PMs need exists in a Bloomberg or a FactSet, it is the optimal presentation of this data, coupled with critical calculations (e.g., regression and correlation analysis), that allows for substantial time savings and efficient information digestion on the part of a user. Showing all critical elements and calculations in one dashboard makes EDS a much more elegant approach to leveraging such an overlay. Unlike other fin-tech platforms, EDS has no manual data input requirement and encourages ever-increasing usage, because more time with it equates to limitless comparative, precise, and profound insights into one’s portfolio and wider idea universe.

 

Key attributes and use cases include:

 

  • Offering rapid and complete data perspectives based on both historical and projected data, including predictive, cross-sectional valuation analysis and regressions, ownership and liquidity trends, sensitivity analyses, correlation screens, and key information for event monitoring and preparedness (cross-sectional analysis implies a PM can look at metrics across multiple sectors, comparing a company in one sector to all other companies that share similar valuation and market-based measures regardless of sector).

  • Saving substantial analyst time and effort that might otherwise be spent manipulating, regressing, and/or rank-ordering valuation, attribution, correlation, performance and risk metrics in Excel, all to get the same answer a dedicated platform like EDS provides with a single mouse-click or pre-loaded view.

  • Ranking a fund’s active portfolio by assets demanding the greatest attention or actionability, providing an organized daily workflow whose main purpose is to create immediate responsiveness and thereby maximize alpha generation.

  • Determining the most appropriate price targets and projected valuations, so that PMs can increase their conviction using evidence- or historically-based data constructs to pinpoint the most likely future valuation parameters.

  • Providing an overall technical and fundamental score that is statistically appropriate and unbiased – for both the entire portfolio or an individual idea – and at a higher level a perspective highlighting whether the exposures the PM has are consistent with the fund’s strategy or positioning.

  • Measuring potential event risk, by enabling clients to understand quickly and visually the current trend in analyst revisions or surprises, as well as performance going into events such as earnings or analyst days.

  • Engaging in correlation analysis, so users can understand factor relationships (such as stock movements vs. interest rates), which can provide both the raw material for idea generation, and a clearer picture of the market environment."

 

Thank you to Dana and Rayne for this exciting overview of our platform. For more information, please contact us at sales@equitydatascience.com or Greg McCall at 203-451-6741.

 

 

 

 

 

 

 

 

 

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