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March 13, 2026 Content Type Case study

Public fund manager unlocks informed investment decisions with automated stock selection

March 13, 2026 Content Type Case study
 

    Background

     

    A public fund manager covering 150-300 listed companies needed a real-time decision matrix that ensured portfolio positions were in line with the rankings of the team’s covered stocks. The goal was to develop a ranking system that would become one of the sources of idea generation, help with portfolio rebalancing and post-trade review, and encourage structured decision-making.

     

    Challenges

     

    • Ranking focused on past results, not fundamentals: Stocks were ranked primarily on invested capital and past returns, rather than fundamental strength and expected returns
    • Portfolio not aligned with market performance: A significant number of stocks expected to generate high returns were often missed
    • Manual and slow review process: Portfolio monitoring was error-prone and slow due to reliance on manual steps
    • No consolidated decision matrix: The portfolio, watchlist and exited stocks were not tracked on a common scale, limiting cross-sectional analysis and structured portfolio reallocation
    • Decisions influenced by subjectivity: A bias towards historical performance sometimes overlooked leverage risks, management quality issues and forward earnings improvement

     

    Our solution

     

    • Aligned ranking with fundamentals and expected returns: Built a composite score combining fundamental strength and expected returns, ensuring that decisions reflect both quality and upside potential
    • Linked ranking directly to portfolio decisions: Built clear rules into the dashboard—top-ranked stocks not held require explanation, and lower-ranked holdings must be reviewed. Alerts flag opportunities after earnings changes or price corrections
    • Fully automated updates: Automated data flow, from input to dashboard. Live pricing and scheduled refresh update the entire universe in ~15 minutes
    • Unified and transparent framework: Created a single 0-100 scoring sheet covering portfolio, watchlist and exited names. Each score can be broken down into drivers, making ranking movements easy to understand and discuss

    Impact

     

     

    Time saved:


    Weekly ranking and review time fell from ~4 hours to ~15 minutes (~90% faster)
     

    Better accuracy:


    Automation and live pricing reduced manual errors by ~90% and kept rankings up to date
     

    Improved alignment:

    Portfolio weight in top-ranked stocks rose 40-50%, strengthening investment discipline

    Quicker decisions:


    Review preparation time dropped from a full day to ~30 minutes, enabling faster action
     

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