Case study

How We Created Impact for a Leading US-Based Long-Only Hedge Fund Focusing on Global Equities

Asset Management Services

BUSINESS SITUATION

• The client’s investment philosophy was to identify undervalued companies using a quantitative approach that leverages detailed financial models with different scenarios (Bull/Base/Bear) and a combination of relative and DCF valuation.

• The client wanted us to develop scenario-based financial models for the shortlisted 300+ companies globally.

• To maintain utmost confidentiality regarding the companies being researched or the proprietary template, the client needed a dedicated service area (DSA).

SGA APPROACH

• Set up a DSA with physical access control that could only be accessed by the respective SGA team or senior management

• Identified five resources experienced in building financial models across TMT, Consumer, Finance, Utilities, Energy, Healthcare, and other sectors, led by a dedicated Project Manager with 10+ years of experience with buy-side clients

• Developed understanding of the client’s proprietary template, and accordingly prepared standardized financial modeling templates for each sector

• Automated a process to capture historical financial statements from company filings (pdf) into a spreadsheet • Developed comp sheets for each sector for valuation and performance benchmarking

ENGAGEMENT

Dedicated five analysts and one project manager to develop financial models across multiple sectors as per the client’s proprietary template.

BENEFITS AND OUTCOMES

• Assumption-driven financial models, providing the user an option to fine-tune forecasts/valuation

• Coverage for both public and private companies • Adjustment for key corporate actions such as M&A and spin-offs

• Scenario and sensitivity analysis to make better investment decisions

• Verified information, sourced from company filings only

KEY TAKEAWAYS

• Delivered 300+ scenario-based detailed financial models with 100% accuracy

• Adhered to committed timelines barring exceptional companies where the historical numbers needed significant normalization to enable like-for-like comparison

• Automation for better quality and productivity

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