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Formerly known as Global Research & Risk Solutions

  • Crisil Integral IQ
  • Principal Component Analysis
  • Quant Modeling
  • Strategy Research
November 21, 2025 Content Type Case study

Enhanced macro strategy research quality and indices coverage of a global bank using scalable Quant model

November 21, 2025 Content Type Case study
 
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Background

  • A leading global investment bank’s macro strategy research team, renowned for its top-down approach to forecasting equity indices, was facing a challenge—limited ability to scale coverage across European indices. The reason? Its dependence on large and resource-intensive traditional forecasting models, which also constrained the team’s capacity to provide comprehensive research to its clients
  • It engaged us to expand the coverage to include global indices and major stocks, and enhance the value proposition of its research services

Crisil Integral IQ solution

  • We employed a Principal Component Analysis-based framework on Python that distilled a wide universe of equity indices into a few key components
  • Each component was rigorously back-tested against macroeconomic drivers, identifying patterns with relevant statistics and enabling forecasts with high confidence levels, based on house views for the underlying drivers
  • We used these components in reconstructing the respective indices to complete with forward-looking predictions
  • This approach improved model efficiency and helped identify new macroeconomic drivers not used in the legacy models. This, in turn, increased overall model quality
  • Efficient python coding ensured forecasts for the entire suite of coverage indices were generated in minutes, significantly streamlining the research process
  • This modelling approach was immediately adopted by the bank and the research team integrated the underlying analysis and research into its publications

Client impact

  • The efficient model framework helped enhance coverage of equity indices by 20%
  • The strategy team could initiate top-down forecasts for all stocks under coverage enabling new research avenues
  • Time spent on model maintenance reduced by 30%, allowing the team to sharpen focus on client communication and marketing
  • The high-quality forecasts sparked increased interest from investor clients of the Bank
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