QSQuantSpace

Quantitative Finance

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QuantSpace JSE Factor Engine

Live Streamlit model for JSE factor analysis, factor views, and quantitative equity intelligence.

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Problem

Investment teams need repeatable factor views for JSE-linked opportunity sets without rebuilding factor tables manually.

Solution

A deployed model app that packages JSE factor analytics into accessible views for research, screening, and portfolio interpretation.

Users

  • Quant analysts
  • Portfolio managers
  • Research teams
  • Investment strategists

Business Model

Model demonstration, research subscription, factor library licensing, and institutional analytics support.

Contact

george@quantspace.co.za

Architecture

Streamlit application with Python factor calculations, market data transformations, analytical tables, and dashboard presentation.

Technology Stack

  • Python
  • Streamlit
  • Pandas
  • Factor modelling
  • Equity analytics

George's Role

Product architect and quantitative builder responsible for factor workflow design, model packaging, and product positioning.

Live Models

Deployed quantitative model apps

Proof Points

  • Live deployed model app available for review.
  • Turns factor analytics into a usable research product.
  • Backed by a dedicated GitHub repository and deployable Streamlit architecture.

Roadmap

  • Expand factor library coverage and documentation.
  • Add portfolio attribution and screening workflows.
  • Package outputs for research reports and API delivery.

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