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Portfolio Optimization Automation
Jun 01 2022 |7 min read
Problem Statement
  • Reduce the cost and provide more capabilities and transparency for outsourcing portfolio optimization. 
  • Leverage the Analytics capabilities, along with cutting edge technologies to support automated portfolio optimization.
Project Objectives
  • Setting up a third party tool for stats models and its APIs for portfolio optimization.
  • Achieve cost savings of $5.5 Mn/Year.
  • Help increase the equity trading capabilities of clients.
  • Fully automate the trading workflow – from the inception of trade to finally booking them and ensuring hassle-free end-to-end trade flow.
  • Application development and set-up of Data Validation and Reconciliation model.
  • Provide GUI to visualize the daily automated steps and take actions based on market conditions.
Scope of Work Included
  • Merge equity risk data coming in from 5 different market vendors and wire that with in house portfolio and benchmark risk measures to prepare input feeds for optimizer.
  • Scheduling of optimizer runs based on cash inflow updates for the day.
  • GUI based in Dash(plotly, flask based ) to track the cash inflows and various trading stages in the system.
  • Data Validation and reconciliation between different systems(optimizer and EMSX).
  • Store each configurable parameter in Oracle Database and develop flexible application to adapt to market trends quickly.
Approach Followed
  • Step by step approach using the adapter design pattern for workflow design.
  • Auto DevOps enabled for continuously and automatically integrating code updates to app.
  • Each step has a test and data validation step wired with it to ensure high data quality.
  • Clearly segregating and documenting the role of each team/member to ensure high quality and on-time delivery.
  • Continuous monitoring and comparison of the performance of in-house optimized portfolio vs outsourced portfolio until they go live.
Technology Stack
  • Core Technologies: Python, Cash, Bash,
  • Python Frameworks: Flask, Dash
  • Configuration Management: SVN/Git, Quick build and Gitlab(CICD), JIRA
  • Databases: Oracle SQL Developer, AWS S3 Data Store
Sunil Kumar

Sunil Kumar

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