Quantstar’s Portfolio Risk Optimizer builds upon its existing Mean-Variance Portfolio Optimizer by adding a full array of VaR based portfolio optimization features. This optimizer estimates the Value at Risk (VaR) of a portfolio and maximizing the expected portfolio return subject to a VaR or Conditional VaR constraint.
The basic model of returns will be a factor model based on relevant indices. VaR is computed using a Gaussian copula, a t-copula, a Monte Carlo simulation and the historical distribution of returns.
Overview of Quantstar’s Portfolio Risk Engine
Quantstar’s MVO will integrate with the overall Portfolio Risk Optimizer engine.
This module will implement the optimization engine to determine the optimal asset allocation given the user specified target VaR constraint. The specific optimization technique will be developed by Quantstar based on our proprietary models.
This component will implement the conditional VaR based portfolio optimization engine.
The above schematic presents the conceptual architecture of the Portfolio Risk Optimizer and identifies the key building blocks. Quantstar provide the core computation engines including the VaR calculators and the portfolio optimizer in the form of reusable components. The end user can then custom develop all the remaining pieces which integrated with our engines and have a complete solution. The end-user can also engages Quantstar’s professional services to build or integrate this framework into a new or existing application
The final solution will provide the end users with the following enhanced functionality:
▶ For a given portfolio the end user can choose between the mean-variance optimizer and/or the VaR based optimizer to achieve an optimal asset allocation.
▶ The end user can now have the ability to include instruments which can be categorized as alternative investments which have non-normal returns. Some of these can be hedge funds, commodities, real estate etc.
▶ The users can integrate the Portfolio Risk Optimizer with the Portfolio Risk Analyzer to implement a comprehensive risk analytics platform within their organizations.