Portfolio Optimisation

Delivering advanced analytics and AI to funds in a managed service wrapper.

Portfolio Optimisation Managed

Let us help you to get the best returns from your portfolio by applying algorithms to optimise those portfolios. All we need is some of your data to prove the value of this approach.

Models Include:
  • Classical Portfolio Optimization
  • Fat-tailed Risk Optimization
  • Neural Network-based Portfolio Optimization
  • Nonlinear and Option Portfolios
  • Asset Liability Management
  • Liability Driven Investment.


  • Principal Component Analysis (PCA)
  • Independent Component Analysis (ICA)
  • Kernel PCA
  • Deep Component Analysis (DCA)

Component Weighting

Weighting components to maximise return per unit of risk

Kelly weighting
  • Risk is Gaussian
  • double return -> double weight
Power law weighting
  • Risk has tails
  • double return -> less than double weight

Fixed weighting (in suitable units)

  • Risk has fat tails
  • double return -> same weight

Non Linear Portfolios

  • Options
  • Implicit optionality around drawdowns
  • There is no static optimal portfolio
  • Dynamic hedging of the portfolio
  • Kernel PCA
  • Deep Component Analysis
  • Neural Network Hedging
  • NLP

NLP Algos

  • An ability to take instrument id data from a portfolio and feed it into a platform that can continuously monitor and interpret signals from virtually any data source using natural language processing. Then feed that interpretation back in the form of summarised, actionable information.
  • To do this in near real time.
  • To do it in a way that is auditable and demonstrable to investors.
  • Used for monitoring social media and other types of text based media.