Hamel's expertise in algorithm design is centred on two areas: mathematical and financial modelling; and processing efficiency. We design all algorithms to achieve the best computational efficiency possible, primarily because it leads to highly robust coding with clear audit trails, but also because we often tackle challenges that push the limits of available computing power.

 

Mathematical and financial modelling

We've cracked some of the hardest challenges going, including creating non-linear behavioural algorithms which are defined dynamically on the fly, and designing auditable parallel processing routines for Monte Carlo simulation. Other modelling achievements have encompassed:

Forecasting demand elasticity, in highly competitive markets with freely available substitutes.
Demand forecasting of consumer markets, distorted by unilateral and multilateral agreements.
Simulating operational behaviour in the supply chain.
Simulating IT process behaviour.
Forecasting performance of securitised products.
Forecasting balance-sheet performance of manufacturing companies.
 

 

Processing efficiency

By definition, good coding is efficient coding - and efficient coding provides clear audit trails which is particularly useful for investigation by third parties and regulatory organisations. That aside, the challenges that our clients engage us to address is such that we often meet the limits of computational power. Therefore we invest a lot effort in creating algorithms that are highly efficient. The benefit to our clients is that we deliver robust, low-maintenance software.