Quantitative Analytics Practice seeks to understand and expose causal relations between relevant variables by applying mathematical and statistical modeling to raw databases. The goal is to extract reliable conclusions based on observable facts.

The output of our Quantitative Analytics Practice is a powerful tool when applied to financial instrument assessment, demand behavior study, client segmentation, demand elasticity analysis and general market trends identification.

Our quantitative analytics experts have experience working with databases of financial, statistical and market information such as Bloomberg, Thomson Reuters and Compustat, and with relational database systems like SQL. The team is also proficient in statistical software packages such as Eviews and Stata, and programming languages including C#.NET, C++, Java and VBA.