Review & Analysis

QP conducts rigorous evaluations of existing structures, models, and workflows, identifying conceptual weaknesses and quantitative blind spots that conventional consultancies routinely overlook. Review and analysis engagements are diagnostic in nature and grounded in academic standards of model validation, statistical inference, and economic coherence, and serve as a starting point of model refinement processes. They are designed to provide an independent, technically deep assessment of whether existing quantitative frameworks are internally consistent, methodologically sound, and fit for their intended decision-making purpose.

Rather than focusing on surface-level outputs, QP examines the assumptions, estimation techniques, and numerical implementations that drive portfolio, risk, and valuation models. This includes assessing sensitivity to inputs, coherence between investment beliefs and their formalisation in models, and the robustness of results under alternative specifications or stress scenarios. Particular attention is paid to issues that often remain hidden in practice, such as implicit leverage, unstable optimisation behaviour, or inconsistencies introduced through ad-hoc model extensions.

Beyond methodological evaluations, QP assesses data structures and analytical workflows, including data sourcing, transformation logic, and the interaction between manual tools and automated systems, with a focus on transparency, reproducibility, and scalability.