Research
MorMag believes rigorous research is the foundation of effective capital allocation. Our analysis combines macroeconomic insight, company-level fundamentals, and long-term structural thinking to identify opportunities across global markets.
Featured Research
Why Most Stock Prediction Models Fail
Many predictive models fail due to overfitting, unstable signals, and changing market dynamics, highlighting the importance of robustness, validation, and disciplined modelling practices.
Who We Are at MorMag
An introduction to MorMag Asset Management, outlining the firm’s philosophy, research approach, and commitment to disciplined, long-term capital allocation.
Feature Engineering in Financial Machine Learning
Effective feature engineering transforms raw financial data into meaningful signals, enabling models to capture patterns within complex and evolving market environments.
Signal vs Noise
Financial markets generate enormous volumes of data, yet distinguishing meaningful signals from background noise remains one of the central challenges of quantitative investing.
Building a Market Intelligence Engine
Designing a systematic market intelligence framework requires integrating data pipelines, analytics, and modelling tools to uncover patterns across global financial markets.