Short, plain-English pieces on how institutional market data should be collected, cleaned and interpreted. All are descriptive — no forecasts, no recommendations.
Key considerations when assembling long-run history across equities, rates and commodities — and why consistent adjustments matter.
Read note →How source differences, time-zone handling and corporate-action adjustments silently skew datasets.
Read note →A purely retrospective look at indicator behaviour and asset-price dispersion. No forecasts.
Read note →For internal research teams, the value of documentation, ownership and a known-issues register.
Read note →When a daily refresh is enough, and when the cost of a real-time platform is justified.
Read note →The small set of quality indicators that actually tell you whether a dataset is usable.
Read note →