Data Integrity
Duplicate rows, stale snapshots, invalid vendor markers, mixed numeric formats, and accidental lookahead can materially change a ranking system.
MidLincoln Research & Advisory
Ranking System Audits for Investment Teams
MidLincoln helps asset managers, research teams, and family offices evaluate whether their ranking models are robust enough for real allocation decisions. We focus on point-in-time data integrity, peer-normalized factor architecture, backtest design, and stability diagnostics.
What We Help Clients Find
Ranking models often fail because of hidden data problems rather than weak investment ideas. A robust audit checks whether the inputs, transformations, peer groups, and return windows are aligned before anyone trusts the output.
Factor Architecture
Signals should be normalized against relevant peers and tested for concentration, instability, and unintended exposure.
Backtest Validity
Forward return windows, lag rules, neutralization, and outlier handling determine whether a backtest is informative or misleading.
Consulting Retainers
Engagements are designed for teams that already have data, models, screens, or investment heuristics and need an independent research partner to make the system testable and defensible.
Ranking Model Audit
- Data lineage review
- Factor normalization review
- Lookahead and survivorship checks
- Backtest redesign
- Executive findings memo
Research Retainer
- Monthly model diagnostics
- New factor experiments
- Portfolio selection reports
- Model drift monitoring
- Decision-support dashboards
Custom Build
- Equity ranking systems
- Sovereign and macro ranking frameworks
- Country and sector-neutral testing
- Prototype pipelines
- Internal documentation
Signals Without Giving Away the Recipe
Public examples can show the discipline of the research process without disclosing proprietary coefficients or exact model rules. We describe factor families, diagnostics, and portfolio-level evidence while keeping the implementation private.
Public-Safe Disclosure
Valuation, quality, growth, balance-sheet strength, shareholder yield, size, and momentum can be discussed as factor families.
Private Work Product
Exact coefficients, mapping rules, vendor fields, data joins, and model variants stay inside the client workroom.
Representative Case Study Results
In a recent global equity ranking reconstruction, higher-ranked groups showed the strongest separation over medium-term horizons after point-in-time controls and outlier-aware summaries.
Representative historical backtest spreads, winsorized, before transaction costs. Backtests are not forecasts and do not guarantee future results.