“A small unexplained residual proves the valuation model is correct.”
Not quite.A small residual is useful control evidence but can coexist with shared data or model errors.
Risk
P&L Explain and Attribution
P&L explain decomposes daily profit and loss into risk-factor moves, new trades, and residuals.
Mental model
P&L explain decomposes the day’s result into understandable market, trade, and residual effects.
P&L explain compares today’s P&L to what would be expected from yesterday’s Greeks and observed market moves.
A clean decomposition separates market-driven P&L, carry and time decay, trade changes, and unexplained residuals.
Explore the mechanism
How much of today's P&L is explained by measured risk-factor moves, and what remains unexplained?
This waterfall decomposes one day of P&L into market move, carry, new trades, and residual. Use the controls to change total P&L and the size of systematic components and see how large the unexplained bucket becomes.
Explain ratio ≈ 95.0%
Numbers
Market P&L ≈ 0.660m · Carry ≈ 0.240m · Trades ≈ 0.240m
Explained P&L ≈ 1.14m · Residual ≈ 0.060m
Explain ratio ≈ 95.0%
Interpretation
P&L explain asks a very concrete question: given yesterday’s Greeks and today’s market moves, plus known trade changes, what P&L should we have seen?The difference between this expected P&L and the realised figure is the residual.
A small, noisy residual is healthy and reflects model miss and higher-order effects. A large, persistent residual hints at deeper issues: stale data, booking problems, wrong risk factors, or structural model deficiencies. Effective control frameworks monitor that residual line as closely as the headline P&L.
UNDERSTAND
What to notice
The analytics framework must provide consistent risk factors and valuations for P&L explain to be meaningful.
Large unexplained P&L signals model, data, or booking issues and is a key control for trading and risk.
Where it appears
- daily trading-desk controls
- validating sensitivities and market data
- separating new-trade, carry, and market effects
Where the intuition breaks
What this view leaves out
- Attribution depends on factor ordering, approximation choices, market snapshots, and model consistency; a residual is evidence to investigate, not automatically an error.
Common mistakes
Where this concept sits
Follow the strongest prerequisites, applications, extensions, and contrasts.
Connections for P&L Explain and Attribution
P&L Explain and AttributionYOU ARE HERE
Built onMark-to-MarketP&L explain begins from changes in marked values between valuation points.
Supported byGreeks and Risk FactorsRisk-factor sensitivities provide the first-order building blocks for explaining daily valuation changes.
Supported byData Lineage and Audit TrailLineage helps determine whether an unexplained P&L move came from market data, transformations, model versions or other upstream changes.
Supported byMarket and Model VersioningVersion changes must be distinguishable from market moves when explaining P&L.
Supported byReplay of Valuation RunsReplaying prior and current valuation states helps distinguish market moves, model changes and data corrections in P&L explain.
Built on · Mark-to-Market
P&L explain begins from changes in marked values between valuation points.
Explore concept →