# P&L and Performance Attribution

> Performance attribution explains where returns came from: allocation, selection, factors, Greeks and costs. Learn Brinson attribution, P&L explain and how to use it.

Source: https://learn.tradelabsai.com/industry/performance-attribution/  
Track: The Trading Industry · Level: Advanced · Updated: 2026-10-03  
Publisher: TradeLabs AI (https://tradelabsai.com). Education, not financial advice.  
Cite as: TradeLabs Learn, "P&L and Performance Attribution", https://learn.tradelabsai.com/industry/performance-attribution/

Knowing that a portfolio returned 9% is only the start. Performance attribution breaks that return into its sources: how much came from the market, from sector choices, from individual stock picks, from factor exposures, from currency moves or from trading costs. On trading desks, the equivalent is P&L explain, which splits daily profit and loss into the effects of price moves, volatility, time decay and new trades. Attribution separates skill from luck and intended bets from accidental ones.

## Brinson attribution

The Brinson model, from work by Gary Brinson and coauthors in the 1980s, splits active return versus a benchmark into:

| Effect | Question |
|---|---|
| Allocation | Did overweighting or underweighting sectors help? |
| Selection | Did the stocks chosen within each sector beat that sector? |
| Interaction | The combined effect of weight and selection differences |

**Example: A two sector attribution**
A benchmark holds 50% technology returning 10% and 50% energy returning 2%, a total of 6%. A portfolio holds 70% technology, whose holdings returned 12%, and 30% energy, whose holdings returned 1%, a total of 8.7%. Active return is 2.7%. Allocation effect: (70% minus 50%) times (10% minus 6%) plus (30% minus 50%) times (2% minus 6%), which is 0.8% plus 0.8%, or 1.6%. Selection effect, using benchmark weights: 50% times (12% minus 10%) plus 50% times (1% minus 2%), which is 1.0% minus 0.5%, or 0.5%. Interaction: 20% times 2% plus minus 20% times minus 1%, which is 0.4% plus 0.2%, or 0.6%. Together: 1.6% plus 0.5% plus 0.6% equals 2.7%.

## Factor based attribution

Factor attribution explains returns by exposure to factors such as market, size, value, momentum and industry. The part not explained by factors is the specific return, a closer measure of stock picking skill. See [Factor Models](https://learn.tradelabsai.com/portfolio/factor-models/) and [Alpha and Beta](https://learn.tradelabsai.com/portfolio/alpha-and-beta/).

## P&L explain for trading desks

| Component | Source |
|---|---|
| Delta P&L | Moves in the underlying price |
| Gamma P&L | Convexity from larger moves. See [Gamma](https://learn.tradelabsai.com/options/gamma/) |
| Vega P&L | Changes in implied volatility. See [Vega](https://learn.tradelabsai.com/options/vega/) |
| Theta P&L | Passage of time. See [Theta](https://learn.tradelabsai.com/options/theta/) |
| Rates and carry | Interest and funding effects |
| New trade P&L | Profit from trades executed today, such as spread capture |
| Unexplained | Residual that may signal model or data problems |

A large unexplained P&L is a warning sign that risk models or position records may be wrong, and it is investigated by risk and product control teams. See [Risk Analyst](https://learn.tradelabsai.com/industry/risk-analyst/).

## Attribution for traders

Individual traders can attribute results by:

| Breakdown | Insight |
|---|---|
| Strategy or setup | Which setups make money. See [Trading Journal](https://learn.tradelabsai.com/start-here/trading-journal/) |
| Instrument | Where you have an edge |
| Long versus short | Directional bias |
| Time of day or market regime | When the strategy works. See [Structural Breaks and Regime Changes](https://learn.tradelabsai.com/math/regime-changes/) |
| Entry versus exit quality | Whether exits give back profits. See [MAE and MFE](https://learn.tradelabsai.com/risk/mae-and-mfe/) |
| Costs | How much commissions and slippage take. See [Slippage Analysis](https://learn.tradelabsai.com/orders/slippage-analysis/) |

## Pitfalls

1. **Wrong benchmark,** making allocation and selection meaningless.
2. **Short periods,** where luck dominates. See [Statistical Significance in Trading](https://learn.tradelabsai.com/math/statistical-significance/).
3. **Ignoring costs and currency effects.**
4. **Different models giving different answers;** state the method used.
5. **Using attribution to justify** rather than to learn.

## Making attribution a habit

Run attribution on a fixed schedule, such as monthly, using the same method and benchmark each time, so results are comparable. Keep a short written note of what the numbers show and what you will change, then check next month whether the change helped.

## Frequently asked questions

### What is performance attribution?

The analysis of where a portfolio's returns came from, such as asset allocation, security selection, factor exposures, currency and costs.

### What is the Brinson model?

A method that splits active return into allocation, selection and interaction effects relative to a benchmark.

### What is P&L explain?

A breakdown of a trading desk's daily profit and loss into price, volatility, time, carry and new trade effects, with an unexplained residual.

Next, learn what happens after a trade is executed in [Clearing, Settlement and Custody](https://learn.tradelabsai.com/industry/clearing-settlement-and-custody/).

## Continue learning

- Next lesson: [Clearing, Settlement and Custody](https://learn.tradelabsai.com/industry/clearing-settlement-and-custody/)
- Previous lesson: [Trade Accounting and Reconciliation](https://learn.tradelabsai.com/industry/trade-reconciliation/)
- Related: [Trade Accounting and Reconciliation](https://learn.tradelabsai.com/industry/trade-reconciliation/): Reconciliation checks that internal records of trades, positions and cash match brokers, custodians and clearing houses. Learn the process, common breaks and fixes.
- Related: [Alpha and Beta](https://learn.tradelabsai.com/portfolio/alpha-and-beta/): Beta measures how much a portfolio moves with the market; alpha is the return beyond what that exposure explains. Learn formulas, CAPM, regression and pitfalls.
- Related: [Factor Models](https://learn.tradelabsai.com/portfolio/factor-models/): Factor models explain asset returns with common drivers such as the market, size, value and momentum. Learn CAPM, Fama French and how to run a factor regression.
- Related: [Information Ratio and Tracking Error](https://learn.tradelabsai.com/portfolio/information-ratio/): The information ratio divides active return by tracking error to measure how consistently a portfolio beats its benchmark. Learn the formulas, values and uses.
- Related: [Risk Contribution and Risk Decomposition](https://learn.tradelabsai.com/portfolio/risk-contribution/): Risk contribution shows how much each position adds to total portfolio risk, including correlations. Learn marginal and total contributions with a worked example.
- Related: [Post-Trade Analysis](https://learn.tradelabsai.com/start-here/post-trade-analysis/): Post-trade analysis turns every trade into a lesson. Learn how to grade decisions separately from results, find repeat mistakes and improve your plan.