What is P&L Attribution Analysis? – Profit Attribution Analysis

The world of finance is as big as it can be. One needs to take several nuances to enhance the financial position of an individual or a company. Wrong are those people who think that finance is just about equalizing our balance sheets. No!

It’s about so much more! Capital markets, Trading, Shares, Bank Statements, and more. One such nuance is Profit and Loss Appropriation. No, it is not in the context of a company, but rather it is a term used by the trading markets. Using Profit and Loss Appropriation, one can back-test any company’s risk management models. Here, we bring different Profit and Loss Account components and observe and analyze them to determine whether the given amount has risen out of a chance due to a calculated, well-thought-off strategy.

p&L typical attribution analysis

Stock markets are one of the most dynamic places to trade your money. It keeps on changing every single day. As it is essential to keep your tab on the trading part, it is also necessary to note the profit and losses of one’s trade. It is also crucial to predict them to plan future things that might happen and compare the expected profit or failure with the actual ones. This helps to ascertain the efficiency of planning. Therefore, profit and Loss Attribution is one of the essential things for money matters.

What is P&L Attribution Analysis?

Profit attribution analysis is a process businesses use to evaluate the profitability of different units or segments within their organization. In essence, profit attribution analysis helps companies answer the question: “Where is our profit coming from?”.

By breaking down profits by product line, geographic region, customer segment, or other criteria, businesses can better understand their revenue and profit sources and make data-driven decisions about optimizing their operations.

Some of the critical steps involved in profit attribution analysis include the following:

  • Defining the relevant units or segments to analyze
  • Gathering financial and operational data for each unit
  • Identifying the key drivers of profitability, such as sales volume, pricing, cost structure, and market trends
  • Analyzing the data to determine which factors have the most significant impact on profitability and how they vary across different units or segments
  • We are developing strategies and tactics to optimize performance based on the insights gained from the analysis.

This is done by analyzing all the conditions that can affect the performance, like time, commodities prices, applicable interest rates, market uncertainty, new contracts, cancellations, etc. it also helps the financial institutions evaluate their decisions and justify their losses. 

When was this model introduced?

The Profit and Loss Attribution (or P&L Attribution Model) was first introduced in October 2013 by the Basel Committee on Banking Supervision (BCBS), which was a part of their FRTB (Fundamental Review of the Trading Book). This test was drawn up as a new requirement for the trading desk’s accreditation to use the IMA (Internal Model Approach) to calculate the market risk capital. 

P&l Attribution Example

One reasonable profit and loss (P&L) attribution example in the stock trading industry could be analyzing the performance of a trading desk within a financial institution.

The trading desk may have multiple traders executing trades in different financial instruments such as equities, futures, options, and commodities. To conduct a P&L attribution analysis, the financial institution would gather data on each trader’s performance in terms of revenue, cost of capital, and risk management.

For example, the analysis may reveal that one trader generated a high amount of revenue but also had a high cost of capital due to the use of leverage or borrowing to finance trades. Conversely, another trader may have had a lower income but a lower cost of capital, resulting in a higher net profit margin.

Based on this analysis, the financial institution could make data-driven decisions to optimize performance by implementing changes to the allocation of capital, risk management, or adjusting trading strategies to improve performance.

By conducting a P&L attribution analysis, the financial institution can gain a deeper understanding of the profitability of each trader and the factors driving their performance. This allows them to make informed decisions on optimizing trading operations, allocating resources, and driving profitability.

What does the P&L Attribution Model aim to represent?

The Profit and Loss Attribution Model aims to ensure that the coverage of the risk factors used in a bank’s internal model approach calculation is adequate to fully capture the range of Profit and Loss variations that occur. Per the standard, every trading desk must ensure it passes the P&L attribution to maintain accreditation to use the IMA for capital calculations.

The P&L attribution compares two measures: A Hypothetical P&L and A Risk Theoretical P&L 

A Hypothetical P&L is generated by the bank’s front office pricing models, and the bank’s risk models generate the risk theoretical P&L. The gap between both is measured using a mean ratio and a variance ratio. The revenue managers should keep in mind that the ratios generated from the two P&Ls should always remain within the established thresholds for the test to be legitimate. Otherwise, a breach can occur if the desk surpasses the limit. 

Why is the P&L Attribution Model so necessary?

A risk or revenue manager should identify whether a company’s decisions resulted in making or losing money. The only way the company can measure its performance is by looking at its books of accounts. The way through which this is possible is by taking into account the decisions that the company has endured throughout the financial year and considering the profits and losses. This is where the P&L attribution Model comes into the picture. Considering all the factors, such as performance, time, prices, etc., helps to measure the company’s efficiency of operations and compare its performance with the predicted performance. 

Methodologies for measuring the Profit and Loss Attribution model:

There are two methodologies for calculating the P&L Attribution:

  • Sensitivities Method – This method involves calculating sensitivities known as the ‘Greeks’ because of the standard practices of representing them using Greek Letters.
  • Revaluation Method calculates trade values on the current and prior day’s prices. The Formula for that is the Impact of Prices= Trade value for Today’s Price- Trade Values for Yesterday’s Prices.


In trading, we have a similar expression.

What are p and l in trading?

The p and l in the reading or P&L statement or the profit and loss statement represents a financial statement that summarizes the trading cost, revenues, and expenses during a specified trading period, usually a month, quarter, or year. Profit and loss statements provide information about a company’s ability or inability to generate profit by reducing costs, increasing revenue, or both. In Metatrader, Profit and loss are a standard part of the trading report.


In the following article, we learned about the Profit and Loss Attribution method, its history, why this model is so necessary, the different methodologies used to measure P&L abortion, and the other constituents of this method. So, from the following, we can understand that P&L Attribution is crucial to the financial scenario.

It helps the financial institutions measure their performance with hypothetical performance and allows the revenue managers to get an idea of operations’ efficiency and eradicate any shortcomings in their organization. The advantage of this method is that it considers all the factors, such as prices and market uncertainty. Hence, it is an excellent measure of financial performance and the institution’s efficiency. 

So, now you know all about the Profit and Loss Attribution method!



Igor has been a trader since 2007. Currently, Igor works for several prop trading companies. He is an expert in financial niche, long-term trading, and weekly technical levels. The primary field of Igor's research is the application of machine learning in algorithmic trading. Education: Computer Engineering and Ph.D. in machine learning. Igor regularly publishes trading-related videos on the Fxigor Youtube channel. To contact Igor write on: igor@forex.in.rs

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