# Understanding the Information Coefficient (IC): Definition, Formula, and Example

> **Definition**
>
> The information coefficient (IC) measures the accuracy of a portfolio manager’s predictions by comparing the manager’s forecasts and the actual outcomes, with +1.0 being a perfect score.

## What Is the Information Coefficient (IC)?

The information coefficient (IC) is a measure used to evaluate the skill of an [investment analyst](https://www.investopedia.com/terms/a/analyst.asp) or an active [portfolio manager](https://www.investopedia.com/articles/wealth-management/021816/portfolio-manager-job-description-average-salary.asp). This is different from the information ratio, which compares a manager's returns to the amount of risk they take on.

The information coefficient shows how closely the analyst's financial forecasts match actual financial results. The IC can range from 1.0 to -1.0, with -1 indicating the analyst's forecasts bear no relation to the actual results, and 1 indicating that the analyst's forecasts perfectly matched actual results.

### Key Takeaways

*   The information coefficient (IC) measures how accurately an analyst's predictions align with actual financial results.  
    
*   An IC of +1.0 indicates perfect prediction accuracy, while -1.0 shows no prediction success.  
    
*   IC is often used for evaluating the skill of investment analysts and portfolio managers.  
    
*   An IC close to zero suggests an analyst's predictions are on par with random chance.  
    
*   IC differs from the Information Ratio (IR), which evaluates excess returns relative to risk.

## Calculating the Information Coefficient (IC)

﻿ $\begin{aligned} &\text{IC} = (2 \times \text{Proportion Correct}) - 1 \\ &\textbf{where:} \\ &\text{Proportion Correct} = \text{Proportion of predictions made} \\ &\text{correctly by the analyst} \\ \end{aligned}$﻿

## Understanding the Impact of the Information Coefficient

The information coefficient describes the correlation between predicted and actual stock returns, sometimes used to measure the contribution of a financial analyst. An IC of +1.0 indicates a perfect linear relationship between predicted and actual returns, while an IC of 0.0 indicates no linear relationship. An IC of -1.0 indicates that the analyst always fails at making a correct prediction.

An IC near +1.0 shows great forecasting skill. However, if "correct" means matching the direction, the odds are 50/50. So even an analyst with no skill whatsoever could be expected to have an IC of around 0, meaning that half of the forecasts were right and half were wrong. A score close to 0 reveals that the analyst's forecasting skills are no better than results that could be achieved by chance, suggesting that ICs approaching -1 are rare.

Don't confuse IC with the [Information Ratio](https://www.investopedia.com/terms/i/informationratio.asp) (IR), which measures skill by comparing [excess returns](https://www.investopedia.com/terms/e/excessreturn.asp) to risk.

The IC and the IR are both components of the Fundamental Law of Active Management, which states that a manager's performance (IR) depends on skill level (IC) and its breadth, or how often it is used.

## Practical Examples of Using the Information Coefficient

As a hypothetical example, if an investment analyst made two predictions and got two right, the information coefficient would be:

$\begin{aligned} &\text{IC} = (2 \times 1.0) - 1 = +1.0 \\ \end{aligned}$

If an analyst is right only half the time:

$\begin{aligned} &\text{IC} = (2 \times 0.5) - 1 = 0.0 \\ \end{aligned}$

If none of the predictions are correct:

$\begin{aligned} &\text{IC} = (2 \times 0.0) - 1 = -1.0 \\ \end{aligned}$

## Analyzing the Limitations of the Information Coefficient

The IC is only meaningful for an analyst who makes a large number of predictions. This is because if there only a small number of predictions, random chance may explain a great deal of the results. So if only two predictions are made and both are right, the IC is +1.0.  If the IC remains near +1.0 after dozens of predictions, it's likely due to skill rather than chance.