> ## Documentation Index
> Fetch the complete documentation index at: https://kalpi.ai/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Information Ratio

> Measure your strategy's ability to consistently generate excess returns against a benchmark.

The **Information Ratio (IR)** is the ultimate metric for active algorithmic system developers. It tells you exactly how much active "alpha" (excess return) your strategy is generating relative to the consistency of that outperformance.

Unlike the Sharpe or Sortino ratios, which compare returns against a risk-free cash rate, the Information Ratio directly pits your strategy against its assigned benchmark index (e.g., the Nifty 50).

## The Mathematical Formula

The ratio calculates your active return divided by your **Tracking Error** (the standard deviation of that active return):

$IR = \frac{R_p - R_b}{TE}$

**Where:**

* $R_p$ = The return of the portfolio.
* $R_b$ = The return of the benchmark index.
* $TE$ = Tracking Error (volatility of the difference between portfolio and benchmark returns).

## Interpreting the Information Ratio

A high Information Ratio proves that your system's outperformance is a result of consistent, repeatable algorithmic skill, rather than one lucky "lottery ticket" trade that skewed the data.

<ResponseField name="Below 0" type="Value Destruction">
  The active strategy is underperforming the passive benchmark. You are paying transaction fees to lose money relative to simply buying the index.
</ResponseField>

<ResponseField name="0.40 to 0.60" type="Good">
  The system is generating solid, consistent alpha over the benchmark index. This is considered a highly successful active fund threshold.
</ResponseField>

<ResponseField name="1.00+" type="Exceptional">
  Institutional top-tier performance. The strategy consistently beats the benchmark month after month with very little deviation or tracking failure.
</ResponseField>