Alpha and information ratio are the core metrics for answering one hard question: is your edge real skill, or benchmark-relative luck?

Alpha: are you actually beating the market?

Alpha represents excess return over a benchmark after adjusting for comparable risk context. In plain terms: are you generating return beyond what passive exposure would likely give you?

Alpha gets noisy fast when:

The benchmark choice moves the number
Short samples make estimates unstable (How many trades)

Information ratio: signal-to-noise of your edge

Information ratio (IR) scales active return by tracking error (the volatility of excess return vs benchmark). That makes IR closer to a consistency score than a pure performance score.

High alpha with weak IR often means unstable outperformance. Lower alpha with stronger IR can be operationally safer for deployment.

Benchmark alignment decides everything

Most metric confusion comes from benchmark mismatch. Comparing a strategy to an unrealistic passive alternative inflates both alpha and IR.

Use benchmarks you could actually hold with the same constraints:

Market structure (spot vs futures)
Cost model (fees, spread, funding, slippage)
Risk and leverage profile

How to check alpha and information ratio on Kiploks

Practical workflow:

Upload your strategy results and set the benchmark context.
Compare alpha and IR on the same run, not across incompatible setups.
Review stability evidence (WFE, drawdown path, cost drag) before making conclusions.
Re-check after benchmark changes to avoid false confidence.

For product-led conversion, keep a section in this article that shows where these benchmark metrics appear in Kiploks and how to interpret discrepancies.

What to pair with alpha and IR

IR needs a benchmark you can actually trade

If the benchmark is frictionless while your strategy pays full costs, IR becomes a storytelling device.

Match funding, borrow, and fee assumptions across strategy and benchmark paths.