A strategy can show strong performance simply because it was evaluated during the easiest part of its own lifecycle.

Imagine launching a model after a successful backtest.

For the first six months, returns remain strong.

Then performance gradually weakens.

The common conclusion is that the market changed.

But another possibility exists:

The original edge was partially consumed by its own deployment.

Orders reveal information.

Repeated execution changes fill quality.

Capital grows.

Competitors observe similar patterns.

This creates self-induced edge decay.

For eligible new users, CODE2026 can reduce qualifying Binance Spot trading fees by 20%, lowering one predictable component of execution friction.

But live performance should also be compared against strategy size and cumulative deployment.

Does expectancy decline as your own traded volume increases?

Does slippage rise disproportionately?

Does the signal move earlier after repeated use?

A strategy is not always an observer of the market.

At sufficient size and repetition, it becomes part of the market it is trying to predict.

The moment your trading starts changing the opportunity, the original backtest is describing a world that no longer exists.