Deterministic Decay

Deterministic decay is the current primary persistence layer in FYOS.

The Canonical Metric: decay_adjusted_return

The primary output is decay_adjusted_return — return after applying deterministic decay to clean economics.

This metric answers:

How much of the headline funding opportunity should remain meaningful after the holding horizon?

What It Replaced

Deterministic decay replaced deprecated survivability-led primary math in the canonical clean-core path.

The old approach mixed persistence with quality scoring. The new approach separates them:

• Persistence: handled by deterministic decay
• Downside quality: handled by observed risk
• Overall attractiveness: synthesized in edge_value_score_v2

How Decay Works

Decay models the expected reduction in funding edge over time:

• Half-life: The time for edge to decay by 50%
• Decay curve: Typically exponential or similar conservative shape
• Horizon adjustment: Returns are adjusted for the assumed holding period

Shorter half-life = faster decay = more conservative return adjustment.

Product Interpretation

Use decay-adjusted return as a better starting point than raw annualized funding.

Raw APR assumes funding rates persist forever. They don't. Decay adjusts for this.

Decay-Adjusted Return vs Raw APR

Always prefer decay_adjusted_return for comparing opportunities.

What Users Should Do

1. Use decay_adjusted_return as the primary economics reference
2. Treat half-life labels as supporting context
3. Combine persistence with deployability and observed risk
4. Don't assume funding rates will persist indefinitely