Decay function visualization

Decay Function of Marketability

M(Xₙ) = M(X₀)·e^(−λ·n·σ(t)) — the master construct. Every transformation between a direct claim and its paper substitute imposes a measurable saleability haircut, exponential in the hop count and amplified by current stress.

Formula

M(Xₙ) = M(X₀) · e^(−λ · n · σ(t))

  M(X₀)  initial marketability (normalized to 1.0)
  n      number of substitution hops from the underlying
  λ      asset-class-specific decay constant
  σ(t)   current substitute-layer stress (Z-score scale)

Inputs

Higher λ → faster saleability decay per hop. Stress-sensitive asset classes (long-duration paper, exotic derivatives) carry higher λ than substrate-grade collateral.

Aggregate substitute-layer stress on a Z-score scale. Calm: 0.5. Mild stress: 1.5–2.0. 2008 / 2020 acute: 3.0+.

Implied hop half-life at current parameters:

6.93 hops

Number of substitution layers at which marketability falls to 50% of the underlying.

Marketability by hop

n = 0 (direct claim)100.0%
n = 190.5%
n = 281.9%
n = 374.1%
n = 467.0%
n = 560.7%
n = 654.9%

Each row is M(Xₙ) at the current λ and σ. The bar height collapses exponentially as substitution hops accumulate.

Worked hop examples

What "n" means in practice, for a precious-metals reference asset:

Physical gold (bullion)

n = 0 · Direct claim. No substitute layer between the holder and the asset.

100.0%

Allocated ETF (e.g., physically backed)

n = 1 · One layer of substitution: custodian relationship + creation/redemption mechanism.

90.5%

Synthetic ETF / unallocated paper claim

n = 2 · Two layers: paper claim on a custodian who holds derivatives, not metal.

81.9%

Tokenized synthetic on a chain

n = 3 · Three layers: chain layer over paper claim over derivative over physical.

74.1%

Lent / rehypothecated tokenized synthetic

n = 4 · Four layers: counterparty exposure stacked on top of all of the above.

67.0%

The decay function is the framework's master construct. The Mengerian Stress Index is its empirical implementation: each MSI component measures the observable spread at a specific n-and-asset combination, and the composite reconstructs the unobservable σ(t).