proxmox/docs/gru-m1/GRU_M1_REAL_DATA_DOMINANCE_ADDENDUM.md

GRU M1 Real-Data Dominance Simulation & Peg Stress-Test Addendum

Last Updated: 2026-01-31
Document Version: 1.0
Status: Active Documentation

---

Purpose of This Addendum

This addendum extends the GRU M1 Master Implementation, Testing & Dry-Run Plan by providing:

1. A real-data dominance simulation framework using current Top-25 crypto market metrics as reference inputs
2. A table-driven supply & peg stress-test worksheet suitable for dry-runs, audits, and pre-listing validation

This addendum is designed to be executable without internal GRU context by external reviewers, while still satisfying GRU governance requirements.

---

SECTION VII — Real-Data Dominance Simulation (Top-25 Referenced)

7.1 Objective

To simulate how the introduction and scaling of GRU M1 stablecoins (cISO(C/T)) affects:

• Total crypto market capitalization
• Stablecoin dominance
• BTC / ETH dominance

This simulation uses current Top-25 market data as a baseline, without modifying existing asset prices.

---

7.2 Baseline Inputs (Reference Snapshot)

Baseline variables (to be populated from live data at run-time):

Variable	Description
Total Market Cap	Aggregate market cap of all crypto assets
BTC Market Cap	Market cap of Bitcoin
ETH Market Cap	Market cap of Ethereum
Stablecoin Market Cap	Aggregate cap of existing stablecoins
BTC Dominance	BTC cap / Total cap
Stablecoin Dominance	Stablecoin cap / Total cap

Note: Values are frozen at simulation start to isolate GRU M1 impact.

---

7.3 Simulation Scenarios (Incremental Issuance)

Each scenario introduces new GRU M1 supply while holding all other assets constant.

Scenario	Added GRU M1 Supply	Description
S0	$0	Baseline (no GRU M1)
S1	$100M	Pilot issuance
S2	$500M	Early institutional usage
S3	$1B	Regional settlement adoption
S4	$5B	Multi-jurisdiction usage
S5	$10B	Systemic settlement scale

---

7.4 Dominance Recalculation Logic

For each scenario:

New Total Market Cap = Baseline Total + GRU M1 Supply
New Stablecoin Cap = Baseline Stablecoin Cap + GRU M1 Supply
BTC Dominance = BTC Cap / New Total
Stablecoin Dominance = New Stablecoin Cap / New Total

No price changes are assumed.

---

7.5 Output Table (Simulation Results Template)

Scenario	Total Cap	Stablecoin Cap	BTC Dom %	ETH Dom %	Stablecoin Dom %
S0
S1
S2
S3
S4
S5

---

7.6 Interpretation Guidance

• BTC/ETH dominance declines mechanically as GRU M1 grows
• No implication of speculative capital shift
• Stablecoin dominance increases without volatility
• Use ex-M1 internal metrics for risk analysis

---

SECTION VIII — Supply & Peg Stress-Test Worksheet

8.1 Objective

To validate that each cISO(C/T) instrument maintains peg integrity and supply accuracy under stress.

---

8.2 Stress-Test Dimensions

Each test isolates one failure mode.

Dimension	Description
Supply Shock	Rapid mint or burn
Redemption Shock	Large redemption requests
Market Volatility	External crypto volatility
Liquidity Drain	Reduced exchange liquidity
Operational Delay	Mint/burn latency
Custody Event	Temporary reserve inaccessibility

---

8.3 Peg Stress-Test Worksheet (Per Instrument)

Test ID	Scenario	Starting Supply	Stress Event	Peak Supply	Price Deviation	Recovery Time	Pass/Fail	Notes
P1	Normal Ops
P2	+20% Mint		Rapid mint
P3	-20% Burn		Large burn
P4	10% Redemption		Withdrawals
P5	Liquidity Shock		Thin books
P6	Ops Delay		Mint delay

---

8.4 Acceptance Criteria (Hard Gates)

Metric	Threshold
Peg Deviation	≤ ±0.50%
Recovery Time	≤ 24 hours
Supply Reconciliation Error	0
Unexplained Variance	None

Failure requires corrective action before listing or scaling.

---

SECTION IX — Evidence & Reporting Artifacts

For each dry-run, archive:

• Input data snapshot
• Completed simulation tables
• Stress-test worksheets
• Commentary on outcomes
• Sign-off by operations & compliance

---

Related Documentation

• GRU M1 Master Implementation Plan
• Peg Stress-Test Worksheet
• GRU M1 Listing Dry-Run Runbook

---

Closing Note

This addendum ensures that GRU M1 instruments can be demonstrated to function predictably within public market data systems, even at scale, without introducing instability, distortion, or misinterpretation.