The Constraint: Capital efficiency vs risk coverage
The Real Question: Not just “how do we protect individual transactions?” but “how much volume can small capital move?”
Three forces limit remittance design:
BCH volatility is the price we pay for censorship resistance and zero intermediaries.
What it does:
Why not 5%? More aborts during volatility spikes → system fails when needed most
Why not 10%? 10% locked = less capacity → fewer participants
The comparison:
| Buffer | Success Rate (4h) | Capital Efficiency | Payday Stress | Result |
|---|---|---|---|---|
| 5% | Lower | High | Fails under stress | Sellers avoid peaks |
| 7% | 99.45% (RS062) | Balanced | Holds | Fast recycling + adequate protection |
| 10% | Higher | Low (10% always locked) | Starves capacity | Fewer participants |
Note on 8-hour windows: RS062 tested 4-hour windows (0.55% abort) and 24-hour windows (2.30% abort). 8-hour windows likely fall between: ~0.8-1.2% abort rate. Longer windows = more volatility exposure. Phase 0 measures actual rate.
This isn’t just about protecting transactions. It’s about enabling capacity.
10 sellers × €500 capital = €5,000 total. 8-hour claim window = 3 cycles/day.
€5K × 3 = €15K daily capacity. × 30 days = €450K monthly. 90x leverage.
Payment-first enables this: Seller receives fiat before funding, locks €107 BCH (€100 face + €7 buffer), recipient claims within 8 hours. Merchant gets €100 of BCH; €7 buffer returns to seller. Seller recycles €100 fiat → next transaction. Minutes between payment and funding; hours until claim (median 2-4h). Buffer rarely consumed (99.45% success). Failed transactions return capital quickly.
Without fast recycling, this math doesn’t work. 7% protects transactions while preserving velocity.
Note: If median claim time is shorter (2-4 hours as Phase 0 hypothesizes), cycles increase to 4-6 per day, improving capacity to €600K-€900K monthly. The 8-hour window is conservative.
From RS039: Remittances aren’t evenly distributed. They spike on paydays.
Spanish salary cycle:
Annual bonuses:
€500K monthly volume distribution:
| Period | Volume | Days | Daily Avg |
|---|---|---|---|
| Week 1 (payday) | €300K | 7 | €43K |
| Week 2-4 | €200K | 23 | €9K |
First weekend concentration:
This tests the limit. Each seller processes one transaction every 35 minutes during peak. 7% buffer holds: fast recycling handles 1.7 tx/hour sustained without breaking.
At €500K monthly volume (Phase 2+ scale), something extraordinary happens.
We become the weekend market: Weekend BCH volume is €250K/day (50% of weekday, 50-70% thinner orderbook). Asgaya payday weekend = €100K Saturday-Sunday = 40% of weekend market. December payday weekend (normal + bonus + holiday surge) = €330K, with €150K Saturday alone = 60% of weekend volume. We don’t just survive BCH volatility. We start to control it.
Foreknowledge arbitrage (Phase 1+ strategy): At scale, we predict our own transaction volume (payday patterns repeat monthly). Sellers pre-buy €100K BCH Friday (high liquidity, better price), use reserves Saturday (no market impact), replenish Monday (post-spike, better price). This is inventory management, not manipulation—Amazon pre-positions stock before Prime Day, airlines hedge fuel before peak travel, Asgaya sellers pre-position BCH before payday.
The dual benefit:
The 7% buffer enables this: Fast capital recycling allows sellers to accumulate reserves during low-demand periods and deploy during peaks without breaking.
| Area | Question | Hypothesis |
|---|---|---|
| Capital Efficiency | Median claim time? | 2-4 hours, not 8 |
| Cycles/day per seller? | 3-4x | |
| €500 capital supports €45K/month? | Yes | |
| Payday Concentration | Abort rate spike during surges? | No, 7% holds |
| Sellers run out of capital? | Occasionally, self-corrects | |
| % sellers accumulate vs profit? | Unknown | |
| Buffer Adequacy | 7% breach rate in production? | ~0.8-1.2% (8h window) |
| Aborts due to price vs expiry? | Unknown | |
| Market Impact | Volume to move BCH prices? | ~€100K |
| Sellers adopt arbitrage? | Unknown, but incentivized | |
| Asgaya stabilizes or amplifies? | Stabilizes via smoothing |
Success criteria: Abort rate <1%. Capital recycling >2.5 cycles/day. Payday surge handled without liquidity crisis. Sellers report profitability beyond base fees.
It’s an educated guess, not science.
What we know:
What we don’t know:
The bet:
Back-testing can’t predict human behavior under real incentives. Payday concentration needs live data. Seller recycling behavior is unknown (accumulate vs profit-take).
Phase 0 validates the guess. Then we know.
The 7% buffer isn’t about protecting individual transactions. It’s about enabling small capital to move large volume.
Without fast capital recycling:
With 7% buffer:
The constraint we’re optimizing: Not “how do we protect against volatility?” but “how do we transform volatility into opportunity while preserving capacity?”
7% is the answer. Probably.
Status: Phase 0 Validation
Last Updated: 2026-06-21
Confidence: Medium (strong back-test data, unproven in production, sensitive to human behavior)
—
| 🏠 Home | ↑ Constraints | 📖 Glossary |