Reserve Growth Simulator
How the model works
This simulator projects RSR’s fundamental value using discounted cash flow (DCF) — the same approach used to value stocks and businesses. It runs 10,000 independent 10-year futures from your assumptions and shows the full distribution of outcomes, not a single prediction.
Three-pass simulation
Each simulated path runs in three passes:
- TVL & revenue (forward, 20 years) — Grow TVL along an S-curve, compute revenue from the fee schedule. This pass is entirely independent of price. The model always simulates at least 20 years internally so the DCF has a long runway, even though only 10 years are displayed.
- DCF valuation (backward) — Starting from year 20, apply a terminal multiple to the final year’s revenue, then discount all future cash flows backward to compute market cap at each year. By year 20 the S-curve has typically saturated, so the terminal value represents a truly mature protocol rather than dominating the valuation.
- Price & supply (forward, 10 years) — Divide market cap by circulating supply to get the token price. Platform fees buy and burn RSR at this price, reducing supply. Burns are capped at 2% of circulating supply per year to reflect real-world liquidity constraints — you can’t buy the entire float without massive slippage.
S-curve adoption
Reserve has two product lines, each with its own adoption speed and market ceiling (TAM): Index DTFs (on-chain ETFs) and Yield DTFs (collateralised yield vaults). Each grows along an S-curve — fast early adoption that naturally decelerates as TVL approaches the ceiling. For reference, the global ETF market is ~$15T; the TAM sliders represent Reserve’s share of this.
Adoption speed is protocol-specific — it represents product strength, independent of market conditions. The market regime only affects noise: volatility and the probability of sharp drawdowns. A bear market doesn’t stop growth — it makes the path bumpier and riskier.
Market regimes
Each path starts in a bull, neutral, or bear regime based on your sentiment slider. Every year the regime can shift via a Markov chain — bull markets last ~2 years on average, bear markets ~1.8 years. Regimes affect volatility, collapse probability, and collateral yields. They do not affect the base adoption rate. Parameters are calibrated from real DeFi TVL histories (Aave, MakerDAO, Lido, 2020-2025).
Revenue
Revenue is deterministic given TVL — no random fee draws. Index DTF fees come from a management fee on TVL plus a mint fee on new deposits; the platform takes a cut (burned as RSR) and governance stakers receive a share. Yield DTF revenue comes from collateral yield (varies by regime), split between platform fees (burned) and staking rewards to RSR holders.
Burns & supply
Platform fees from both Index and Yield DTFs are used to buy and permanently burn RSR. Because market cap is set by the DCF (independent of token count), burning tokens increases each remaining token’s share of that value. Annual burns are capped at 2% of circulating supply to model real liquidity constraints. Token emissions are currently paused — 37.45B tokens remain locked and are not entering circulation.
What’s random vs deterministic
Random: adoption trajectory (S-curve noise + collapse events), market regime path (Markov chain), and collateral yields (regime-dependent draws). Deterministic: fee rates, revenue calculation, DCF math, burn mechanics, supply accounting. The same configuration always produces identical results (fixed random seed).
10-Year Projection
We ran 10000 independent simulations of Reserve's growth over 10 years. Each path models TVL adoption along an S-curve, computes protocol revenue from fees, and derives a fundamental token price via discounted cash flow. Market conditions (bull/bear cycles, volatility, crashes) vary randomly across paths — what you see below is the full range of outcomes, not a single prediction. Pick a story from the sidebar to explore different scenarios, or adjust individual parameters for full control.
In the middle 50% of outcomes, RSR lands between $0.1243 and $0.6306 by year 10.
Median price at year 10
$0.2403
Worst 10%
$0.0783
90% do better
Below avg
$0.1243
75% do better
Median
$0.2403
middle outcome
Above avg
$0.6306
25% do better
Best 10%
$2.26
top 10% outcome
What are the odds?
% of the 10000 simulated paths that reach or exceed each return multiple from your entry price of $0.001560.
| Target | Yr 1 | Yr 2 | Yr 3 | Yr 4 | Yr 5 | Yr 6 | Yr 7 | Yr 8 | Yr 9 | Yr 10 |
|---|---|---|---|---|---|---|---|---|---|---|
| Break even $0.001560 | 100% | 100% | 100% | 100% | 100% | 100% | 100% | 100% | 100% | 100% |
| 2× $0.003119 | 100% | 100% | 100% | 100% | 100% | 100% | 100% | 100% | 100% | 100% |
| 5× $0.007798 | 98% | 99% | 99% | 100% | 100% | 100% | 100% | 100% | 100% | 100% |
| 10× $0.0156 | 85% | 92% | 96% | 98% | 99% | 100% | 100% | 100% | 100% | 100% |
| 20× $0.0312 | 56% | 67% | 79% | 87% | 93% | 96% | 98% | 99% | 99% | 100% |
| 50× $0.0780 | 26% | 33% | 41% | 50% | 60% | 69% | 77% | 83% | 87% | 90% |
| 100× $0.1560 | 14% | 18% | 23% | 28% | 34% | 41% | 48% | 55% | 61% | 66% |
| 1000× $1.56 | 2% | 3% | 3% | 4% | 5% | 6% | 8% | 9% | 11% | 13% |
Price & Valuation
Price distribution across all simulated paths (log scale), and the implied P/E ratio the DCF model assigns at each year — starts high (growth priced in) and converges toward the terminal multiple.
Price distribution
Implied P/E over time
TVL & Holders Revenue
TVL is the total value locked across all DTFs. Holders revenue is all protocol revenue flowing to RSR holders — platform fees (used to buy back and burn RSR), governance rewards, and staking yield.
Total TVL
Holders Revenue 81% index / 19% yield
Revenue breakdown (median)
Market cap
Burns, Emissions & Supply
Platform fees buy RSR on the open market and burn it permanently. Locked tokens unlock over time. The net effect determines whether circulating supply shrinks or grows.
Net supply change
-9.80%
over 10 years
range 6.63% - 12.02%
Circulating supply
56.42B RSR
median at yr 10
range 55.03B RSR - 58.40B RSR
Burns vs Unlocks per year
Circulating supply over time