How to forecast
Quick read • Every proposal has two markets—Funded and Not Funded—both predicting the same metric (e.g., average Unichain TVL over a 30-day period) under opposite conditions. • Compare the market's current implied forecast for that metric with your own analysis. • An accurate forecast that differs from the market consensus represents a potential trading opportunity.
Why it matters
Trading that corrects mis-priced forecasts is doubly valuable: you earn the spread and push capital toward the proposals the market now sees as most impactful.
Acting on a mis-price
If your forecast is higher than the market's implied forecast, it suggests the scenario is undervalued.
If your forecast is lower than the market's implied forecast, it suggests the scenario is overvalued.
This difference between your valuation and the market's represents a potential forecasting edge.
Example The Not Funded market for a proposal implies a 30-day trailing average TVL of $18m. However, your analysis suggests the baseline is closer to $14m. This discrepancy indicates the market may be overestimating the metric in the Not Funded scenario.
What exactly am I forecasting?
Takeaway You forecast the trailing 30-day Unichain TVL over the one-month evaluation period after markets close (in this case July 10 - August 10th) not a single end-of-period snapshot.
Details
Average TVL weights when growth happens: fast early growth raises the average more than late-period growth.
The scalar range is mapped so that $0 corresponds to 0 TVL and $1 to a Funding-Entity-defined upper bound (see the CFM parameters).
Therefore, a market forecast implying a $0.70 payout means the metric is expected to reach “≈70% of max TVL on average.”
Example – If the upper bound is $40 M and the market's implied forecast for the Funded market corresponds to a 0.25 payout, it implies a $10 M average TVL (0.25 × 40 M) for the 30-day period following funding.
Forecasting the Not Funded market
Takeaway Project the metric’s baseline path without new funding: extend existing trends, account for announced but unfunded events, and sanity‑check with comparables.
Details
Current trend
Identify drivers (new chain launch, incentives running down, security incident, macro moves, airdrop expectations).
Classify each driver as persistent or one‑off.
Sustainability check
Compare with similar protocols on DefiLlama or the same protocol on other chains straight after launch.
Look for mean‑reversion signals (e.g., inflated TVL from mercenary liquidity).
External shocks
Governance votes, token unlocks, or competing protocol launches within the evaluation period can alter adoption.
Volatility reference
Use historical 30-day TVL volatility of analogues to size error bars.
Write the baseline number
Express it as an average TVL; translate to the $0–$1 payout scale.
Example baseline – Protocol currently holds $11 M TVL and has lost $2 M over the last 30 days (-15 %). Assuming the same bleed continues, average TVL for the next 30-day period ≈ $10 M. With upper bound $50 M, this implies a payout of 10 ÷ 50 = 0.20.
Forecasting the Funded market
Takeaway Start with your Not Funded baseline, then layer on proposal impact—mainly the effect of incentives, product upgrades, and marketing funded by the grant.
Details
Reuse Not Funded analysis
Everything that moves TVL without the grant still matters with funding.
Quantify proposal impact
Incentive magnitude and timing
Check the proposal’s requested amount and emission schedule.
Benchmark versus the Key metrics → Incentives table on DefiLlama (expand to view 24 h, 30 d, and cumulative emissions).
e.g. – If similar protocols show a median $3 M TVL bump per $10 K in incentives over 30 days, a $100 K grant suggests ≈ $30 M incremental TVL.
Mechanism design
Targeted liquidity mining, ve‑token models, volume rebates—all influence stickiness and effectiveness.
Lead time
Grants paid near the end of the evaluation period may only minimally impact the 30‑day average.
Speed to new equilibrium
Investigate how long similar protocols took for TVL to increase after incentives began (DefiLlama TVL chart).
Example – Past launches hit 80% of their eventual uplift within 7 days; if incentives start on day 15, only ~½ of the uplift affects the 30-day average.
Execution risk
Track record, technical complexity, etc. Discount accordingly.
Cross‑scenario sanity
Ensure your Funded forecast ≥ Not Funded forecast (unless the proposal has negative value!).
Convert to payout scale
Add the incremental TVL to the baseline, then map to the $0–$1 scalar range.
Putting it together – Baseline $10 M + incentive uplift $30M = $40M. Implied payout with 50M cap = 40M ÷ 50M = 0.8. Compare this with the market's implied forecast.
Forecasting Risks
Metric shock risk – The longer the evaluation period, the more unknowns (security hacks, macro swings). Your forecast should account for this increased range of potential outcomes, if you do not plan to close out your position during the trading period.
Data sources and tools
Historical and live TVL
Each protocol's DefiLlama page (Include Borrowing TVL) & UF CFM1 Dune dashboard
Incentive benchmarks
DefiLlama → Key metrics → Incentives (expand for 24 h / 30 d / cumulative)
Forecasting insights & discussion
Proposal details
Butter app → proposal page → Click "Project application" link
Macro market context
L2 TVL dashboards, ETH gas trends, stablecoin supply
Crowd sentiment
Butter market prices at Butter app
Last updated