Data-led risk management for all.
Stay in when the market's healthy. Step aside when it isn't.
Most plans don't fail because the market drops. They fail because people can't sit through years of losses waiting for the rebound — so they sell at the bottom. Limnal watches the economy and the market every day and turns it into one clear call: lean in, or play defense. The aim isn't to out-sprint a roaring bull — it's to keep most of the good years while sidestepping the deep, multi-year losses that break most investors.
Headline risk score
as of 2026-04-13Synthesized from the macro and treasury-flow models at this rebalance. The full model on Overview combines six independent strategies into a 1.0–3.0 scale.
Whether you're new to managing risk or a professional running an active overlay, it's the same product: simple on the surface, fully detailed underneath.
Planning for retirement and tired of markets feeling like a coin flip? You get one plain-English readout every day: is the model favorable or cautious right now? Choose how often you want to adjust — anywhere from weekly to once a year — match it to your account, and you're done. No charts to decode, no jargon required.
The same product exposes the underlying scores, the per-asset weighting, the full simulation mechanics, and a methodology that names every data source. Nothing is hidden. Run Limnal as one active overlay among several, or take the live signals into your own framework.
The complexity is on our side. Detailed enough for a professional, simple enough for someone doing this for the first time.
You don't have to hand over your whole portfolio. The two most common ways to use Limnal are very different — and either is a sound place to start.
Hold the portfolio Limnal recommends
Use it in a retirement account (Roth IRA, traditional IRA, or a 401(k) rollover). Hold what Limnal recommends and adjust at the pace you picked. Most people start with Adaptive — it checks in weekly and automatically pulls equity down to 20% when the market is clearly in a sustained decline. In a retirement account you don't owe tax each time the model adjusts, which is what makes a weekly check-in practical.
Best for: people who want their retirement savings risk-managed without watching markets every week.
Keep your portfolio; use Limnal to time new contributions
Leave everything you own exactly as it is. When the model reads favorable, put that month's contribution into the market. When it reads cautious, hold it as cash and wait for a friendlier read. This works in any account, because you're only deciding when new money goes in — never selling what you already hold.
Best for: people who already index but want a data-led way to time the money they add each month, instead of buying blind.
Adjusting a portfolio often in a regular taxable account triggers short-term taxes that quietly eat returns. The less often you adjust, the smaller that bite. Match how often Limnal adjusts to the account you'll run it in.
| Cadence | Best fit | Caveat |
|---|---|---|
| Adaptive flagship | Roth IRA, traditional IRA, 401(k) rollover | Weekly rebalance with a daily kill switch that caps equity at 20% on confirmed bear days; IRA-best because of weekly turnover |
| Adaptive+ | Roth IRA, traditional IRA only | Adaptive plus 0–15% leverage overlay; daily leverage trigger creates short-term gains; tax-shelter required |
| Monthly | IRA preferred; works in taxable for higher net worth | Some short-term gain drag in a taxable account |
| Quarterly | Taxable accounts, IRAs, anything | Lower tax drag than Monthly; mostly long-term gains |
| Semi-Annual | Taxable accounts, IRAs, anything | Even lower tax drag; most realized gains end up long-term |
| Annual | Taxable accounts, IRAs, anything | Lowest tax drag; least responsive between annual syncs (5pp threshold still fires intra-year for big regime shifts) |
Information, not tax advice. The right pace depends on your tax bracket, how long you've held positions, and prior capital losses, among other things. If you're unsure, talk to a CPA before automating anything in a taxable account.
$10,000, simulated day by day over the historical window
What a $10,000 starting balance would have done in Limnal Adaptive (our flagship), traced against three things most people already hold: the S&P 500, a classic 60/40 stocks-and-bonds mix, and a 2050 target-date retirement fund.
See the worst-drop, month-by-month, and “does it hold up in every window” views → /performance
A look at what subscribers actually see. The risk score and recommended mix replay the last few weeks of model output so you can watch how it moves — illustrations of the mechanics, not a recommendation for today.
Headline risk score
as of 2026-04-13Synthesized from the macro and treasury-flow models at this rebalance. The full model on Overview combines six independent strategies into a 1.0–3.0 scale.
Recommended allocation
as of 2026-04-13Animating through 8 historical weekly snapshots (2026-04-13 to 2026-06-01). Illustrative only; not a current recommendation.
Allocation over time
| Equity | 2.2% | 72.8% | 87.0% | range 84.8pp |
| Fixed income | 0.1% | 4.8% | 15.1% | range 15.0pp |
| Credit | 0.0% | 1.4% | 4.6% | range 4.6pp |
| Commodities | 1.9% | 11.6% | 18.7% | range 16.7pp |
| Alts | 0.0% | 8.5% | 13.1% | range 13.1pp |
| Cash | 0.0% | 0.0% | 72.4% | range 72.4pp |
Drawdown
Monthly returns
| Portfolio | Jan '16 | Feb '16 | Mar '16 | Apr '16 | May '16 | Jun '16 | Jul '16 | Aug '16 | Sep '16 | Oct '16 | Nov '16 | Dec '16 | Jan '17 | Feb '17 | Mar '17 | Apr '17 | May '17 | Jun '17 | Jul '17 | Aug '17 | Sep '17 | Oct '17 | Nov '17 | Dec '17 | Jan '18 | Feb '18 | Mar '18 | Apr '18 | May '18 | Jun '18 | Jul '18 | Aug '18 | Sep '18 | Oct '18 | Nov '18 | Dec '18 | Jan '19 | Feb '19 | Mar '19 | Apr '19 | May '19 | Jun '19 | Jul '19 | Aug '19 | Sep '19 | Oct '19 | Nov '19 | Dec '19 | Jan '20 | Feb '20 | Mar '20 | Apr '20 | May '20 | Jun '20 | Jul '20 | Aug '20 | Sep '20 | Oct '20 | Nov '20 | Dec '20 | Jan '21 | Feb '21 | Mar '21 | Apr '21 | May '21 | Jun '21 | Jul '21 | Aug '21 | Sep '21 | Oct '21 | Nov '21 | Dec '21 | Jan '22 | Feb '22 | Mar '22 | Apr '22 | May '22 | Jun '22 | Jul '22 | Aug '22 | Sep '22 | Oct '22 | Nov '22 | Dec '22 | Jan '23 | Feb '23 | Mar '23 | Apr '23 | May '23 | Jun '23 | Jul '23 | Aug '23 | Sep '23 | Oct '23 | Nov '23 | Dec '23 | Jan '24 | Feb '24 | Mar '24 | Apr '24 | May '24 | Jun '24 | Jul '24 | Aug '24 | Sep '24 | Oct '24 | Nov '24 | Dec '24 | Jan '25 | Feb '25 | Mar '25 | Apr '25 | May '25 | Jun '25 | Jul '25 | Aug '25 | Sep '25 | Oct '25 | Nov '25 | Dec '25 | Jan '26 | Feb '26 | Mar '26 | Apr '26 | May '26 | Jun '26 | Total |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Adapt·SA·Trim | -2.3 | 0.0 | 4.1 | 1.0 | -0.2 | 1.4 | 2.8 | -0.1 | 0.8 | -1.7 | 0.1 | 1.8 | 2.2 | 2.6 | 0.5 | -0.4 | 1.6 | 0.1 | 2.7 | 0.6 | 1.4 | 2.9 | 1.3 | 1.7 | 5.4 | -4.1 | -1.3 | 1.1 | -0.2 | -1.1 | 2.3 | 1.1 | 0.4 | -5.1 | 0.0 | -1.2 | 2.6 | 1.0 | 2.0 | 2.3 | -3.8 | 4.4 | 0.3 | -0.6 | 1.6 | 1.8 | 1.9 | 2.5 | -1.7 | -3.0 | -2.6 | 4.1 | 3.2 | 1.6 | 5.1 | 4.3 | -2.9 | -2.2 | 11.3 | 4.7 | 0.3 | 2.8 | 2.3 | 3.7 | -0.5 | 0.6 | 0.5 | 1.4 | -3.4 | 4.6 | -2.5 | 3.5 | -0.3 | 0.4 | 1.3 | -0.6 | 0.9 | -3.6 | 1.8 | -2.6 | -5.1 | 1.8 | 4.6 | -1.9 | 5.7 | -3.8 | 2.4 | 1.5 | -2.3 | 4.8 | 3.1 | -1.8 | -2.5 | 0.0 | 0.7 | 3.1 | 0.4 | 3.7 | 3.8 | -2.0 | 3.0 | 1.5 | 1.0 | -0.8 | 2.0 | -2.4 | 2.8 | -1.8 | 3.5 | -0.4 | 0.3 | 0.8 | 1.6 | 3.3 | 0.3 | 2.7 | 3.4 | 1.8 | 0.5 | 1.1 | 4.6 | 3.5 | -4.3 | 4.2 | 3.5 | 0.9 | +229.4% |
| Simple·Trim | -2.2 | 0.2 | 3.5 | 1.2 | -0.3 | 1.9 | 2.5 | -0.1 | 1.1 | -1.7 | -0.1 | 2.0 | 1.3 | 2.4 | 0.0 | -0.4 | 1.6 | -0.1 | 2.6 | 0.6 | 1.3 | 3.5 | 1.0 | 1.7 | 5.8 | -4.2 | -1.6 | 1.0 | -0.0 | 0.1 | 1.8 | 3.0 | 0.6 | -5.7 | 0.0 | -1.4 | 3.2 | 1.3 | 1.9 | 1.9 | -3.1 | 4.2 | 0.5 | -0.8 | 1.4 | 2.1 | 1.6 | 3.5 | -1.8 | -3.3 | -3.4 | 4.1 | 2.6 | 2.2 | 5.0 | 4.1 | -3.1 | -1.9 | 10.1 | 4.7 | 0.4 | 2.6 | 1.8 | 3.5 | 0.2 | 0.5 | -0.3 | 1.5 | -2.4 | 4.2 | -2.7 | 3.4 | 0.4 | 0.3 | 0.9 | -0.9 | 0.9 | -4.2 | 1.6 | -1.9 | -4.8 | 3.0 | 2.9 | -2.0 | 5.3 | -3.7 | 2.0 | 1.3 | -2.5 | 4.8 | 3.1 | -2.1 | -2.3 | -0.2 | 0.7 | 3.0 | 0.8 | 3.7 | 3.9 | -2.2 | 3.0 | 1.3 | 1.0 | -0.6 | 2.0 | -1.8 | 3.5 | -1.9 | 3.5 | -0.2 | 0.3 | 1.2 | 1.5 | 3.2 | -0.0 | 2.9 | 3.4 | 1.8 | 0.6 | 1.4 | 4.8 | 4.1 | -4.7 | 4.0 | 3.3 | 1.0 | +227.1% |
| SPY | -3.6 | -0.1 | 6.7 | 0.4 | 1.7 | 0.3 | 3.6 | 0.1 | 0.0 | -1.7 | 3.7 | 2.0 | 1.8 | 3.9 | 0.1 | 1.0 | 1.4 | 0.6 | 2.1 | 0.3 | 2.0 | 2.4 | 3.1 | 1.2 | 5.6 | -3.6 | -2.7 | 0.5 | 2.4 | 0.6 | 3.7 | 3.2 | 0.6 | -6.9 | 1.9 | -8.8 | 8.0 | 3.2 | 1.8 | 4.1 | -6.4 | 7.0 | 1.5 | -1.7 | 1.9 | 2.2 | 3.6 | 2.9 | -0.0 | -7.9 | -12.5 | 12.7 | 4.8 | 1.8 | 5.9 | 7.0 | -3.7 | -2.5 | 10.9 | 3.7 | -1.0 | 2.8 | 4.5 | 5.3 | 0.7 | 2.2 | 2.4 | 3.0 | -4.7 | 7.0 | -0.8 | 4.6 | -5.3 | -3.0 | 3.8 | -8.8 | 0.2 | -8.2 | 9.2 | -4.1 | -9.2 | 8.1 | 5.6 | -5.8 | 6.3 | -2.5 | 3.7 | 1.6 | 0.5 | 6.5 | 3.3 | -1.6 | -4.7 | -2.2 | 9.1 | 4.6 | 1.6 | 5.2 | 3.3 | -4.0 | 5.1 | 3.5 | 1.2 | 2.3 | 2.1 | -0.9 | 6.0 | -2.4 | 2.7 | -1.3 | -5.6 | -0.9 | 6.3 | 5.1 | 2.3 | 2.1 | 3.6 | 2.4 | 0.2 | 0.1 | 1.5 | -0.9 | -4.9 | 10.5 | 5.3 | 0.4 | +347.1% |
| 60/40 | -1.6 | 0.3 | 4.4 | 0.4 | 1.0 | 1.0 | 2.4 | -0.0 | 0.0 | -1.4 | 1.2 | 1.3 | 1.2 | 2.6 | 0.1 | 1.0 | 1.1 | 0.4 | 1.4 | 0.6 | 1.0 | 1.5 | 1.8 | 0.9 | 2.9 | -2.5 | -1.3 | -0.0 | 1.7 | 0.4 | 2.2 | 2.1 | 0.1 | -4.4 | 1.5 | -4.6 | 5.2 | 1.9 | 2.0 | 2.4 | -3.1 | 4.6 | 1.0 | 0.2 | 0.9 | 1.4 | 2.1 | 1.7 | 0.8 | -4.2 | -7.1 | 8.3 | 3.2 | 1.4 | 4.1 | 3.8 | -2.2 | -1.7 | 6.9 | 2.3 | -0.9 | 1.1 | 2.3 | 3.5 | 0.5 | 1.7 | 1.9 | 1.7 | -3.2 | 4.2 | -0.4 | 2.6 | -3.9 | -2.2 | 1.1 | -6.8 | 0.5 | -5.6 | 6.5 | -3.6 | -7.2 | 4.3 | 4.9 | -3.8 | 5.1 | -2.6 | 3.3 | 1.2 | -0.2 | 3.7 | 1.9 | -1.2 | -3.9 | -1.9 | 7.3 | 4.2 | 0.9 | 2.5 | 2.3 | -3.4 | 3.7 | 2.5 | 1.7 | 2.0 | 1.8 | -1.5 | 4.0 | -2.1 | 1.8 | 0.1 | -3.3 | -0.1 | 3.5 | 3.7 | 1.3 | 1.7 | 2.6 | 1.7 | 0.4 | -0.1 | 1.0 | 0.1 | -3.7 | 6.3 | 3.3 | 0.2 | +177.1% |
| VFIFX | -3.5 | -0.8 | 6.8 | 1.2 | 0.6 | 0.0 | 3.8 | 0.4 | 0.6 | -1.9 | 1.4 | 1.8 | 2.4 | 2.6 | 1.0 | 1.5 | 1.7 | 0.7 | 2.3 | 0.4 | 1.9 | 1.9 | 1.9 | 1.3 | 4.8 | -3.9 | -1.2 | 0.4 | 0.9 | -0.4 | 2.7 | 1.1 | 0.2 | -7.1 | 1.6 | -6.6 | 7.4 | 2.5 | 1.2 | 3.1 | -5.3 | 6.0 | 0.2 | -1.7 | 1.8 | 2.3 | 2.4 | 3.1 | -1.0 | -6.7 | -13.3 | 10.3 | 4.6 | 2.9 | 4.7 | 5.3 | -2.6 | -2.0 | 11.3 | 4.5 | -0.3 | 2.4 | 2.4 | 3.8 | 1.4 | 1.3 | 0.6 | 2.1 | -3.7 | 4.5 | -2.3 | 3.5 | -4.5 | -2.5 | 1.3 | -7.5 | 0.4 | -7.6 | 6.6 | -3.8 | -9.0 | 5.5 | 7.9 | -4.1 | 7.1 | -3.0 | 2.7 | 1.2 | -1.1 | 5.2 | 3.3 | -2.7 | -4.0 | -2.8 | 8.5 | 5.1 | -0.0 | 3.9 | 2.9 | -3.4 | 4.1 | 1.5 | 2.2 | 2.2 | 2.2 | -2.3 | 3.6 | -2.7 | 2.9 | -0.3 | -3.1 | 0.9 | 5.0 | 4.3 | 0.9 | 2.8 | 3.3 | 1.8 | 0.3 | 0.9 | 3.0 | 1.8 | -6.0 | 8.4 | 4.2 | 0.3 | +222.6% |
Buy-and-hold is great — until you hit a decade you can't sit through
For ~50 years, simply buying the market and holding it has beaten most professional stock-pickers. Bogle, Buffett, and the data all agree: roughly 80% of active US funds lose to their benchmark over ten years. Passive investing works. The catch is what you have to survive for it to work.
Buy the S&P 500 at the 2000 peak and, after inflation, you were underwater for 13 years — until 2013. Buy in 1929 and the wait was 25 years. Most people brace for a bad year or two. Almost no one plans for a decade of watching their biggest investment sit below water — and most sell long before it comes back.
$10k in the S&P 500 at the March 2000 peak, in real (inflation-adjusted) dollars through 2013. The shaded band is the entire stretch spent below what you paid.
Stylized; based on S&P 500 total return adjusted for inflation.
We're not predicting the future, and in a roaring bull the S&P's raw return can beat us. What Limnal is built for is the part buy-and-hold can't give you: far shallower drops, and better return for the risk you take. It reads the signals — the economy and price action — and shifts to a clear allocation as conditions change.
Think of Limnal as a weather station for the economy and the market. Fair weather, lean in. Storm coming, move to shelter. Over a full cycle, that discipline spares you the real cost: being stuck in a losing position for years, waiting on a recovery that may not arrive in time.
“Active management loses to indexing” is true for stock-picking. The evidence on systematic, rules-based strategies that shift with conditions is a different story:
- Peer-reviewed tactical-allocation research (2007) — a simple trend rule cut the S&P's worst drop from −51% to −14%, with comparable returns.
- Time-series momentum literature (2012) — trend-following earns positive risk-adjusted returns across stocks, bonds, currencies and commodities back to 1880.
- Dual-momentum frameworks (2014) — 16% annualized over 1974–2013, with a −23% worst drop vs the S&P's −51%.
Stock-picking loses to indices. Systematic, regime-aware investing doesn't have to.
Pull Data
Pulls economic data from the Federal Reserve and pairs it with price, momentum and volatility — a full read of the current market environment.
Calculate and Score
Six independent models score risk across the market, each with its own method.
Allocate Portfolio
Their consensus becomes a concrete portfolio: 17 ETFs, adjusted weekly, every weight shown.
Limnal is rules-based. Every input feeds a fixed calculation — no AI, no black box. The same inputs always produce the same portfolio.
Macro Regime
Growth · Inflation · LiquidityRisk assets behave very differently across regimes. Getting on the right side of a regime shift early is worth more than picking the perfect security inside one.
DTS Liquidity
US Treasury fiscal flowsWhen the Treasury runs a surplus, it pulls cash out of risk assets. When it runs a deficit, it pushes cash in. These flows tend to lead price by days to weeks.
Momentum
8 macro categoriesTrend persistence is one of the most-replicated anomalies in finance. Things moving in one direction tend to keep moving; investors are slow to update priors.
COT Positioning
Speculator vs commercialExtreme positioning often precedes mean reversion; persistent positioning can confirm a trend. The model reads both.
Expected Returns
Forward-looking CMAForward-looking expected return per asset class, anchored on yield, growth, and valuation. Sets the baseline portfolio envelope; the other models tilt allocations away from that baseline when their signals warrant.
Dealer Flow
Options dealer hedgingWhen dealers are short gamma, every move forces them to chase, amplifying volatility. When long, they dampen it. Predictable price gravity around expirations.
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This is information, not investment advice. Past backtest performance does not guarantee future results. Frictionless simulations don't reflect transaction costs, tax effects, or individual circumstances. Limnal Research provides analytics; investment decisions are yours.