The Exposure Model
A rules-based signal decides how much levered S&P 500 exposure to hold. When the signal is favorable, exposure goes up, and so does the potential for losses.
For late-start investors
Levered S&P 500 exposure.
Rules designed to reduce drawdowns.
Risks stated plainly.
3xit.ai is a mobile app for late-start investors. It applies a rules-based model that sets how much levered S&P 500 exposure to hold, and cuts that exposure when its risk signals rise, in an effort to limit losses.
Leverage amplifies losses as well as gains. Losses can be large and fast, the risk controls may not work in every market, and you can lose most of what you invest.
The math you've already done
Is your 401(k) on track?
If not, here's one option to consider.
If you've run the numbers and your current plan won't reach the retirement you envisioned, you may be weighing different approaches. 3xit.ai is one of them: concentrated, levered exposure to the S&P 500, governed by rules designed to reduce drawdowns. It carries more risk than a diversified, unlevered portfolio and is not suitable for everyone. Whether it fits you is what onboarding decides.
40–55
The late-start window — when traditional timelines can stop adding up
Higher risk
A levered, concentrated strategy can lose more, and faster, than a diversified one.
The gap
The distance between where your savings are and where you want them to be
A disciplined, rules-based process, with the risks stated up front.
Rules-based leverage
Leverage, with rules attached.
Leveraged ETFs amplify losses as much as gains, and so can 3xit.ai. The difference is a rules-based model that seeks to limit losses by reducing exposure when its risk signals rise. It may not succeed: in sudden market moves, losses can be large before the model reacts.
Drawdown Controls
Designed to reduce drawdowns: when the model's risk signals rise, it cuts exposure. Risk controls can fail or react too late, and you can still lose most of what you invest.
What It Is, and Isn't
A systematic model, not a human adviser. It trades S&P 500 exposure only and does not diversify across asset classes, so a broad market decline hits it directly.
Where 3xit.ai stands
How it compares.
Robo-advisors
Diversified across asset classes, typically unlevered.
3xit.ai is concentrated in the S&P 500 and levered, with higher potential for both gains and losses.
Self-directed trading
Tools, but you make every decision.
3xit.ai uses a rules-based model to make exposure decisions. You still bear the risk of those decisions.
Leveraged ETFs
Fixed daily leverage, held through every market.
3xit.ai changes exposure with the model's signals. That can reduce drawdowns or miss rebounds, and it is not guaranteed to do better.
Hypothetical backtest
Hypothetical performance is not for everyone.
We show our hypothetical backtest only to people whose answers suggest a levered strategy may fit their situation. Your answers are recorded. They are not individual advice, and passing does not mean the strategy is suitable for you. You can take this once every 24 hours.
Hypothetical backtest
The growth of $100,000
These are hypothetical results, not actual trading. They were produced by applying the strategy's rules to historical data. No client account achieved them, and you could not have invested in them.
Methodology. An automated walk-forward strategy. The signal is computed on 5-minute SPXL/SPXS bars and executed as 3x S&P 500 exposure via index futures; returns are modeled on the S&P 500 index path with financing and dividends, net of estimated transaction costs (5 bps one way). Trading decisions use only prior-bar information (no look-ahead). Drawdowns are daily peak-to-trough; the chart plots weekly values. The 60/40 portfolio assumes a 2.5%/yr bond sleeve.
Fees.
Limitations. The rules were designed with knowledge of past markets, and walk-forward testing reduces but does not remove that hindsight bias. Backtests do not capture every real-world factor, such as liquidity, execution delays, slippage beyond the cost estimate, margin calls or changes in financing costs, and they do not reflect how investors actually behave during losses. The test covers one 12-year period that was mostly favorable to U.S. stocks; a different period could give very different results. Actual results will differ and may be much worse, including large losses.
| Strategy | Max drawdown | CAGR | Sharpe | $100k became |
|---|
Insights
Understanding leverage.
Strategy
Rethinking Late-Start Retirement Timelines
What the numbers look like when you start later, and the trade-offs of different approaches.
Read → RiskLeverage and Drawdowns: What Can Go Wrong
How drawdown controls are meant to work, and why they can fail.
Read → MechanicsRules-Based Leverage vs. Margin Trading
How the two differ, and the risks they share.
Read →See whether 3xit.ai fits you.
Join the waitlist to hear when access opens. Onboarding will ask about your goals and risk tolerance to determine whether a levered strategy is suitable for you.