Risk On means the conditions a strategy requires for holding equities are being met, so it holds them. Risk Off means they are not, so it holds something defensive instead: treasuries, short-duration bonds, or cash equivalents depending on the strategy.
The terms describe a state the rules produce, not a forecast anyone is making. A strategy is Risk Off because a measurable condition failed, not because a decline is expected.
The site-wide Risk On / Risk Off indicator
The indicator shown on the site is a single, simple comparison:
Risk Off when the weighted momentum of US large-cap equities is at or below the weighted momentum of cash. Risk On otherwise.
In plain terms: if broad US equities have not been outperforming cash on a blended measure of recent returns, the market is in a Risk Off state.
The momentum figure here is the standard DMS weighted average, which blends the trailing 1, 3, and 6-month returns with half the weight on the 6-month leg. See the momentum FAQ for why it is built that way.
This indicator is a general market read. It is deliberately simple, it is stateless, and it is the same measure regardless of which strategy you happen to be looking at.
Individual strategies use their own gates
Here is the part worth understanding clearly: a strategy's own Risk On / Risk Off decision is not necessarily the same as the site-wide indicator.
Global Navigator, for example, considers both US and international equities. It goes Risk Off only when both fail to beat cash. So there are months where the site-wide indicator reads Risk Off, because US equities are lagging cash, while Global Navigator is fully Risk On and holding international equities, because those are beating cash comfortably.
Other strategies differ more still. Some use moving-average gates rather than momentum comparisons. Some have multiple sleeves that can be in different states simultaneously, so the strategy as a whole is neither wholly Risk On nor wholly Risk Off. Some use a canary asset, where an unrelated instrument acts as the trigger.
The site-wide indicator tells you the general weather. The strategy's allocation tells you what that strategy is actually doing, and the allocation is authoritative.
The signal is lagged deliberately
Signals are computed from the prior month's completed data, then applied to the month ahead. No strategy uses data from the month it is trading in, because that data does not exist yet when the decision has to be made.
This is a correctness requirement rather than a design preference. A backtest that decides January's allocation using January's returns is reporting results nobody could have achieved.
What being Risk Off does and does not mean
Why the equity-versus-cash comparison
The comparison is not "are equities rising" but "are equities beating cash." Those are different questions, and the second is the one that matters to someone deciding where to put money.
Equities grinding out 1% a year while cash pays 5% are rising and are also the wrong place to be. Using cash as the reference point builds that judgment into the rule automatically, and it is what makes the same rule sensible across eras with wildly different interest rates.
Momentum in these strategies means something specific and mechanical: a number computed from an asset's own recent returns, used to rank it against other assets or to test it against cash. Different strategy families use different formulas, and the differences are deliberate.
The DMS weighted average
The formula used by Global Navigator, LT Gain, Smart Leverage, and the site-wide Risk On / Risk Off indicator is:
wa = 0.25 x (1-month return) + 0.25 x (3-month return) + 0.50 x (6-month return)
Each component is the cumulative return over that trailing window, through the end of the most recently completed month. Half the total weight sits on the 6-month leg.
Why six months carries half the weight
The instinct is usually the opposite. Recent data feels more relevant, so weighting the most recent month heavily seems more responsive and therefore more protective.
We tested exactly that. Reversing the emphasis to put half the weight on the 1-month leg was run across the full history of the Global Navigator family. It was worse. The reason is instructive: a signal dominated by the most recent month is easily flipped by a single counter-trend bounce, and counter-trend bounces are a defining feature of the exact market episodes a defensive rule exists to catch. In both October 1987 and the 1994 bond selloff, a one-month rebound would have vetoed a defensive move that the slower weighting correctly took.
The current weighting also sits on a wide plateau. Varying the 1-month weight anywhere from zero to 0.40 produces identical results, which is the signature of a robust setting rather than a tuned one. A parameter that only works at one precise value is usually fitted to history rather than measuring anything real.
Other formulas in use
Not every strategy on the site uses the DMS weighted average. The third-party strategies published here use the formulas their original authors specified, because reproducing someone else's strategy means reproducing their rules, not substituting ours.
What all of these have in common
Why any of this works
The honest answer is that nobody knows with certainty, and the strategies do not depend on knowing. Momentum's persistence across a century of data, across asset classes, and across markets is one of the most heavily documented effects in finance, and it has survived publication, which most claimed anomalies do not.
The common explanations involve investors reacting to news gradually rather than instantly, and then overreacting once a trend is established. Whether that is the true mechanism is not something a backtest can settle.
What we can say is narrower and more useful: over the full record available, ranking assets by these formulas and holding the leaders has produced better risk-adjusted outcomes than holding everything through everything. That is an empirical claim about the past, and it is the only kind of claim any of this can support.
Where to see the numbers
Each strategy's page shows the signal values driving its current allocation, using whichever formula that strategy actually employs. If a strategy is Risk Off and you want to know how close the call was, that is where to look.
Smart Leverage is a rules-based overlay used in several DMS strategies that selectively deploys leveraged ETFs during market recovery windows - when the odds are in your favor of capturing additional gains on the upside without large downside risk. It is not the same as being permanently leveraged. The base strategy operates unleveraged; leverage is an occasional, conditional event triggered by a market drawdown.
Arming, then deploying
Smart Leverage works in two steps, and the distinction matters when you are watching a live allocation.
Step one: arming. Smart Leverage watches the month-end drawdown of IWB (the iShares Russell 1000 ETF) from its highest month-end close on record. When that drawdown reaches 10% or greater, Smart Leverage arms. Nothing changes in the portfolio yet.
Step two: deploying. Once armed, Smart Leverage waits for a month where all of the following are true:
Only then does the substitution happen:
The wait can be long. In the spec's worked example the drawdown armed Smart Leverage in March 1980, but momentum did not turn until June, so June is when leverage was actually deployed.
The drawdown is measured from month-end close to month-end close; intraday swings do not trigger Smart Leverage. It can accumulate across multiple months of declining markets, so it is not a single-month measure.
If the strategy rotates to international instead
For strategies that can hold international equities, there is an important exception. If the strategy's Risk On choice turns out to be international rather than IWB while Smart Leverage is armed, the arm is cancelled rather than deployed.
The reasoning: the drawdown fired during a stretch where the strategy preferred international markets. Coming back to IWB later is a different environment, not a continuation of the recovery that armed it.
A cancelled arm also blocks re-arming until the strategy passes through a Risk Off month. Without that block, the drawdown still sitting on the books would simply re-arm Smart Leverage the following month and undo the cancellation.
The exit rule
A live deployment ends on whichever of these comes first:
When the position closes, the strategy returns to its unleveraged default.
One trigger, one deployment
This is the rule most often misread. Once a deployment ends, for any of the three reasons above, the original drawdown is spent. If momentum flips favorable again the very next month, Smart Leverage does not redeploy. Only a fresh 10% drawdown in IWB can arm it again.
The spec's diagnostic case is April 1981: IWB was beating cash, the strategy was in equities, and Smart Leverage stayed on the sidelines because the drawdown that had armed it earlier was already used up.
A note on taxes
The 12-month cap is deliberately set where it is partly with taxable accounts in mind, since a longer hold is more likely to reach favorable long-term treatment than rapid in-and-out trading. Treat that as a design leaning, not a promise - the IRS long-term test requires holding more than one year, and a position closed at the twelve-month cap sits right at that boundary. Your own treatment depends on actual trade dates and your tax situation.
How often does it trigger?
Smart Leverage triggers infrequently and selectively. The goal is not to be leveraged most of the time, but to concentrate leverage in high-conviction recovery setups - periods where a meaningful market pullback has already occurred and momentum signals a return to equities.
Historical track record
The historical results have been compelling. For Global Navigator, only one of its Smart Leverage periods produced a worse outcome than staying unleveraged would have.
What Smart Leverage is not
Smart Leverage is not a guarantee. Leverage amplifies both gains and losses - if the market continues to fall after deployment, the impact is magnified compared to holding the unleveraged fund. The historical win rate is high, but no rule works every time. Anyone using a leveraged strategy variant should be comfortable with the possibility of outsized drawdowns during the periods when leverage is active.
To date, the Smart Leverage variants have not recorded deeper maximum drawdowns than their unleveraged parents. That is a historical observation, not a property of the design, and it may not hold in future.
Which strategies use Smart Leverage?
Six: Global Navigator 200 and 300, LT Gain 200 and 300, and Triad 135 and 170.
The three-digit number in a strategy's name indicates its maximum total notional leverage - Triad 135 can reach 135%, Global Navigator 300 can reach 300%. Some strategies carry such a number without running the overlay themselves. Calculated Risk 229 and Calculated Risk 288 are portfolios of other strategies, and their leverage comes from the leveraged components they hold rather than from their own Smart Leverage instance.
If you pull up a strategy on the Strategy View page, you can see the maximum and average leverage positions by strategy at the bottom of the ALLOCATIONS & CONTRIBUTIONS section.
Treasury Duration Limiter, TDL. A protective overlay built into several DMS strategies that steers the Risk Off holding into short-duration treasuries when long-duration treasuries look hazardous.
Why it exists
Several DMS strategies hold long-duration treasuries as their Risk Off asset. Historically, when equities fall, investors flee to long-duration treasuries, which drives their prices up and helps cushion market drawdowns. That relationship held reliably for decades, but it is not guaranteed. In early 2022, rising interest rates caused long-duration treasuries to fall at the same time as equities - one of the worst years on record for long-duration treasury returns. Strategies that rotated defensively into long-term treasuries in that environment found that the expected safe harbor was also under water.
TDL was developed in response to that reality. The goal: if long-duration treasuries look likely to be hazardous, steer into short-duration treasuries instead and avoid compounding a bad equity period with a bad treasury period.
How the signal works
TDL uses a momentum signal on long-duration treasuries themselves. It applies a weighted lookback to long-duration treasury returns, blending the trailing 1, 3, and 6-month results with half the weight on the 6-month leg. If that weighted result is negative - long duration is losing money on its own terms - TDL fires and the Risk Off allocation moves to short-duration treasuries.
The deliberate emphasis on the slower 6-month leg matters. The episodes TDL exists to catch are ones where long duration has been damaged for months but has just bounced. A faster, more recent-weighted formula would let a single flight-to-quality month veto the signal. Testing across 44 years of history confirmed this: weighting the most recent month more heavily caused TDL to miss both October 1987 and the 1994 bond massacre. The current weighting also sits on a wide plateau, meaning small changes to it produce identical results - a sign the setting is robust rather than tuned.
Once TDL fires, it stays fired
TDL is not re-evaluated every month. Once it fires within a Risk Off run, the short-duration position is locked and held for the remainder of that run. The lock clears only when the strategy returns to Risk On.
This is intentional. It prevents whipsawing back into long duration on a single-month reversal, and it produces a smoother path with fewer trades. The tradeoff is real: if long-duration treasuries rally later in the same Risk Off run, the strategy sits it out. That cost was measured and accepted.
What TDL does not do
TDL is only active when a strategy is already in its Risk Off, defensive position. It has no effect on equity allocations and does not determine when to enter or exit equities - that remains the exclusive domain of the strategy's momentum rules. TDL is purely a safety layer within the treasury sleeve.
Which strategies use it
TDL is built into the Global Navigator family (Global Navigator, 200, and 300) and the LT Gain family (LT Gain, 200, and 300). It is part of those strategies, not a separately configurable option.
Not every DMS strategy needs it. Triad, for example, was tested with four different TDL variants on its defensive sleeve and every one performed worse than leaving the sleeve alone. Global Navigator needs a TDL because it goes fully Risk Off for extended runs. Triad's defensive weight is much smaller and is already conditioned by three separate trend gates, so a second timing layer adds whipsaw rather than protection.
Every DMS strategy makes a decision once a month. Whether that decision produces a trade is a separate question, and the answer varies enormously across the lineup.
Two different rebalancing philosophies
Signal-driven strategies trade whenever their rules point somewhere new. A momentum strategy that rotates from equities to treasuries acts on that immediately and completely. If the signal is unchanged, the position is generally left alone.
Band-based strategies hold fixed target weights and only trade when a holding drifts far enough away from its target to matter. Between those breaches they do nothing at all, sometimes for years.
Many strategies combine both: signals decide what to hold, bands decide when it is worth trading to get back to precise weights.
How drift bands work
Suppose a strategy targets 25% in an asset. Rather than restoring exactly 25% every month, it defines a band around that target, and trades only when the position leaves the band.
The Permanent Portfolio strategies use a wide band on their four equal sleeves, rebalancing a sleeve only when it falls below 15% or rises above 35%. They also rebalance every January regardless. In practice this means long stretches with no trading at all.
Other strategies use tighter bands. Triad allows its sleeves to drift within a 5% band before pulling them back. GPMv uses a similar tolerance.
Why not just rebalance every month?
Because precision is not free and it is not obviously better.
The tradeoff is that a band-based strategy carries somewhat different weights than its stated targets most of the time. The bands are set so that difference stays within a range that does not change the strategy's character.
What this looks like on the site
Two consequences you will notice in the Allocations view:
Published weights change even when nothing was traded. A portfolio left completely alone still shows different percentages next month, because the holdings grew and shrank at different rates. That is drift, not activity.
Trading costs do not track changes in published weights. The friction model compares each month's targets against what the strategy was actually holding after drift, not against last month's published percentages. A month spent holding costs nothing even though the numbers moved. A rebalance back to unchanged targets does cost something, because real money moved. The Trading Friction FAQ covers this in detail.
Why the difference matters when choosing a strategy
Turnover is a real consideration, not a technicality:
None of this makes low turnover better in the abstract. A strategy that trades often because its rules genuinely call for it is doing its job. But two strategies with similar returns and very different turnover are not equally attractive in every account.
Where to check
Each strategy's page reports its historical turnover and trading costs, and the Allocations view shows exactly what changed month to month. If you want to know what running a strategy would actually involve month to month, that is the place to look before committing to it.