The minimum-trading-days drag. Nearly free — until it forces you to keep trading.

A minimum-trading-days clause says a funded-in-waiting account cannot pass until it has traded on at least some number of separate days — even if it reached the profit target on day two. On its face this is administrative: a guard against a single lucky session. The question this study asks is narrower and quantitative. For a trader who could have finished early, what does being forced to keep trading actually cost?

Holding one synthetic archetype fixed and moving only the minimum — 1, 5, 10 and 15 days inside a 20-day window — the peak probability of passing fell from 36.1% with no real minimum to 35.4% at 5 days, 31.0% at 10, and 25.3% at 15. The first steps are nearly free; the cost becomes real only once the minimum is a large fraction of the window.

The picture below overlays the four curves. Three of them — 1, 5 and 10 days — sit almost on top of one another through the useful sizing range, so a modest minimum is close to invisible. The 15-day curve, in wine, is the one pulled down and to the left. A minimum-days rule is not a fixed toll you pay up front; it is a drag that stays negligible while it fits comfortably inside the window and then grows as it eats into time a fast finisher would never otherwise have used.

The cost is not administrative; it is exposure. Under a trailing drawdown the breach line follows the account’s high-water mark upward and never comes back down. An account that hits its target has, by definition, just printed new highs — so its floor is now sitting close beneath it. A minimum-days rule then forbids it from banking the pass and sends it back into the market for more days, each one a fresh chance to touch a floor that is now near.

The effect is sharpest exactly where a trader is most tempted to over-size. At 2.5% risk per trade — aggressive for this archetype — 33.2% of attempts passed when the account was allowed to finish in a single day, because the fast winners banked the target before the floor could catch them. Force that same oversized trader to complete 15 days and only 0.0% of attempts passed: the forced days convert nearly every early win into a later breach.

Near the best size the same mechanism is gentler but still present. At 0.8% risk — the peak size under the 15-day rule — 33.9% of attempts passed under a 1-day minimum against 25.3% under the 15-day minimum. So the drag has a shape: near zero when the minimum is small relative to the window, growing as the minimum consumes more of it, and brutal for anyone sizing large enough to have finished in a day or two.

This is why the answer is not “minimum-days rules are hard” or “minimum-days rules are trivial.” It depends entirely on how much of the window the minimum occupies and on how fast the trader would otherwise have finished — the same edge and the same position size meet the rule very differently.

Plot the peak of each curve against the minimum it came from and the cost is easy to read in one line. It is nearly flat at first and then bends down — a drag that accelerates rather than a toll that is charged all at once.

Measured against the no-real-minimum baseline, the drag was about 0.7 of a point at 5 days — a quarter of the window — about 5.1 points at 10 days (half the window), and about 10.8 points at 15 (three-quarters). It is not linear: the step from 5 to 10 days cost several times what the step from 1 to 5 did, and 10 to 15 cost more again.

A rule of thumb falls out of the shape: while a minimum sits below roughly half the window it is close to free for this trader; once it climbs past half, every additional forced day is paid for in peak probability. The same four numbers as bars:

• Minimum 1 day · size 1.1%36.1%
• Minimum 5 days · size 0.9%35.4%
• Minimum 10 days · size 0.8%31.0%
• Minimum 15 days · size 0.8%25.3%

The best position size drifts down as the minimum rises — from 1.1% toward 0.8% of balance — because a trader who will be forced to stay in longer is better off swinging smaller. That shift is small and sits inside the simulation’s noise, but its direction is consistent, and it points the same way as the drag: a longer forced stay rewards a lighter hand. Which rule breaks first ranks the clauses for a single set of numbers.

The practical value is a quick self-test, and it has two inputs you already know: how much of the window the minimum takes up, and how quickly you tend to reach the target.

If you routinely finish with days to spare and the minimum is a small slice of the window, this study says the rule is costing you little — spend your attention on edge and sizing instead. If the minimum is a large fraction of the window, or you tend to finish fast and size large, the rule is quietly taxing you. The cure is not to trade more carefully on the forced days; it is to size down beforehand, so that when you are made to keep trading the extra days are less likely to reach the floor.

This is one clause measured in isolation. A sibling study, the daily-loss-limit cost, measures a daily cap the same way, and which rule breaks first ranks the clauses against one concrete set of numbers. To see the drag for your own inputs rather than this archetype’s, the PropSurvival simulator runs exactly this sweep and reports the same peak.

Every number here is model-derived for one synthetic archetype and one illustrative trader; none is a claim about any named firm or a real group of traders. The archetype was deliberately stripped to a single target and a single trailing drawdown so the minimum-days rule was the only thing that moved. A real evaluation may combine the minimum with a daily loss limit or a consistency rule, and the whole picture is anchored to the reference edge: a stronger edge lifts every curve, a weaker one sinks them. The value here is the shape, not the coordinate.

Three things carry across, and they are the point:

• A minimum-days rule is close to free while it is a small fraction of the window — a modest minimum barely moves the probability of passing.
• It turns into a real, compounding cost once it forces a fast finisher to keep trading — a hidden drawdown-exposure tax, not a scheduling formality.
• The more it binds, the smaller the best position size becomes; a longer forced stay rewards a lighter hand.

Finding the cost for a specific set of numbers is a computation, not a guess. The PropSurvival simulator runs this same sweep on a trader’s own win rate, average win and loss, cost and trade frequency against a chosen rule set, and reports the same peak shown here. The companion how much to risk per trade study maps the sizing curve this one holds in the background.

Does a minimum-trading-days rule make an evaluation harder?

It can, but usually only a little. In this study a minimum of 5 days inside a 20-day window cost about 0.7 of a percentage point of peak probability — effectively nothing — while a 15-day minimum cost about 10.8 points. The rule stays close to free while it is a small fraction of the window and becomes a real cost only when it forces a fast finisher to keep trading past the target.

Why would trading more days lower the probability of passing?

Under a trailing drawdown the breach line follows the account’s high-water mark up and never falls. An account that has just reached its target is sitting close above its floor, so every forced extra day is another chance to touch it. The days after the account has effectively won carry drawdown risk without adding reward.

Should I size differently under a minimum-days rule?

The model’s best size drifts smaller as the minimum grows — from about 1.1% toward 0.8% of balance here — because a longer forced stay rewards a lighter hand. The effect is modest and the peak is broad, so being roughly right matters more than an exact figure.

Is a minimum-days rule the biggest thing between me and a pass?

Rarely. Even with no meaningful minimum at all, 36.1% was the peak probability of passing for this illustrative trader — most attempts still failed for other reasons. A minimum-days rule is a secondary drag, not the main wall.

Are these percentages real pass rates?

No. They are model-derived probabilities of passing a synthetic archetype under stated assumptions, not observed outcomes for any real firm or group of traders. Your own edge, cost and trade frequency move every number.