Short answer: Scaling a funded account means one of two different things, and you need to know which one you are doing. This guide covers position-size scaling, meaning increasing risk inside an account you already hold, and it argues that the decision should be driven by your drawdown headroom rather than your return. Our FX JetBot account on iFunds produced roughly 2% over three months with a maximum floating loss of 0.99%, and because iFunds calculates drawdown statically from the initial balance, every retained dollar of profit widens the distance to the failure level. The correct next move is a small staged increase with the numbers checked first, not the doubling or tripling that a low drawdown figure tempts you toward.
Let me start with the distinction that most articles on this topic skip.
Two Ways a Funded Account Can Scale
| Scaling type | What changes | Who controls it |
| Position-size scaling | You increase lot size or risk per trade inside the same account | You |
| Firm allocation scaling | The provider raises the nominal account size after qualifying performance | The platform |
This article focuses primarily on the first. A provider’s formal scaling plan is a separate mechanism that may depend on profit reached, payout history, minimum trading days, consistency, and rule compliance, and the terms differ by firm.
Both matter. They just answer different questions. Position-size scaling asks how hard you can push the capital you have; allocation scaling asks how you get more capital to push.
Collect These Rules Before You Change Anything
Before touching lot size, write down the answers for your specific account. Not the general industry version, yours.
| Rule | What you need to know |
| Maximum drawdown | The exact figure, and whether it is static or trailing |
| Measurement basis | Whether the limit is applied to balance, equity, intraday equity, or end-of-day equity |
| Reference point | Initial balance, highest equity, or a value reset after each payout |
| Daily loss limit | Whether one exists, and how it is calculated |
| Consistency rule | Whether a single strong day can disqualify a payout |
| Maximum lot rule | Whether your proposed size exceeds permitted exposure |
| Automation policy | Whether expert advisors are allowed, and under what conditions |
| News and weekend rules | Whether larger positions could breach a strategy restriction |
| Payout treatment | Whether withdrawals reduce your drawdown buffer |
I would put that list somewhere you can see it. Traders lose funded accounts to rules they never read far more often than to bad strategies.
Static Versus Trailing Drawdown
This distinction decides whether patience is rewarded or punished.
A static limit is fixed from a reference point that does not move. A trailing limit follows your equity upward, so profits raise the failure level along with them.
iFunds states that its drawdown calculation is static, based on the initial balance (iFunds). On a 10K account with a 10% limit, the failure level sits at 9K and stays there.
Watch what that produces as the account grows:
| Account balance | Failure level | Effective buffer |
| $10,000 | $9,000 | 10% |
| $11,000 | $9,000 | About 18% |
| $12,000 | $9,000 | 25% |
The threshold does not move. Your distance from it does. Under a trailing structure this table would not exist, because the failure level would climb with every new equity high.
One point I want to be careful about: iFunds describes the limit as a maximum drawdown from initial balance, and I have not confirmed from the public pages whether breach is assessed on balance or on floating equity. That distinction matters enormously to anyone running an EA that carries open positions overnight. Check the account agreement rather than trusting the summary in this or any other article.
Daily Loss Limits, and Why iFunds Is Unusual
Most funded accounts carry two constraints: a maximum overall drawdown and a maximum daily loss. An account can hold a comfortable total buffer and still fail inside a single session.
iFunds is an exception here. Their published material states there is no set limit on daily losses, no minimum trading days, and no time limit, with a single maximum drawdown rule instead (iFunds). They also state that third-party robots and expert advisors can be integrated without restriction, which is the reason this account exists at all.
If your provider does impose a daily cap, your scaling calculation has to satisfy both limits, and the smaller one governs. A strategy whose worst single day is 4% cannot be scaled into a 3% daily rule regardless of how much total headroom the account has.
The Scaling Calculation
Here is where I want to replace instinct with arithmetic, because “the drawdown is small so let us double it” is not a method.
Gather these inputs:
| Input | Meaning |
| Current equity | Where the account sits at the decision point |
| Firm breach level | The exact figure that closes the account |
| Gross buffer | Current equity minus breach level |
| Safety reserve | Held back for slippage, gaps, spread expansion, and surprises |
| Risk budget | Gross buffer minus safety reserve |
| Stressed drawdown at current size | A conservative estimate, not your best observed period |
| Recovery-trade exposure | Worst case from the EA’s larger recovery position |
| Maximum safe multiple | Risk budget divided by stressed drawdown |
The decision rule I would apply:
Increase risk only when the estimated stressed drawdown at the new lot size stays below the smallest applicable limit, whether that is total drawdown headroom, daily loss headroom, or your EA’s internal account-level stop, after subtracting the safety reserve.
Worked through with our own account:
| Component | Amount |
| Current equity | About $10,202 |
| Firm breach level | $9,000 |
| Gross buffer | About $1,202 |
| Safety reserve | $400 |
| Risk budget | About $802 |
| Stressed drawdown at current size | To be documented |
| Maximum safe multiple | Risk budget divided by stressed drawdown |
I am deliberately leaving the stressed drawdown blank rather than filling it with our observed 0.99%. Three months of calm is not a stress estimate, and using it as the denominator would produce a multiple large enough to be dangerous. Working out that figure properly, using our live results, the developer’s longer record, and the recovery-trade exposure together, is the actual next task.
The Case Study: FX JetBot on iFunds
| Metric | Funded account (iFunds) | Live account |
| Period measured | About three months to review date | Since April to review date |
| Total profit | About $202, roughly 2% | Not stated separately |
| Monthly pace | About 0.66% | About 1.3% |
| Maximum floating loss | 0.99% | 2.66% |
| Pairs traded | USD/CAD, EUR/GBP | AUD/USD, EUR/GBP |
| Risk level | Lower | Slightly higher |
We track this through the Account Tracker, an app Marin built in house after we grew frustrated with FX Blue and Myfxbook. Building your own reporting sounds excessive until you have spent an hour trying to answer a simple question about your own trades.

Concentration Hiding Inside Apparent Diversification
Exposure across the two funded pairs looked almost identical. Even split, roughly.
The closed trades told a different story. Virtually every trade was USD/CAD. Exactly one EUR/GBP trade contributed to the result.


So the profit is essentially a single-pair result wearing a two-pair costume. That matters for scaling, because a strategy whose realized returns come from one instrument carries single-instrument risk no matter how many charts are open.

The 0.26 Lot, and What It Means When You Scale
Entry sizing was consistent. USD/CAD opened at 0.05 and every subsequent trade came in at 0.05, with no grid and no martingale. EUR/GBP ran at 0.06.
Then I found one USD/CAD trade at 0.26, roughly five times the standard size, appearing immediately after two consecutive losses. It exited fairly quickly.
This is a Forex Store product, so we do not have access to every internal setting, but checking the developer’s material afterward confirmed the behavior. They state the robot trades with a fixed lot in about 96.5% of cases, and that in roughly 3.5% of cases, following a series of losses, it increases the lot once for a single trade (source).
An independent reviewer treats this as the main risk in the system, noting that a stop loss on two positions triggers a trade at five times the lot size, which erases the prior loss if it works and produces a significant loss if it does not (source). That is a fair reading.
A Correction to How I Framed This Previously
I earlier described doubling risk as doubling “a worst case that already includes a 5x multiplier,” implying something more than linear. That was imprecise, and I want to fix it rather than leave it standing.
Doubling the base lot doubles the recovery lot too. A 0.05 entry becomes 0.10, and a five-times recovery trade moves from roughly 0.25 to 0.50. Monetary risk scales linearly. The genuine issue is not nonlinearity; it is that the worst-case position is already five times a standard trade before you scale anything.
| Base lot | Recovery lot (5x) | Relative worst-case exposure |
| 0.05 | 0.25 | Baseline |
| 0.10 | 0.50 | Double |
| 0.15 | 0.75 | Triple |
Any stressed drawdown estimate has to be built from the recovery lot, not the entry lot. That is the number that decides whether a scaling step is survivable.
Settings, and the Limits of the EA’s Own Safety Net
| Setting | Our choice | Note |
| Auto Risk (money management) | Off | We size manually |
| Entry lot, EUR/GBP | 0.06 | Fixed |
| Entry lot, USD/CAD | 0.05 | Fixed |
| Drawdown Control | True | Limits drawdown per the manual |
| Risk Limit | Not applicable | Only active when Auto Risk is on |
The manual states that with Drawdown Control set to true the EA operates normally and limits drawdown, while setting it to false removes stop losses from the last trade in the strategy and stops limiting drawdown. Practically, a threshold of 10 closes every trade at 10% drawdown, and you can set it lower for more buffer.

Before relying on it, though, there are questions the setting’s description does not answer:
- Does the threshold measure balance or equity?
- Does it monitor account-wide drawdown, or only this EA’s orders and magic numbers?
- Does it close positions immediately or on the next tick?
- Can slippage push the realized loss past the threshold?
- Does the setting persist across a platform restart?
- Can other robots keep trading after it triggers?
So the honest formulation: an EA-level drawdown setting should not be treated as a complete account safeguard unless it monitors every position included in the platform’s loss calculation. Set it below the firm’s threshold by all means. Do not assume it replaces the firm’s threshold.
The iFunds Structure, and the Profit Split Decision
iFunds is an instant funding platform: you buy the account rather than passing an evaluation. At the time we set ours up, a 5K account cost $400 and a 10K account cost $700.

You also choose your own maximum drawdown at signup, on a scale running from 6% to 10%, and that choice sets your profit split.
| Chosen drawdown | Profit split |
| 6% | 80% |
| 7% | 70% |
| 10% | 50% |
We keep ours at 10%, and the scorecard-worthy question is whether that is rational or merely cautious. So here is the arithmetic on a hypothetical $500 gross profit on a 10K account:
| Choice | Gross profit | Your share | Permitted drawdown | Net before fees |
| 6% limit, 80% split | $500 | $400 | $600 | $400 |
| 10% limit, 50% split | $500 | $250 | $1,000 | $250 |
You give up $150 of that payout in exchange for $400 of additional stated drawdown capacity. Whether that trade is worthwhile depends on how confident you are in your stressed drawdown estimate, which for a three-month sample is not very. I would rather hold the wider limit and take half.
Factor in the purchase fee, any reset cost, minimum payout thresholds, withdrawal frequency, and the fact that profits left in the account remain exposed to platform risk. None of those appear in the split percentage.
Withdrawals Versus Buffer Growth
Under a static limit these pull in opposite directions.
Withdraw regularly and you realize gains and reduce platform exposure, while keeping the balance near its starting level and therefore near the original drawdown percentage. Leave profits in and the buffer widens, which is what creates room to scale.
iFunds permits withdrawal of any amount from $50 upward without restriction, per their published terms. A middle path, taking a fixed portion while retaining enough to grow the buffer, is what I would suggest to most people, though I hold that view loosely.
Formal Scaling Plans
The other meaning of scaling. iFunds states that traders can use profit to move up to the next account tier, with no profit target required and no wipeout of excess profit.
Providers generally attach conditions to allocation increases, which may include a percentage gain, a number of profitable months, completed payouts, absence of rule violations, consistency requirements, minimum trading days, or continued use of the same risk profile. Terms vary widely, so read your provider’s current scaling-plan rules rather than any published summary.
Our Staged Scaling Process
Replacing the instinct to double or triple:
- Start small enough that the strategy’s natural drawdown uses a small fraction of the risk budget
- Target a modest monthly percentage. We aim for around 2%, and the funded account runs below that
- Measure drawdown across varied conditions, not merely across time. Three quiet months is one condition
- Let the buffer grow by retaining profit, since a static limit converts growth directly into risk capacity
- Document a stressed drawdown estimate built from the recovery lot, the developer’s longer record, and your own results
- Increase by a limited increment, not a multiple
- Observe a predefined number of trades or market regimes at the new size
- Compare actual drawdown against the stressed estimate. Revert to the previous size if it exceeds your trigger
- Only then scale again, with the new risk profile documented
Step 4 is where most traders skip ahead, and I understand why. Leaving money in an account you could withdraw from requires a patience that does not come naturally.
What Could Go Wrong
The three-month sample is flattering. Forex Store’s own listing for this EA shows a considerably deeper drawdown on the developer’s long-running account (listing). Ours is low because of two pairs, small fixed lots, and a short window.
The recovery trade scales with everything else. Covered above, and the reason any scaling estimate must be built from the 5x position.
Single-pair concentration. If USD/CAD behavior changes, the account changes with it.
Rule ambiguity. Until the balance-versus-equity question is settled in writing, our buffer calculation carries an assumption inside it.
Platform terms shifting. Instant funding pricing, splits, and drawdown structures change without notice.
My Verdict
The account has built an initial buffer, which is a real achievement and not the same thing as permission to size up.
Three months is not enough to establish this strategy’s likely maximum drawdown. Before increasing size I want to stress the five-times recovery trade at each candidate lot, confirm iFunds’ exact breach calculation in the agreement, and run the proposed size against a conservative estimate rather than our best observed period.
What the present results support is continued observation and possibly a small staged increase. Not an immediate doubling or tripling, which is what I was leaning toward before working through the arithmetic properly.
FX JetBot sells for $345 on Forex Store and supports five pairs. It is not the highest-returning system we have tested, and that is rather the point: on an account with a hard failure line drawn beneath it, consistency and risk control matter more than the headline number.
You can see the funded trading platforms we use, including the one in this article, on our funded trading page.
Frequently Asked Questions
How is a consistency rule different from a drawdown rule?
A drawdown rule governs how much you may lose; a consistency rule governs how your profit is distributed. Firms applying one cap the share of total profit that any single day may represent, so an unusually strong session can flag a payout for review even though no loss limit was breached. Traders scaling position size should check this before increasing, since larger positions naturally produce larger single-day results and can trip a rule that smaller sizing never approached.
Does a payout reset my drawdown level?
That depends entirely on the provider. Under a static structure calculated from initial balance, withdrawing profit reduces your equity while the failure level stays put, which narrows the buffer you spent months building. Some firms recalculate the reference point after a payout, others do not. Confirm the treatment in writing before planning a withdrawal schedule around it, because the answer determines whether regular payouts and position-size scaling can coexist in your account.
Can I run the same EA on funded and live accounts simultaneously?
Yes, and we do, with different pairs and risk levels so the two produce independent readings of the same system. Check the vendor’s license terms first, since some restrict the number of real accounts. Confirm the funded platform permits automation as well: iFunds publishes that third-party robots and expert advisors may be integrated without restriction, though policies differ substantially between providers and some prohibit automated trading entirely.
What is the difference between maximum drawdown and maximum floating loss?
Maximum drawdown usually measures the largest decline from a peak, and it may be calculated on balance or on equity depending on the source. Maximum floating loss measures unrealized loss on open positions from peak equity. For strategies holding positions across sessions the two figures can differ considerably. Before using either as a scaling input, confirm which one your tracking software reports and which one your funded platform uses to assess a breach.
Should I scale position size or wait for a larger account allocation?
They serve different purposes and carry different risks. Increasing position size raises return and drawdown proportionally within capital you already control. Moving to a larger allocation raises capital while typically resetting you to a fresh drawdown percentage, which removes the buffer you accumulated. Traders with an unproven stressed drawdown estimate generally benefit more from patience at current size; those with a well-documented risk profile may find allocation increases the more efficient route.
How long should I trade before increasing position sizing?
Duration matters less than variety. Three quiet months tells you about quiet markets, while a shorter period covering a genuine volatility event may be more informative. Strategies entering infrequently need longer simply to accumulate trades. Whatever the window, measure drawdown afresh after every increase rather than scaling repeatedly on a single earlier measurement, since a new lot size produces a new risk profile that the old data cannot describe.
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Disclosure: Algo Trading Space may earn a commission from some links on this page. It does not change our figures, our results, or our conclusions.
Risk warning: Trading leveraged products carries a high risk of losing money rapidly. Funded and instant funding accounts carry the additional risk of losing the purchase price if a drawdown limit is breached. The figures here come from two accounts traded over roughly three months, a period too short to establish reliability, and past performance does not indicate future results. Increasing position sizing increases both potential return and potential loss. Platform rules, pricing, and profit splits change; verify current terms directly with the provider. Nothing here constitutes investment advice.

Ilan



