EA VERDICT · independent audit

Apex Predator

XAUUSD · H1 (2003.05.05 - 2026.09.08) · run capital 100,000 · vendor deposit 200 · leverage 1:5000 · tested to 2026-09-08 · engine 0.4.2
on MQL5 Market by Abdelrahman Ahmed Mahmoud Ahmed Test settings
1 of 6 red
Verdict summary
✗Data qualityRED
Why RED?
  • ! 2675 failed entry attempts in the logThe tester rejected these entry requests. Repeated attempts may belong to the same intended entry; this count does not establish how many trades were missed. Recorded reasons: Market closed (2675).
  • ✗ EA refuses to trade the first 16.7 yearsThe EA refuses to trade the first 16.7 years of available data. The long history claim is untested before 2020-01-02.
✓StructureOK
Why OK?
  • No findings in this dimension. Measured clean.
✓CostsOK
Why OK?
  • No findings in this dimension. Measured clean.
✓ConcentrationOK
Why OK?
  • No findings in this dimension. Measured clean.
✓Regime dependenceOK
Why OK?
  • No findings in this dimension. Measured clean.
✓Prop-firm fitOK
Why OK?
  • No findings in this dimension. Measured clean.
8,908.46USD
Net profit
9,619
Trades
10.47
EOD Sharpeannualized
37.4%
Max drawdownof vendor deposit, end of day
+4454.2%
Return, arithmeticon vendor deposit
13.53
Profit factorreport head

Percent return and max drawdown are arithmetic on vendor deposit, fixed lots, no compounding. USD figures are divided by 200 USD, the vendor recommended deposit. Run capital of 100,000 USD is the measurement frame, not the story basis.

EA refuses to trade the first 16.7 years. 2675 failed entry attempts in the log. At least one dimension is rated red. Treat the marketed performance with corresponding distrust.
What this audit measures. Apex Predator MT5, version 1.00, as delivered with EA defaults and fixed lot 0.01. The tester used 100,000 USD run capital and 1:5000 leverage as the measurement frame. Percent return and drawdown are evaluated on the 200 USD vendor deposit. The window is H1 (2003.05.05 - 2026.09.08), using 100% real ticks.

Not measured here. live signal performance, individual risk sizing, alternative settings. Declared alternatives can be measured as separate matrix runs.

Sizing invariant Profit concentration, Active trading days, Trade count, Spread sensitivity per trade, Drawdown duration in trading days, Holding times, Win rate.

Sizing dependent CAGR, Drawdown in percent, Absolute PnL.

How this audit was made. One documented protocol for every EA: real tick history, the vendor's own default settings, a fixed cost model. Every deal is rebuilt from the tester report and the balance chain is verified against it. The engine version in the header stamps the exact rule set this page was computed with.

Apex Predator is sold by Abdelrahman Ahmed Mahmoud Ahmed for a listed $199.00 on MQL5 Market.

+0%+2%+5%+8%+10% 1,725 trading days

The observed backtest (red) against 1000 resampled orderings of its own trades. Median dashed, bands P25 to P75 and P5 to P95. Hover or touch for exact values per trading day.

01 Findings

2 findings, 1 of them red.

✗REDEA refuses to trade the first 16.7 yearssee the evidence
The EA refuses to trade the first 16.7 years of available data. The long history claim is untested before 2020-01-02.
!CAUTION2675 failed entry attempts in the logsee the evidence
The tester rejected these entry requests. Repeated attempts may belong to the same intended entry; this count does not establish how many trades were missed. Recorded reasons: Market closed (2675).
02 What we measured

9,619 trades, rebuilt deal by deal.

✓Report
✓Tester log
✓Pairing
✓Balance
✓History
iDelay

sampled at deal timestamps. Intrabar floating equity between deals is unobservable from a report, so the tester-head equity DD (tick-based) is the upper reference before added commissions; validation allows their total cost divided by initial capital, scaled by the native drawdown bound above 100%

The measurement record
Trades reconstructed9,619exact
Pairing confidenceexact
Balance reconstructionexact
History quality100% echter Ticksexact
Real ticks fromXAUUSD: 2003.05.05 00:00:00
Generated tick minutesn/a
Execution delay10 ms
Tester log providedyes
Tester log files20260908.log
Randomizer prints0
Report SHA-256853e3e16c75c7aaa...

Reconstructed floating equity

Floating drawdown (sampled)0.1%reconstructed
Balance drawdown (deal-wise)0.1%reconstructed
Report-head equity DD (tick-based)0.09% (90.56)exact
Equity samples (deal timestamps)19,238
Worst sampled point2020-03-13 18:49:23 at 99,980.43 (from 100,060)reconstructed
Equity between dealsunobservable in a tester reportunavailable

Settings used in this run: apex-predator-mt5.set (Version 1.00; 1,386 bytes). Measurement configuration of this audit, not a recommendation.

View the tested set file and reproduction recipe.

Use the dated measurement badge or audit-card embed.

03 Structure and exits

One strategy, one exit signature.

How trades actually ended

SL: 9,576 (99.6%)TP: 43 (0.4%)

Nearly all exits are stop-loss exits with a material share closing in profit, a trailing-stop management signature.

04 Underlying vs. strategy

The symbol itself moved +185.7%.

LONG+4,439
SHORT+4,469
HOLD+2,853
XAUUSD itself moved +185.7% over the same span (2020-01-02 … 2026-08-13)

approximated from entry prices, because a tester report carries no independent price series. HOLD is buying and holding the median traded lot size over the same span, before costs, using the contract value calibrated from this run's own paired deals. It is additive like the strategy PnL, so the three bars share one USD scale. Percent figures in the tooltips are arithmetic on the vendor deposit, no compounding.

Underlying table
SymbolTradesEntry-price moveTraded spanLong/Short tradesLong PnLShort PnLBuy and hold
XAUUSD9,619+185.7%2020-01-02 … 2026-08-134970/46494,439 (+2219.7%)4,469 (+2234.5%)2,853 (+1426.6%)

approximated from entry prices, because a tester report carries no independent price series. The buy-and-hold column is the entry-price move expressed in USD at the median traded lot size, before costs, using the contract value calibrated from this run's own paired deals. It is additive like the PnL columns. Percent figures in brackets are arithmetic on the vendor deposit, no compounding.

05 Year by year

7 calendar years on record.

1,3500+64%0%PnL per year, USDthe symbol's own move (entry-price approx.)2020202120222023202420252026
long PnLshort PnLsymbol move
Year-by-year table
YearTradesPnLWin %Long PnLShort PnL
20201,18683596.5%489345
202188178298.1%390393
20221,02484197.9%337504
202389272997.4%325404
20241,2401,12098.7%477642
20252,1632,12598.8%1,0711,055
20262,2332,47798.5%1,3501,127
06 Costs and honest metrics

Costs include the commission retrofit.

From gross to net

Gross before costs9,724.10Commission-769.52 (retrofit)Swap-46.12Net profit8,908.46

Commission retrofitted at 3.5 USD per lot per side on every deal, not tester-native. The balance chain was rebuilt deterministically.

Which Sharpe to trust

Report-head 'Sharpe'11.03EOD Sharpe (annualized)10.47
Cost and metric table
Net profit8,908.46reconstructed
Commission-769.52reconstructed
Commission modelcommission retrofitted at 3.50/lot/side, not tester-native
Swap-46.12reconstructed
Gross before costs9,724.10reconstructed
Cost share of gross8.4%reconstructed
Overnight trades448reconstructed
Tested historyFirst trade 16.7 years after the window opens. The tested history effectively starts 2020-01-02exact
EOD Sharpe (annualized)10.47reconstructed
Report-head 'Sharpe'11.03exact
CAGR1.2% on 100,000 USD run capitalreconstructed
Max drawdown (EOD)37.4% of 200 USD vendor depositreconstructed
07 Concentration

80% of the profit happened on 616 of 1,502 active trading days (41.0%). That is 10.1% of the 23.3 year window.

616 days of 1,502 carry 80% of the profit41.0% of active trading days; 10.1% of the 23.3 year window

Best days

2026-02-04+63
2026-04-08+58
2026-03-23+55

Worst days

2020-01-06-44
2022-09-15-41
2020-10-28-41
08 Drawdown episodes

The deepest drawdown recovered after 24 trading days.

200420062008201020122014201620182020202220242026#1: 0.1%, 24 days under water#2: 0.0%, 14 days under water#3: 0.0%, 12 days under waterthe 3 deepest of 29 drawdown episodes · depth = percent below the peak balance · width = time from peak to recovery
Episode table

Top 3 of 29 episodes on the end-of-day balance curve.

#PeakTroughDepthTo troughUnderwaterTrades (losers)Worst trade
12020-02-19 (100,060)2020-03-03 (99,985)75 (0.1%)9 d24 d (recovered 2020-03-24)53 (3)-40 on 2020-03-03
22020-01-03 (100,003)2020-01-06 (99,958)44 (0.0%)1 d14 d (recovered 2020-01-23)3 (1)-47 on 2020-01-06
32020-10-27 (100,713)2020-10-28 (100,672)41 (0.0%)1 d12 d (recovered 2020-11-12)1 (1)-41 on 2020-10-28

end-of-day balance curve, peak to recovery, the same series and formula as 'Max drawdown (EOD)', so the deepest episode reproduces that figure. trades listed are those CLOSED between the peak and trough day. Floating drawdown between day boundaries is invisible here, see the reconstructed-equity section where present.

09 Fresh start survival

0.0% of all start dates end in a dead account.

If you had started this EA fresh on any day of the tested history with a fresh 200 USD account (the vendor recommended deposit. The run itself used 100,000 USD as measurement frame), 0.0% of all 19,238 start dates end in a dead account. The strip shows the measured fate of every possible start date. The curve below it shows why.

STARTDD200 USD deposit floor202120222023202420252026strip: red = a fresh account started on that date dies, neutral = it survives · curve: drawdown below the running balance peak

No death zones at this deposit. No start date loses a full deposit from its entry level on the closed balance curve.

Drawdown ribbon

The same history as one color band: how deep the account sat under its running peak in any week, measured against the 200 USD basis. Red weeks are the phases where a fresh account entering just before would have been wiped out.

202120222023202420252026weekly max drawdown vs. deposit: neutral under 25%, sand under 50%, orange under 100%, red 100% and above (a fresh account is dead)

Computed death chain. Zero account deaths over the full history at this deposit (balance to zero on the closed curve). The final run is alive for 2416 days since 2020-01-02.

Deposit ladder

DepositShare of dying start datesComputed chain deaths
200 USD (vendor)0.0%0
400 USD0.0%0
800 USD0.0%0

Basis: closed balance curve, where floating drawdown would only be stricter. Fixed lot settings only (measured policy fixed). For compounding EAs this map is not transferable. Evaluation deposit 200 USD (vendor recommended deposit). Run capital 100,000 USD is the measurement frame. Small gap on each restart day of a chain is inherent to the tester workflow.

10 Release timeline

Only 0 days are guaranteed out of sample.

Net 0.00 USD at profit factor None out of sample, against 12.34 before release.

Product facts: released 2026-08-21, 0 recorded version entries, vendor recommended deposit 200 USD, list price 199 USD.

The backtest runs the CURRENT version over the whole history. Every candle before the release was visible while the EA was built. Only the window after the last update is guaranteed out of sample, and it must be judged together with its length.

Price on record: 199 USD since 2026-09-07 (tracking baseline, append-only archive).

Window table
WindowFromToDaysTradesNet USDPFWin rate
Before release2020-01-022026-08-132,4169,6198,908.4612.3498.1%
Release to last updaten/an/a000.00n/an/a
After last update (out of sample)n/an/a000.00n/an/a
11 Cost fragility

The whole edge dies at +0.93 USD extra cost per trade.

Add that much cost to every trade (worse spread, slippage, commission) and the result is gone. The average position size is 0.01 lots.

Cost shock

break-even +0.934,0990-39,187+0.50+1.00+2.00+5.00

Remove the best N trades

-1-5-10-208,8750
Sensitivity tables
Extra cost per tradeNet profitProfit factorWin %
+0.50 USD4,0994.8878.2
+1.00 USD-7110.78234.8
+2.00 USD-10,3300.0757.9
+5.00 USD-39,1870.0040.5
Best trades removedTheir PnLShare of gross winsNet without them
1340.3%8,875
51181.2%8,790
101651.7%8,743
202432.5%8,666

flat USD shock per trade, not lot-scaled, so judge it against the average lot size. Leave-best-out removes the N most profitable trades from the observed set.

12 Prop-firm fit

3 rule sets, simulated day by day.

IQ Capital Classic (funded)

Account deaths per sizing

01/1first death-free01/1.501/201/301/401/601/8deaths at

0 breach years under the consistency rule

20212223242526
✓0Position-loss breaches
Rules used for this simulation (as of 2026-08-13)
dd_modeeod_trailing
dd_pct6.0
max_position_loss_pct0.5
consistency_pct30.0
overnight_allowedTrue
weekend_allowedTrue

Source: https://support.iqcapital.io

Worst days: -44 on 2020-01-06, -41 on 2022-09-15, -41 on 2020-10-28 · 448 overnight trades · 140 spanning weekends

FTMO Challenge

Account deaths per sizing

01/1first death-free01/1.501/201/301/401/601/8deaths at
✓0Daily-loss breaches (EOD)✓0Daily-loss breaches (intraday)

The intraday row samples equity against the day anchor (server-day boundary). The EOD row is shown for comparison.

Rules used for this simulation (as of 2026-08-13)
dd_modestatic
dd_pct10.0
daily_loss_pct5.0
overnight_allowedTrue
weekend_allowedTrue

Source: https://ftmo.com/en/how-it-works/ + academy/maximum-daily-loss + faq weekend

Worst days: -44 on 2020-01-06, -41 on 2022-09-15, -41 on 2020-10-28 · 448 overnight trades · 140 spanning weekends

Generic 6% EOD trailing

Account deaths per sizing

01/1first death-free01/1.501/201/301/401/601/8deaths at
Rules used for this simulation (as of 2026-08-12)
dd_modeeod_trailing
dd_pct6.0
overnight_allowedTrue
weekend_allowedTrue

Source: generic, no firm source

Worst days: -44 on 2020-01-06, -41 on 2022-09-15, -41 on 2020-10-28 · 448 overnight trades · 140 spanning weekends

13 Monte-Carlo resampling

The same trades, a thousand other orderings.

1000 paths per method, seed 42, block length 5 trading days, additive resampling at the tested sizing. Drawdowns are expressed as % of start balance. Paths are not stopped at account death, so drawdowns beyond 100% mean repeated wipeouts at this sizing.

Resampled max-drawdown range vs. observed

Permutation (order only)P90P95P99Bootstrap (IID)P90P95P99Block bootstrapP90P95P99observed 0.1%

Bars and observed marker use percent of start balance.

Bootstrap intervals

Profit factor9.10212.70218.64Expectancy per trade0.90.930.96

The share of resampled paths ending at or below zero net profit is 0.0%.

Streaks and recovery (block-bootstrap paths)
MetricMedianP90P95P99
Max losing streak (days)1222
Time under water (days)20303441

Ruin probability per profile and sizing

Profile1/11/1.51/21/31/41/61/8
iqcapital_classicfloor 6.0%0000000
ftmo_challengefloor 10.0%0000000
generic_6pct_trailingfloor 6.0%0000000

Cell = probability that a resampled path breaches the profile floor at that sizing, in percent. Green ring = first sizing at or below the 10% target. This checks the floor only. The full rule set is stricter.

Challenge pass probability, ftmo_challenge

phase11.4%

phase1: pass 1.4%, fail 0.0%, undecided 98.6%.

98.6% of paths reached neither the target nor a failure boundary within 1,725 days.

phase2100.0%

phase2: pass 100.0%, fail 0.0%, undecided 0.0%.

The probability of passing both phases (independent-resample approximation) is 1.4%.

Attempt economics. Passing phase 1 takes 71.4 expected attempts, a 90% chance of at least one pass needs 164 attempts, and the probability of 5 consecutive fails is 93.2%. multiply attempts by your challenge fee for the expected cost to fund.

Challenge detail tables

ftmo_challenge. Daily and floor checks are based on intraday-sampled equity vs. day anchor.

StageTargetP(pass)P(fail: floor)P(fail: daily)UndecidedMedian days to pass
phase110%1.4%0.0%0.0%98.6%1694
phase25%100.0%0.0%0.0%0.0%966

Does reducing risk raise the pass chance? Phase 1 at each sizing.

Sizing1/11/1.51/21/31/41/61/8
P(pass)1.4%0.0%0.0%0.0%0.0%0.0%0.0%
Median days1694n/an/an/an/an/an/a
What these numbers can and cannot say
  • Monte Carlo resamples the SIMULATED trades of this backtest. It inherits every weakness of the simulation (in-sample bias, regime luck, execution gap) and cannot add information. All it does is reveal how fragile the observed path is.
  • Same trades, different order. This answers only how path-dependent the drawdown is. Treats trades as exchangeable, which grid and martingale sequences are not (their order is caused by the market path), so read this as a diagnostic, not a forecast.
  • Draws trades independently with replacement (IID assumption). Real EAs violate IID through clustering and position chains. Intervals are tighter than reality for such systems.
  • Resamples 5-trading-day blocks of the end-of-day PnL series. The blocks are circular and wrap at the series end, so every day carries equal weight. Without wrapping, a crash on the final day would be undersampled. This preserves short-range clustering and losing streaks up to the block length. Longer regime shifts remain unmodeled.
  • Floor breaches only, on block-bootstrap paths over a horizon equal to the tested history, profits above start swept (same convention as the prop-fit sweep). The firms' full rule sets (daily loss, consistency, position loss) are stricter, so treat every probability as a lower bound, and the safe-sizing answer as an upper bound on the truly safe size.
  • The fan bands are pointwise percentiles across resampled paths. The envelope is not a single achievable path. Paths use the tested sizing and are not stopped at account death.
  • Challenge-pass probabilities run each resampled path until profit target, max-loss floor or a daily-loss day is hit (checked in that day's order, daily first, then floor). Where the audit has reconstructed equity, daily-loss and floor checks use the intraday equity drop below the day anchor (sampled at deal timestamps, server-day boundary), which is still a lower bound on breaches, but far closer to the firms' equity-based rules than EOD deltas. Phases are treated as independent resamples for the combined figure. The sizing curve keeps the targets fixed while scaling the trading, which is why less risk can also mean more undecided paths.
14 Withdrawal replay

The longest dry stretch lasted 1 months.

Lot policy detected: fixed. The monthly rule (monthly sweep to start balance) covers the active span 2020-01-02 … 2026-08-13.

fixed lots
8,907 USD
78/80 months paid · dry streak 1 mo · 1.3%/a
balance scaled
8,915 USD
78/80 months paid · dry streak 1 mo · 1.3%/a

Monthly PnL heatmap

JFMAMJJASOND2020+36-28+85+100+65+69+97+106+108+39+82+762021+73+65+68-5+84+79+76+90+66+70+81+362022+49+74+90+105+91+38+81+65+33+74+79+632023+71+59+79+73+71+80+11+38+34+92+86+352024+28+59+89+161+94+84+96+104+66+109+139+892025+75+105+111+313+204+156+159+92+165+310+173+2632026+326+423+455+304+226+318+310+115

Across 1000 resampled paths (fixed lots), total withdrawn spans 8,153 to 8,888 to 9,689 USD (P5/median/P95). The share of paths paying nothing at all is 0.0%.

Capital what-if (fixed lots)

0%50%100%iqcapital_classicftmo_challengegeneric_6pct_trailing200 (vendor)1,0002,5005,00010,00025,000100,000 (tested)
Withdrawal and what-if tables
Sizing modelMonths paidTotal withdrawnWithdrawn %/aMedian paid monthBest monthDry streak (months)
fixed_lots78/808,9071.3824551
balance_scaled78/808,9151.3824561
CapitalMaxDD %P(breach) iqcapital_classicP(breach) ftmo_challengeP(breach) generic_6pct_trailing
200 (vendor basis)37.38100.0% (hit)100.0% (hit)100.0% (hit)
1,0007.4760.7% (hit)2.8%60.7% (hit)
2,5002.990.0%0.0%0.0%
5,0001.50.0%0.0%0.0%
10,0000.750.0%0.0%0.0%
25,0000.30.0%0.0%0.0%
100,000 (tested)0.070.0%0.0%0.0%

(hit) = the observed backtest itself breached this floor at that capital.

Assumptions and their direction
  • Withdrawals are simulated monthly on the last trading day. Everything above the start balance is taken out. A month without surplus pays nothing. The dry-streak figure shows how long that can last. Paths are the OBSERVED backtest days. Replay deltas start after the first sampled weekday balance, excluding the move from the initial deposit to that sample. The withdrawal distribution adds resampled paths (same circular block bootstrap as the MC section, own seed).
  • balance_scaled multiplies each day's PnL by balance/start. This is an approximation. Min-lot granularity and balance-coupled EA defaults do not scale linearly. The direction is optimistic for small accounts.
  • Capital what-if keeps the observed USD path (fixed lots) and re-expresses risk against each capital. Margin requirements are NOT modeled. A small account may be unable to hold the positions at all. The direction is optimistic. Under balance_scaled sizing, percent metrics are unchanged by construction. Only the min-lot limit differs, which is why no table is shown.
15 Glossary

Every term, in plain language.

Glossary
Pairing confidenceHow entry and exit deals were matched into trades. 'Exact' means taken from the tester log, 'validated' means FIFO/LIFO reproduced the report's holding-time figures, and 'heuristic' means an unconfirmed FIFO assumption.
EOD Sharpe (annualized)Sharpe ratio computed from end-of-day balance returns, annualized with the square root of 252. Comparable across systems, unlike the report-head 'Sharpe', which is per-trade.
Cost share of grossCommission plus swap as a share of gross profit before costs. High values mean the edge is eaten by fees and financing.
Max drawdown (EOD)Largest peak-to-trough loss of the end-of-day balance curve.
Floating drawdown (sampled)Largest drawdown of reconstructed equity (balance plus open-position value), sampled at deal timestamps. Between deals equity is unobservable from a report. The tester-head equity DD is tick-based.
MartingalePosition sizing that grows after losses. Looks smooth for months, then loses the account in one streak.
Consistency ruleProp-firm rule capping the best day's share of total profit. It punishes concentrated profit profiles.
Account deathsNumber of times the simulated account breached the profile's drawdown floor over this history (account is then reset and the simulation continues).
Withdrawal %/aYearly withdrawal as percent of account size in the sweep simulation (profits above start are swept daily).
Z-ScoreSerial correlation of the win/loss sequence. Strongly negative values often just reflect several sub-strategies interleaving, not necessarily a defect.
UndecidedA resampled challenge path reached neither its target nor a failure boundary within the sampled horizon. Each path spans the tested history's daily observations, not the duration of a real challenge. Undecided does not mean failed.
Monte-Carlo resamplingRe-arranging or re-drawing the audited trades many times to see the range of drawdowns and streaks the same trading could have produced. It cannot add information. It reveals path fragility, not future returns.
Block bootstrapBootstrap that draws whole multi-day blocks of the daily PnL series instead of single trades, preserving short-range clustering (losing weeks stay losing weeks).
Ruin probability (floor only)Share of resampled paths that breach the profile's drawdown floor at least once, with profits above start swept. The firm's full rule set is stricter, so this is a lower bound.
Time under waterLongest stretch of trading days a path spends below its previous balance peak.
Withdrawal replayRe-plays the backtest with a monthly payout. On the last trading day of each month, everything above the start balance is withdrawn. Shows what the strategy pays a trader who lives off it, instead of compounding like a backtest.
Dry streakLongest run of consecutive months in which the monthly withdrawal was zero, the months a trader living off the account would have earned nothing.
Lot policyWhether the EA trades fixed lot sizes or scales them with the balance, detected from the variation of lot sizes across the deal list.
Capital what-ifThe observed USD path re-expressed against a different account size (fixed lots). Drawdown percentages and floor-breach risk change with capital even though the trades are identical. Margin limits are not modeled.
Underlying vs. strategyThe symbol's own price move over the traded span, approximated from entry prices. If most profit is long-side while the symbol itself rose strongly, part of the result is the market's tailwind, not the mechanics. The tester cannot separate the two.
Drawdown episodesOne episode runs from a balance peak through its deepest trough until the peak is regained (peak to recovery), on the end-of-day balance curve. The deepest episode is the max drawdown (EOD). The table shows which trades and sub-strategies dug each hole.
Take-home after taxTotal withdrawn multiplied by one minus a user-supplied flat rate. Pure arithmetic on the withdrawal table, no tax law modeled. It stays off unless a rate is provided.
Cost fragilityHow quickly the result dies as per-trade costs rise. The break-even shock is the extra cost per trade (spread, slippage, commission) at which net profit reaches zero. High-frequency systems often die at cents.
Fresh start survivalWith fixed lots the dollar swings that follow any date are identical for every account, so each start date has an exact, measured fate. A fresh account started there dies if the balance path later falls at least one deposit below its starting level. Death-chain runs concatenate into one continuous profit path. Computed from the closed balance curve, where a floating check would only be stricter.
Release timelineThe backtest runs the current EA version over history that mostly predates it. Candles before the release were visible during development, and candles up to the last update were visible to at least one refit. Only the window after the last update is guaranteed out of sample, and it must be judged together with its length.
Provenance labelsWhere a number comes from. 'Exact' is taken as printed from the tester report or journal. 'Reconstructed' is recomputed by the engine from the deal list and journal, deterministic but a model of the run. 'Unavailable' cannot be derived from a report at all and is stated instead of silently approximated.
16 What this audit cannot tell you

The honest boundary.

A good backtest cannot prove an edge. This audit dissects the simulation you gave it. It can expose structural risks (martingale, grids, hidden concentration, cost fragility, rule conflicts), but it cannot tell you that the strategy will make money. Three limits are fundamental.

  • In-sample bias. Commercial EAs are typically released and updated after most of the tested window. A strong report may replay what the vendor optimized against, not what the market will do.
  • Regime dependence. A profitable window can reward almost any mechanic aligned with the prevailing trend. Year slices and long/short splits above hint at this, but cannot settle it.
  • Simulation gap. Even with real ticks and execution delay, the tester does not model live spreads, slippage beyond the next tick, or broker-specific behavior.

This audit is software analysis, not investment advice, and contains no recommendation to buy or trade anything.

17 Download

This audit is free, in full.

This audit is free. The list price of this EA is at or under 200 USD, so the complete audit is open. Every number, table and simulation on this page is the full deliverable.

18 Questions before you buy

Straight answers, measured where possible.

Can Apex Predator MT5 pass a prop firm challenge?

We measure it instead of guessing. The audit replays three prop rule sets (IQ Capital, FTMO, a generic 6% trailing profile) day by day over all 9,619 reconstructed trades, then runs the challenge as a Monte Carlo simulation at seven position sizings, with intraday equity resolution. The pass probability curve for Apex Predator MT5 is inside the audit.

What monthly withdrawal could Apex Predator MT5 sustain?

The audit contains a withdrawal replay. The strategy is re run as if someone lived off it, with monthly payouts, months paid versus dry months and the longest dry streak, plus a safe sizing table answering how small you must trade to keep ruin risk under 10%. The numbers for Apex Predator MT5 are inside the audit.

Is Apex Predator MT5 a grid or martingale EA?

We classify structure from the deal list, not from the equity curve. Split tickets, adds into adverse moves and size escalation are counted, not guessed. The audit states the classification for Apex Predator MT5 with the exact counts behind it.

Does Apex Predator MT5 have verified live results?

Vendor live signals and social screenshots are outside our control, so we do not grade them. What we audit is a controlled strategy tester run under one documented protocol, real ticks, vendor defaults, tester log included. That evidence is reproducible and cannot be cherry picked after the fact. The audit shows exactly what that run supports for Apex Predator MT5.

What settings were tested for Apex Predator MT5?

The vendor's own recommended defaults, unchanged. Deposit, leverage and every input follow the product page or the vendor's published set, and the audit records the full input list from the tester run. Where a preset series exists, each preset is audited separately and the page names the one you are reading.

Is Apex Predator MT5 worth buying?

We do not answer that with an opinion. The audit answers it with measurements. The verdict lamps on this page are public, and behind them sit the exact numbers, the cost autopsy, the concentration test, the prop rule replay and the Monte Carlo stress for Apex Predator MT5. Read those and the answer becomes yours, not ours.

Why is this audit free?

Audits of EAs listed at 200 USD or less are free. The risk of a cheap EA is not worth a paywall, and open audits show the depth of the method. Audits of more expensive EAs are paid.

Prop-rule replay

Prop: not verifiable

Rule profileMeasured pathSource
5% daily / 10% staticnot verifiable from this audit's account pathrules checked 2026-09-21
4% daily / 8% staticnot verifiable from this audit's account pathrules checked 2026-09-21
3% daily / 6% trailingnot verifiable from this audit's account pathrules checked 2026-09-21

Daily close basis; intraday breaches are not counted.

7 checks before you buy an EA

Five short emails show how to check costs, data, versions, drawdown, live evidence, strategy shape and account rules. Confirm by email; unsubscribe with one click.

Download the one-page checklist.