Funded Trading Plus Master Scaling Plan & Milestone Formula
Funded Trading Plus features an industry-leading scaling model: every time you achieve a 10% profit milestone on a funded account, your account capital doubles (e.g., $100k -> $200k -> $400k up to $2.5 Million). On each scale-up, your relative drawdown resets, providing enhanced risk capacity.
Funded Trading Plus caters to systematic and algorithmic traders with clear, non-subjective scaling milestones. Understanding the interaction between relative drawdown and account scaling allows traders to compound capital systematically.
INTERACTIVE POSITION SIZING & RISK SIMULATOR
2026 BENCHMARK & COMPARISON DATA MATRIX
| Scaling Milestone | Account Balance | Max Drawdown (Relative) | Dollar Risk Buffer | Permitted Lot (0.5% Risk) |
|---|---|---|---|---|
| Starting Account | $100,000 | 6% Relative | $6,000 Buffer | 2.50 Lots |
| 1st Scale (10% Target) | $200,000 | 6% Relative | $12,000 Buffer | 5.00 Lots |
| 2nd Scale (10% Target) | $400,000 | 6% Relative | $24,000 Buffer | 10.00 Lots |
| 3rd Scale (10% Target) | $800,000 | 6% Relative | $48,000 Buffer | 20.00 Lots |
Relative vs Trailing Drawdown at FTP
Relative drawdown trails your highest closed balance until your initial capital is protected. Once profit milestones are achieved, the drawdown locks at the initial balance level, converting into static drawdown security.
Size Trades for Funded Trading Plus Scaling
Engineered for zero-math error execution. Tested across MT4/MT5 and Binance futures.
FREQUENTLY ASKED QUESTIONS & EXPERT CLARIFICATIONS
Is there a time limit to achieve the 10% scaling milestone at FTP?
No, Funded Trading Plus accounts have no time limits, allowing traders to wait patiently for high-probability market setups.
Author: TradeCoreHub Quantitative Risk & Algorithmic Desk. Peer-reviewed against CME tick specifications, FTMO/FundedNext drawdown contracts, and Binance USD-M liquidation mechanics.
Audit Standard: Zero-Math-Error validation. Formulas are calibrated to ensure absolute capital survivability across statistical losing streaks.
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