QT Funded prohibited strategies explained: HFT, tick scalping, arbitrage, latency trading, group hedging, reverse trading, all-or-nothing risk, server flooding and the current "BRIDGE" 60% offer.
Akash Mane is the Founder and CEO of Prop Firm Bridge, where he leads the company’s vision, platform growth, and long term strategic direction. He oversees operations across research, marketing, content systems, SEO, and product positioning while driving the platform’s mission of becoming a trusted authority in the prop firm industry. At Prop Firm Bridge, Akash plays a direct role in shaping educational frameworks, comparison systems, and trader focused resources designed to help users make informed decisions with transparency and confidence. His work focuses on building scalable organic growth systems, improving platform authority, and strengthening trust through accurate, structured, and search optimized content. In addition to leadership responsibilities, he actively manages growth strategy, social media marketing, search visibility, and brand development to expand the platform’s reach across global trading audiences.
Manoj Gholap is responsible for content accuracy, compliance, and factual integrity at Prop Firm Bridge. He acts as the final verification layer for all published content, ensuring that prop firm reviews, rules, and comparisons are clear, accurate, and aligned with transparency standards. Manoj plays a key role in maintaining trust and credibility across the platform.
Quick answer: QT Funded’s current prohibited-strategy policy is specific enough that traders should read it before building a strategy around speed, automation, multiple accounts or extreme risk. The policy currently prohibits arbitrage trading, latency trading, front-running price feeds, mispricing exploitation, high-frequency trading including tick scalping, order-book spamming, excessive order placement, server flooding through algorithm misuse, reverse trading or group hedging across accounts, one-sided manipulative betting, toxic or disruptive trading behavior and an all-or-nothing trading approach. The separate reverse-trading rule also prohibits sustained or repeated opposite positions across accounts under the stated conditions.
For traders who are researching QT before buying, QT Funded coupon code "BRIDGE" currently gives 60% off covered purchases. Traders can enter "BRIDGE" manually or use the QT Funded auto-discount registration route. These are alternative ways to access the same current offer, not stackable discounts. The discount changes purchase economics; it does not make a prohibited strategy acceptable.
This article is directed by Akash Mane, Founder and CEO of Prop Firm Bridge, with the research structured around the current QT Help Centre rather than old screenshots or generic prop-firm assumptions. The practical goal is to help traders answer a more useful question than “Is my strategy allowed?”: Which part of my actual execution could trigger a rule problem, and how do I redesign it before risking an account?
Many traders describe themselves with labels: scalper, swing trader, algorithmic trader, news trader, grid trader, breakout trader. QT’s prohibited-strategy policy is more concerned with what the account actually does. A trader can call a system “scalping” and still have ordinary market risk, reasonable holding time and normal execution. Another trader can call a system “mean reversion” while the engine is actually exploiting stale quotes. The label does not decide compliance.
The current QT policy names several behaviors directly. Pricing-error exploitation is prohibited. Arbitrage and latency trading are prohibited. High-frequency trading, including tick scalping, is prohibited. Order-book spamming, excessive order placement and server flooding are prohibited. Reverse trading or group hedging across accounts is prohibited. All-or-nothing risk behavior is prohibited. Those categories give traders a practical map.
The best way to review a strategy is to describe its mechanics. How many orders does it place? How long are positions normally held? Where does the edge come from? Does it rely on a faster external price feed? Can it trade without a stop? Does it add size after losses? Does it open opposite positions on other accounts? Does it rely on abnormal spread or liquidity conditions? Those answers matter more than the strategy name.
A common mental trap is to assume that a profitable strategy must be acceptable because it takes market risk. That is not how prop-firm rules work. A strategy can be profitable and still violate the operating conditions of the account. The account is a rule-based service, and the trader’s responsibility is to make sure the method fits the rule set.
This matters especially with purchased robots. A vendor may advertise a high win rate without explaining that the system depends on latency differences, tick-level execution, aggressive order cancellation or a martingale recovery sequence. The trader who connects the robot remains responsible for the resulting account behavior.
Before buying any system for QT, request enough information to classify the behavior. If the vendor will not explain average holding time, maximum number of simultaneous orders, recovery logic, stop-loss use or whether the edge depends on multiple feeds, that uncertainty should be treated as risk.
QT has active and discontinued programs. The current active family includes QT ONE, QT TWO, QT POWER, the new QT Instant plan, QT 1 Step Buy Now Pay Later and QT Bonus. Older QT 2 Step, QT 2 Step Elite and the old Instant plan are marked discontinued. A strategy guide built around a legacy plan can therefore be misleading even if it was once accurate.
Use the active plan page and current account dashboard before trading. If the public prohibited-strategy page and a plan-specific page both apply, read them together. A plan can add a news, exposure, consistency, stop-loss or floating-loss condition that changes how an otherwise ordinary strategy should be executed.
Founder experience: The safest way to audit a prop strategy is to ignore the marketing name and write down the actual execution sequence from signal to exit. Problems become much easier to see when the behavior is described plainly.
Book insight: In Thinking in Systems, Donella Meadows focuses on behavior produced by system structure. The same logic applies here: the relevant question is what the strategy does inside QT’s rules, not what the strategy is called. Page references vary by edition.
The current policy names arbitrage trading and latency trading under exploiting unrealistic market conditions. It also prohibits front-running price feeds and mispricing exploitation. These strategies attempt to benefit from discrepancies in how prices are delivered or updated rather than from ordinary directional market risk.
A classic latency setup compares two feeds, identifies that one feed updates faster, and trades on the slower environment before its price catches up. The trader may see this as “low-risk arbitrage,” but QT specifically lists latency trading as prohibited. The same applies to systems that enter because a quote is clearly stale or incorrect relative to a normal market price.
Not every strategy that uses multiple data sources is prohibited. A trader can use macro data, order-flow information or correlated markets as analysis. The compliance problem appears when the edge depends on a platform price being wrong, delayed or abnormally different and the strategy is designed to capture that defect.
Markets occasionally produce unusual quotes, spikes or execution errors. A trader who builds a system specifically to search for those anomalies is entering the area QT’s policy addresses. The current wording includes pricing errors, misquotes and abnormal fills.
For manual traders, this means an obviously erroneous price should not be treated as a free opportunity. For automated traders, filters should prevent the system from firing on impossible or highly abnormal price changes. A robot that enters only when the platform deviates sharply from an external benchmark deserves immediate review.
Backtests can be deceptive here. Historical data can contain bad ticks that make an exploitative strategy look extremely profitable. Cleaning data and using realistic bid/ask spreads helps reveal whether the edge survives normal market conditions.
Some sophisticated strategies trade relationships between assets. That is not automatically the same as prohibited arbitrage. A trader might believe two correlated instruments have diverged and expect the relationship to normalize. The key difference is that the trade still carries ordinary market risk and does not depend on a stale or erroneous quote.
Document the thesis. If the expected profit comes from economic convergence, that is different from expecting one platform to update later than another. When the distinction is unclear, ask QT support with a precise description of the execution logic.
Founder experience: The easiest red flag is a strategy that claims unusually stable profits because it is “faster than the broker.” In a prop environment, speed-based pricing exploitation usually deserves far more scrutiny than the sales page suggests.
Book insight: Michael Lewis’ Flash Boys explores how speed and market structure can create advantages. The lesson for QT traders is not to imitate those mechanics inside a rule set that explicitly prohibits latency and high-frequency exploitation. Chapter references vary by edition.
QT’s current prohibited-strategy policy directly lists high-frequency trading, including tick scalping. That is one of the clearest rules in the document. A trader should not connect an HFT system and rely on a generic statement that “EAs are allowed” or “scalping is allowed” somewhere else. The specific prohibited behavior controls.
High-frequency trading is not simply “many trades.” The practical concern includes very rapid execution, extremely short holding times, large message volume and strategies that depend on microsecond or tick-level market structure. A manual trader taking several intraday setups is not automatically HFT. A robot firing large numbers of orders to capture tiny tick differences is much closer to the prohibited category.
Tick scalping deserves separate attention because some commercial robots use that exact approach. If the system’s edge comes from one or two ticks and requires extremely fast entry and exit, the trader should assume it is incompatible with the current QT policy unless QT provides specific written clarification.
A strategy can produce a modest number of completed trades while generating a huge number of order messages. Pending orders may be added, modified and cancelled repeatedly. Stops can be changed every tick. Rejected orders can be retried automatically. QT separately prohibits order-book spamming, excessive order placement and server flooding through algorithm misuse, so message behavior matters.
Automated traders should log order submissions, modifications, cancellations and retries, not only completed trades. A robot with 20 trades but 3,000 order modifications can create a different compliance profile from a robot with 20 trades and 40 total messages.
Rate limiting is good engineering. If the strategy requires constant message bursts to work, it is not a good fit for a policy that explicitly restricts manipulative or excessive high-frequency activity.
A short-hold strategy can still use a defined stop, reasonable order frequency and normal market risk. The trader should be able to explain why the trade can lose money under ordinary conditions, not only through a technical failure. If the strategy’s losses occur only when latency fails, that suggests the edge may depend on the prohibited mechanism.
For a fast discretionary trader, build a personal frequency cap and session stop. The goal is to prevent a volatile period from turning normal scalping into frantic overtrading or an all-or-nothing recovery sequence.
Founder experience: The word “scalping” is too broad to answer the rule question. The real audit starts with holding time, order-message volume, edge source and risk per trade.
Book insight: Jim Paul and Brendan Moynihan’s What I Learned Losing a Million Dollars shows how quickly decision quality can deteriorate when activity becomes emotionally reactive. Speed does not excuse the need for a defined process. Page references vary by edition.
QT lists order-book spamming or excessive order placement under prohibited high-frequency and manipulative activity. This matters because a trader can avoid traditional HFT and still create excessive platform traffic through poor software design.
A grid EA may continuously cancel and replace dozens of pending orders. A trailing-stop script may modify an order on every small price movement. A connection error may cause repeated submissions. The trader may not intend to manipulate anything, but the resulting message volume can still be excessive.
Build controls before live use. Set a maximum number of active pending orders. Limit modification frequency. Stop retry loops after a small number of failures. Alert the trader instead of sending hundreds of requests.
QT’s wording specifically mentions flooding servers via algorithm misuse. A badly coded loop can therefore create risk even when the strategy itself is ordinary. The software should be designed to fail safely.
If the platform rejects an order, the system should identify the reason before retrying. If the connection drops, the system should not assume every failed response means the order was not placed. Duplicate orders can appear when the software submits again before confirming the first state.
Testing should include failure scenarios: delayed fills, rejected orders, disconnections, partial fills and platform restarts. A robust strategy is not only profitable under normal conditions; it also behaves predictably when technology fails.
Server-flooding rules are often discussed as an EA issue, but a manual trader can also submit and cancel excessive orders during a fast market. Rapidly clicking in and out because of frustration is poor risk management even before it reaches any technical threshold.
Use a maximum number of attempts per idea. If the market moves away or the order is rejected repeatedly, stand down. Missing a trade is less costly than turning one idea into dozens of unnecessary messages.
Founder experience: Good automation is boring when technology fails. It pauses, reconciles and alerts. The dangerous automation is the one that responds to uncertainty by sending more instructions.
Book insight: Gene Kim’s The Phoenix Project emphasizes reliable systems and controlled failure. The trading equivalent is simple: design the EA so an error reduces activity instead of multiplying it. Chapter references vary by edition.
QT’s current policy defines reverse trading as taking opposing positions on the same asset across different accounts. It states that opposing trades are not permitted when they remain opposite for more than two minutes or when the behavior occurs more than three individual times regardless of duration.
This can happen intentionally or accidentally. A trader may buy EURUSD on one account and sell it on another as an offset. A copier may fail to close a stale position and then mirror the new opposite direction. Two independent systems can also disagree. The account-level result is what matters.
The safest workflow prevents intentional opposite positions entirely. If an accidental conflict appears, correct it immediately and investigate the cause before continuing.
The policy also prohibits group hedging across accounts. That wording matters for coordinated trading between people. If a group deliberately takes opposite sides across accounts so that one side benefits regardless of market direction, the behavior can fall within the prohibited coordination category.
Do not assume that using different devices, networks or names makes coordinated hedging acceptable. The trading behavior is still coordinated. Each trader should operate an independent strategy within the account terms.
This is also why signal groups should be treated carefully. Following a public signal is not automatically the same as group hedging, but a group organized around opposite positioning or coordinated risk offset is a different structure.
QT’s current exposure policy says opposing positions do not automatically reduce exposure unless the defined maximum potential loss is actually reduced. This is an important risk calculation. A long and short position can still carry commissions, slippage and separate stop risk.
Traders should calculate exposure from the actual maximum loss of the combined positions rather than assuming opposite direction equals zero risk. When positions are across accounts, the separate account rules make that assumption even less reliable.
Founder experience: The cleanest multi-account rule is that another account should never be used as insurance for the first. Real risk control belongs inside the position and account being traded.
Book insight: Peter Bernstein’s Against the Gods is fundamentally about measuring risk rather than hiding it. A hedge that only moves risk to another account is not the same as reducing the underlying exposure. Page references vary by edition.
The current policy describes an all-or-nothing trading approach as excessively high-risk and unsustainable. Examples include trading without stop-loss protection, holding positions through major news without risk control, risking more than 75% of the daily drawdown limit on trades, and applying inconsistent or poor risk management.
The 75% figure should not be treated as a recommended risk level. It is a boundary inside a prohibited-behavior description. A trader building normal risk around 70% of daily drawdown is operating with almost no buffer for slippage, commission or another open position.
A stronger personal risk framework is much tighter. Define a normal per-trade risk, maximum correlated exposure and personal daily stop that sits comfortably inside the account limit.
QT’s responsible-trading language emphasizes that evaluations are designed to assess consistent risk management rather than the ability to pass using a single oversized trade. On relevant evaluation plans, exposure reaching the stated threshold can lead to funding denial or reset.
This means a trader should not think only about avoiding a technical breach. The path used to reach the target can matter. A 6% or 8% target reached through one extreme bet can create a very different risk profile from the same target reached through normal-sized trades.
Plan the evaluation around the strategy’s ordinary expectancy. If the target looks unreachable without increasing risk far beyond tested behavior, the chosen account or timeline is not a good fit.
Many traders do not start the day intending to take excessive risk. It happens after losses. A trader loses 1%, increases size to recover, loses again, and suddenly the next trade is carrying most of the remaining daily room.
Prevent that sequence with a fixed personal daily stop and a rule that position size cannot increase after a loss. A recovery plan should reduce activity, not escalate it.
Founder experience: Oversizing usually appears late in a bad session, not at the beginning. The best defense is a written stop that removes the decision when emotions are strongest.
Book insight: Mark Douglas’ Trading in the Zone emphasizes thinking in probabilities rather than forcing one trade to matter too much. All-or-nothing behavior does the opposite: it turns one outcome into a referendum on the whole account. Chapter references vary by edition.
QT’s all-or-nothing examples include trading without stop-loss protection. The separate exposure framework also uses stop-loss placement and floating loss to calculate risk. If no stop is placed, or floating loss exceeds the defined stop risk, exposure can be determined from the floating loss.
This means a trader cannot remove the stop and assume the account has less measured risk. The opposite is more likely: undefined downside makes exposure harder to control.
Use a stop that reflects the strategy’s invalidation point and calculate the dollar loss before entry. If the required stop creates too much risk, reduce position size rather than tightening the stop arbitrarily.
QT’s exposure guidance says traders cannot reduce exposure by temporarily placing tight stops and later widening them. The rule is designed around maximum potential loss, not cosmetic stop placement.
An automated strategy that continually widens stops after entry should be reviewed carefully. If the strategy needs that behavior, calculate exposure from the widest intended stop before opening the position. The account should be sized for the real risk.
This also applies to manual traders who move a stop because they do not want to accept a loss. Stop widening changes the risk profile and can push the account into an exposure problem.
QT’s current exposure page explicitly says commissions count toward exposure and that slippage must be factored into risk calculations. Stop orders are not guaranteed fills; once triggered, they execute at the next available market price.
A trade sized to land exactly on the formal limit has no room for real execution. Build a buffer. The faster or more volatile the market, the larger the uncertainty around the final loss.
Founder experience: Traders often calculate risk with a clean stop-loss number and forget costs. Prop rules are enforced on the actual account result, not the spreadsheet ideal.
Book insight: Benjamin Graham’s The Intelligent Investor is famous for the margin-of-safety concept. In prop trading, slippage and commissions are exactly why the trader needs margin inside the hard rule. Page references vary by edition.
QT’s current prohibited-strategy wording says trades executed during extreme volatility may be reviewed and, if deemed unrealistic, removed from PnL. This does not mean every volatile trade is prohibited. It means traders should not build an account strategy around abnormal execution or price behavior.
The safest approach is to follow the plan-specific news rule and maintain normal risk control. If a plan allows news trading, that permission does not guarantee normal spreads or fills. If a plan restricts entries and exits around certain events, the trader must follow the exact window.
Do not assume a large profit created by an obvious price glitch will necessarily be treated as ordinary market profit. The current rules give QT room to review unrealistic conditions.
QT POWER and the new Instant plan have current news treatment that differs from QT TWO. A trader may be allowed to hold or trade through an event on one plan while another plan has restrictions. Regardless of permission, all-or-nothing exposure around major news without risk control remains a problem.
Reduce size when slippage risk expands. A stop that normally loses 0.5% can lose more during a gap. If the account cannot absorb that uncertainty, staying flat is a valid decision.
A single abnormal fill can create a spectacular result. It can also tempt the trader to search for the same anomaly again. That is exactly the wrong lesson if the firm treats unrealistic market exploitation as prohibited.
Judge the strategy on normal conditions. A method that only looks attractive when the market or platform behaves abnormally is not a durable prop-firm process.
Founder experience: The most trustworthy performance records are built from ordinary conditions. Windfall trades are exciting, but they are a poor foundation for a rule-sensitive account.
Book insight: Nassim Nicholas Taleb’s Fooled by Randomness warns against confusing unusual outcomes with skill. Extreme-volatility profits deserve the same skepticism. Chapter references vary by edition.
Automation magnifies whatever logic is coded into it. If the system uses latency arbitrage, it can repeat the prohibited behavior hundreds of times. If it has a retry bug, it can flood the server. If it opens reverse positions across accounts, the pattern can recur before the trader notices.
That is why automation requires a behavior audit. Check holding time, message volume, data-feed dependencies, stop logic, recovery sizing, cross-account behavior and news awareness before connecting the system.
A vendor’s statement that the EA “works with prop firms” is not enough. Compare the actual logic with QT’s current rules.
A good prop EA has account-level controls: maximum risk per trade, maximum combined exposure, maximum daily loss, maximum number of orders, stop-loss requirement, news calendar logic where needed and a kill switch.
If a data feed fails, the EA should reduce activity. If it cannot read equity, it should stop opening new trades. If an order is rejected, it should not retry indefinitely. Safe automation is designed around uncertainty.
Even a well-designed system can face a platform update, symbol change or new rule. The trader should review the account state regularly and compare the EA’s behavior with the current QT documentation.
Keep versioned settings by plan. A QT TWO profile should not automatically be copied into POWER or Instant because the rule environment differs.
Founder experience: Automation removes clicks, not responsibility. The trader still owns the decision to connect the system to a particular rule set.
Book insight: Donella Meadows’ Thinking in Systems is useful here again: automation creates feedback loops. The faster the loop, the more important it is to design safe boundaries. Page references vary by edition.
QT TWO’s current active page includes a responsible-trading exposure rule during evaluation and a structured news framework. A strategy that is ordinary on another plan can become inappropriate if it creates too much combined risk or executes inside the restricted window.
Funded TWO also has its own stop-loss and exposure expectations. Traders should read the active plan page rather than importing rules from the discontinued QT 2 Step page.
Because TWO has two phases, the trader also needs to maintain compliance through both evaluation stages. Passing Phase 1 does not reset the need for disciplined behavior in Phase 2.
QT POWER currently uses a 35% consistency score in challenge and funded periods and says the standard news rule does not apply. That changes the practical compliance picture. A strategy can trade events under the current POWER rule, but it still cannot use prohibited HFT, arbitrage, all-or-nothing risk or other banned behavior.
Consistency can also turn one oversized winning day into a payout delay. The fact that a trade is not prohibited does not mean it is optimal for the account’s payout structure.
The new QT Instant plan includes a trailing maximum drawdown, a 30% consistency rule, one-percent maximum exposure per instrument and stop-loss requirements. BNPL includes its own floating-loss rule and funded-stage conditions. A strategy should be configured around the exact plan.
This is why a single “QT strategy” profile is too broad. Each plan needs its own risk settings even though the prohibited-strategy policy applies across the account family.
Founder experience: Traders often ask whether a strategy is allowed at a firm. The better question is whether it is both allowed and structurally suitable for the exact plan.
Book insight: Daniel Kahneman’s Thinking, Fast and Slow shows how people prefer simple generalizations. “Allowed at QT” is a tempting shortcut; plan-specific rules make that shortcut unreliable. Chapter references vary by edition.
For traders searching for a QT Funded coupon code, QT Funded discount code, QT Funded promo code or QT challenge deal, the current relevant code is "BRIDGE" for 60% off covered purchases. The central QT Funded coupon page remains the primary Prop Firm Bridge page for generic discount intent.
The purchase math is simple. A covered $100 price becomes $40 after a full 60% reduction. A covered $250 price becomes $100. A covered $500 price becomes $200. The live checkout is the final confirmation because product eligibility and pricing can change.
The manual code and auto-discount registration link are alternative routes to the same current offer. They should not be stacked or described as two separate discounts.
The worst use of a coupon is to make a trader feel comfortable testing a method that clearly conflicts with the rules. A 60% lower fee reduces the purchase cost; it does not reduce the chance of a hard breach if the strategy uses HFT, latency arbitrage, reverse trading or all-or-nothing risk.
Choose the plan because the strategy fits. Then use "BRIDGE" to improve the purchase economics. That order keeps the commercial decision separate from the trading decision.
QT Buy Now Pay Later has two payment stages. Do not assume the later activation fee receives a 60% reduction unless that activation checkout actually shows it. The current overall offer can be referenced for the purchase path, but each payment stage should be verified independently.
Founder experience: The strongest coupon content is useful when it helps a trader pay less for the right account, not when it persuades someone to buy the wrong account more cheaply.
Book insight: Morgan Housel’s The Psychology of Money emphasizes that good financial decisions are behaviorally sustainable. Discounts are arithmetic; discipline determines whether the purchase has value. Chapter references vary by edition.
Before trading, write a plain-language description: instruments, average holding time, maximum trades per day, stop-loss method, maximum risk per trade, maximum combined exposure, news behavior, automation used and whether the strategy interacts with other accounts.
Then compare each sentence with QT’s prohibited-strategy page and the exact plan. This makes hidden conflicts visible. “Fast scalper” is vague. “Robot places 60 trades per minute and holds for one or two ticks” is specific enough to identify a problem.
Ask what happens after three losses, a connection failure, a volatile event and a large unrealized drawdown. A strategy can look compliant on average and become all-or-nothing during stress.
For automation, test retry loops, stop-loss failure, duplicate orders and stale positions. For manual trading, define the point where the session ends. The account should survive the trader’s bad day, not only the normal day.
If the method sits near a boundary, send QT support a precise description. Do not ask only “Is my EA allowed?” Explain the number of trades, holding time, data source, stop logic and cross-account behavior.
Save the response with the date and plan name. Rules can change, so re-check after major updates.
Founder experience: A precise support question is one of the cheapest risk-management tools available. Vague questions create vague answers.
Book insight: Atul Gawande’s The Checklist Manifesto shows that expertise improves when critical steps are made explicit. A short strategy-compliance checklist can prevent expensive avoidable mistakes. Page references vary by edition.
Akash Mane is the Founder and CEO of Prop Firm Bridge. He leads founder-led, data-backed research, SEO-driven content systems and transparent prop-firm education designed around current rules rather than promotional shortcuts. He oversees content accuracy, editorial strategy and the platform’s long-term organic trust standards. Connect with him on LinkedIn.
Prop Firm Bridge publishes current prop-firm reviews, account-rule guides and verified coupon information. Before buying a QT account, compare the exact plan rules, verify the current "BRIDGE" 60% off result at checkout, and use a strategy that can operate comfortably inside the published restrictions.
The structured FAQ section immediately below answers the most common QT Funded prohibited-strategy questions, including HFT, arbitrage, latency trading, group hedging, all-or-nothing risk, extreme-volatility reviews and the current "BRIDGE" offer. The detailed Q&As are maintained in the dedicated FAQ field so the page presents them once, keeps the FAQ cluster clickable from the TOC, and preserves FAQPage structured data without duplicating article content.
QT Funded currently prohibits pricing-error exploitation, arbitrage, latency trading, front-running price feeds, mispricing exploitation, high-frequency trading including tick scalping, order-book spamming, excessive order placement, server flooding through algorithm misuse, reverse trading, group hedging, one-sided manipulative betting, toxic trading behavior and all-or-nothing risk practices.
No. QT Funded's current prohibited-strategy policy explicitly lists high-frequency trading, including tick scalping, as prohibited.
No. The current policy explicitly prohibits arbitrage trading, latency trading, front-running price feeds and mispricing exploitation.
QT Funded prohibits excessively high-risk behavior such as trading without stop-loss protection, holding major-news exposure without risk control, risking more than 75% of the daily drawdown limit on trades and using inconsistent or poor risk management.
QT's current prohibited-strategy wording says trades executed during extreme volatility may be reviewed and, if deemed unrealistic, removed from PnL. Traders should follow the active plan and news rules and avoid relying on abnormal execution conditions.
QT Funded discount code "BRIDGE" currently gives 60% off covered purchases. Verify the final live checkout total before payment.
