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Trendshift [CHE] StrategyTrendshift Strategy — First-Shift Structural Regime Trading Profitfactor 2,603 Summary Trendshift Strategy implements a structural regime-shift trading model built around the earliest confirmed change in directional structure. It identifies major swing highs and lows, validates breakouts through optional ATR-based conviction, and reacts only to the first confirmed shift in each direction. After a regime reversal, the strategy constructs a premium and discount band between the breakout candle and the previous opposite swing. This band is used as contextual bias and may optionally inform stop placement and position sizing. The strategy focuses on clear, interpretable structural events rather than continuous signal generation. By limiting entries to the first valid shift, it reduces false recycles and allows the structural state to stabilize before a new trade occurs. All signals operate on closed-bar logic, and the strategy avoids higher-timeframe calls to stabilize execution behavior. Motivation: Why this design? Many structure-based systems repeatedly trigger as price fluctuates around prior highs and lows. This often leads to multiple flips during volatile or choppy conditions. Trendshift Strategy addresses this problem by restricting execution to the first confirmed structural event in each direction. ATR-based filters help differentiate genuine structural breaks from noise, while the contextual band ensures that the breakout is meaningful in relation to recent volatility. The design aims to represent a minimalistic structural trading framework focused on regime turns rather than continuous trend signaling. This reduces chart noise and clarifies where the market transitions from one regime to another. What’s different vs. standard approaches? Baseline reference Typical swing-based structure indicators report every break above or below recent swing points. Architecture differences First-shift-only regime logic that blocks repeated signals until direction reverses ATR-filtered validation to avoid weak or momentum-less breaks Premium and discount bands derived from breakout structure Optional band-driven stop placement Optional band-dependent position-sizing factor Regime timeout system to neutralize structure after extended inactivity Persistent-state architecture to prevent re-triggering Practical effect Only the earliest actionable structure change is traded Fewer but higher-quality signals Premium/discount tint assists contextual evaluation Stops and sizing can be aligned with structural context rather than arbitrary volatility measures Improved chart interpretability due to reduced marker frequency How it works (technical) The algorithm evaluates symmetric swing points using a fixed bar window. When a swing forms, its value and bar index are stored as persistent state. A structural shift occurs when price closes beyond the most recent major swing on the opposite side. If ATR filtering is enabled, the breakout must exceed a volatility-scaled distance to prevent micro-breaks from firing. Once a valid shift is confirmed, the regime is updated to bullish or bearish. The script records the breakout level, the opposite swing, and derives a band between them. This band is checked for minimum size relative to ATR to avoid unrealistic contexts. The first shift in a new direction generates both the strategy entry and a visual marker. Additional shifts in the same direction are suppressed until a reversal occurs. If a timeout is enabled, the regime resets after a specified number of bars without structural change, optionally clearing the band. Stop placement, if enabled, uses either the opposite or same band edge depending on configuration. Position size is computed from account percentage and may optionally scale with the price-span-to-ATR relationship. Parameter Guide Market Structure Swing length (default 5): Controls swing sensitivity. Lower values increase responsiveness. Use ATR filter (default true): Requires breakouts to show momentum relative to ATR. Reduces false shifts. ATR length (default 14): Volatility estimation for breakout and band validation. Break ATR multiplier (default 1.0): Required breakout strength relative to ATR. Premium/Discount Framework Enable framework (default true): Activates premium/discount evaluation. Persist band on timeout (default true): Keeps structural band after timeout. Min band ATR mult (default 0.5): Rejects narrow bands. Regime timeout bars (default 500): Neutralizes regime after inactivity. Invert colors (default false): Color scheme toggle. Visuals Show zone tint (default true): Background shade in premium or discount region. Show shift markers (default true): Display first-shift markers. Execution and Risk Risk per trade percent (default 1.0): Determines position size as account percentage. Use band for size (default false): Scales size relative to band width behavior. Flat on opposite shift (default true): Forces reversal behavior. Use stop at band (default false): Stop anchored to band edges. Stop band side: Chooses which band edge is used for stop generation. Reading & Interpretation A green background indicates discount conditions within the structural band; red indicates premium conditions. A green triangle below price marks the first bullish structural shift after a bearish regime. A red triangle above price marks the first bearish structural shift after a bullish regime. When stops are active, the opposite band edge typically defines the protective level. Band width relative to ATR indicates how significant a structural change is: wider bands imply stronger volatility structure, while narrow bands may be suppressed by the minimum-size filter. Practical Workflows & Combinations Trend following: Use first-shift entries as initial regime confirmation. Add higher-timeframe trend filters for additional context. Swing trading: Combine with simple liquidity or fair-value-gap concepts to refine entries. Bias mapping: Use higher timeframes for structural regime and lower timeframes for execution within the premium/discount context. Exit management: When using stops, consider ATR-scaling or multi-stage profit targets. When not using stops, reversals become the primary exit. Behavior, Constraints & Performance The strategy uses only confirmed swings and closed-bar logic, avoiding intrabar repaint. Pivot-based swings inherently appear after the pivot window completes, which is standard behavior. No higher-timeframe calls are used, preventing HTF-related repaint issues. Persistent variables track regime and structural levels, minimizing recomputation. The maximum bars back setting is five-thousand. The design avoids loops and arrays, keeping performance stable. Known limitations include limited signal density during consolidations, delayed swing confirmation, and sensitivity to extreme gaps that stretch band logic. ATR filtering mitigates some of these effects but does not eliminate them entirely. Sensible Defaults & Quick Tuning Fewer but stronger entries: Increase swing length or ATR breakout multiplier. More responsive entries: Reduce swing length to capture earlier shifts. More active band behavior: Lower the minimum band ATR threshold. Stricter stop logic: Use the opposite band edge for stop placement. Volatile markets: Increase ATR length slightly to stabilize behavior. What this indicator is—and isn’t Trendshift Strategy is a structural-regime trading engine that evaluates major directional shifts. It is not a complete trading system and does not include take-profit logic or prediction features. It does not attempt to forecast future price movement and should be used alongside broader market structure, volatility context, and disciplined risk management. Disclaimer The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context. Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved. By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk. Do not use this indicator on Heikin-Ashi, Renko, Kagi, Point-and-Figure, or Range charts, as these chart types can produce unrealistic results for signal markers and alerts. Best regards and happy trading Chervolino
Strategia Pine Script®
di chervolino
Liquidity Sweep & FVG StrategyThis strategy combines higher-timeframe liquidity levels, stop-hunt (sweep) logic, Fair Value Gaps (FVGs) and structure-based take-profits into a single execution engine. It is not a simple mash-up of indicators: every module (HTF levels, sweeps, FVGs, ZigZag, sessions) feeds the same entry/exit logic. 1. Core Idea The script looks for situations where price: Sweeps a higher-timeframe high/low (takes liquidity around obvious levels), Then forms a displacement candle with a gap (FVG) in the opposite direction, Then uses the edge of that FVG as a limit entry, And manages exits using unswept structural levels (ZigZag swings or HTF levels) as targets. The intent is to systematically trade failed breakouts / stop hunts with a defined structure and risk model. It is a backtesting / study tool, not a signal service. 2. How the Logic Works (Conceptual) a) Higher-Timeframe Liquidity Engine Daily, Weekly and Monthly highs/lows are pulled via request.security() and stored as HTF liquidity levels. Each level is drawn as a line with optional label (1D/1W/1M High/Low). A level is marked as “swept” once price trades through it; swept levels may be removed or shortened depending on settings. b) Sweep & Manipulation Filter A low sweep occurs when the current low trades through a stored HTF low. A high sweep occurs when the current high trades through a stored HTF high. If both a high and a low are swept in the same bar, the script flags this as “manipulation” and blocks new entries around that noise. The script also tracks the sweep wick, bar index and HTF timeframe for later use in SL placement and labels. c) FVG Detection & Management FVGs are defined using a 3-candle displacement model: Bullish FVG: high < low Bearish FVG: low > high Only gaps larger than a minimum size (ATR-based if no manual value is set) are kept. FVGs are stored in arrays as boxes with: top, bottom, mid (CE), direction, and state (filled / reclaimed). Boxes are auto-extended and visually faded when price is far away, or deleted when filled. d) Entry Conditions (Sweep + FVG) For each recent sweep window: After a low sweep, the script searches for the nearest bullish FVG below price and uses its top edge as a long limit entry. After a high sweep, it searches for the nearest bearish FVG above price and uses its bottom edge as a short limit entry. A “knife protection” check blocks trades where price is already trading through the proposed stop. Only one entry per sweep is allowed; entries are only placed inside the configured NY trading sessions and only if no manipulation flag is active and EOD protection allows it. e) Stop-Loss Placement (“Tick-Free” SL) The stop is not placed directly on the HTF level; instead, the script scans a window around the sweep bar to find a local extreme: Longs: lowest low in a configurable bar window around the sweep. Shorts: highest high in that window. This produces a structure-based SL that is generally outside the main sweep wick. f) Take-Profit Logic (ZigZag + HTF Levels) A lightweight ZigZag engine tracks swing highs/lows and removes levels that have already been broken. For intraday timeframes (< 1h), TP candidates come from unswept ZigZag swings above/below the entry. For higher timeframes (≥ 1h), TP candidates fall back to unswept HTF liquidity levels. The script picks up to two targets: TP1: nearest valid target in the trade direction (or a 2R fallback if none exists), TP2: second target (or a 4R fallback if none exists). A multi-TP model is used: typically 50% at TP1, remainder managed towards TP2 with breakeven plus offset once TP1 is hit. g) Session & End-of-Day Filters Three predefined NY sessions (Early, Open, Afternoon) are available; entries are only allowed inside active sessions. An End-of-Day filter checks a user-defined NY close time and: Blocks new entries close to the end of the day, Optionally forces flat before the close. 3. Inputs Overview (Conceptual) Liquidity settings: which HTF levels to track (1D/1W/1M), how many to show, and sweep priority (highest TF vs nearest vs any). FVG settings: visibility radius, search window after a sweep, minimum FVG size. ZigZag settings: swing length used for TP discovery. Execution & protection: limit order timeout, breakeven offset, EOD protection. Visuals: labels, sweep markers, manipulation warning, session highlighting, TP lines, etc. For exact meaning of each input, please refer to the inline comments in the open-source code. 4. Strategy Properties & Backtesting Notes Default strategy properties in this script: Initial capital: 100,000 Order size: 10% of equity (strategy.percent_of_equity) Commission: 0.01% per trade (adjust as needed for your broker/asset) Slippage: must be set manually in the Strategy Tester (recommended: at least a few ticks on fast markets). Even though the order size is 10% of equity, actual risk per trade depends on the SL distance and is typically much lower than 10% of the account. You should still adjust these values to keep risk within what you personally consider sustainable (e.g. somewhere in the 1–2% range per trade). For more meaningful results: Test on liquid instruments (e.g. major indices, FX, or liquid futures). Use enough history to reach 100+ closed trades on your market/timeframe. Always include realistic commission and slippage. Do not assume that past performance will continue. 5. How to Use Apply the strategy to your preferred symbol and timeframe. Set broker-like commission and slippage in the Strategy Tester. Adjust: HTF levels (1D/1W/1M), Sessions (NY windows), FVG search window and minimum size, ZigZag length and EOD filter. Observe how entries only appear: After a HTF sweep, In the configured session, At a FVG edge, With TP lines anchored at unswept structure / liquidity. Use this primarily as a research and backtesting tool to study how your own ICT / SMC ideas behave over a large sample of trades. 6. Disclaimer This script is for educational and research purposes only. It does not constitute financial advice, and it does not guarantee profitability. Always validate results with realistic assumptions and use your own judgment before trading live.
Strategia Pine Script®
di mehmettopbas_
RSI Strategy [PrimeAutomation]⯁ OVERVIEW The RSI Strategy is a momentum-driven trading system built around the behavior of the Relative Strength Index (RSI). Instead of using traditional overbought/oversold zones, this strategy focuses on RSI breakouts with volatility-based trailing stops, adaptive profit-targets, and optional early-exit logic. It is designed to capture strong continuation moves after momentum shifts while protecting trades using ATR-based dynamic risk management. ⯁ CONCEPTS RSI Breakout Momentum: Entries happen when RSI breaks above/below custom thresholds, signaling a shift in momentum rather than mean reversion. Volatility-Adjusted Risk: ATR defines both stop-loss and profit-target distances, scaling positions based on market volatility. Dynamic Trailing Stop: The strategy maintains an adaptive trailing level that tightens as price moves in the trade’s favor. Single-Position System: Only one trade at a time (no pyramiding), maximizing clarity and simplifying execution. ⯁ KEY FEATURES RSI Signal Engine • Long when RSI crosses above Upper threshold • Short when RSI crosses below Lower threshold These levels are configurable and optimized for trend-momentum detection. ATR-Based Stop-Loss A custom ATR multiplier defines the initial stop. • Long stop = price – ATR × multiplier • Short stop = price + ATR × multiplier Stops adjust continuously using a trailing model. ATR-Based Take Profit (Optional) Profit targets scale with volatility. • Long TP = entry + ATR × TP-multiplier • Short TP = entry – ATR × TP-multiplier Users can disable TP and rely solely on trailing stops. Real-Time Trailing Logic The stop updates bar-by-bar: • In a long trade → stop moves upward only • In a short trade → stop moves downward only This keeps the stop tight as trends develop. Early Exit Module (Optional) After X bars in a trade, opposite RSI signals trigger exit. This reduces holding time during weak follow-through phases. Full Visual Layer • RSI plotted with threshold fills • Entry/TP/Stop visual lines • Color-coded zones for clarity ⯁ HOW TO USE Look for RSI Breakouts: Focus on RSI crossing above the upper boundary (long) or below the lower boundary (short). These moments identify fresh momentum surges. Use ATR Levels to Manage Risk: Because stops and targets scale with volatility, the strategy adapts well to both quiet and explosive market phases. Monitor Trailing Stops for Trend Continuation: The trailing stop is the primary driver of exits—often outperforming fixed targets by catching larger runs. Use on Liquid Markets & Mid-Higher Timeframes: The system performs best where RSI and ATR signals are clean—crypto majors, FX, and indices. ⯁ CONCLUSION The RSI Strategy is a modern RSI breakout system enhanced with volatility-adaptive risk management and flexible exit logic. It is designed for traders who prefer momentum confirmation over mean reversion, offering a disciplined framework with robust protections and dynamic trend-following capability. Its blend of ATR-based stops, optional profit targets, and RSI-driven entries makes it a reliable strategy across a wide range of market conditions.
Strategia Pine Script®
di ChartPrime
5
Anchor SafeSwing Gold StrategyOverview: The Anchor SafeSwing Gold Strategy is designed for users who prefer structured, rule-based swing trading on XAUUSD. It focuses on identifying high-quality trade setups rather than frequent entries. This strategy analyzes the market using multiple technical indicators and methods—including trend analysis, multi-chart confirmation, and support/resistance evaluation—to identify potential swing points. It also incorporates a dynamic approach to risk management through adaptive stop-loss and take-profit logic. How the Strategy Works 1. Multi-Chart & Trend Analysis: The strategy evaluates trend direction using several indicators and multiple charts. This helps determine whether the trend favors long or short setups. 2. Buy/Sell Conditions: a. Buy Conditions: When the broader trend is identified as bullish, the strategy waits for the formation of a strong support zone before considering a long position. b. Sell Conditions: When the trend is bearish, it waits for a confirmed resistance zone before initiating short positions. 3. Dynamic Take-Profit Logic The strategy uses adaptive take-profit behavior based on evolving market conditions. It monitors new support/resistance structures and various overbought/oversold signals to dynamically exit trades. 4. Dynamic and Configurable Stop-Loss: A flexible stop-loss system adjusts according to volatility and market structure. Users can modify the stop-loss threshold in the settings based on their own risk tolerance and account size. Trading Frequency : This strategy focuses on select, high-quality setups. As a result, trade frequency is relatively low and may vary depending on market conditions. Backtesting may show roughly several trades per month, but actual live performance can differ. Important Notes All trading involves risk, and users should evaluate the strategy and adjust settings according to their own risk management preferences.
Strategia Pine Script®
di mdaupu
6
Hash Supertrend [Hash Capital Research]Hash Supertrend Strategy by Hash Capital Research Overview Hash Supertrend is a professional-grade trend-following strategy that combines the proven Supertrend indicator with institutional visual design and flexible time filtering. The strategy uses ATR-based volatility bands to identify trend direction and executes position reversals when the trend flips.This implementation features a distinctive fluorescent color system with customizable glow effects, making trend changes immediately visible while maintaining the clean, professional aesthetic expected in quantitative trading environments. Entry Signals: Long Entry: Price crosses above the Supertrend line (trend flips bullish) Short Entry: Price crosses below the Supertrend line (trend flips bearish) Controls the lookback period for volatility calculation Lower values (7-10): More sensitive to price changes, generates more signals Higher values (12-14): Smoother response, fewer signals but potentially delayed entries Recommended range: 7-14 depending on market volatility Factor (Default: 3.0) Restricts trading to specific hours Useful for avoiding low-liquidity sessions, overnight gaps, or known choppy periods When disabled, strategy trades 24/7 Start Hour (Default: 9) & Start Minute (Default: 30) Define when the trading session begins Uses exchange timezone in 24-hour format Example: 9:30 = 9:30 AM End Hour (Default: 16) & End Minute (Default: 0) Controls the vibrancy of the fluorescent color system 1-3: Subtle, muted colors 4-6: Balanced, moderate saturation 7-10: Bright, highly saturated fluorescent appearance Affects both the Supertrend line and trend zones Glow Effect (Default: On) Adds luminous halo around the Supertrend line Creates a multi-layered visual with depth Particularly effective during strong trends Glow Intensity (Default: 5.0) Displays tiny fluorescent dots at entry points Green dot below bar: Long entry Red dot above bar: Short entry Provides clear visual confirmation of executed trades Show Trend Zone (Default: On) Strong trending markets (2020-style bull runs, sustained bear markets) Markets with clear directional bias Instruments with consistent volatility patterns Timeframes: 15m to Daily (optimal on 1H-4H) Challenging Conditions: Choppy, range-bound markets Low volatility consolidation periods Highly news-driven instruments with frequent gaps Very low timeframes (1m-5m) prone to noise Recommended AssetsCryptocurrency:
Strategia Pine Script®
di Hash_Capital
PA Builder [PrimeAutomation]1. PA Builder – Overview PA Builder is not a fixed strategy; it’s a framework for building strategies. Instead of giving traders one rigid system, it provides a toolbox where entries, exits, filters, risk parameters, and automation rules can all be defined and combined. The core philosophy is confluence: the idea that a trade should only be taken when multiple independent signals agree. The Builder is built around this principle. Every module; trend, reactors, bands, reversals, volume, structure, divergences, externals can be treated as one layer of confidence. The stronger the alignment across layers, the higher the quality of the setup in theory. In practice, this means PA Builder encourages traders to think in terms of “confluence,” not single indicators. Trend and positioning define whether you should even be looking for longs or shorts. Timing tools such as bands, reversals and candlestick structures determine when inside that broader bias you want to engage. Confirmation tools like volume and flow tell you whether capital is actually supporting the move. Filter systems then ensure that even if everything looks good locally, you still respect higher-timeframe or opposing warnings. The Builder’s philosophy is simple: enter less often, but only when conditions are genuinely in your favour. 2. Core Entry Signal Components The entry logic in PA Builder is built on a set of signal engines that can be combined in many ways. Trend Signals form a natural foundation. They use low-lag low-pass filters, borrowed from audio signal processing, to extract directional bias from price without the classic delay of classical moving averages. The sensitivity parameter controls how reactive this engine is: lower values favour cleaner trends and fewer whipsaws, while higher values are better suited to short-term intraday trading where speed matters more than smoothness. Many traders start by requiring that Trend Signals show “all bullish” or “all bearish” before allowing any entries in that direction. Trend signals firing short positions On top of this directional backbone, the Dynamic Reactor behaves as an adaptive baseline. It accelerates in volatile phases and slows down during consolidation, effectively acting as a moving reference point for both trend and price position. A typical use of this module is to insist that, for long trades, the price sits above a bullish reactor; for shorts, below a bearish one. At the higher-timeframe level, the Quantum Reactor provides a VWAP-style reference that can be anchored to larger candles than the chart you are trading. A common configuration is to trade on a 15-minute chart while requiring that price is above the 4-hour Quantum Reactor for longs or below it for shorts. The “fast” and “slow” options determine how quickly this reference adapts to new information. Timing is then refined with tools like Quantum Bands, reversals and candle structure analysis. Quantum Bands identify extremes within the current environment. In an uptrend, a tag of the lower band can be treated as a pullback rather than a breakdown; in a downtrend, the upper band acts like a shorting zone. Many traders combine “trend up and above higher-timeframe reactor” with “price temporarily below lower band” to construct a mean-reversion entry inside a larger uptrend. Reversal detection modules examine recent bars to find turning points, with shorter lookbacks capturing fast flips and longer lookbacks tracking deeper structural changes. Candle structure logic goes beyond classical candlestick names and instead focuses on whether price action confirms follow-through or reversion behaviour, with options like “2X” modes that wait for two successive confirmations before acting. Before and after filtering using reactor applied. Additional confirmation layers come from Volume Matrix, Money Flow, OSC True7 and divergence detection. Volume and flow tools answer whether actual capital is participating in the move or whether price is drifting on thin activity. OSC True7 categorises the state of the trend into intuitive buckets, strong, healthy, neutral, or exhausted, making it easier to avoid chasing extremes. Divergences between price and momentum can be used either as entry triggers in contrarian systems or as hard filters that block trades when warning signs are present. Finally, two external indicator inputs make it possible to integrate RSI, MACD, custom indicators or even other strategies into the Builder, either as simple thresholds or as comparative logic between two external sources (for example, requiring a fast EMA to be above a slow EMA before allowing longs). 3. Exit System & Trade Management The exit systems in PA Builder are designed to be as vital as the entry logic. It assumes exits are not an afterthought, but half of the edge. Instead of forcing a single take profit point, the system uses a three-tier structure where you can assign different portions of the position to different targets. A common pattern is to scale out a small portion early (for example at one ATR), another portion at an intermediate level, and keep the largest slice for a deeper move. This creates a natural balance: you book something early to reduce emotional stress, while leaving room to participate in the full potential of a trend. Targets can be defined using ATR multiples or risk-to-reward ratios that are directly tied to the initial stop distance. Using ATR keeps exits proportional to current volatility. A two ATR target in a quiet environment is very different in absolute price distance from the same multiple in a high-volatility environment, yet conceptually it represents the same “size” move. Risk-to-reward exits build on this by ensuring that if you risk one unit (1R), the reward targets are set at predefined multiples of that risk. This enforces positive expectancy at the structural level: the strategy cannot generate entries with inherently negative payoffs. Once price begins to move in your favour, trailing logic takes over if you choose to enable it. Trailing can begin immediately from entry or only after a target has been hit. Many users prefer to let TP1 and TP2 behave as fixed profit points and then apply a trailing stop or trailing take profit to the final remainder. That way, routine winners are banked mechanically, while occasional explosive moves can be ridden for as long as the market allows. The breakeven module supports this behaviour by automatically moving stops to entry (or slightly through entry into profit) after a specified condition such as TP1 being hit. This transforms the risk profile mid trade: once breakeven has been secured, remaining size can be managed with much less psychological pressure. The system also recognises the cost of time. Kill Switch functionality exits trades that have been open too long under mediocre conditions, typically when they are in modest profit but not progressing. This protects you from capital being tied up while better opportunities appear elsewhere. Underlying all of this are several trailing stop mechanisms: percentage-based, tick-based for very short-term strategies, TP linked trailing that activates only once a certain profit threshold has been achieved, and ATR based trailing that automatically scales the trail distance with volatility. Each method serves a slightly different profile of strategy, but all share the same aim: preserve gains and limit downside in a structured way rather than rely on discretionary judgement after the fact. 4. Filters and Risk Management The filter systems in PA Builder formalise the idea that good trading is often about knowing when not to act. “Do Not Trade” conditions can be configured so that even a perfectly aligned bullish entry stack is overridden if certain bearish evidence is present. These can include higher timeframe reversal structures, powerful opposing divergences, or conflicting signals in key modules. By assigning conditions specifically to “Do Not Long” and “Do Not Short” rather than only to entries, you create asymmetry: buying requires bullish evidence and an absence of strong bearish warnings; selling requires the mirror. Volatility filters extend this logic to the regime level. Some strategies are inherently suited to low volatility, range bound environments where fading extremes is profitable; others require expansion and energy to function properly. By binding trading permission to volatility ranges, you ensure that a mean-reversion system does not blindly attempt to fade a breakout, and that a momentum system does not spin its wheels in a dead, sideways market. You can even reference volatility from a higher timeframe than the one you trade, so that a five-minute strategy is still aware of the broader one-hour volatility regime it sits inside. Applied DO NOT TRADE - removes poor signal Risk management and position sizing are configured so each trade is expressed in units of risk rather than arbitrary size. Leverage, in this framework, is simply a scaling factor for capital efficiency; the actual risk per trade is still controlled by the distance between entry and stop and the percentage of equity you choose to expose. Reinvestment options then decide what proportion of accumulated profit is fed back into position sizing. A more aggressive reinvestment setting accelerates compounding but increases the amplitude of drawdowns; a more conservative one smooths the equity curve at the cost of slower growth. The Base Trade Value parameter ties all of this together by deciding how much nominal capital or how many contracts are committed per trade in light of your maximum allowed simultaneous positions and your intended use of leverage. External exit conditions provide further flexibility. For example, you might design a system whose entries rely purely on PA Builder’s internal modules, but whose exits use RSI readings, moving average crosses, or a proprietary external indicator. The separation of entry and exit logic allows you to bolt on different behaviours at the tail end of trades while keeping your core signal engine intact. In all cases, the objective is the same: express risk in a controlled, repeatable way that can survive long stretches of unfavourable market conditions. 5. PDT, Cooldowns and Visual Modes For traders subject to Pattern Day Trading rules, PA Builder includes a day-trade tracking system that counts business days correctly and respects the three-trades-in-five-days limit. This goes beyond simple compliance; it forces discipline. When intraday trading is heavily constrained, you are naturally pushed toward swing-oriented strategies with fewer, more selective entries. The tool visually marks your PDT status so you never inadvertently cross the line and trigger a lockout. Cooldown systems address another reality: psychological vulnerability after streaks. Following several consecutive wins, many traders unconsciously loosen their standards, take marginal signals, oversize positions, or overtrade. A win-streak cooldown deliberately pauses trading after a configured number of wins, giving you time to reset. The same applies to losing streaks. After a run of losses, the strongest temptation is often to “make it back now,” which is exactly when discipline is weakest. A loss-streak cooldown enforces a break in activity during this high-risk emotional state, helping to prevent cascading damage driven by revenge trading. Visualisation comes in two main modes. Classic mode emphasises precision: it draws explicit entry lines, stop levels, target levels and fill zones, making it easy to audit risk/reward on each trade, verify that the exit logic behaves as intended, and review historical trades in detail. Modern mode emphasises market feel: instead of focusing on exact levels, it colours candles and backgrounds to reflect momentum, profit state and dynamics. This helps you see at a glance whether a strategy is operating in a smooth trending environment or a choppy, fragmented one, and whether current trades are broadly working or struggling. Many users develop and debug in Classic mode and then monitor live performance in Modern mode, so both representations become part of the workflow. 6. Strategy Design Workflow, Examples and Cautions Designing with PA Builder is inherently iterative. You begin with a simple theory and a minimal configuration, perhaps just a trend filter and a basic stop/target structure, and run a backtest. You then examine where the system fails. If you see many losses occurring in counter-trend conditions, you add an additional directional filter or restrict entries with a higher-timeframe reactor condition. If you observe many small whipsaw losses, you might require candle structure confirmation or volume confirmation before allowing an entry. Each change is made one at a time and evaluated. This process gradually builds a layered system where every component has a clear purpose: some reduce drawdown, some increase win rate, some cut out only the worst trades, and others help capture more of the best ones. A conservative swing strategy might need an agreement between short-term trend signals, a higher-timeframe Quantum position, and a bullish Dynamic Reactor state, while checking that volume supports the move and that no significant bearish reversals or divergences are present on higher timeframes. It might accept relatively few trades, but each trade would be tightly controlled, scaled out over several ATR-based targets and protected with breakeven and trailing logic. On the opposite end, an aggressive scalping configuration would relax some filters, favour faster sensitivities, use short lookback reversals, and tighten stops and targets dramatically, relying on high frequency and careful volatility filtering to maintain edge. Throughout all of this, overfitting remains the main danger. The more parameters you tune and the more coincidental rules you add to make the backtest equity curve smoother, the more likely it is that you are capturing noise rather than a real, repeatable edge. Signs of overfitting include heavily optimised numeric values with no intuitive justification, large differences between in-sample and out-of-sample results, or strategies that work spectacularly in very specific regimes and collapse elsewhere. To mitigate this, keep strategies as simple as possible, test across different market regimes (bull, bear, range), and accept that robust systems usually look less “perfect” on the historical chart. Bridging the gap from backtest to live trading is another critical step. Before risking capital, it is wise to paper trade the configuration for a number of trades to confirm that signal frequency, behaviour and execution align with expectations. When going live, starting with minimal size and gradually scaling up based on real-world performance helps manage both financial and psychological risk. If live results diverge significantly from backtest expectations due to slippage, fees, or changing market conditions, you can adjust, reduce size, or temporarily pause rather than commit fully to a failing configuration. Ultimately, PA Builder is designed to be a tool for building structured, rules-driven trading systems. It gives you the tools to express your ideas, test them, refine them, and run them under controlled risk. It does not remove uncertainty or guarantee results, but it does provide a clear, transparent way to translate trading concepts into executable, testable logic, and to evolve those systems as markets change and your understanding deepens.
Strategia Pine Script®
di ChartPrime
4
ParabolicSAR+EMA[TS_Indie]🚀 EMA + Parabolic SAR Reversal Trading Strategy This trading system effectively combines the use of Exponential Moving Averages (EMA) with the Parabolic SAR to identify both price trends and key reversal points. The EMA Fast is used to signal the primary short-term trend, while the EMA Slow acts as a filter for the long-term trend direction. The Parabolic SAR then helps to confirm the reversal signals. 🛠️ Tools Used 1. EMA Fast – Primary Short-Term Trend 2. EMA Slow – Long-Term Trend Filter 3. Parabolic SAR – Reversal Confirmation 🎯 Entry Rules 📈 Buy Setup 1. Trend Filter: EMA Fast > EMA Slow → Uptrend 2. Pullback: Price pulls back and closes below the EMA Fast line. 3. Reversal: Price reverses/pulls back up and closes above the EMA Fast line. 4. SAR Confirmation: The previous Parabolic SAR dot is above the high, and the dot in the current candle is below the low → Reversal signal confirmed. 5. Entry: Enter Buy immediately. 📉 Sell Setup 1. Trend Filter: EMA Fast < EMA Slow → Downtrend 2. Pullback: Price pulls back and closes above the EMA Fast line. 3. Reversal: Price reverses/pulls back down and closes below the EMA Fast line. 4. SAR Confirmation: The previous Parabolic SAR dot is below the low, and the dot in the current candle is above the high → Reversal signal confirmed. 5. Entry: Enter Sell immediately. 💰 Exit Management (Entry, Stop Loss, Take Profit) 1. Entry: Enter the order at the closing price of the signal candle. 2. Stop Loss (SL): Set the Stop Loss at the Parabolic SAR dot. 3. Take Profit (TP): Calculated from the Entry and Stop Loss points, multiplied by the Risk Reward Ratio. ⚙️ Optional Parameters ➭ Custom Risk/Reward Ratio for Take Profit. ➭ Option to add an ATR buffer to the Stop Loss. ➭ Adjustable EMA Fast period. ➭ Adjustable EMA Slow period. ➭ Adjustable Parabolic SAR parameters. ➭ Option to enable Long-only / Short-only positions. ➭ Customizable Backtest start and end date. ➭ Customizable trading session time. 🔔 Alert Function Alerts display: ➭ Entry Price ➭ Stop Loss Price ➭ Take Profit Price 💡 This strategy allows for many parameter adjustments, such as the MA type, adding/subtracting from the Stop Loss using ATR, and selecting specific sessions for backtesting. If you find interesting or profitable results after adjusting the parameters, please share your comments with other traders! ⚠️ Disclaimer This indicator is designed for educational and research purposes only. It does not guarantee profits and should not be considered financial advice. Trading in financial markets involves significant risk , including the potential loss of capital.
Strategia Pine Script®
di Truth_Strategy_Indie
Simple MA Crossover w/ SLTPPicture two cheetahs on a racetrack made of price candles. One cheetah is fast and twitchy (the short-term EMA). The other is chill, lumbering, and takes its sweet time (the long-term EMA). When the twitchy cheetah sprints ahead and crosses above the chill one → “BUY, YOU MAGNIFICENT DEGEN!” When the twitchy one gets tired, slows down, and gets lapped from above → “SELL before this turns into a horror movie!” That, my friend, is the EMA crossover strategy in its purest, most dramatic form.
Strategia Pine Script®
di Thighighs
Seawolf Pivot Hunter [Strategy]Overview Seawolf Pivot Hunter is a practical trading strategy that enhances the classic pivot-box breakout system with a structured risk-management framework. Using ATR-based stop loss and take-profit calculations, position sizing, multi-layer filtering, and daily loss-limit protection, it provides a stable and sustainable trading environment. It preserves the strengths of the original version while adding systems designed to manage real-market risks more effectively. Core Philosophy The most important element in trading is not generating profits but controlling losses. Even the best entry signals cannot compensate for a single large loss that wipes out accumulated gains. This strategy precisely calculates the risk exposure for every trade and includes multiple layers of protection to safeguard the account under worst-case scenarios. Indicator Setup Link kr.tradingview.com Example of Optimal Parameter Settings Asset (Exchange): ETH/USDT (Binance) Timeframe: 15-minute chart Pivot Detection Length: 5 Upper Box Width: 2 Lower Box Width: 2 Enable Risk Management: False Use Trailing Stop: False Use Volume Filter -Min Buy Volume % for Long: 50 -Min Sell Volume % for Short: 50 Use Trend Filter (EMA): False Enable Max Loss Protection -Max Daily Loss ($): 200 -Max Trades Per Day: 10 Calculated Bars: 50,000 Risk-Management System Every trade automatically receives a stop-loss level at the moment of entry. The stop is calculated using ATR, adjusting dynamically to market volatility. When volatility increases, the stop widens; in stable conditions, it tightens to reduce unnecessary exits. The default distance is set to twice the ATR. The standard take-profit level is set to four times the ATR, providing a 1:2 risk-reward structure. With this ratio, even a 50 percent win rate can produce profitability—while the typical trade structure aims for small losses and larger gains to support long-term performance. A trailing-stop option is also available. Once the trade moves into profit, the stop level automatically trails behind price action, protecting gains while allowing the position to expand when momentum continues. Position size is calculated automatically based on the selected risk percentage. For example, with a 2 percent risk setting, each stop-loss hit would result in exactly 2 percent of the account balance being lost. This ensures a consistent risk profile regardless of account size. The daily loss-limit function prevents excessive drawdown by halting new trades once a predefined loss threshold is reached. This helps avoid emotional decision-making after consecutive losses. A daily trade-limit feature is included as well. The default is 10 trades per day, protecting traders from overtrading and unnecessary fees. Filtering System The volume filter analyzes buying and selling pressure within the pivot box. Long trades are allowed only when buy volume exceeds a specified percentage; shorts require sell-volume dominance. The default threshold is 55 percent. The trend filter uses an EMA to determine market direction. When price is above the 200-EMA, only long signals are permitted; when below, only shorts are allowed. This ensures alignment with the broader trend and reduces counter-trend risk. Each filter can be toggled independently. More filters generally reduce trade frequency but improve signal quality. Real-Time Monitoring A real-time statistics panel displays daily profit/loss, the number of trades taken, the maximum allowed trades, and whether new trades are currently permitted. When daily limits are reached, the panel provides clear visual warnings. Entry Logic A trade is validated only after a pivot-box breakout occurs and all active filters—volume, trend, daily loss limit, and daily trade limit—are satisfied. Position size, stop loss, and take-profit levels are then calculated automatically. Entry arrows and labels on the chart help with later review and analysis. Setup Guide Risk percentage is the most critical setting. Beginners should start at 1 percent. Anything above 3 percent becomes aggressive. ATR stop-loss multipliers should reflect asset volatility. ATR take-profit multipliers determine reward ratio; 4.0 is the standard. Volume thresholds are typically set between 50–60 percent depending on market conditions. Daily loss limits are typically 2–5 percent of the account. Trading Strategy This strategy performs best in trending environments and works especially well on the 4-hour and daily charts. New users should begin with all filters enabled and trade conservatively. A minimum of one month of paper trading is recommended before committing real capital. Suitable Users The strategy is ideal for beginners who lack risk-management experience as well as advanced traders seeking a customizable structure. It is particularly helpful for traders who struggle with emotional decision-making, as pre-defined limits and rules enforce discipline. Backtesting Guide Use at least 2–3 years of historical data that includes bullish, bearish, and sideways conditions. Target metrics: Sharpe ratio: 1.5 or higher Maximum drawdown: below 25 percent Win rate: 40 percent or higher Total trades: at least 100 for statistical relevance Optimization Precautions Avoid over-fitting parameters. Always test values around the “best” setting to verify stability. Out-of-sample testing is essential for confirming robustness. Test across multiple assets and timeframes to ensure consistency. Live Deployment Roadmap After successful backtesting, follow a gradual rollout: Paper trading for at least one month Small-account live testing Slow scaling as performance stabilizes Continuous Improvement Keep a detailed trading journal and evaluate performance each quarter using recent data. Adapt settings as market conditions evolve. Conclusion Seawolf Pivot Hunter aims to provide more than simple trade signals—it is designed to create a stable and sustainable trading system built on disciplined risk management. No strategy is perfect, and long-term success depends on consistency, patience, and strict adherence to rules. Start small, verify results, and scale progressively. Disclaimer This strategy is for educational and research purposes only. Past performance does not guarantee future results. All trading decisions are the responsibility of the user. 개요 Seawolf Pivot Hunter는 기본 피봇 박스 브레이크아웃 전략에 전문적인 리스크 관리 시스템을 더한 실전형 트레이딩 전략입니다. ATR 기반의 손절매와 목표가 설정, 포지션 사이징, 다층 필터링 시스템, 일일 손실 제한 기능을 통해 안정적이고 지속 가능한 트레이딩 환경을 제공합니다. 기본 버전의 장점은 유지하면서 실제 시장에서 발생할 수 있는 위험을 체계적으로 관리할 수 있도록 설계되었습니다. 핵심 철학 트레이딩에서 가장 중요한 것은 수익이 아니라 손실 관리입니다. 아무리 훌륭한 진입 조건이 있어도 한 번의 큰 손실로 모든 수익이 사라질 수 있습니다. 이 전략은 각 거래마다 감수할 리스크를 명확히 계산하고, 최악의 상황에서도 계좌를 보호하기 위한 다양한 안전장치를 제공합니다. 지표 적용 링크 공유 kr.tradingview.com 최적 조건값 설정(예시) "종목(거래소): ETH/USDT(Binance)", "15 분봉 기준" -Pivot Detection Length: 5 -Upper Box width: 2 -Lower Box width: 2 -Enable Risk Management: False -Use Trailing Stop: False -Use Volume Filter -Min Buy Volume % for Long: 50 -Min Buy Volume % for Long: 50 -Use Trend Filter(EMA): False -Enable Max Loss Protection -Max Daily Loss($): 200 -Max Trades Per Day: 10 -Calucated bars: 50000 리스크 관리 시스템 모든 거래는 진입과 동시에 손절매 주문이 자동 설정됩니다. 손절가는 ATR을 기준으로 계산되며, 시장의 변동성에 따라 자동으로 조정됩니다. 변동성이 큰 시장에서는 넓은 손절폭을, 안정적인 시장에서는 좁은 손절폭을 사용해 불필요한 청산을 줄입니다. 기본값은 ATR의 2배입니다. 목표가는 ATR의 4배를 기본값으로 설정하여 손익비 1:2 구조를 유지합니다. 승률이 50퍼센트만 되어도 수익성이 가능하며, 실제로는 손절은 짧고 이익은 길게 가져가는 방식으로 장기 성과를 확보합니다. 트레일링 스톱 기능도 제공됩니다. 포지션이 수익 구간에 들어서면 손절가가 자동으로 함께 움직이며 수익을 보호합니다. 이 기능은 사용자가 켜거나 끌 수 있습니다. 포지션 크기는 리스크 퍼센트 기반으로 자동 계산됩니다. 예를 들어 리스크를 2퍼센트로 설정하면 손절 시 계좌 자산의 2퍼센트만 잃도록 수량이 조절됩니다. 계좌 크기와 무관하게 항상 일정한 비율의 리스크만 감수하게 되는 방식입니다. 일일 손실 제한 기능은 하루에 허용 가능한 최대 손실을 초과하지 않도록 합니다. 지정 금액에 도달하면 당일 거래는 더 이상 실행되지 않습니다. 감정적 거래를 막고 일정한 규율을 유지하도록 돕습니다. 일일 거래 횟수 제한 기능도 제공됩니다. 기본값은 하루 10회로, 과매매와 수수료 증가를 방지합니다. 필터링 시스템 볼륨 필터는 박스 구간 내 매수·매도 압력을 분석해 진입 신호를 검증합니다. 롱은 매수 볼륨이 일정 비율 이상일 때, 숏은 매도 볼륨이 우세할 때만 진입합니다. 기본값은 55퍼센트입니다. 추세 필터는 EMA를 사용하며, 가격이 200EMA 위에 있을 때는 롱 신호만, 아래에서는 숏 신호만 허용합니다. 큰 추세 방향에만 거래하여 역추세 리스크를 줄입니다. 필터는 독립적으로 켜고 끌 수 있으며, 필터가 많을수록 거래 횟수는 줄지만 신호 품질은 향상됩니다. 실시간 모니터링 화면에 실시간 통계 테이블이 표시되며, 일일 손익, 거래 횟수, 최대 허용 횟수, 현재 거래 가능 여부가 즉시 확인됩니다. 손실 제한 또는 거래 제한 도달 시 시각적으로 표시됩니다. 진입 로직 피봇 박스 브레이크아웃 발생 후 볼륨 필터, 추세 필터, 일일 손실·거래 제한을 모두 통과하면 포지션 크기를 계산하고 손절·목표가를 설정한 뒤 진입합니다. 진입 지점에는 화살표와 레이블이 표시되어 분석에 도움을 줍니다. 설정 가이드 리스크 퍼센트는 가장 중요한 설정입니다. 초보자는 1퍼센트를 추천하며 3퍼센트 이상은 위험합니다. 손절 ATR 배수는 자산 특성에 맞게 조절합니다. 목표가 ATR 배수는 손익비를 결정하며 기본값은 4.0입니다. 볼륨 비율은 시장 상황에 따라 50~60퍼센트 내외로 조정합니다. 일일 손실 제한은 계좌의 2~5퍼센트 수준이 적절합니다. 사용 전략 추세가 명확한 시장에서 가장 효과적이며, 4시간봉 또는 일봉을 추천합니다. 초반에는 모든 필터를 켜고 보수적으로 시작하며, 최소 한 달간 페이퍼 트레이딩을 권장합니다. 적합한 사용자 리스크 관리 경험이 부족한 초보자부터, 커스터마이징을 원하는 경험자까지 폭넓게 적합합니다. 감정적 트레이딩을 억제하는 기능이 있어 규율 유지가 어렵던 트레이더에게 특히 유용합니다. 백테스트 가이드 최소 2~3년 데이터로 테스트하며, 상승·하락·횡보 모두 포함해야 합니다. 샤프비율 1.5 이상, 최대 낙폭 25퍼센트 이하를 목표로 합니다. 승률은 40퍼센트 이상이면 충분합니다. 최소 100회 이상 거래가 있어야 통계적으로 의미가 있습니다. 최적화 주의사항 과최적화를 피하고 주변 값도 테스트해야 합니다. 샘플 외 기간 검증은 필수입니다. 여러 자산·여러 시간대에서 테스트하여 일관성을 확인해야 합니다. 실전 적용 로드맵 백테스트 후 바로 실전 투입하지 말고, 한 달 이상의 페이퍼 트레이딩 → 소액 실전 → 점진적 확대 순으로 진행합니다. 지속적 개선 일지를 기록하고 분기마다 최신 데이터로 점검합니다. 시장 변화에 따라 유연하게 조정해야 합니다. 마치며 Seawolf Pivot Hunter는 단순 신호 제공을 넘어, 안전하고 지속 가능한 트레이딩 환경 구축을 목표로 합니다. 어떤 전략도 완벽할 수 없으며, 장기적 성공을 위해서는 규칙 준수와 인내가 가장 중요합니다. 충분한 검증을 거쳐 작은 금액으로 시작하고 점진적으로 확장해나가는 접근을 추천합니다. 면책 조항 이 전략은 교육 및 연구 목적이며, 과거 성과는 미래를 보장하지 않습니다. 모든 투자 결정은 본인의 판단과 책임 하에 이루어져야 합니다.
Strategia Pine Script®
di Seawolf_AGI
Quasimodo Pattern Strategy Back Test [TradingFinder] QM Trading🔵 Introduction The QM pattern, also known as the Quasimodo pattern, is one of the popular patterns in price action, and it is often used by technical analysts. The QM pattern is used to identify trend reversals and provides a very good risk-to-reward ratio. One of the advantages of the QM pattern is its high frequency and visibility in charts. Additionally, due to its strength, it is highly profitable, and as mentioned, its risk-to-reward ratio is very good. The QM pattern is highly popular among traders in supply and demand, and traders also use this pattern. The Price Action QM pattern, like other Price Action patterns, has two types: Bullish QM and Bearish QM patterns. To identify this pattern, you need to be familiar with its types to recognize it. 🔵 Identifying the QM Pattern 🟣 Bullish QM In the bullish QM pattern, as you can see in the image below, an LL and HH are formed. As you can see, the neckline is marked as a dashed line. When the price reaches this range, it will start its upward movement. 🟣 Bearish QM The Price Action QM pattern also has a bearish pattern. As you can see in the image below, initially, an HH and LL are formed. The neckline in this image is the dashed line, and when the LL is formed, the price reaches this neckline. However, it cannot pass it, and the downward trend resumes. 🔵 How to Use The Quasimodo pattern is one of the clearest structures used to identify market reversals. It is built around the concept of a structural break followed by a pullback into an area of trapped liquidity. Instead of relying on lagging indicators, this pattern focuses purely on price action and how the market reacts after exhausting one side of liquidity. When understood correctly, it provides traders with precise entry points at the transition between trend phases. 🟣 Bullish Quasimodo A bullish Quasimodo forms after a clear downtrend when sellers start losing control. The market continues to make lower lows until a sudden higher high appears, signaling that buyers are entering with strength. Price then pulls back to retest the previous low, creating what is known as the Quasimodo low. This area often becomes the final trap for sellers before the market shifts upward. A visible rejection or displacement from this zone confirms bullish momentum. Traders usually place entries near this level, stops below the low, and targets at previous highs or the next resistance zone. Combining the setup with demand zones or Fair Value Gaps increases its accuracy. 🟣 Bearish Quasimodo A bearish Quasimodo forms near the top of an uptrend when buyers begin to lose strength. The market continues to make higher highs until a sudden lower low breaks the bullish structure, showing that selling pressure is entering the market. Price then retraces upward to retest the previous high, forming the Quasimodo high, where breakout buyers are often trapped. Once rejection appears at this level, it indicates a likely reversal. Traders can enter short near this area, with stop-losses placed above the high and targets near the next support or previous lows. The setup gains more reliability when aligned with supply zones, SMT divergence, or bearish Fair Value Gaps. 🔵 Setting Pivot Period : You can use this parameter to use your desired period to identify the QM pattern. By default, this parameter is set to the number 5. Take Profit Mode : You can choose your desired Take Profit in three ways. Based on the logic of the QM strategy, you can select two Take Profit levels, TP1 and TP2. You can also choose your take profit based on the Reward to Risk ratio. You must enter your desired R/R in the Reward to Risk Ratio parameter. Stop Loss Refine : The loss limit of the QM strategy is based on its logic on the Head pattern. You can refine it using the ATR Refine option to prevent Stop Hunt. You can enter your desired coefficient in the Stop Loss ATR Adjustment Coefficient parameter. Reward to Risk Ratio : If you set Take Profit Mode to R/R, you must enter your desired R/R here. For example, if your loss limit is 10 pips and you set R/R to 2, your take profit will be reached when the price is 20 pips away from your entry point. Stop Loss ATR Adjustment Coefficient : If you set Stop Loss Refine to ATR Refine, you must adjust your loss limit coefficient here. For example, if your buy position's loss limit is at the price of 1000, and your ATR is 10, if you set Stop Loss ATR Adjustment Coefficient to 2, your loss limit will be at the price of 980. Entry Level Validity : Determines how long the Entry level remains valid. The higher the level, the longer the entry level will remain valid. By default it is 2 and it can be set between 2 and 15. 🔵 Results The following examples show the backtest results of the Quasimodo (QM) strategy in action. Each image is based on specific settings for the symbol, timeframe, and input parameters, illustrating how the QM logic can generate signals under different market conditions. The detailed configuration for each backtest is also displayed on the image. ⚠ Important Note : Even with identical settings and the same symbol, results may vary slightly across different brokers due to data feed variations and pricing differences. Default Properties of Backtests : OANDA:XAUUSD | TimeFrame: 5min | Duration: 1 Year : BINANCE:BTCUSD | TimeFrame: 5min | Duration: 1 Year : CAPITALCOM:US30 | TimeFrame: 5min | Duration: 1 Year : NASDAQ:QQQ | TimeFrame: 5min | Duration: 5 Year : OANDA:EURUSD | TimeFrame: 5min | Duration: 5 Year : PEPPERSTONE:US500 | TimeFrame: 5min | Duration: 5 Year :
Strategia Pine Script®
di TFlab
18
AlgoIndexOS-ES-FuturesAlgoIndexOS — ES Futures Strategy v2.0 (5-Minute RTH) Scope (read first) ES on 5-minute only, RTH session. The strategy operates on U.S. Regular Trading Hours (09:30–16:00 ET) using a 5-minute ES chart. It builds an Opening Session Range (OSR) from the RTH open, then runs a breakout engine when internal quality conditions are met. Exits are target-based with an intrabar touch-to-flat safety. Positions are flattened at the RTH session end by default. Alerts can post JSON to your Webhook URL for automation. What this is One intraday engine with four curated presets (“Stages”) tuned for distinct segments of the NY session. Stages keep the core logic consistent while applying time-of-day context and conservative governors. Single invite-only listing; not a multi-post suite. How it trades (high-level) Range context: Builds and locks the OSR from the opening bell; entries only arm after the range is set. Quality gating: Trades only when internal trend/volatility/confirmation conditions align (no parameter disclosure). Breakout execution: Signals at bar close; bracket exits manage take-profit (limit) with an intrabar “TP-touch” safety to avoid phantom fills; optional stop-loss. Session safety: Positions flat at RTH close by default (time exit). (No settings or thresholds are disclosed; presets encapsulate research choices.) Stages (session templates; one engine) A single Stage selector chooses among four presets optimized for different parts of the RTH session (morning vs mid-day; long/short focus). Internal parameters remain fixed to preserve tested behavior. Public inputs (kept minimal) Stage (choose your preset) TP / SL (points) shown for transparency; effective values are governed by the selected preset to maintain consistency with research. Optional display overlays (status line/markers) for readability. Alerts (how to use) Create an alert on the strategy and choose Strategy → Order fills. Use a webhook if you want automation. The payload includes the exact chart symbol so it works on ES1! or a specific ES contract: { "tv_symbol": "{{ticker}}", "tv_exchange": "{{exchange}}", "action": "buy|sell|exit", "price": {{close}}, "time": "{{timenow}}" } If your receiver needs a fixed root (e.g., “ES”), map it on your server using tv_symbol for context. Backtest & assumptions Backtest assumptions (initial capital, commission, slippage, margin) are user-configurable in TradingView. Results on your chart reflect your settings. This script evaluates ES fills on 5-minute RTH bars; live execution will differ. Operating notes Use on ES only, 5-minute timeframe, RTH session. If you run multiple Stages, use separate charts/tabs and coordinate net exposure in your own tooling if needed. Publish with a clean chart for clarity. Disclosures (compliance) No investment advice. This script is for research/education and tooling only. It does not provide investment, legal, tax, or accounting advice and does not recommend any security, instrument, or strategy. Use at your own risk. Hypothetical performance (CFTC 4.41). Hypothetical or simulated results have many limitations, and no representation is made that any account will achieve similar outcomes. Past performance is not necessarily indicative of future results. Futures risk. Trading futures involves substantial risk of loss and is not suitable for all investors. Leverage, gaps, slippage, and connectivity can cause losses exceeding initial investment. Backtesting limitations. Results depend on data quality, chart resolution, session filters, and user assumptions; live execution will differ. Intellectual property. © 2025 AlgoIndex. All Rights Reserved. Redistribution, resale, or decompilation prohibited without written consent.
Strategia Pine Script®
di MyAlgoIndex
QQQ TimingThis is a trend-following position trading strategy designed for the QQQ and the leveraged ETF QLD (ProShares Ultra QQQ). The primary goal is to capture multi-month holds for maximal profit. Key Instruments & Performance The strategy performs best with QLD, which yields far superior results compared to QQQ. TQQQ (triple-leveraged) results in higher drawdowns and is not the optimal choice. Important: The system is not intended for use with other indexes, individual stocks, or investments (like crypto or gold), as performance can vary widely. Buy Signals The strategy's signals are rooted in the S&P 500 Index (SPX), as testing showed it provides more reliable triggers than using QQQ itself. Primary Buy Signal (Credit to IBD/Mike Webster): The SPX triggers a buy when its low closes above the 21-day Exponential Moving Average (EMA) for three consecutive days. Refinement with Downtrend Lines: During corrective or bear periods, results and drawdowns can be significantly improved by incorporating downtrend lines. These lines connect lower highs. The strategy waits for the price to close above a drawn downtrend line before executing a buy. This refinement can modify the primary signal, either by allowing for an earlier entry or, in some cases, completely nullifying a false signal until the trend change proves itself. Risk Management & Exit Strategy Initial Buy Risk: A 3.7% stop loss is applied immediately upon the initial entry. Initial Exit Rule: An exit is required if the QQQ's low drops below the 50-day Simple Moving Average (SMA). Note: The 3.7% stop often provides protection when the initial buy occurs below the 50-day SMA. However, if QQQ is already trading above its 50-day SMA at the time of the SPX signal (indicating relative strength), historically, it has been better to use the 50-day SMA rule to give the position more room to run. Trend Exit (Profit-Taking): To stay in a strong trend for the optimal amount of time, the long position is exited when a moving average crossover to the downside is triggered, based around the 107-day Simple Moving Average (SMA).
Strategia Pine Script®
di market_quester
Quantura - Quantified Price Action StrategyIntroduction “Quantura – Quantified Price Action Strategy” is an invite-only Pine Script strategy designed to combine multiple price action concepts into a single trading framework. It integrates supply and demand zones, liquidity sweeps and runs, fair value gaps (FVGs), RSI filters, and EMA trend confirmation. The strategy also provides a visual overlay with dynamic trend-colored candles for easier chart interpretation. It is intended for multi-market use across cryptocurrencies, Forex, equities, and indices. Originality & Value The strategy is original in how it unifies several institutional-style price action elements and validates trades only when they align. This reduces noise compared to using single indicators in isolation. Its unique value lies in the combination of: Supply & Demand detection: Dynamic boxes identified through pivots, ATR, and volume sensitivity. Liquidity sweeps and runs: Detects when swing highs/lows are broken and retested, distinguishing between liquidity grabs (sweeps) and directional runs. RSI filter: Can be set to normal or aggressive, confirming momentum before trades. Fair Value Gaps (FVGs): Optional detection and filtering of price inefficiencies. EMA filter: Aligns trades with the broader market trend. Trend candle visualization: Candles dynamically colored bullish, bearish, or neutral, based on strategy positions. This layered confluence approach ensures that entries are not taken on a single condition but require agreement across several dimensions of market structure, momentum, and order flow. Functionality & Indicators Supply & Demand Zones: Zones are created when pivots, ATR sensitivity, and volume thresholds overlap. Liquidity: Swing highs and lows are tracked, with options for sweep (fakeout/reversal) or run (continuation) detection. RSI: Confirms long signals when oversold and shorts when overbought, with configurable aggressiveness. FVG filter: Adds validation by requiring price interaction with inefficiency zones. EMA filter: Ensures longs are above EMA and shorts below EMA. Signals & Visualization: Trade entries are marked on the chart, while candles change color to reflect trade direction and status. Parameters & Customization Supply & Demand: Sensitivity (swing range, volume multiplier, ATR multiplier) and display options. Liquidity filter: Mode (Run or Sweep), display, and swing length. RSI: Enable/disable, length, and style (normal or aggressive). Fair Value Gaps: Sensitivity via ATR factor, optional volume filter, and display toggles. EMA: Length, enable/disable, and visualization. Risk management: Up to three configurable take-profit levels, stop-loss, break-even logic, and capital-based position sizing. Visualization: Custom candle coloring and optional overlay for better clarity. Default Properties (Strategy Settings) Initial Capital: 10,000 USD Position Size: 100% of equity per trade (backtest default) Commission: 0.1% Slippage: 1 Pyramiding: 0 (only one position at a time) Note: The default of 100% equity per trade is used for testing purposes only and would not be sustainable in real trading. A typical allocation in practice would be between 1–5% of account equity per trade, sometimes up to 10%. Backtesting & Performance Backtests on XPTUSD over 2.5 years with the default settings produced: 164 trades 67.68% win rate Profit factor: 1.7 Maximum drawdown: 27.81% These results show how the confluence of supply/demand, liquidity, and RSI filters can produce robust setups. However, past performance does not guarantee future results. While the trade count (164) is sufficient for statistical analysis, results may vary across markets and timeframes. Risk Management Three configurable take-profit levels with percentage allocation. Initial stop-loss based on user-defined percentage. Dynamic stop-loss that adjusts with market movement. Break-even logic that shifts stops to entry after predefined gains. Position sizing based on risk percentage of equity. This framework allows both conservative and aggressive configurations, depending on user preference. Limitations & Market Conditions Works best in volatile and liquid markets such as crypto, metals, indices, and FX. May produce false signals in low-volume or sideways environments. Unexpected news or macro events can override technical conditions. Default position sizing of 100% equity is highly aggressive and should be reduced before any practical use. Usage Guide Add “Quantura – Quantified Price Action Strategy” to your chart. Select Supply & Demand, Liquidity, RSI, EMA, and FVG settings according to your market and timeframe. Configure risk management: take-profits, stop-loss, and risk-per-trade percentage. Use the Strategy Tester to analyze statistics, equity curve, and performance under different conditions. Optimize parameters before applying the strategy to different markets. Author & Access Developed 100% by Quantura. Published as an Invite-Only script. Important This description complies with TradingView’s publishing rules. It clarifies originality, explains the underlying logic, discloses default properties, and presents backtest results with realistic disclaimers.
Strategia Pine Script®
di Quantura
Quantura - Quantitative AlgorythmIntroduction “Quantura – Quantitative Algorithm” is an invite-only Pine Script strategy designed for multi-timeframe analysis, combining technical filters with user-adjustable fundamental sentiment. It was primarily developed for cryptocurrency markets but can also be applied across other assets such as Forex, stocks, and indices. The goal is to generate structured trade signals through a confluence of techniques rather than relying on a single indicator. Originality & Value Quantura is not a simple mashup of indicators. Its originality comes from how multiple layers of analysis are integrated into a single decision framework . Instead of showing indicators separately, the strategy only issues trades when several conditions align simultaneously: RSI entry triggers confirm overbought/oversold reversals. Market structure on a higher timeframe confirms trend direction. Order block detection highlights zones of concentrated supply and demand. Premium/Discount zones identify potential over- and undervaluation. HTF EMA provides trend confirmation. Optional candlestick patterns strengthen reversal or continuation signals. An optional correlation filter compares the main asset to a reference instrument. This design forces agreement between different methodologies (momentum, structure, value, volume, sentiment), which reduces noise compared to using them in isolation. Functionality & Indicators Entry trigger: RSI exits from extreme zones. Filters: Only valid when all selected filters (HTF structure, EMA, order blocks, premium/discount, candlesticks, correlation, volume) confirm the direction. Fundamental bias: User-defined sentiment and analysis settings (bullish, bearish, neutral) influence whether long or short trades are permitted. Exits: ATR-based take profit and stop loss, with optional breakeven, opposite-signal exit, and session-end exit. Visualization: Buy/Sell markers, trend-colored candles, and an optional dashboard summarizing indicator status. Parameters & Customization Timeframes: Independent HTF and LTF selection. Trading direction: Long / Short / Both. Session and weekday filters. RSI length and thresholds. Filters: HTF structure, order blocks, premium/discount, EMA, candlestick, ATR volatility, volume zones, correlation. Exit rules: ATR multipliers for TP/SL, breakeven logic, session-end exit, opposite-signal exit. Visuals: Toggle signals, candles, dashboard, custom colors. Default Properties (Strategy Settings) Initial Capital: 100,000 USD Position Size: 15% of equity per trade Commission: 0.25% Slippage: enabled Pyramiding: 0 (one position at a time) Note: The position sizing of 15% equity per trade is intentionally set for backtesting demonstration. In real trading, risking this much is considered aggressive. Most traders prefer to risk 1-5% of equity, and rarely above 10%. Backtesting & Performance Backtests on BTCUSD (2 years) with the above defaults showed: 112 trades Win rate: 40% Profit factor: 1.4 Maximum drawdown: 34% These results illustrate how the confluence model behaves, but they are not predictive of future performance . The trade sample size (72 trades) is below the 100+ usually recommended for statistical robustness. Users should re-test with their own preferred symbols, settings, and timeframes. Risk Management ATR-based stops and targets scale with volatility. Commission and slippage are included by default for realistic modeling. Opposite-signal exit helps capture trend reversals. Session-end exit can close intraday positions before illiquid hours. Breakeven option protects profits when available. Although the default allocation uses 15% per trade for demonstration, this is not a recommendation. Users are encouraged to adjust risk sizing downwards to sustainable levels (commonly 1-5%). Limitations & Market Conditions Performs best in volatile, liquid markets (e.g., crypto). May struggle in prolonged sideways markets with low volatility. News events and fundamentals outside user inputs can override signals. Backtests below 100 trades should be considered exploratory, not statistically conclusive. Usage Guide Add “Quantura – Quantitative Algorithm” to your chart in strategy mode. Select HTF and LTF timeframes, trading direction, and session filters. Configure confluence filters (structure, EMA, order blocks, premium/discount, candlestick, correlation, volume). Set sentiment and analysis bias in fundamental settings. Adjust ATR multipliers and exits. Review buy/sell signals and analyze performance in the Strategy Tester. Author & Access Developed 100% by Quantura . Distributed as an Invite-Only script . Details are provided in the Author’s Instructions field. Important: This description complies with TradingView’s Script Publishing Rules and House Rules. It does not guarantee profitability, avoids unrealistic claims, and explains how the strategy integrates multiple methods into a coherent decision framework.
Strategia Pine Script®
di Quantura
Turtles StrategyBorn from the 1980s "Turtle" experiment, this method of trading captures breakouts and places or closes trades with intrabar entries or exits and realized-equity risk controls. How It Works The strategy buys/sells on breakouts from recent highs/lows, using ATR for volatility-adjusted stops and sizing. It risks a fixed % (default 1%) of realized equity per trade—initial capital plus closed P&L, ignoring open positions for conservatism. Drawdown protection auto-reduces risk by 20% at 10% drops (up to three times), resetting only on full peak recovery. Single positions only, with 1-tick slippage simulated for realistic fills. Best for trending assets like forex,commodities, crypto, stocks. Backtest for optimal parameters. Main Operations The strategy works on any timeframe but it's meant to be used on daily charts. Entry Signals: Long: Buy-stop 1 tick above 20-bar high (default "Entry Period") when no position—enters intrabar on breakout. Short: Sell-stop 1 tick below 20-bar low. OCA cancels opposites. Size: (Realized equity × adjusted risk %) ÷ (2× ATR stop distance), scaled by point value. Exit Signals: Longs: Stop at tighter of (entry - 2× ATR) or (10-bar low - 1 tick trailing, default "Exit Period"). Shorts: Stop at tighter of (entry + 2× ATR) or (10-bar high + 1 tick trailing). Locks profits in trends, exits fast on fades. Risk Controls: Tracks realized equity peak. 10% drawdown: Risk ×0.8; 20%/30%: Further ×0.8 (max 3x). Full reset above peak—preserves capital in slumps.
Strategia Pine Script®
di nepo123
Strategy Builder v1.0.0 [BigBeluga]🔵 OVERVIEW The Strategy Builder combines advanced price-action logic, smart-money concepts, and volatility-adaptive momentum signals to automate high-quality entries and exits across any market. It blends trend recognition, market structure shifts, order block reactions, imbalance (FVG) signals, liquidity sweeps, candlestick confirmations, and oscillator-powered divergences into one cohesive engine. Whether used as a full automation workflow or as a structured confirmation framework, this strategy provides a disciplined, rules-driven method to trade with logic — not emotion. 🔵 BACKTEST WINDOW CONTROL This module allows you to restrict strategy execution to a specific historical period. Ideal for performance isolation, regime testing, and forward-walk validation. Limit Backtest Window Enabling this option activates custom date filters for the backtest engine. Start — Define the starting date & time for backtesting End — Define the ending date & time for backtesting Only trades and signals inside this window are executed Reduces computation load on large datasets Useful for testing specific market environments (e.g., bull cycles, crash periods, sideways regimes) 🔵 SIGNAL GLOSSARY (Advanced Technical Explanation) Traders can build long and short setups using up to 6 configurable entry conditions for each direction. Every condition can be set as Bullish or Bearish and mapped to any signal source — allowing deep customization Below is the full internal logic overview of every signal available in the Strategy Builder. Signals are based on trend models, volatility structures, liquidity logic, oscillator behavior, and market structure mapping. Trend Signals (Low-Lag Trend Engine) Uses a proprietary low-lag baseline + momentum gradient model to detect directional bias. Trend Signal — Momentum breaks above/below adaptive trend baseline. Trend Signal+ — Stronger trend confirmation using volatility-weighted momentum. Trend Signal Any — Triggers when any bullish/bearish trend signal appears. SmartBand & Retests (Adaptive Volatility Bands) Dynamic envelope that contracts/expands with volatility & trend strength. SmartBand Retest — Price retests dynamic band and rejects, confirming continuation. ActionWave Signals (Impulse-Pullback Engine) Tracks wave behavior, acceleration and deceleration in price. ActionWave — Detects directional impulse strength vs pullback weakness. ActionWave Cross — Momentum acceleration threshold crossed → trend ignition. Magnet Signals (Liquidity Gravity + Mean Reversion Bias) Detects zones where price is being drawn due to liquidity voids or imbalance. Magnet — Trend and liquidity pressure align, creating directional “pull.” MagnetBar Low Momentum — Low-volatility compression → pre-breakout condition. Flow Trend (Directional Flow State + ATR Envelope) Higher-timeframe bias confirmation + dynamic volatility filter. FlowTrend — Confirms major directional bias (uptrend or downtrend). FlowTrend Retest — Price tests HTF flow band and rejects → trend resume. Voltix (Volatility Expansion Pulse) Detects regime shift from quiet accumulation → trending expansion. Voltix — Breakout volatility signature, trend acceleration trigger. Candlestick Pattern (Algorithmic Price Action Recognition) Auto-recognizes meaningful reversal or continuation candle formations. Candlestick Pattern — Confirms momentum reversal/continuation via candle logic. OrderBlock Logic (Institutional Footprint System) Institutional demand/supply zone tracking with mitigation logic. Order Block Touch — Price taps institutional zone → reaction filter. Order Block Break — OB invalidation → institutional flow shift. Market Structure Engine (Swing Logic + Volume Confirmation) Tracks major swing breaks and structural reversals. BoS — Break of Structure in trend direction (continuation bias). ChoCh — Change of Character — early reversal marker. Fair Value Gaps (Imbalance & Volume Displacement) Identifies inefficiencies caused by rapid displacement moves. FVG Created — Price leaves inefficiency behind. FVG Retest — Price returns to rebalance inefficiency → reaction zone. Liquidity Events (Stop-Run & Reversal Logic) Detects stop-hunt events and liquidity sweeps. SFP — Swing failure & wick sweep → reversal confirmation. Liquidity Created — New equal highs/lows form liquidity pool. Liquidity Grab — Sweep through liquidity line followed by rejection. Support / Resistance Break Logic Adaptive zone recognition + momentum confirmation. Support/Resistance Cross — Zone decisively broken → structural shift. Pattern Breakouts (Market Geometry Engine) Tracks breakout from compression & expansion formations. Channel Break — Channel breakout → trend acceleration. Wedge Break — Break from contraction wedge → burst of momentum. Session Logic (Opening Range Behavior) Session-based volatility trigger. Session Break — Break above/below session opening range. Momentum / Reversal Oscillator Suite Oscillator-driven exhaustion & reversal signals. Nautilus Signals — Momentum reversal signature (oscillator shift). Nautilus Peak — Momentum peak → exhaustion risk. OverSold/Overbought ❖ — Extreme exhaustion zones → reversal setup. DipX Signals ✦ — Dip buy / Dip sell timing, micro-reversal engine. Advanced Divergence Engine Momentum/price disagreement layer with multi-trigger confirmation. Normal Divergence — Classic divergence reversal. Hidden Divergence — Trend continuation divergence. Multiple Divergence — Multiple divergence confirmations stacked → high confidence. 🔧 Adjustable Signal Logic Some signals in this system can be additionally refined through the strategy settings panel. This allows traders to tune internal behavior for different market regimes, assets, and volatility conditions. 🔵 LONG / SHORT EXIT CONDITIONS This section allows you to automate exits using the same advanced market conditions available for entries. Each exit rule consists of: Toggle — Enable/disable individual exit rule. Direction Filter — Trigger exit only if selected market bias appears (Bullish/Bearish). Signal Type — Choose which market event triggers the exit (same list as entry conditions). When the active conditions are met, the strategy automatically closes the current position — ensuring emotion-free risk management and systematic trade control. 🔵 TAKE PROFIT & STOP LOSS SYSTEM This strategy builder provides a fully dynamic risk-management engine designed for both systematic traders and discretionary confirmation users. Take Profit Logic Scale out of trades progressively or exit fully using algorithmic TP levels. Up to 3 Take-Profit targets available Choose TP calculation method: • ATR-based distance (volatility-adaptive targets) • %-based distance (fixed percentage from entry) Define Size — ATR multiplier or % value Custom Exit Size per TP (e.g., 25% / 25% / 50%) Visual TP plotting on chart for clarity Stop Loss Logic Automated protection logic for every trade. Two SL Modes: • Fixed Stop Loss — static SL from entry • Trailing Stop Loss — SL follows price as trade progresses Distance options: • ATR multiplier (adapts to volatility) • %-based from entry (fixed distance) SL dynamically draws on chart for transparency Trailing SL behavior: Follows price only in profitable direction Never moves against the trade Locks profits as trend develops 🔵 Strategy Dashboard A compact on-chart performance dashboard is included to help monitor live trade status and backtest results in real time. It displays key metrics: Start Capital — Initial account balance used in simulation. Position Size — % of capital allocated per trade based on user settings (It changes if the trade hits take profits, when more than one take profit is selected). Current Trade — Shows active trade direction (Long / Short) and real-time % return from entry. Closed Trades — Counter of completed positions, useful for reading sample size during testing. 🔵 CONCLUSION The Strategy Builder brings together a powerful suite of smart-money and momentum-driven signals, allowing traders to automate robust trade logic built on modern market structure concepts. With access to trend filters, order blocks, liquidity events, divergence signals, volatility cues, and session-based triggers, it provides a deeply adaptive trade engine capable of fitting many market environments.
Strategia Pine Script®
di BigBeluga
20
Futures Fighter MO: Multi-Confluence Day Trading System ADX/SMI👋 Strategy Overview: The Multi-Confluence Mashup The Futures Fighter MO is a comprehensive, multi-layered day trading strategy designed for experienced traders focusing on high-liquidity futures contracts (e.g., NQ, ES, R2K). This strategy is a sophisticated mashup that uses the 1-minute chart for surgical entries while enforcing strict environmental filtering through higher-timeframe data. We aim to capture high-conviction moves only when multiple, uncorrelated signals align. 🧠 How the Logic Works (Concepts & Confluence) Our logic is built on four pillars, which must align for a trade to be executed: Primary Trend Filter Indicators : ADX/DMI (15-Minute Lookback) Role : Price action is filtered to ensure the ADX (17/14) is above 25, confirming a strong, prevailing market trend (Bullish or Bearish). Trades are strictly rejected during "Flat" (sideways) market regimes. Entry Signal Types The system uses multiple entry types: - 🟢 Trend Long/Short: A breakout/rejection near the 200-Period EMA is confirmed by the primary ADX trend. - 🔴 Engulfing Rejection: A strong signal when a Bullish/Bearish Engulfing or Doji prints near the long-term 500-Period EMA (emaGOD) while the Stochastic Momentum Index (SMI on 30M) is in an extreme overbought/oversold state (below $-40$ or above $40$). Volatility & Volume Confirmation Indicators: Average True Range (ATR) and 20-Period SMA of Volume Role: Every entry requires a volume spike (Current Volume $> 1.5 \times$ SMA Volume) to confirm that the move is supported by significant liquidity. Volatility is tracked via ATR to define bar range and stop boundaries. Structural Guardrails Indicators: Daily Pivot Points (PP, S1-S3, R1-R3) Role: Trades are disabled if the current bar's price range intersects with a Daily Pivot Point. This is a critical filter to avoid high-chop consolidation zones near key structural levels. 📊 Strategy Results & Required Disclosures I strive to publish backtesting results that are transparent and realistic for the retail futures trader. - Initial Capital: $50,000 - A realistic base for Mini/Micro futures contracts. - Order Size: 1 Contract (Pyramiding up to 3) - Conservative risk relative to the account size. - Commission: $0.11 USD per order - Represents realistic costs for low-cost brokers. - Slippage: 2 Ticks - Accounts for expected market friction. ⚠️ Risk Management & Deviations Stop-Loss: The strategy uses a dynamic stop-loss system where positions are closed upon a reversal (e.g., breaking the 50-Period EMA or failure to hold a Pivot Point), rather than a fixed tick-based stop. This is suited for experienced traders using a low relative risk (single Micro-contract entry) on a larger account. Users must confirm that the first entry's maximum potential loss remains below $10\%$ of their capital for compliance. Trade Sample Size: Due to data limitations of the TradingView Essential plan (showing $\approx 50$ trades over 2 weeks), the sample size is under the ideal $100+$ target. Justification: This system is designed to generate signals across a portfolio of correlated futures markets (NQ, ES, R2K, Gold, Crude), meaning the real sample size for a user tracking the portfolio is significantly higher. Drawdown Control: This strategy is designed for manual management. It requires the user to turn the script/alerts OFF after a significant drawdown and only reactivate it once a recovery trend is established externally. The strategy uses a combination of dynamic trailing stops, structural support/resistance zones, and a fixed profit target to manage open positions. 🛑 Strategy Exit Logic 1. General Stop-Loss (Dynamic Trailing Stop) These conditions act as the primary dynamic stop, closing the position if the market reverses past a key Moving Average (MA): - Long Positions Closed When: The current bar's close crosses under the 50-Period EMA (emaLong). - Short Positions Closed When: The current bar's close crosses above the 50-Period EMA (emaLong). 2. Profit Target (Fixed Percentage) The script includes a general exit based on a user-defined profit percentage: Take Profit Trigger: The position is closed when the currentProfitPercent meets or exceeds the input Profit Target (%) (default is 1.0% of the entry price). 3. Structural Exits (Daily Pivot Points) These exits are high-priority, "close all" orders that trigger when the price fails to hold or reclaims a recent Daily Pivot Point, suggesting a failure of the current move. - VR Close All - Long ($\sym{size} > 0$) - Price crosses under a Daily Resistance Level (R1, R2, or R3) minus 1 ATR within the last 10 bars. This indicates the current momentum failed to hold Resistance as support. - VS Close All - Short ($\sym{size} < 0$) - Price crosses above a Daily Support Level (S1, S2, or S3) plus 1 ATR within the last 10 bars. This indicates the current momentum failed to hold Support as resistance. 4. Trend Failure Exit (Trend-Following Signals Only) This exit protects against holding a position when the primary high-timeframe trend used for the entry has failed: - Long Positions Closed When: The primary trend is no longer "bullish" for more than 2 consecutive bars (i.e., it turned "bearish" or "flat"). - Short Positions Closed When: The primary trend is no longer "bearish" for more than 2 consecutive bars (i.e., it turned "bullish" or "flat"). 5. End of Day (EOD) Session Control The final hard exits based on time: - End of Session (EoS): At 11:30 AM, new trades are disabled (TradingDay := false). Open positions are kept. - End of Day (EoD): At 1:30 PM, all remaining open positions are closed (strategy.close_all). 🤝 Development & Disclaimer This script and description were created with assistance from Gemini and GitHub Copilot. My focus is on helping fellow real estate investors and day traders develop mechanically sound systems. Disclaimer: This is for educational purposes only and does not constitute financial advice. Always abide by the Realtor Code and manage your own risk.
Strategia Pine Script®
di SauceSlinger
1
Trend Entry_0 [TS_Indie]Trend Entry_0 — Mechanism Overview The core structure of this strategy is based on a price action reversal pattern, as detailed below: In the case of a Bullish Trend Reversal: The price initially moves in a bearish direction. When candle A forms a low lower than the previous low, the high of candle A becomes a key reference point.
If the next candle closes above the high of candle A , it confirms a Bullish Trend Reversal. * Upon a Bullish signal, a Long position is opened at the opening price of the next candle (candle B). * When a subsequent Bearish signal occurs, the Long position is closed at the opening price of the next candle (candle C). In the case of a Bearish Trend Reversal: The price initially moves in a bullish direction. When candle A forms a high higher than the previous high, the low of candle A becomes a key reference point.
If the next candle closes below the low of candle A , it confirms a Bearish Trend Reversal. * Upon a Bearish signal, a Short position is opened at the opening price of the next candle (candle B). * When a subsequent Bullish signal occurs, the Short position is closed at the opening price of the next candle (candle C). Options * The start and end dates of the backtest can be customized. * The swing lines of the trend can be displayed as an optional visual aid. * The user can choose whether to open only Long or Short positions. Backtest Results and Observations Based on the backtesting results of this strategy across various assets and timeframes, it has been observed that this approach works best on trending assets such as Gold, BTC, and stocks.
It also performs well on higher timeframes, starting from the Daily timeframe and above, especially when taking Long positions only. 
 However, when applied to currency pairs such as EUR/USD, the results tend to be less impressive. I encourage everyone to try backtesting and further developing this strategy — adding new conditions or filters may potentially lead to improved performance. Disclaimer This script is intended solely for backtesting purposes, based on a particular price action pattern.
It does not constitute financial or investment advice.
Backtest results do not guarantee future performance.
Strategia Pine Script®
di Truth_Strategy_Indie
2
AnkeAlgo A68 strategy™ || AnkeAlgo®[16.6]## ✅ Multi-Timeframe Trend Strategy Based on MFI and Momentum Factors ### 📌 Overview This strategy combines **Money Flow Index (MFI)** and **Momentum** to identify trend continuation and momentum reversal opportunities in the crypto market. It focuses on volume-weighted capital flow and price strength, generating trend-biased signals suitable for swing and intraday traders. --- ### 📊 Technical Indicators Used | Indicator | Purpose | |-----------|---------| | **MFI (Money Flow Index)** | Detects capital inflow/outflow and filters range-bound markets | | **Momentum Indicator** | Measures price acceleration and confirms breakout strength | | **Optional: ATR / EMA Filters** | Can be added for volatility stop or trend validation | --- ### ⚙️ Core Logic - **Trend Confirmation**: MFI exceeds threshold and aligns with price direction - **Momentum Entry Trigger**: Trades are executed only when momentum crosses a signal level - **Noise Filter**: Avoids entries when MFI divergence or momentum weakness is detected - **Position Management**: Supports ATR-based or percentage-based stop-loss systems --- ### 🪙 Market and Asset ✅ Designed for crypto derivatives **Recommended symbol:** `ETHUSDT.P` (Perpetual Futures) --- ### ⏱️ Recommended Timeframes - 30-minute - 45-minute - 1-hour > The **45m timeframe** shows the most stable performance in forward testing. --- ### 📈 Strategy Features - Performs best during trending and high-momentum phases - Low overfitting risk, adaptable across different volatility environments - Can be used as a signal engine for grid, martingale, or multi-asset systems - Easily extendable to BTC, SOL, BNB, and other high-liquidity assets --- ### ⚠️ Risk Disclaimer - This is **not** a mean-reversion strategy and may produce false signals in sideways markets - Stop-loss management and position sizing are required for live deployment - Backtest results do not guarantee live trading performance due to slippage and trading fees ---
Strategia Pine Script®
di AnkeAlgo
1