CryptoFlux Dynamo [JOAT]CryptoFlux Dynamo: Velocity Scalping Strategy
WHAT THIS STRATEGY IS
CryptoFlux Dynamo is an open-source Pine Script v6 strategy designed for momentum-based scalping on cryptocurrency perpetual futures. It combines multiple technical analysis methods into a unified system that adapts its behavior based on current market volatility conditions.
This script is published open-source so you can read, understand, and modify the complete logic. The description below explains everything the strategy does so that traders who cannot read Pine Script can fully understand how it works before using it.
HOW THIS STRATEGY IS ORIGINAL AND WHY THE INDICATORS ARE COMBINED
This strategy uses well-known indicators (MACD, EMA, RSI, MFI, Bollinger Bands, Keltner Channels, ATR). The originality is not in the individual indicators themselves, but in the specific way they are integrated into a regime-adaptive system. Here is the detailed justification for why these components are combined and how they work together:
The Problem Being Solved:
Standard indicator-based strategies use fixed thresholds. For example, a typical MACD strategy might enter when the histogram crosses above zero. However, in cryptocurrency markets, volatility changes dramatically throughout the day and week. A MACD crossover during a low-volatility consolidation period has very different implications than the same crossover during a high-volatility trending period. Using the same entry thresholds and stop distances in both conditions leads to either:
Too many false signals during consolidation (if thresholds are loose)
Missing valid opportunities during expansion (if thresholds are tight)
Stops that are too tight during volatility spikes (causing premature exits)
Stops that are too wide during compression (giving back profits)
The Solution Approach:
This strategy first classifies the current volatility regime using normalized ATR (ATR as a percentage of price), then dynamically adjusts ALL other parameters based on that classification. This creates a context-aware system rather than a static threshold comparison.
How Each Component Contributes to the System:
ATR-Based Regime Classification (The Foundation)
The strategy calculates ATR over 21 periods, smooths it with a 13-period EMA to reduce noise from wicks, then divides by price to get a normalized percentage. This ATR% is classified into three regimes:
- Compression (ATR% < 0.8%): Market is consolidating, breakouts are more likely but false signals are common
- Expansion (ATR% 0.8% - 1.6%): Normal trending conditions
- Velocity (ATR% > 1.6%): High volatility, larger moves but also larger adverse excursions
This regime classification then controls stop distances, profit targets, trailing stop offsets, and signal strength requirements. The regime acts as a "meta-parameter" that tunes the entire system.
EMA Ribbon (8/21/34) - Trend Structure Detection
The three EMAs establish trend direction and structure. When EMA 8 > EMA 21 > EMA 34, the trend structure is bullish. The slope of the middle EMA (21) is calculated over 8 bars and converted to degrees using arctangent. This slope measurement quantifies trend strength, not just direction.
Why these specific periods? The 8/21/34 sequence follows Fibonacci-like spacing and provides good separation on 5-minute cryptocurrency charts. The fast EMA (8) responds to immediate price action, the mid EMA (21) represents the short-term trend, and the slow EMA (34) acts as a trend filter.
The EMA ribbon works with the regime classification: during compression regimes, the strategy requires stronger ribbon alignment before entry because false breakouts are more common.
MACD (8/21/5) - Momentum Measurement
The MACD uses faster parameters (8/21/5) than the standard (12/26/9) because cryptocurrency markets move faster than traditional markets. The histogram is smoothed with a 5-period EMA to reduce noise.
The key innovation is the adaptive histogram baseline. Instead of using a fixed threshold, the strategy calculates a rolling baseline from the smoothed absolute histogram value, then multiplies by a sensitivity factor (1.15). This means the threshold for "significant momentum" automatically adjusts based on recent momentum levels.
The MACD works with the regime classification: during velocity regimes, the histogram baseline is effectively higher because recent momentum has been stronger, preventing entries on relatively weak momentum.
RSI (21 period) and MFI (21 period) - Independent Momentum Confirmation
RSI measures momentum using price changes only. MFI (Money Flow Index) measures momentum using price AND volume. By requiring both to confirm, the strategy filters out price moves that lack volume support.
The 21-period length is longer than typical (14) to reduce noise on 5-minute charts. The trigger threshold (55 for longs, 45 for shorts) is slightly offset from 50 to require momentum in the trade direction, not just neutral readings.
These indicators work together: a signal requires RSI > 55 AND MFI > 55 for longs. This dual confirmation reduces false signals from price manipulation or low-volume moves.
Bollinger Bands (1.5 mult) and Keltner Channels (1.8 mult) - Squeeze Detection
When Bollinger Bands contract inside Keltner Channels, volatility is compressing and a breakout is likely. This is the "squeeze" condition. When the bands expand back outside the channels, the squeeze "releases."
The strategy uses a 1.5 multiplier for Bollinger Bands (tighter than standard 2.0) and 1.8 for Keltner Channels. These values were chosen to identify meaningful squeezes on 5-minute cryptocurrency charts without triggering too frequently.
The squeeze detection works with the regime classification: squeeze releases during compression regimes receive additional signal strength points because breakouts from consolidation are more significant.
Volume Impulse Detection - Institutional Participation Filter
The strategy calculates a volume baseline (34-period SMA) and standard deviation. A "volume impulse" is detected when current volume exceeds the baseline by 1.15x OR when the volume z-score exceeds 0.5.
This filter ensures entries occur when there is meaningful market participation, not during low-volume periods where price moves are less reliable.
Volume impulse is required for all entries and adds points to the composite signal strength score.
Cycle Oscillator - Trend Alignment Filter
The strategy calculates a 55-period EMA as a cycle basis, then measures price deviation from this basis as a percentage. When price is more than 0.15% above the cycle basis, the cycle is bullish. When more than 0.15% below, the cycle is bearish.
This filter prevents counter-trend entries. Long signals require bullish cycle alignment; short signals require bearish cycle alignment.
BTC Dominance Filter (Optional) - Market Regime Filter
The strategy can optionally use BTC.D (Bitcoin Dominance) as a market regime filter. When BTC dominance is rising (slope > 0.12), the market is in "risk-off" mode and long entries on altcoins are filtered. When dominance is falling (slope < -0.12), short entries are filtered.
This filter is optional because the BTC.D data feed may lag during low-liquidity periods.
How The Components Work Together (The Mashup Justification):
The strategy uses a composite scoring system where each signal pathway contributes points:
Trend Break pathway (30 points): Requires EMA ribbon alignment + positive slope + price breaks above recent structure high
Momentum Surge pathway (30 points): Requires MACD histogram > adaptive baseline + MACD line > signal + RSI > 55 + MFI > 55 + volume impulse
Squeeze Release pathway (25 points): Requires BB inside KC (squeeze) then release + momentum bias + histogram confirmation
Micro Pullback pathway (15 points): Requires shallow retracement to fast EMA within established trend + histogram confirmation + volume impulse
Additional modifiers:
+5 points if volume impulse is present, -5 if absent
+5 points in velocity regime, -2 in compression regime
+5 points if cycle is aligned, -5 if counter-trend
A trade only executes when the composite score reaches the minimum threshold (default 55) AND all filters agree (session, cycle bias, BTC dominance if enabled).
This scoring system is the core innovation: instead of requiring ALL conditions to be true (which would generate very few signals) or ANY condition to be true (which would generate too many false signals), the strategy requires ENOUGH conditions to be true, with different conditions contributing different weights based on their reliability.
HOW THE STRATEGY CALCULATES ENTRIES AND EXITS
Entry Logic:
1. Calculate current volatility regime from ATR%
2. Calculate all indicator values (MACD, EMA, RSI, MFI, squeeze, volume)
3. Evaluate each signal pathway and sum points
4. Check all filters (session, cycle, dominance, kill switch)
5. If composite score >= 55 AND all filters pass, generate entry signal
6. Calculate position size based on risk per trade and regime-adjusted stop distance
7. Execute entry with regime name as comment
Position Sizing Formula:
RiskCapital = Equity * (0.65 / 100)
StopDistance = ATR * StopMultiplier(regime)
RawQuantity = RiskCapital / StopDistance
MaxQuantity = Equity * (12 / 100) / Price
Quantity = min(RawQuantity, MaxQuantity)
Quantity = round(Quantity / 0.001) * 0.001
This ensures each trade risks approximately 0.65% of equity regardless of volatility, while capping total exposure at 12% of equity.
Stop Loss Calculation:
Stop distance is ATR multiplied by a regime-specific multiplier:
Compression regime: 1.05x ATR (tighter stops because moves are smaller)
Expansion regime: 1.55x ATR (standard stops)
Velocity regime: 2.1x ATR (wider stops to avoid premature exits during volatility)
Take Profit Calculation:
Target distance is ATR multiplied by regime-specific multiplier and base risk/reward:
Compression regime: 1.6x ATR * 1.8 base R:R * 0.9 regime bonus = approximately 2.6x ATR
Expansion regime: 2.05x ATR * 1.8 base R:R * 1.0 regime bonus = approximately 3.7x ATR
Velocity regime: 2.8x ATR * 1.8 base R:R * 1.15 regime bonus = approximately 5.8x ATR
Trailing Stop Logic:
When adaptive trailing is enabled, the strategy calculates a trailing offset based on ATR and regime:
Compression regime: 1.1x base offset (looser trailing to avoid noise)
Expansion regime: 1.0x base offset (standard)
Velocity regime: 0.8x base offset (tighter trailing to lock in profits during fast moves)
The trailing stop only activates when it would be tighter than the initial stop.
Momentum Fail-Safe Exits:
The strategy closes positions early if momentum reverses:
Long positions close if MACD histogram turns negative OR EMA ribbon structure breaks (fast EMA crosses below mid EMA)
Short positions close if MACD histogram turns positive OR EMA ribbon structure breaks
This prevents holding through momentum reversals even if stop loss hasn't been hit.
Kill Switch:
If maximum drawdown exceeds 6.5%, the strategy disables new entries until manually reset. This prevents continued trading during adverse conditions.
HOW TO USE THIS STRATEGY
Step 1: Apply to Chart
Use a 5-minute chart of a high-liquidity cryptocurrency perpetual (BTC/USDT, ETH/USDT recommended)
Ensure at least 200 bars of history are loaded for indicator stabilization
Use standard candlestick charts only (not Heikin Ashi, Renko, or other non-standard types)
Step 2: Understand the Visual Elements
EMA Ribbon: Three lines (8/21/34 periods) showing trend structure. Bullish when stacked upward, bearish when stacked downward.
Background Color: Shows current volatility regime
- Indigo/dark blue = Compression (low volatility)
- Purple = Expansion (normal volatility)
- Magenta/pink = Velocity (high volatility)
Bar Colors: Reflect signal strength divergence. Brighter colors indicate stronger directional bias.
Triangle Markers: Entry signals. Up triangles below bars = long entry. Down triangles above bars = short entry.
Dashboard (top-right): Real-time display of regime, ATR%, signal strengths, position status, stops, targets, and risk metrics.
Step 3: Interpret the Dashboard
Regime: Current volatility classification (Compression/Expansion/Velocity)
ATR%: Normalized volatility as percentage of price
Long/Short Strength: Current composite signal scores (0-100)
Cycle Osc: Price deviation from 55-period EMA as percentage
Dominance: BTC.D slope and filter status
Position: Current position direction or "Flat"
Stop/Target: Current stop loss and take profit levels
Kill Switch: Status of drawdown protection
Volume Z: Current volume z-score
Impulse: Whether volume impulse condition is met
Step 4: Adjust Parameters for Your Needs
For more conservative trading: Increase "Minimum Composite Signal Strength" to 65 or higher
For more aggressive trading: Decrease to 50 (but expect more false signals)
For higher timeframes (15m+): Increase "Structure Break Window" to 12-15, increase "RSI Momentum Trigger" to 58
For lower liquidity pairs: Increase "Volume Impulse Multiplier" to 1.3, increase slippage in strategy properties
To disable short selling: Uncheck "Enable Short Structure"
To disable BTC dominance filter: Uncheck "BTC Dominance Confirmation"
STRATEGY PROPERTIES (BACKTEST SETTINGS)
These are the exact settings used in the strategy's Properties dialog box. You must use these same settings when evaluating the backtest results shown in the publication:
Initial Capital: $100,000
Justification: This amount is higher than typical retail accounts. I chose this value to demonstrate percentage-based returns that scale proportionally. The strategy uses percentage-based position sizing (0.65% risk per trade), so a $10,000 account would see the same percentage returns with 10x smaller position sizes. The absolute dollar amounts in the backtest should be interpreted as percentages of capital.
Commission: 0.04% (commission_value = 0.04)
Justification: This reflects typical perpetual futures exchange fees. Major exchanges charge between 0.02% (maker) and 0.075% (taker). The 0.04% value is a reasonable middle estimate. If your exchange charges different fees, adjust this value accordingly. Higher fees will reduce net profitability.
Slippage: 1 tick
Justification: This is conservative for liquid pairs like BTC/USDT on major exchanges during normal conditions. For less liquid altcoins or during high volatility, actual slippage may be higher. If you trade less liquid pairs, increase this value to 2-3 ticks for more realistic results.
Pyramiding: 1
Justification: No position stacking. The strategy holds only one position at a time. This simplifies risk management and prevents overexposure.
calc_on_every_tick: true
Justification: The strategy evaluates on every price update, not just bar close. This is necessary for scalping timeframes where waiting for bar close would miss opportunities. Note that this setting means backtest results may differ slightly from bar-close-only evaluation.
calc_on_order_fills: true
Justification: The strategy recalculates immediately after order fills for faster response to position changes.
RISK PER TRADE JUSTIFICATION
The default risk per trade is 0.65% of equity. This is well within the TradingView guideline that "risking more than 5-10% on a trade is not typically considered viable."
With the 12% maximum exposure cap, even if the strategy takes multiple consecutive losses, the total risk remains manageable. The kill switch at 6.5% drawdown provides additional protection by halting new entries during adverse conditions.
The position sizing formula ensures that stop distance (which varies by regime) is accounted for, so actual risk per trade remains approximately 0.65% regardless of volatility conditions.
SAMPLE SIZE CONSIDERATIONS
For statistically meaningful backtest results, you should select a dataset that generates at least 100 trades. On 5-minute BTC/USDT charts, this typically requires:
2-3 months of data during normal market conditions
1-2 months during high-volatility periods
3-4 months during low-volatility consolidation periods
The strategy's selectivity (requiring 55+ composite score plus all filters) means it generates fewer signals than less filtered approaches. If your backtest shows fewer than 100 trades, extend the date range or reduce the minimum signal strength threshold.
Fewer than 100 trades produces statistically unreliable results. Win rate, profit factor, and other metrics can vary significantly with small sample sizes.
STRATEGY DESIGN COMPROMISES AND LIMITATIONS
Every strategy involves trade-offs. Here are the compromises made in this design and the limitations you should understand:
Selectivity vs. Opportunity Trade-off
The 55-point minimum threshold filters many potential trades. This reduces false signals but also misses valid setups that don't meet all criteria. Lowering the threshold increases trade frequency but decreases win rate. There is no "correct" threshold; it depends on your preference for fewer higher-quality signals vs. more signals with lower individual quality.
Regime Classification Lag
The ATR-based regime detection uses historical data (21 periods + 13-period smoothing). It cannot predict sudden volatility spikes. During flash crashes or black swan events, the strategy may be classified in the wrong regime for several bars before the classification updates. This is an inherent limitation of any lagging indicator.
Indicator Parameter Sensitivity
The default parameters (MACD 8/21/5, EMA 8/21/34, RSI 21, etc.) are tuned for BTC/ETH perpetuals on 5-minute charts during 2024 market conditions. Different assets, timeframes, or market regimes may require different parameters. There is no guarantee that parameters optimized on historical data will perform similarly in the future.
BTC Dominance Filter Limitations
The CRYPTOCAP:BTC.D data feed may lag during low-liquidity periods or weekends. The dominance slope calculation uses a 5-bar SMA, adding additional delay. If you notice the filter behaving unexpectedly, consider disabling it.
Backtest vs. Live Execution Differences
TradingView backtesting does not replicate actual broker execution. Key differences:
Backtests assume perfect fills at calculated prices; real execution involves order book depth, latency, and partial fills
The calc_on_every_tick setting improves backtest realism but still cannot capture sub-bar price action or order book dynamics
Commission and slippage settings are estimates; actual costs vary by exchange, time of day, and market conditions
Funding rates on perpetual futures are not modeled in backtests and can significantly impact profitability over time
Exchange-specific limitations (position limits, liquidation mechanics, order types) are not modeled
Market Condition Dependencies
This strategy is designed for trending and breakout conditions. During extended sideways consolidation with no clear direction, the strategy may generate few signals or experience whipsaws. No strategy performs well in all market conditions.
Cryptocurrency-Specific Risks
Cryptocurrency markets operate 24/7 without session boundaries. This means:
No natural "overnight" risk reduction
Volatility can spike at any time
Liquidity varies significantly by time of day
Exchange outages or issues can occur at any time
WHAT THIS STRATEGY DOES NOT DO
To be straightforward about limitations:
This strategy does not guarantee profits. Past backtest performance does not indicate future results.
This strategy does not predict the future. It reacts to current conditions based on historical patterns.
This strategy does not account for funding rates, which can significantly impact perpetual futures profitability.
This strategy does not model exchange-specific execution issues (partial fills, requotes, outages).
This strategy does not adapt to fundamental news events or black swan scenarios.
This strategy is not optimized for all market conditions. It may underperform during extended consolidation.
IMPORTANT RISK WARNINGS
Past performance does not guarantee future results. The backtest results shown reflect specific historical market conditions and parameter settings. Markets change constantly, and strategies that performed well historically may underperform or lose money in the future. A single backtest run does not constitute proof of future profitability.
Trading involves substantial risk of loss. Cryptocurrency derivatives are highly volatile instruments. You can lose your entire investment. Only trade with capital you can afford to lose completely.
This is not financial advice. This strategy is provided for educational and informational purposes only. It does not constitute investment advice, trading recommendations, or any form of financial guidance. The author is not a licensed financial advisor.
You are responsible for your own decisions. Before using this strategy with real capital:
Thoroughly understand the code and logic by reading the open-source implementation
Forward test with paper trading or very small positions for an extended period
Verify that commission, slippage, and execution assumptions match your actual trading environment
Understand that live results will differ from backtest results
Consider consulting with a qualified financial advisor
No guarantees or warranties. This strategy is provided "as is" without any guarantees of profitability, accuracy, or suitability for any purpose. The author is not responsible for any losses incurred from using this strategy.
OPEN-SOURCE CODE STRUCTURE
The strategy code is organized into these sections for readability:
Configuration Architecture: Input parameters organized into logical groups (Core Controls, Optimization Constants, Regime Intelligence, Signal Pathways, Risk Architecture, Visualization)
Helper Functions: calcQty() for position sizing, clamp01() and normalize() for value normalization, calcMFI() for Money Flow Index calculation
Core Indicator Engine: EMA ribbon, ATR and regime classification, MACD with adaptive baseline, RSI, MFI, volume analytics, cycle oscillator, BTC dominance filter, squeeze detection
Signal Pathway Logic: Trend break, momentum surge, squeeze release, micro pullback pathways with composite scoring
Entry/Exit Orchestration: Signal filtering, position sizing, entry execution, stop/target calculation, trailing stop logic, momentum fail-safe exits
Visualization Layer: EMA plots, regime background, bar coloring, signal labels, dashboard table
You can read and modify any part of the code. Understanding the logic before deployment is strongly recommended.
- Made with passion by officialjackofalltrades
Indicators and strategies
LR Candles V2.1IMPORTANT: Use this strategy only with Heikin Ashi candles; otherwise, the results will be negative.
The use of this strategy is solely and exclusively under the responsibility of the operator.
To perform testing correctly and as close to market reality as possible, we suggest setting the strategy preferences as follows:
Slippage = 3
Using bar magnifico = Enabled
Commission = Completed
Detail: It is important to include at least 1,000 trades in the test. This provides a certain robustness in the historical analysis of a strategy. Values lower than this may alter the expected results when trading in real life.
Tip:
Play around with different time frames and calibrations on the strategic indicator. Examples include unchecking Ling-Reg, unchecking EMA, or using both in combination. Look for the best probability and results for a specific asset.
The strategy usually performs well on time frames longer than 1 hour; this is what has been observed.
Elite MTF EMA Reclaim StrategyThis script is a 6-minute execution MTF EMA “retest → reclaim” strategy. It looks for trend-aligned pullbacks into fast EMAs, then enters when price reclaims and (optionally) retests the reclaim level—while filtering out chop (low trend strength/volatility or recent EMA20/50 crosses) and enforcing higher-timeframe alignment (Daily + 1H, or whichever you select).
How to use
Run it on a 6-minute chart (that’s what the presets are tuned for).
Pick your Market (Forex / XAUUSD / Crypto / Indices) and a Preset:
Elite = strictest, cleanest (fewer signals)
Balanced = middle ground
Aggressive = most signals, loosest filters
Set HTF Alignment Mode:
D + H1 (recommended) for highest quality
Off if you want more trades / LTF-only testing
Leave Kill Chop = ON (recommended). If you’re not getting trades, this is usually the blocker.
Choose entry behavior:
If Require Retest = true, entries happen on the retest after reclaim (cleaner, later).
If Require Retest = false, entries trigger on reclaim using Reclaim Timing Default:
“Preset” uses the strategy’s recommended default per market/preset
or force Reclaim close / Next bar confirmation
For backtesting, keep Mode = Strategy (Backtest). For alerts/visual-only, set Mode = Indicator (Signals Only).
Use Show Signals (All Modes) to toggle triangles on/off without affecting trades.
Tip: If TradingView says “not enough data,” switch symbol history to “All,” reduce HTF alignment (try H1 only), or backtest a more recent date range.
Prop ES Bollinger Bands Strat during Single/Dual Trading SessionBollinger Band strategy for ES futures optimized for prop firm rules.
Choose long-only, short-only, or both directions.
Customizable BB length and multiplier.
Enter trades during one or two configurable sessions specified in New York time.
Fixed TP/SL in ticks with forced close by 4:59 PM NY time.
CK INDEX Strategy Open-source code, Free, No Cost.Aqui está a tradução fiel e técnica para o inglês, ideal para a descrição do seu script no TradingView:
### 1. Requirements (The 3 Principles)
1. **Study** the code.
2. **Modify** the code.
3. **Distribute** copies or derivative versions (respecting the original credits).
Description: Direction and Strength — CK Index
The **CK Index** is a composite indicator formed by the conceptual sum of two CCIs and the PVT (Price Volume Trend) with an arithmetic mean. Its function is to simultaneously validate direction and accumulated flow.
For a **buy operation**, both CCIs must be above zero, indicating bullish dominance across different time horizons, and the PVT must be above its average. For a **sell operation**, the CCIs must be below zero and the PVT below its average.
It is important to emphasize that it acts as an **entry trigger**: the candle will turn **blue** to indicate a buy, **yellow** for a sell, and **white** when there is neutrality (meaning the color will be white when there is no clear definition—these are my personal settings). In its default form, it uses **green, red, and gray**, respectively.
Good trades, and make the world a better and freer place!
ICT FVG MNQ (Fixed Stop + Multi-TP Toggles)use- 18 min timeframe.
ICT FVG - use on MNQ 18 min time frame.
it has muti TP levels.-
Prop firm compatible.
Enjoy trading
ICT FVG MNQ (Fixed Stop + Multi-TP Toggles)ICT FVG
use-18 Min timeframe
0) Stabilizer
Evaluation Mode: PriceCh... (PriceChange mode selected)
Bypass Session Filter: OFF (unchecked)
Bypass Open Delay: OFF
Bypass Cooldown: OFF
1) Entry Logic
Swing Strength (past-only): 4
FVG Min Size (ticks): 8
FVG Expire Bars: 12
2) Risk Management
Contracts (integer): 10
Hard Stop (ticks): 65
Use Trailing Stop: OFF
Trail Activation (ticks): 30
Trail Offset (ticks): 15
Use BreakEven (only with Trailing): OFF
BE Trigger (ticks): 20
BE Plus (ticks): 2
Cooldown Bars: 3
Market Open Delay (minutes): 2
2B) Multi Take Profit (No Trailing)
Use TP1/TP2/TP3 when Trailing OFF: ON (checked)
Enable TP1: ON
Enable TP2: ON
Enable TP3: OFF
TP1 Ticks: 29
TP2 Ticks: 54
TP3 Ticks: 54
TP1 %: 30
TP2 %: 60
TP3 %: 30
Move SL to Entry when TP2 fills: OFF (unchecked)
2C) Safety Exits
Force Exit at Session End: ON (checked)
(A “Max Bars In Trade” box is partially visible but not fully shown.)
3) Sessions
Timezone (IANA): America/New... (looks like America/New_York)
Enable Session 1: ON
S1 Start: 0 : 00
S1 End: 16 : 55
Enable Session 2: OFF
(Values shown: S2 Start 18:02, S2 End 23:55, but session 2 is disabled)
4) Visual
Show FVG Zones: ON
Show Dashboard: ON
Dashboard Position: TopRight
RSI Ladder TP Strategy v1.0 Overview
This strategy is an RSI-based reversal entry system with a ladder-style take-profit mechanism.
It supports Long-only, Short-only, or Both directions and provides optional Average Entry Price, Stop Loss, and Take Profit reference lines on the chart.
Entry Rules
Long Entry: RSI crosses above the Oversold level (default: 20).
Short Entry: RSI crosses below the Overbought level (default: 80).
Optional: If enabled, the script will close the current position when an opposite signal appears before opening a new one.
Exit Rules (Ladder Take Profit)
Take profit is placed as a ladder using tpLevels and tpStepPct.
Example (default tpStepPct = 1%, tpLevels = 10):
TP1 at +1%, TP2 at +2%, … TP10 at +10% (relative to current average entry price).
Each TP level closes tpClosePct of the remaining position, meaning it scales out geometrically:
If tpClosePct = 50% → remaining position becomes 50%, then 25%, then 12.5%, etc.
Stop Loss
Optional stop loss is placed at slPct (%) away from the average entry price:
Long: avg * (1 - slPct%)
Short: avg * (1 + slPct%)
Visual Lines
Average Entry Price Line: current strategy.position_avg_price
Stop Loss Line: based on slPct
Next TP Line: shows the estimated next TP level based on current profit%
All TP Lines: optional (can clutter the chart)
==============================================================
Recommended Use
This strategy is best used on markets with strong mean-reversion behavior.
For exchanges/bots that do not support hedge mode in a single strategy, run two separate instances:
One set to Long Only
One set to Short Only
TradingView Alert Adapter for AlgoWayTRALADAL is a universal TradingView alert adapter designed for traders who work with indicators and want to test and automate indicator-based signals in a structured way.
It allows users to convert indicator outputs into a TradingView strategy and forward the same logic through alerts for multi-platform execution via AlgoWay.
This script can be used as TradingView indicator automation, enabling traders to build a TradingView strategy from indicators and route TradingView alerts through an AlgoWay connector TradingView workflow for multi-platform execution.
Why this adapter is needed
Most TradingView indicators are not available as strategies.
Traders often receive visual signals or alerts but have no access to objective statistics such as win rate, drawdown, or profit factor.
This adapter solves that problem by providing a generic framework that transforms indicator signals into a backtestable strategy — without modifying indicator code and without requiring Pine Script knowledge.
Input source–based design (including closed indicators)
All conditions in TRALADAL are built using input sources, which means you can connect:
Event-based signals (1 / non-zero values, arrows, shapes)
Indicator lines and values (EMA, VWAP, RSI, MACD, etc.)
Outputs from invite-only or closed-source indicators
If an indicator produces a visible signal or alert-compatible output, it can be evaluated and tested using this adapter, even when the source code is locked.
Three-level signal logic
The strategy uses a three-layer condition model commonly applied in discretionary and systematic trading:
Signal — primary entry trigger
Confirmation — directional validation
Filter — additional noise reduction
Each level can be enabled independently and combined using AND / OR logic, allowing traders to test multi-indicator systems without writing complex scripts.
Risk management and alert execution
The adapter supports practical risk parameters:
Stop Loss (pips)
Take Profit (pips)
Trailing Stop (pips)
Two execution modes are available:
Strategy Mode — risk rules are applied inside the TradingView Strategy Tester
Alert Mode — risk parameters are embedded into structured TradingView alerts and handled by AlgoWay during execution
Position sizing follows TradingView conventions (percent of equity, cash, or contracts) to keep strategy results and alerts aligned.
Typical use cases
This TradingView alert adapter is intended for:
Indicator-based trading systems
Backtesting signals from closed or invite-only scripts
Comparing multiple indicators within a single strategy
Sending TradingView alerts to external trading platforms via AlgoWay
The adapter does not generate signals or trading recommendations.
Its purpose is to provide a transparent and testable workflow from indicator signals to TradingView alerts and automated execution.
A-Share Broad-Based ETF Dual-Core Timing System1. Strategy Overview
The "A-Share Broad-Based ETF Dual-Core Timing System" is a quantitative trading strategy tailored for the Chinese A-share market (specifically for broad-based ETFs like CSI 300, CSI 500, STAR 50). Recognizing the market's characteristic of "short bulls, long bears, and sharp bottoms," this strategy employs a "Left-Side Latency + Right-Side Full Position" dual-core driver. It aims to safely bottom-fish during the late stages of a bear market and maximize profits during the main ascending waves of a bull market.
2. Core Logic
A. Left-Side Latency (Rebound/Bottom Fishing)
Capital Allocation: Defaults to 50% position.
Philosophy: "Buy when others fear." Seeks opportunities in extreme panic or momentum divergence.
Entry Signals (Triggered by any of the following):
Extreme Panic: RSI Oversold (<30) + Price below Bollinger Lower Band + Bullish Candle Close (Avoid catching falling knives).
Oversold Bias: Price deviates more than 15% from the 60-day MA (Life Line), betting on mean reversion.
MACD Bullish Divergence: Price makes a new low while MACD histogram does not, accompanied by strengthening momentum.
B. Right-Side Full Position (Trend Following)
Capital Allocation: Aggressively scales up to Full Position (~99%) upon signal trigger.
Philosophy: "Follow the trend." Strike heavily once the trend is confirmed.
Entry Signals (All must be met):
Upward Trend: MACD Golden Cross + Price above 20-day MA.
Breakout Confirmation: CCI indicator breaks above 100, confirming a main ascending wave.
Volume Support: Volume MACD Golden Cross, ensuring price increase is backed by volume.
C. Smart Risk Control
Bear Market Exhaustion Exit: In a bearish trend (MA20 < MA60), the strategy does not "hold and hope." It immediately liquidates left-side positions upon signs of rebound exhaustion (breaking below MA20, touching MA60 resistance, or RSI failure).
ATR Trailing Stop: Uses Average True Range (ATR) to calculate a dynamic stop-profit line that rises with the price to lock in profits.
Hard Stop Loss: Forces a stop-loss if the left-side bottom fishing fails and losses exceed a set ATR multiple, preventing deep drawdowns.
3. Recommendations
Target Assets: High liquidity broad-based ETFs such as CSI 300 ETF (510300), CSI 500 ETF (510500), ChiNext ETF (159915), STAR 50 ETF (588000).
Timeframe: Daily Chart.
Xbirch_Turtle_ Crypto_CalcМодернизированная стратегия Черепах.
Вход/выход по каналу Дончиана, стопы по величине ATR, возможность выбора лонг/шорт/всё. Имеется пирамидинг - добавление по +0,5ATR от первого бая, не более 4х входов. Модернизированный стоп - по ATR от первого бая.
Не финансовый совет.
A modernized Turtle strategy.
Entry/exit based on the Donchian Channel, stops based on the ATR value, and the ability to choose long/short/all options. Pyramiding is available – adding +0.5 ATR from the first buy, with a maximum of four entries. The modernized stop is based on the ATR value from the first buy.
This is not financial advice.
extradestrategy.limited.editiom 2026cocok untuk btc usd tidak di perjual belikan harap tidak menggunakan sembarangan
The Engulfing Liquidity Signal with Adjustable Trailing StopEngulfing Liquidity Signal with Adjustable Trailing Stop
This strategy is designed to enter long trades based on the Engulfing Liquidity Signal combined with a Trailing Stop. The strategy uses custom volume analysis and price action to detect potential market opportunities. The Trailing Stop is adjustable, allowing traders to customize the distance at which the stop will trail the price.
Key Features:
Engulfing Liquidity Signal: The strategy enters a trade when the market shows signs of strong liquidity and price action, typically when there is a strong reversal signal (bullish engulfing) accompanied by higher volume.
Trailing Stop: A dynamic exit strategy that locks in profits by trailing the stop level behind the highest price achieved since the trade entry. This prevents the position from being closed prematurely while still protecting profits if the market reverses.
Customizable Trailing Stop: Users can adjust the trailing stop percentage via the settings. This allows for greater flexibility in how closely the stop will trail the price.
No Fixed Take Profit: The strategy uses only the trailing stop, ensuring that profits are maximized based on price action without a fixed profit target.
How the Strategy Works:
Buy Signal (LongC):
The strategy triggers a buy signal when a bullish engulfing pattern occurs, and the liquidity conditions align (i.e., the volume is increasing and price action shows signs of a potential reversal).
The strategy enters a long position when the signal conditions are met.
Trailing Stop Logic:
Once the trade is initiated, a trailing stop is applied. The stop level follows the highest price achieved since entry, trailing the price based on a user-defined percentage.
The stop level adjusts upward as the price increases, locking in profits. If the price reverses and hits the trailing stop, the trade is closed.
The trailing stop is dynamic, meaning it moves only in the direction of profit, but it will not move lower once it has been set.
Sell Signal (ShortC):
The position will also be closed if a sell signal (ShortC) is generated. This ensures that the strategy exits the trade when a potential reversal is detected in the market.
No Fixed Take Profit:
The strategy does not use a fixed take profit level. Instead, the profit is managed entirely by the trailing stop, which ensures that positions remain open as long as the market is moving in favor of the trade, allowing the position to capture the maximum possible profit.
Settings:
Trailing Stop Percentage: The user can adjust the trailing stop distance by setting a percentage value between 10% and 100%. This controls how tightly or loosely the trailing stop will follow the price.
Benefits:
Maximized Profits: By using a trailing stop, the strategy aims to capture as much profit as possible without prematurely exiting trades.
Customizable: The adjustable trailing stop allows traders to tailor the strategy to their risk tolerance and market conditions.
Simple & Effective: The strategy is straightforward, relying on price action and volume signals, making it easy to understand and implement.
Ideal Use Case:
This strategy is suitable for traders who prefer to let their profits run and manage risk with a trailing stop. It is particularly useful in trending markets where the price continues to move in one direction for an extended period. By using a trailing stop, the strategy allows you to stay in the market and capture large moves while protecting profits.
This strategy provides an excellent combination of automated trade management with a Trailing Stop and Engulfing Liquidity Signal, making it a solid choice for traders seeking to automate their trades with customizable risk management.
Gold Smart Scalper V3 - Clean ChartOverview
The Gold Smart Scalper V3 is a trend-following momentum strategy specifically optimized for XAU/USD (Gold). It focuses on catching "value pullbacks" within a strong trend, avoiding the noise of sideways markets. Unlike many scalpers that use lagging indicators for exits, this version uses fixed ATR-based targets to lock in profits during high-volatility moves common in Gold.
Core Methodology
The strategy operates on three layers of confirmation:
Macro Trend (HTF Filter): Uses a 50-period EMA to ensure trades are only taken in the direction of the higher-timeframe momentum.
The Value Zone: Instead of "chasing" green or red candles, the script waits for a pullback to the space between the 9 EMA and 21 EMA. This ensures a better risk-to-reward entry point.
The Trigger: A trade is only executed when price confirms the resumption of the trend by crossing back over the signal EMA after the pullback.
Key Features
Fixed Profit Targets: Replaced dynamic trailing stops with fixed Take Profit (TP) and Stop Loss (SL) levels based on ATR, ensuring exits aren't "hunted" by Gold's signature volatility spikes.
C lean Chart Interface : All moving average plots are hidden. The only visuals provided are the active TP/SL levels when a trade is live, keeping your workspace clutter-free.
Single-Trade Logic: The script includes a "One Trade Per Cross" gate, preventing the strategy from over-trading or "stacking" positions during choppy price action.
Settings & OptimizationATR Multipliers :
Stop Loss (SL): Default $2.0 \times ATR$. Protects against standard market noise.Take Profit (TP): Default $3.0 \times ATR$. Designed for a high Risk/Reward profile.Timeframe Recommendation: Optimized for 15m and 1H for swing scalping, or 5m for aggressive scalping.Instrument: Specifically tuned for Gold (XAU/USD), but applicable to other high-volatility pairs like GBP/JPY or NASDAQ.
Disclaimer
This script is for educational and backtesting purposes only. Past performance does not guarantee future results. Always practice proper risk management.
UT Bot + Hull MA Close-Cross Confirm (Strategy)UT Bot + Hull MA Close-Cross Confirm (Strategy)
This strategy combines the classic UT Bot ATR trailing stop with a Hull Moving Average (HMA) close-cross confirmation to reduce false signals and improve trade quality.
The system works in two stages:
UT Bot Signal Detection
A volatility-adjusted ATR trailing stop identifies potential trend shifts using a 1-period EMA crossover. This provides early buy and sell signals based on momentum and volatility.
Hull MA Close-Cross Confirmation
UT Bot signals are only confirmed once price closes across the Hull Moving Average. If a UT signal occurs on the wrong side of the Hull MA, the strategy waits until a valid close-cross occurs before triggering an entry. This confirmation step helps filter chop and late-trend reversals.
Key Features
Non-repainting logic (uses bar-close confirmation)
Futures-friendly design (fixed contracts, point-based TP/SL)
Supports Long, Short, or Both directions
Built-in Take Profit & Stop Loss
Configurable Hull MA type (HMA / EHMA / THMA)
Optional Heikin Ashi signal source
Clean Buy/Sell alerts for automation and webhook execution
Trade Logic Summary
Long Entry:
UT Bot buy signal + confirmed close above Hull MA
Short Entry:
UT Bot sell signal + confirmed close below Hull MA
Exit:
Fixed Take Profit or Stop Loss (user-defined in points)
Alerts & Automation
The strategy includes dedicated Buy Alert and Sell Alert conditions designed for webhook automation (e.g., trade logging, execution engines, or external dashboards). Alerts trigger only on confirmed bar closes, matching backtest behavior.
Intended Use
This strategy is designed for futures markets (e.g., MNQ, ES, GC) and performs best on intraday timeframes. Session filters, risk rules, and trade management can be handled externally if desired.
Disclaimer
This script is provided for educational and research purposes only and is not financial advice. Always test thoroughly and use proper risk management.
RSI Strategy with Auto Tuner (PF)# RSI Auto‑Tuner Strategy — How To Use
This document explains **how to use** the RSI Auto‑Tuner strategy. It intentionally avoids math and implementation details. Follow this as an operating guide.
---
## 1. What This Tool Is For
This strategy helps you:
* Discover **which RSI length works best** on a given ticker and timeframe
* Measure performance using **Profit Factor (PF)**
* Improve RSI performance on noisy markets by **transforming price first**
The auto‑tuner is a **research tool**, not a live trading signal generator.
---
## 2. Two Modes You Must Treat Differently
### Research Mode
Used to explore and discover parameters.
* Auto‑Tune: **ON**
* Parameters are allowed to change
* Results may look very good
* Overfitting risk is real
### Trading Mode
Used for forward testing or live trading.
* Auto‑Tune: **OFF**
* Parameters are fixed
* Behavior is stable and repeatable
* This is the only acceptable mode for live use
**Never trade live with Auto‑Tune enabled.**
---
## 3. Manual Mode (Trading Mode)
Use this after parameters are finalized.
Steps:
1. Set **Auto‑Tune = OFF**
2. Choose:
* Source (raw price or transformed price)
* RSI Length (manual, default 14)
* Oversold / Overbought levels
3. The strategy will:
* Enter long when RSI crosses up through Oversold
* Enter short when RSI crosses down through Overbought
* Flip positions on opposite signals
This mode is predictable and safe for forward testing.
---
## 4. Auto‑Tune Mode (Research Mode)
Use this to find optimal RSI lengths.
Steps:
1. Set **Auto‑Tune = ON**
2. Configure the search range:
* Minimum Length (default 5)
* Maximum Length (default 14)
* Step Size (default 1)
3. The strategy will:
* Internally simulate trades for each RSI length
* Track gross profit, gross loss, and trades
* Select the length with the highest Profit Factor
4. The best length is applied automatically
Auto‑Tune evaluates historical data only.
---
## 5. Using a Transform on Price (Critical)
RSI does **not** have to run on raw price.
You can significantly improve results by:
* Applying a **price transform** first
* Feeding the transformed series into the RSI Source input
Examples of transforms:
* Moving averages
* Low‑pass filters
* Butterworth filters
* Any smoother or denoiser
Why this works:
* Busy, wicky markets cause RSI to whipsaw
* Transforms remove micro‑noise
* RSI responds to structure instead of chaos
* Profit Factor often increases dramatically
Best practice:
* Auto‑tune on raw price
* Auto‑tune on transformed price
* Compare PF, trade count, and stability
---
## 6. Reading the Status Label
At the last bar, the on‑chart label shows:
* Whether Auto‑Tune is ON or OFF
* Whether candidates were built successfully
* Number of RSI lengths tested
* Best RSI length found
* Profit Factor and trade count
If Auto‑Tune is OFF, the label shows the manual length.
---
## 7. Recommended Workflow
1. Choose ticker and timeframe
2. Enable Auto‑Tune on **raw price**
3. Record best RSI length and PF
4. Enable Auto‑Tune on **transformed price**
5. Compare results
6. Lock parameters
7. Disable Auto‑Tune
8. Forward test
---
## 8. Warnings and Discipline
* High PF with few trades is unreliable
* Transforms can hide execution costs
* Always validate on a different period
* Auto‑Tune is a **lens**, not an edge
Treat this tool as a research microscope, not an autopilot.
Prop ES EMA Cross during Single/Dual Trading SessionEMA crossover strategy for ES futures optimized for prop firm rules.
Choose long-only, short-only, or both directions.
Customizable short and long EMA lengths.
Enter trades during one or two configurable sessions specified in New York time.
Fixed TP/SL in ticks with forced close by 4:59 PM NY time.
EMA 1 & SALMA Intersection StrategyTrading Strategy: EMA 1 & SALMA Crossover System
This strategy is a Trend-Following system that focuses on the direct interaction between the price (represented by EMA 1) and a smoothed trendline (SALMA). Instead of relying on the color changes of the indicator, it uses mechanical crossover signals to enter and exit trades.
1. Indicators Used
EMA 1 (Exponential Moving Average): Since the period is 1, it effectively represents the Current Price. It reacts instantly to every market move.
SALMA v3.0 (Smoothed Adaptive Lattice Moving Average): A double-smoothed moving average that acts as the "Base Line" or "Trend Support/Resistance."
RSI (Relative Strength Index): Used as a Momentum Filter to ensure we don't trade against the market's strength.
2. Buy (Long) Entry Rules
You enter a Long position when the following conditions are met:
The Crossover: The EMA 1 (Price) crosses ABOVE the SALMA line. This indicates that the short-term momentum is shifting higher than the average trend.
The Filter (RSI): The RSI must be above 50. This confirms that the buyers are in control and the upward move has enough strength.
3. Sell (Short) Entry Rules
You enter a Short position when the following conditions are met:
The Crossunder: The EMA 1 (Price) crosses BELOW the SALMA line. This indicates a breakdown in price action.
The Filter (RSI): The RSI must be below 50. This confirms that the sellers are dominating and the downward momentum is real.
4. Key Advantages of This System
Objectivity: You don't guess based on the color of the line; you wait for a clear physical break (cross) of the line.
Precision: By using EMA 1, you get the earliest possible entry signal compared to slower moving averages.
False Signal Protection: The RSI 50 filter prevents you from entering "weak" trades where the price crosses the line but lacks the volume or momentum to continue.
OCC Strategy Optimized (MA 5 + Delayed TSL)# OCC Strategy Optimized (MA 5 + Delayed TSL) - User Guide
## Introduction
The **OCC Strategy Optimized** is an enhanced version of the classic **Open Close Cross (OCC)** strategy. This strategy is designed for high-precision trend following, utilizing the crossover logic of Open and Close moving averages to identify market shifts. This optimized version incorporates advanced risk management, multi-timeframe analysis, and a variety of moving average types to provide a robust trading solution for modern markets.
>
> **Special Thanks:** This strategy is based on the original work of **JustUncleL**, a renowned Pine Script developer. You can find their work and profile on TradingView here: (in.tradingview.com).
---
## Key Features
### 1. Optimized Core Logic
- **MA Period (Default: 5):** The strategy is tuned with a shorter MA length to reduce lag and capture trends earlier.
- **Crossing Logic:** Signals are generated when the Moving Average of the **Close** crosses the Moving Average of the **Open**.
### 2. Multi-Timeframe (MTF) Analysis
- **Alternate Resolution:** Use a higher timeframe (Resolution Multiplier) to filter out noise. By default, it uses $3 \times$ your current chart timeframe to confirm the trend.
- **Non-Repainting:** Includes an optional delay offset to ensure signals are confirmed and do not disappear (repaint) after the bar closes.
### 3. Advanced Risk Management
This script features a hierarchical exit system to protect your capital and lock in profits:
- **Fixed Stop Loss (Initial):** Protects against sudden market reversals immediately after entry.
- **Delayed Trailing Stop Loss (TSL):**
- **Activation Delay:** The TSL only activates after the trade reaches a specific profit threshold (e.g., 1%). This prevents being stopped out too early in the trade's development.
- **Ratchet Trail:** Once activated, the stop loss "ratchets" up/down, never moving backward, ensuring you lock in profits as the trend continues.
- **Take Profit (TP):** A fixed percentage target to exit the trade at a pre-defined profit level.
### 4. Versatility
- **12 MA Types:** Choose from SMA, EMA, DEMA, TEMA, WMA, VWMA, SMMA, HullMA, LSMA, ALMA, SSMA, and TMA.
- **Trade Direction:** Toggle between Long-only, Short-only, or Both.
- **Visuals:** Optional bar coloring to visualize the trend directly on the candlesticks.
---
## User Input Guide
### Core Settings
- **Use Alternate Resolution?:** Enable this to use the MTF logic.
- **Multiplier for Alternate Resolution:** How many charts higher the "filter" timeframe should be.
- **MA Type:** Select your preferred moving average smoothing method.
- **MA Period:** The length of the Open/Close averages.
- **Delay Open/Close MA:** Use `1` or higher to force non-repainting behavior.
### Risk Management Settings
- **Use Trailing Stop Loss?:** Enables the TSL system.
- **Trailing Stop %:** The distance the stop follows behind the price (Optimized Default: 1.5%).
- **TSL Activation % (Delay):** The profit % required before the TSL starts moving. (Optimized Default: 2.0% to ensure 0.5% profit is locked immediately).
- **Initial Fixed Stop Loss %:** Your hard stop if the trade immediately goes against you.
- **Take Profit %:** Your ultimate profit target for the trade.
---
## How to Trade with This Strategy
1. **Identify the Trend:** Look for the Moving Average lines (Close vs Open) to cross.
2. **Wait for Confirmation:** If using MTF, ensure the higher timeframe also shows a trend change.
3. **Manage the Trade:** Let the TSL work. With the default **2.0% Activation** and **1.5% Trail**, the strategy will automatically lock in **0.5% profit** the moment the threshold is hit, then follow the price higher.
4. **Position Sizing:** Adjust the `Properties` tab in the script settings to match your desired capital allocation (Default is 10% of equity).
---
## Recommended Settings
1. Trialing < Activation
2. Check ranging
## Credits
Original Strategy by: **JustUncleL**
Optimized and Enhanced by: **Antigravity AI**
Butterworth LPF Flip + AutoTune (PF)Butterworth LPF Flip + AutoTune (PF)
This strategy trades price trend flips using two Butterworth low-pass filters (a FAST filter and a SLOW filter). A trade is taken when the FAST filter crosses the SLOW filter. Optionally, the script can auto-tune the filter lengths by simulating many Fast/Slow combinations and selecting the pair with the best Profit Factor (PF).
What the Script Does
- Computes two 2‑pole Butterworth low‑pass filters on price.
- Enters LONG when FAST crosses above SLOW.
- Enters SHORT when FAST crosses below SLOW.
- Optionally simulates many Fast/Slow length combinations internally.
- Chooses the Fast/Slow pair with the highest Profit Factor.
- Trades only the selected best pair.
Manual Mode (Default)
1. Leave Auto‑Tune OFF.
2. Set:
- FAST cutoff period (bars)
- SLOW cutoff period (bars)
3. The strategy will trade using only these values.
Use this mode for normal trading or live deployment.
Auto‑Tune Mode
1. Enable Auto‑Tune.
2. Define Fast and Slow ranges:
- FAST min / max / step
- SLOW min / max / step
3. The script simulates ALL Fast × Slow combinations bar‑by‑bar.
4. Each combination tracks:
- Gross Profit
- Gross Loss
- Closed trades
- Profit Factor (PF = GP / GL)
5. At the end of the chart, the best PF pair is selected and used for trading.
Interpreting the End Box
The status label at the end of the chart reports:
- Whether Auto‑Tune is enabled
- Number of candidate pairs tested
- Best FAST period
- Best SLOW period
- Profit Factor of the best pair
- Win Rate (wins ÷ closed trades)
If PF is near 1.0 or trades are very low, expand the range or length of the test.
Best Practices
- Use Auto‑Tune ONLY for research and optimization.
- After finding good parameters, disable Auto‑Tune and trade manually.
- Keep Fast < Slow (logical separation).
- Longer charts produce more reliable PF results.
- Avoid very small step sizes (performance + noise).
Known Limitations
- Pine Script runs bar‑by‑bar; tuning is approximate, not vectorized.
- Large grids increase execution time.
- Results are historical and NOT predictive.
- Not suitable for live auto‑optimization.
Summary
This script is best viewed as a *research tool first, strategy second*. Use it to discover stable Fast/Slow regimes, then lock them in for simple, repeatable trading.
ES Multi-Timeframe SMC Entry SystemOverviewThis is a comprehensive Smart Money Concepts (SMC) trading strategy for ES1! (E-mini S&P 500) futures that provides simultaneous buy and sell signals across three timeframes: Daily, Weekly, and Monthly. It incorporates your complete entry checklists, confluence scoring system, and automated risk management.Core Features1. Multi-Timeframe Signal Generation
Daily Signals (D) - For intraday/swing trades (1-3 day holds)
Weekly Signals (W) - For swing trades (3-10 day holds)
Monthly Signals (M) - For position trades (weeks to months)
All three timeframes can trigger simultaneously (pyramiding enabled)
2. Smart Money Concepts ImplementationOrder Blocks (OB)
Automatically detects bullish and bearish order blocks
Bullish OB = Down candle before strong impulse up
Bearish OB = Up candle before strong impulse down
Validates freshness (< 10 bars = higher quality)
Visual boxes displayed on chart
Fair Value Gaps (FVG)
Identifies 3-candle imbalance patterns
Bullish FVG = Gap between high and current low
Bearish FVG = Gap between low and current high
Tracks unfilled gaps as targets/entry zones
Auto-removes when filled
Premium/Discount Zones
Calculates 50-period swing range
Premium = Upper 50% (short from here)
Discount = Lower 50% (long from here)
Deep zones (<30% or >70%) for higher quality setups
Visual shading: Red = Premium, Green = Discount
Liquidity Sweeps
Sell-Side Sweep (SSL) = False break below lows → reversal up
Buy-Side Sweep (BSL) = False break above highs → reversal down
Marked with yellow labels on chart
Valid for 10 bars after occurrence
Break of Structure (BOS)
Identifies when price breaks recent swing high/low
Confirms trend continuation
Marked with small circles on chart
3. Confluence Scoring SystemEach timeframe has a 10-point scoring system based on your checklist requirements:Daily Score (10 points max)
HTF Trend Alignment (2 pts) - 4H and Daily EMAs aligned
SMC Structure (2 pts) - OB in correct zone with HTF bias
Liquidity Sweep (1 pt) - Recent SSL/BSL occurred
Volume Confirmation (1 pt) - Volume > 1.2x 20-period average
Optimal Time (1 pt) - 9:30-12 PM or 2-4 PM ET (avoids lunch)
Risk-Reward >2:1 (1 pt) - Built into exit strategy
Clean Price Action (1 pt) - BOS occurred
FVG Present (1 pt) - Near unfilled fair value gap
Minimum Required: 6/10 (adjustable)Weekly Score (10 points max)
Weekly/Monthly Alignment (2 pts) - W and M EMAs aligned
Daily/Weekly Alignment (2 pts) - D and W trends match
Premium/Discount Correct (2 pts) - Deep zone + trend alignment
Major Liquidity Event (1 pt) - SSL/BSL sweep
Order Block Present (1 pt) - Valid OB detected
Risk-Reward >3:1 (1 pt) - Built into exit
Fresh Order Block (1 pt) - OB < 10 bars old
Minimum Required: 7/10 (adjustable)Monthly Score (10 points max)
Monthly/Weekly Alignment (2 pts) - M and W trends match
Weekly OB in Monthly Zone (2 pts) - OB in deep discount/premium
Major Liquidity Sweep (2 pts) - Significant SSL/BSL
Strong Trend Alignment (2 pts) - D, W, M all aligned
Risk-Reward >4:1 (1 pt) - Built into exit
Extreme Zone (1 pt) - Price <20% or >80% of range
Minimum Required: 8/10 (adjustable)4. Entry ConditionsDaily Long Entry
✅ Daily score ≥ 6/10
✅ 4H trend bullish (price > EMAs)
✅ Price in discount zone
✅ Bullish OB OR SSL sweep OR near bullish FVG
✅ NOT during avoid times (lunch/first 5 min)Daily Short Entry
✅ Daily score ≥ 6/10
✅ 4H trend bearish
✅ Price in premium zone
✅ Bearish OB OR BSL sweep OR near bearish FVG
✅ NOT during avoid timesWeekly Long Entry
✅ Weekly score ≥ 7/10
✅ Weekly trend bullish
✅ Daily trend bullish
✅ Price in discount
✅ Bullish OB OR SSL sweepWeekly Short Entry
✅ Weekly score ≥ 7/10
✅ Weekly trend bearish
✅ Daily trend bearish
✅ Price in premium
✅ Bearish OB OR BSL sweepMonthly Long Entry
✅ Monthly score ≥ 8/10
✅ Monthly trend bullish
✅ Weekly trend bullish
✅ Price in DEEP discount (<30%)
✅ Bullish order block presentMonthly Short Entry
✅ Monthly score ≥ 8/10
✅ Monthly trend bearish
✅ Weekly trend bearish
✅ Price in DEEP premium (>70%)
✅ Bearish order block present5. Automated Risk ManagementPosition Sizing (Per Entry)
Daily: 1.0% account risk per trade
Weekly: 0.75% account risk per trade
Monthly: 0.5% account risk per trade
Formula:
Contracts = (Account Equity × Risk%) ÷ (Stop Points × $50)
Minimum = 1 contractStop Losses
Daily: 12 points ($600 per contract)
Weekly: 40 points ($2,000 per contract)
Monthly: 100 points ($5,000 per contract)
Profit Targets (Risk:Reward)
Daily: 2:1 = 24 points ($1,200 profit)
Weekly: 3:1 = 120 points ($6,000 profit)
Monthly: 4:1 = 400 points ($20,000 profit)
Example with $50,000 AccountDaily Trade:
Risk = $500 (1% of $50k)
Stop = 12 points × $50 = $600
Contracts = $500 ÷ $600 = 0.83 → 1 contract
Target = 24 points = $1,200 profit
Weekly Trade:
Risk = $375 (0.75% of $50k)
Stop = 40 points × $50 = $2,000
Contracts = $375 ÷ $2,000 = 0.18 → 1 contract
Target = 120 points = $6,000 profit
Monthly Trade:
Risk = $250 (0.5% of $50k)
Stop = 100 points × $50 = $5,000
Contracts = $250 ÷ $5,000 = 0.05 → 1 contract
Target = 400 points = $20,000 profit
6. Visual Elements on ChartKey Levels
Previous Daily High/Low - Red/Green solid lines
Previous Weekly High/Low - Red/Green circles
Previous Monthly High/Low - Red/Green crosses
Equilibrium Line - White dotted line (50% of range)
Zones
Premium Zone - Light red shading (upper 50%)
Discount Zone - Light green shading (lower 50%)
SMC Markings
Bullish Order Blocks - Green boxes with "Bull OB" label
Bearish Order Blocks - Red boxes with "Bear OB" label
Bullish FVGs - Green boxes with "FVG↑"
Bearish FVGs - Red boxes with "FVG↓"
Liquidity Sweeps - Yellow "SSL" (down) or "BSL" (up) labels
Break of Structure - Small lime/red circles
Entry Signals
Daily Long - Small lime triangle ▲ with "D" below price
Daily Short - Small red triangle ▼ with "D" above price
Weekly Long - Medium green triangle ▲ with "W" below price
Weekly Short - Medium maroon triangle ▼ with "W" above price
Monthly Long - Large aqua triangle ▲ with "M" below price
Monthly Short - Large fuchsia triangle ▼ with "M" above price
7. Information TablesConfluence Score Table (Top Right)
┌──────────┬────────┬────────┬────────┐
│ TF │ SCORE │ STATUS │ SIGNAL │
├──────────┼────────┼────────┼────────┤
│ 📊 DAILY │ 7/10 │ ✓ PASS │ 🔼 │
│ 📈 WEEKLY│ 6/10 │ ✗ WAIT │ ━ │
│ 🌙 MONTH │ 9/10 │ ✓ PASS │ 🔽 │
├──────────┴────────┴────────┴────────┤
│ P&L: $2,450 │
└─────────────────────────────────────┘
Green scores = Pass (meets minimum threshold)
Orange/Red scores = Fail (wait for better setup)
🔼 = Long signal active
🔽 = Short signal active
━ = No signal
Entry Checklist Table (Bottom Right)
┌──────────────┬───┐
│ CHECKLIST │ ✓ │
├──────────────┼───┤
│ ━ DAILY ━ │ │
│ HTF Trend │ ✓ │
│ Zone │ ✓ │
│ OB │ ✗ │
│ Liq Sweep │ ✓ │
│ Volume │ ✓ │
│ ━ WEEKLY ━ │ │
│ W/M Align │ ✓ │
│ Deep Zone │ ✗ │
│ ━ MONTHLY ━ │ │
│ M/W/D Align │ ✓ │
│ Zone: Discount│ │
└──────────────┴───┘
Green ✓ = Condition met
Red ✗ = Condition not met
Real-time updates as market conditions change
8. Alert SystemIndividual Alerts:
"Daily Long" - Triggers when daily long setup appears
"Daily Short" - Triggers when daily short setup appears
"Weekly Long" - Triggers when weekly long setup appears
"Weekly Short" - Triggers when weekly short setup appears
"Monthly Long" - Triggers when monthly long setup appears
"Monthly Short" - Triggers when monthly short setup appears
Combined Alerts:
"Any Long Signal" - Catches any bullish opportunity (D/W/M)
"Any Short Signal" - Catches any bearish opportunity (D/W/M)
Alert Messages Include:
🔼/🔽 Direction indicator
Timeframe (DAILY/WEEKLY/MONTHLY)
Current confluence score
Liquidity Maxing [JOAT]Liquidity Maxing - Institutional Liquidity Matrix
Introduction
Liquidity Maxing is an open-source strategy for TradingView built around institutional market structure concepts. It identifies structural shifts, evaluates trades through multi-factor confluence, and implements layered risk controls.
The strategy is designed for swing trading on 4-hour timeframes, focusing on how institutional order flow manifests in price action through structure breaks, inducements, and liquidity sweeps.
Core Functionality
Liquidity Maxing performs three primary functions:
Tracks market structure to identify when control shifts between buyers and sellers
Scores potential trades using an eight-factor confluence system
Manages position sizing and risk exposure dynamically based on volatility and user-defined limits
The goal is selective trading when multiple conditions align, rather than frequent entries.
Market Structure Engine
The structure engine tracks three key events:
Break of Structure (BOS): Price pushes beyond a prior pivot in the direction of trend
Change of Character (CHoCH): Control flips from bullish to bearish or vice versa
Inducement Sweeps (IDM): Market briefly runs stops against trend before moving in the real direction
The structure module continuously updates strong highs and lows, labeling structural shifts visually. IDM markers are optional and disabled by default to maintain chart clarity.
The trade engine requires valid structure alignment before considering entries. No structure, no trade.
Eight-Factor Confluence System
Instead of relying on a single indicator, Liquidity Maxing uses an eight-factor scoring system:
Structure alignment with current trend
RSI within healthy bands (different ranges for up and down trends)
MACD momentum agreement with direction
Volume above adaptive baseline
Price relative to main trend EMA
Session and weekend filter (configurable)
Volatility expansion/contraction via ATR shifts
Higher-timeframe EMA confirmation
Each factor contributes one point to the confluence score. The default minimum confluence threshold is 6 out of 8, but you can adjust this from 1-8 based on your preference for trade frequency versus selectivity.
Only when structure and confluence agree does the strategy proceed to risk evaluation.
Dynamic Risk Management
Risk controls are implemented in multiple layers:
ATR-based stops and targets with configurable risk-to-reward ratio (default 2:1)
Volatility-adjusted position sizing to maintain consistent risk per trade as ranges expand or compress
Daily and weekly risk budgets that halt new entries once thresholds are reached
Correlation cooldown to prevent clustered trades in the same direction
Global circuit breaker with maximum drawdown limit and emergency kill switch
If any guardrail is breached, the strategy will not open new positions. The dashboard clearly displays risk state for transparency.
Market Presets
The strategy includes configuration presets optimized for different market types:
Crypto (BTC/ETH): RSI bands 70/30, volume multiplier 1.2, enhanced ATR scaling
Forex Majors: RSI bands 75/25, volume multiplier 1.5
Indices (SPY/QQQ): RSI bands 70/30, volume multiplier 1.3
Custom: Default values for user customization
For crypto assets, the strategy automatically applies ATR volatility scaling to account for higher volatility characteristics.
Monitoring and Dashboards
The strategy includes optional monitoring layers:
Risk Operations Dashboard (top-right):
Trend state
Confluence score
ATR value
Current position size percentage
Global drawdown
Daily and weekly risk consumption
Correlation guard state
Alert mode status
Performance Console (top-left):
Net profit
Current equity
Win rate percentage
Average trade value
Sharpe-style ratio (rolling 50-bar window)
Profit factor
Open trade count
Optional risk tint on chart background provides visual indication of "safe to trade" versus "halted" state.
All visualization elements can be toggled on/off from the inputs for clean chart viewing or full telemetry during parameter tuning.
Alerts and Automation
The strategy supports alert integration with two formats:
Standard alerts: Human-readable messages for long, short, and risk-halt conditions
Webhook format: JSON-formatted payloads ready for external execution systems (optional)
Alert messages are predictable and unambiguous, suitable for manual review or automated forwarding to execution engines.
Built-in Validation Suite
The strategy includes an optional validation layer that can be enabled from inputs. It checks:
Internal consistency of structure and confluence metrics
Sanity and ordering of risk parameters
Position sizing compliance with user-defined floors and caps
This validation is optional and not required for trading, but provides transparency into system operation during development or troubleshooting.
Strategy Parameters
Market Presets:
Configuration Preset: Choose between Crypto (BTC/ETH), Forex Majors, Indices (SPY/QQQ), or Custom
Market Structure Architecture:
Pivot Length: Default 5 bars
Filter by Inducement (IDM): Default enabled
Visualize Structure: Default enabled
Structure Lookback: Default 50 bars
Risk & Capital Preservation:
Risk:Reward Ratio: Default 2.0
ATR Period: Default 14
ATR Multiplier (Stop): Default 2.0
Max Drawdown Circuit Breaker: Default 10%
Risk per Trade (% Equity): Default 1.5%
Daily Risk Limit: Default 6%
Weekly Risk Limit: Default 12%
Min Position Size (% Equity): Default 0.25%
Max Position Size (% Equity): Default 5%
Correlation Cooldown (bars): Default 3
Emergency Kill Switch: Default disabled
Signal Confluence:
RSI Length: Default 14
Trend EMA: Default 200
HTF Confirmation TF: Default Daily
Allow Weekend Trading: Default enabled
Minimum Confluence Score (0-8): Default 6
Backtesting Considerations
When backtesting this strategy, consider the following:
Commission: Default 0.05% (adjustable in strategy settings)
Initial Capital: Default $100,000 (adjustable)
Position Sizing: Uses percentage of equity (default 2% per trade)
Timeframe: Optimized for 4-hour charts, though can be tested on other timeframes
Results will vary significantly based on:
Market conditions and volatility regimes
Parameter settings, especially confluence threshold
Risk limit configuration
Symbol characteristics (crypto vs forex vs equities)
Past performance does not guarantee future results. Win rate, profit factor, and other metrics should be evaluated in context of drawdown periods, trade frequency, and market conditions.
How to Use This Strategy
This is a framework that requires understanding and parameter tuning, not a one-size-fits-all solution.
Recommended workflow:
Start on 4-hour timeframe with default parameters and appropriate market preset
Run backtests and study performance console metrics: focus on drawdown behavior, win rate, profit factor, and trade frequency
Adjust confluence threshold to match your risk appetite—higher thresholds mean fewer but more selective trades
Set realistic daily and weekly risk budgets appropriate for your account size and risk tolerance
Consider ATR multiplier adjustments based on market volatility characteristics
Only connect alerts or automation after thorough testing and parameter validation
Treat this as a risk framework with an integrated entry engine, not merely an entry signal generator. The risk controls are as important as the trade signals.
Strategy Limitations
Designed for swing trading timeframes; may not perform optimally on very short timeframes
Requires sufficient market structure to identify pivots; may struggle in choppy or low-volatility environments
Crypto markets require different parameter tuning than traditional markets
Risk limits may prevent entries during favorable setups if daily/weekly budgets are exhausted
Correlation cooldown may delay entries that would otherwise be valid
Backtesting results depend on data quality and may not reflect live trading with slippage
Design Philosophy
Many indicators tell you when price crossed a moving average or RSI left oversold. This strategy addresses questions institutional traders ask:
Who is in control of the market right now?
Is this move structurally significant or just noise?
Do I want to add more risk given what I've already done today/week?
If I'm wrong, exactly how painful can this be?
The strategy provides disciplined, repeatable answers to these questions through systematic structure analysis, confluence filtering, and multi-layer risk management.
Technical Implementation
The strategy uses Pine Script v6 with:
Custom types for structure, confluence, and risk state management
Functional programming approach for reusable calculations
State management through persistent variables
Optional visual elements that can be toggled independently
The code is open-source and can be modified to suit individual needs. All important logic is visible in the source code.
Disclaimer
This script is provided for educational and informational purposes only. It is not intended as financial, investment, trading, or any other type of advice or recommendation. Trading involves substantial risk of loss and is not suitable for all investors. Past performance, whether real or indicated by historical tests of strategies, is not indicative of future results.
No representation is being made that any account will or is likely to achieve profits or losses similar to those shown. In fact, there are frequently sharp differences between backtested results and actual results subsequently achieved by any particular trading strategy.
The user should be aware of the risks involved in trading and should trade only with risk capital. The authors and publishers of this script are not responsible for any losses or damages, including without limitation, any loss of profit, which may arise directly or indirectly from use of or reliance on this script.
This strategy uses technical analysis methods and indicators that are not guaranteed to be accurate or profitable. Market conditions change, and strategies that worked in the past may not work in the future. Users should thoroughly test any strategy in a paper trading environment before risking real capital.
Commission and slippage settings in backtests may not accurately reflect live trading conditions. Real trading results will vary based on execution quality, market liquidity, and other factors not captured in backtesting.
The user assumes full responsibility for all trading decisions made using this script. Always consult with a qualified financial advisor before making investment decisions.
Enjoy - officialjackofalltrades
