ilker %90This strategy is a short-term momentum approach based on moving averages and volume. Studies show it performs more effectively on the 1-hour and 4-hour timeframes. Take-profit and stop-loss distances are kept short, resulting in a high win rate, while the profit factor ranges between 1.4 and 2.
Medias móviles
S/R + RSI + EMA + Trend"Multi-functional All-in-One Indicator optimized for the Crypto market. The system combines 5 core components to identify precise entry and exit points:
* Trend: A zero-lag EMA algorithm integrated with Volatility Bands that dynamically changes the candle colors. This serves as the primary trend filter, helping traders ride long waves and eliminate sideways noise.
* Dynamic Support & Resistance: Automatically identifies key price reaction zones based on Pivot Points, featuring price labels and real-time distance percentages.
* Multi-Timeframe (MTF) RSI: An on-screen RSI dashboard tracking timeframes from 1-minute to 1-day, allowing for quick monitoring of market-wide overbought and oversold conditions.
* Classic EMA System: Includes 4 exponential moving averages (34, 89, 200, 633) acting as psychological levels and long-term trend bias.
* Auto-Trendlines: Automatically plots trendlines once new swing highs and lows are confirmed."
40 SMA Scaling StrategyThis trend-following strategy focuses on capturing momentum when price breaks above the 40-period Simple Moving Average (SMA) while utilizing a systematic scale-out (Take Profit) approach to lock in gains during extended runs.
Strategy Logic
Entry: Opens a Long position with 100% of current equity when the price closes above the 40 SMA. This ensures maximum capital efficiency at the start of a new perceived trend.
Scaling Take Profits: To reduce risk as the trade progresses, the strategy automatically closes 25% of the initial position for every 1% increase in price from the entry point.
Exit: The entire remaining position is closed immediately if the price closes below the 40 SMA, acting as a trailing stop that adapts to the moving average.
Key Features
Capital-Efficient: Starts with a full account allocation to maximize exposure to the initial breakout.
Systematic De-risking: By scaling out in 25% increments, the strategy banks profits early while leaving a portion of the trade active for potential "moon shots."
Trend-Following Exit: Uses a classic SMA filter to exit, aiming to stay in the trade as long as the medium-term trend remains bullish.
%-to-Tick Trailing Stop & VisualizerPercent-to-Tick Trailing Stop (strategy.exit Framework + Visualizer)
Overview
This script focuses on exit management and visualization, not entry performance. The included MA crossover entry is intentionally simple and replaceable.
Core idea (Percent → Tick conversion)
strategy.exit() trailing parameters are tick-based (trail_points, trail_offset, and loss).
This script lets you input distances in percent (%) and converts them into integer ticks using syminfo.mintick, making the same exit logic portable across most tick-based symbols/exchanges with different tick sizes.
//==What it provides==//
1. % → tick conversion for:
- Fixed stop loss (loss)
- Trailing activation distance (trail_points)
- Trailing offset distance (trail_offset)
2. On-chart visualization:
- Entry average price
- Trailing activation threshold
- Fixed stop-loss line
- Trailing stop line (with an exit-bar alignment attempt to reduce gaps)
//==How to use==//
1. Keep the included MA crossover entries, or replace them with your own entries.
2. Configure:
- Fixed Stop Loss % (loss_pct)
- Trailing Activation % (t_points_pct)
- Trailing Offset % (t_offset_pct)
3. Adjust commission/slippage defaults to match your market.
//==Important limitations (must read)==//
- calc_on_every_tick=true recalculates on realtime bars only; historical bars are evaluated differently. Backtests can differ from realtime behavior and may change after reload.
- Tick rounding: percent distances are rounded to integer ticks, so small differences can occur depending on tick size and price level.
- For more realistic intrabar backtesting, consider enabling Bar Magnifier in Strategy Properties (if available).
# Average Entry Price (Basis):
"Calculations are based on the position's average entry price (strategy.position_avg_price)."
# Pine Script v6:
"Written in the latest Pine Script v6."
요약
이 스크립트의 핵심은 “진입 전략”이 아니라 **strategy.exit()의 tick 기반 트레일링 파라미터를 % 입력으로 일반화(%→ticks 변환)**하여, 다양한 심볼/거래소의 서로 다른 tick size 환경에서도 동일한 exit 로직을 재사용할 수 있게 만든 “청산 프레임워크”입니다. 또한 calc_on_every_tick=true 환경에서 트리거/손절/트레일 라인을 실시간에 가깝게 시각화하는 데 중점을 두었습니다.
단, calc_on_every_tick은 실시간 바에서만 틱 단위 재계산이 적용되며, 히스토리 바/백테스트는 평가 방식이 달라 결과가 다를 수 있습니다.
SMAcross-mvrOverview
SMAcross-mvrNew is a flexible, non-repainting moving-average strategy designed for clarity, configurability, and reliable backtesting.
It supports multiple entry styles, optional layered exits, and full-capital position sizing, while remaining stable during chart zooming and dragging.
🚀 What’s New in v2
✅ Multiple Entry Modes
You can now choose how trades are entered:
Entry Mode A: Short SMA crosses Long SMA
Entry Mode B: Price crosses Long SMA
This allows both classic MA-crossover trading and trend-continuation pullback entries using the same strategy.
✅ Modular Exit System (Checkbox-Based)
Exit logic is now fully modular using independent checkboxes:
☑ Exit on opposite signal
☑ Exit when price closes beyond Short SMA
You may enable one, both, or neither.
If both are enabled, the strategy exits on whichever condition occurs first.
✅ Terminology Clarity
All labels, inputs, and alerts now use semantic naming:
Short SMA (formerly 13 SMA)
Long SMA (formerly 30 SMA)
This makes the strategy easier to understand and future-proof if SMA lengths are changed.
✅ Full-Capital Position Sizing
Each trade uses 100% of available equity, allowing performance to naturally compound over time during backtests.
✅ Optional Visual Enhancements
Optional cross price labels (can be toggled on/off)
Color-filled zone between Short and Long SMAs for quick trend recognition
Optional 200 SMA (off by default) for higher-timeframe context
✅ Alert-Ready (TV-Safe)
All alerts use static messages compatible with TradingView’s alert system, making the strategy suitable for:
Manual trade notifications
Webhook-based automation
Broker integrations
🔒 Design Principles
No repainting
No line continuations (TradingView-safe formatting)
Stable behavior when zooming or scrolling
Clear separation of entry logic, exit logic, and visuals
⚠️ Notes
This script is intended for educational and research purposes.
Always forward-test and apply proper risk management before live trading.
Tabla de EMA's y TimeframesGraphic and permanent representation of the trend of an action/CFD/stock/crypto, directly related to the technical analysis of its EMA's.
Nested SMA WaveThe "Nested SMA Wave" is a custom Pine Script (v5) indicator for TradingView that overlays a series of 8 Simple Moving Averages (SMAs) on the price chart. These SMAs use exponentially increasing lengths based on powers of 2, starting from a user-defined base length (default: 25). This creates lengths like 25, 50, 100, 200, 400, 800, 1600, and 3200.
Each SMA is plotted in a distinct color, forming a "wave" of nested lines that fan out from short-term (faster, more responsive) to long-term (slower, smoother). Semi-transparent colored fills (shaded zones) are added between consecutive SMAs, with customizable toggles and transparency levels, creating layered visual bands that highlight the spaces between different trend timescales.
Use Cases
Multi-Timeframe Trend Visualization: The power-of-2 nesting approximates higher timeframe trends on lower timeframes without switching charts. Shorter SMAs react quickly to price changes, while longer ones show major trends, helping identify overall market structure at a glance.
Support/Resistance Identification: Price interacting with the SMA lines or shaded zones can act as dynamic support/resistance. Crossovers between nested SMAs signal potential momentum shifts.
Trend Strength and Alignment: When SMAs are widely spaced and aligned (e.g., all sloping up), it indicates strong trends. Converging or crossing SMAs suggest consolidation or reversals. The shaded zones add depth, making expansions/contractions in volatility or trend power visually obvious.
Ribbon-Style Trading: Similar to moving average ribbons, traders can look for price pulling back to inner zones for entries in the direction of the broader "wave," or use zone breaks for signals.
Customization for Different Assets/Timeframes: Adjust the base length (e.g., smaller for crypto volatility, larger for stocks) and toggle shades to reduce clutter.
This creates a visually rich, rainbow-like overlay that's particularly useful for trend-following strategies on any chart.
MAs + Bollinger Bands by @ETERNYWORLDMAs + Bollinger Bands by @ETERNYWORLD is the core trend and volatility layer inside the Trend Mastery Pro ecosystem, engineered by EternityWorld to deliver a clean, structured, and highly customizable market bias reading directly on the chart.
What’s Inside the Indicator
5 independent Moving Averages (EMA or SMA) with individual enable/disable toggles, lengths, colors, and widths.
Bollinger Bands with professional basis options: SMA, EMA, RMA/SMMA, WMA, VWMA, plus adjustable deviation multiplier and visual band fill.
Chart overlay compatibility, making trend and volatility easy to interpret for fast decisions.
Fully configurable alerts, enabling traders to stay proactive without missing high-probability expansion triggers.
Enhanced by Trend Mastery Pro Workflow
This indicator complements the 3-step methodology of Trend Mastery Pro:
Bias → defines the dominant trend direction.
Trigger → identifies breakout or momentum expansion zones using confluence with volatility.
Management → supports consistent risk execution when combined with external strategy rules and trade plans.
Key Strengths
✔ Unified trend + volatility envelope on chart
✔ Individual component control (no clutter, no guesswork)
✔ Noise reduction in consolidation environments
✔ Adaptable to crypto, forex, indices, commodities, and equities
✔ Reliable for intraday impulse plays and structured directional setups
How to Use It
Context: Align your analysis with the broader bias before execution.
Signal: Watch for volatility expansion and trend alignment for breakout scenarios.
Execution: Apply your risk plan (position size, partials, BE/trailing) based on your trading model.
Best Practices
🛡️ Tune sensitivity according to asset volatility and timeframe horizon
🛡️ Avoid trading against dominant bias during compression phases
🛡️ Always validate through backtesting and forward testing before scaling
🛡️ Log performance and refine parameters iteratively
Who It's For
Traders who want:
A repeatable and disciplined process
A professional visual structure
Less noise, more clarity, better bias alignment
A premium indicator suite that supports real decision-making
Compatibility
Seamlessly works with any asset and timeframe on TradingView supporting chart overlay indicators. Alerts are designed to help monitoring without being glued to the screen.
Disclaimer ⚠️
This product is not financial advice and does not guarantee results. Performance varies depending on market conditions, asset behavior, user configuration, and applied risk management. Always trade responsibly and follow your own risk plan.
Bollinger Bands and SMAsThis strategy combines Bollinger Bands with Simple Moving Averages (SMAs) to identify trend direction, volatility, and high-probability entry and exit zones. It is effective for stocks, options, and crypto across multiple timeframes.
Bollinger Bands:
Bollinger Bands consist of a middle band (20-period SMA) and upper/lower bands that expand and contract based on market volatility.
• Upper Band: Indicates potential overbought conditions
• Lower Band: Indicates potential oversold conditions
• Band Squeeze: Low volatility; often precedes strong breakouts
• Band Expansion: Rising volatility; confirms momentum moves
Price reactions at the bands help identify reversals, continuations, and breakout setups.
Simple Moving Averages (SMAs):
SMAs define trend structure and dynamic support/resistance.
• SMA 20: Short-term trend and momentum
• SMA 40: Intermediate trend confirmation
• SMA 100: Medium-term trend and strong reaction level
• SMA 200: Long-term trend and major institutional bias
Trend Bias Rules
• Price above SMAs = bullish bias
• Price below SMAs = bearish bias
• SMA crossovers signal trend shifts and momentum changes
Velocity Divergence Radar [JOAT]
Velocity Divergence Radar - Momentum Physics Edition
Overview
Velocity Divergence Radar is an open-source oscillator indicator that applies physics concepts to market analysis. It calculates price velocity (rate of change), acceleration (rate of velocity change), and jerk (rate of acceleration change) to provide a multi-dimensional view of momentum. The indicator also includes divergence detection and force vector analysis.
What This Indicator Does
The indicator calculates and displays:
Velocity - Rate of price change over a configurable period, smoothed with EMA
Acceleration - Rate of velocity change, showing momentum shifts
Jerk (3rd Derivative) - Rate of acceleration change, indicating momentum stability
Force Vectors - Volume-weighted acceleration representing market force
Kinetic Energy - Calculated as 0.5 * mass (volume ratio) * velocity squared
Momentum Conservation - Tracks momentum relative to historical average
Divergence Detection - Identifies when price and velocity diverge at pivots
How It Works
Velocity is calculated as smoothed rate of change:
calculateVelocity(series float price, simple int period) =>
float roc = ta.roc(price, period)
float velocity = ta.ema(roc, period / 2)
velocity
Acceleration is the change in velocity:
calculateAcceleration(series float velocity, simple int period) =>
float accel = ta.change(velocity, period)
float smoothAccel = ta.ema(accel, period / 2)
smoothAccel
Jerk is the change in acceleration:
calculateJerk(series float acceleration, simple int period) =>
float jerk = ta.change(acceleration, period)
float smoothJerk = ta.ema(jerk, period / 2)
smoothJerk
Force is calculated using F = m * a (mass approximated by volume ratio):
calculateForceVector(series float mass, series float acceleration) =>
float force = mass * acceleration
float forceDirection = math.sign(force)
float forceMagnitude = math.abs(force)
Signal Generation
Signals are generated based on velocity behavior:
Bullish Divergence: Price makes lower low while velocity makes higher low
Bearish Divergence: Price makes higher high while velocity makes lower high
Velocity Cross: Velocity crosses above/below zero line
Extreme Velocity: Velocity exceeds 1.5x the upper/lower zone threshold
Jerk Extreme: Jerk exceeds 2x standard deviation
Force Extreme: Force magnitude exceeds 2x average
Dashboard Panel (Top-Right)
Velocity - Current velocity value
Acceleration - Current acceleration value
Momentum Strength - Combined velocity and acceleration strength
Radar Score - Composite score based on velocity and acceleration
Direction - STRONG UP/SLOWING UP/STRONG DOWN/SLOWING DOWN/FLAT
Jerk - Current jerk value
Force Vector - Current force magnitude
Kinetic Energy - Current kinetic energy value
Physics Score - Overall physics-based momentum score
Signal - Current actionable status
Visual Elements
Velocity Line - Main oscillator line with color based on direction
Velocity EMA - Smoothed velocity for trend reference
Acceleration Histogram - Bar chart showing acceleration direction
Jerk Area - Filled area showing jerk magnitude
Vector Magnitude - Line showing combined vector strength
Radar Scan - Oscillating pattern for visual effect
Zone Lines - Upper and lower threshold lines
Divergence Labels - BULL DIV / BEAR DIV markers
Extreme Markers - Triangles at velocity extremes
Input Parameters
Velocity Period (default: 14) - Period for velocity calculation
Acceleration Period (default: 7) - Period for acceleration calculation
Divergence Lookback (default: 10) - Bars to scan for divergence
Radar Sensitivity (default: 1.0) - Zone threshold multiplier
Jerk Analysis (default: true) - Enable 3rd derivative calculation
Force Vectors (default: true) - Enable force analysis
Kinetic Energy (default: true) - Enable energy calculation
Momentum Conservation (default: true) - Enable momentum tracking
Suggested Use Cases
Identify momentum direction using velocity sign and magnitude
Watch for divergences as potential reversal warnings
Use acceleration to detect momentum shifts before price confirms
Monitor jerk for momentum stability assessment
Combine force and kinetic energy for conviction analysis
Timeframe Recommendations
Works on all timeframes. Higher timeframes provide smoother readings; lower timeframes show more granular momentum changes.
Limitations
Physics analogies are conceptual and not literal market physics
Divergence detection uses pivot-based lookback and may lag
Force calculation uses volume ratio as mass proxy
Kinetic energy is a derived metric, not actual energy
Open-Source and Disclaimer
This script is published as open-source under the Mozilla Public License 2.0 for educational purposes. It does not constitute financial advice. Past performance does not guarantee future results. Always use proper risk management.
- Made with passion by officialjackofalltrades
EMA 9 vs VWMA 30 Portillo Valentin “It uses a 9‑period moving average and a volume‑weighted moving average. It gives a crossover signal, and the parameters can be adjusted.”
Liquidity Areas StrategyBeschreibung (EN + DE):
English
Liquidity Areas Strategy (HTF Fractals + MA Reversal)
This strategy marks higher-timeframe fractal levels (pivot highs/lows) as potential liquidity areas and trades a reversal after a break.
How it works
HTF fractal levels are drawn as horizontal lines until the first break (Close or Wick – selectable).
A setup is only valid if the break happens during the selected trading session (Europe/Zurich/Berlin).
After the break, the strategy waits for a moving-average reversal confirmation (cross + close).
Entry is placed at the open of the next candle (orders are not processed on close).
Risk is defined as a percentage of equity per trade, with take profit based on a fixed RR.
SL/TP lines and trade boxes can be shown for visual review.
Notes
Educational / training use only. Not financial advice.
Results depend on symbol, timeframe, spread/fees, and execution assumptions.
SessionVWAP + ORBThis TradingView Pine Script indicator combines two powerful intraday tools:
Multiple Rolling VWAPs: It plots up to four independent rolling (continuous) Volume Weighted Average Prices (VWAPs) with user-defined periods (e.g., 1-hour, 2-hour, 4-hour, daily). These are "anchored" to a customizable session start time and roll forward accurately without daily resets, providing dynamic fair-value benchmarks that react at different speeds (fastest/shortest on top).
Opening Range Breakout (ORB) Zones: It displays the high/low range (with optional background shading and lines) for major global trading sessions — Sydney, Tokyo, London, New York, and US RTH (Regular Trading Hours, starting at 9:30 ET) — over the first configurable minutes (default 30) after each session open, with history for several prior days.
The latest version adds full timezone flexibility (e.g., Chicago, New York, UTC, London, Tokyo, Sydney), automatically adjusting anchor times and session opens.
Use Case
This script is ideal for intraday and day traders (especially in stocks, futures, forex, or indices) seeking confluence between volume-based value areas and session momentum.
VWAP Component: Use the layered rolling VWAPs as dynamic support/resistance. Price above the fastest VWAPs suggests bullish bias; pullbacks to slower VWAPs offer mean-reversion entries. The multi-timeframe view helps gauge short-term vs. longer-term "fair value."
ORB Component: Trade breakouts from major session opening ranges — e.g., buy above the New York ORB high (red line) for momentum longs, or fade failures for reversals. Combine with VWAP (e.g., only take NY ORB longs if price is above session VWAP) for higher-probability filters.
Overall: Overlay on lower timeframes (1-15 min) to spot setups like ORB breakouts aligning with VWAP crosses, or use for risk management (stops beyond ORB extremes). The timezone support makes it versatile for global markets without manual adjustments.
Gold DipperDescription: The Gold Dipper is not just a simple EMA crossover; it is a comprehensive trend-following system designed to filter out market noise and capture entries during price retracements.
How the logic works together:
Trend Confirmation: The script utilizes a dual-layered filtering process. It compares the interaction between a fast-response EMA (20) and a baseline EMA (50) to establish the primary trend direction.
Volume/Momentum Filter (The "Dip" Detection): The script identifies a "Dip" by monitoring price action proximity to the baseline. A signal is only triggered when price 'kisses' the EMA 20 zone while the 50 EMA slope remains positive, ensuring we are not catching a falling knife but buying a controlled pullback.
Dynamic Risk Control: Unlike standard static SL/TP, this script calculates exit points based on recent Swing Lows/Highs within a specific look-back period, allowing the stop loss to adapt to current market volatility (ATR-like behavior).
Why this Mashup is Useful: This script solves the "Late Entry" problem common in crossover strategies. By merging trend detection with a precise pullback trigger and dynamic risk levels, it provides a complete trading plan in one tool, reducing the need for multiple cluttered indicators.
How to Use:
Best for XAUUSD on 15M.
Wait for the background/trend color to confirm an uptrend.
Execute when the "Buy" label appears at the touch of the EMA 20 line.
Institutional Adaptive MA Intelligence System (ML) V2.0The Institutional Adaptive MA Intelligence System (ML) V2.0: A Deep Dive into Algorithmic Momentum Trading
Executive Summary
The financial markets are dominated by noise. For retail and institutional traders alike, the Holy Grail has historically been the elimination of lag—the delay between price action and the indicator’s response. The Institutional Adaptive MA Intelligence System (ML) V2.0 represents a paradigm shift in technical analysis. It moves away from static, single-logic indicators (like a standard RSI or SMA) and employs a Machine Learning (ML) ensemble approach utilizing Gradient Boosting logic.
This system is not merely an indicator; it is a computational engine that runs real-time optimization loops to fit Moving Averages (MAs) to the current market fractal. By dynamically adjusting both the length of the lookback periods and the weight of eight distinct MA types, the system creates a "Composite MA" that hugs price action with near-zero lag while maintaining smoothness.
Crucial Disclaimer: This system is engineered specifically for High-Momentum Assets and Short-Term Speculation (Scalping/Day Trading). Due to its hyper-reactive nature (utilizing lengths as low as 3 bars), it is mathematically unsuited for long-term "Buy and Hold" investing strategies, where noise tolerance is required.
Part 1: The Algorithmic Architecture
The core philosophy of this script is "Ensemble Learning." In Data Science, an ensemble method uses multiple learning algorithms to obtain better predictive performance than could be obtained from any of the constituent learning algorithms alone.
1. The "Weak Learners" (The 8 MA Types)
The system utilizes eight distinct, sophisticated Moving Average calculations. These are chosen specifically for their low-lag and noise-reduction properties. Standard SMAs or EMAs are excluded as they are mathematically obsolete for high-frequency trading.
JMA (Jurik Moving Average): Famous for its "phase" and "power" parameters, JMA is designed to eliminate overshoot and undershoot, offering the best phase-delay performance in the industry.
HMA (Hull Moving Average): Utilizes weighted moving averages (WMA) of different periods to mathematically eliminate lag, resulting in a curve that is incredibly smooth and responsive.
DEMA (Double Exponential MA): Attempts to remove the lag of a standard EMA by subtracting the EMA of the EMA from the original.
TEMA (Triple Exponential MA): Similar to DEMA but with a triple smoothing layer, offering even faster reaction times to volatility spikes.
ZLEMA (Zero Lag EMA): Uses historical data to remove lag by tracking the momentum of the price over a specific window and adding it back to the current price before smoothing.
ALMA (Arnaud Legoux MA): Applies a Gaussian filter (Normal Distribution) to the window, allowing the user to offset the weight to the most recent data points (Sigma and Offset).
FRAMA (Fractal Adaptive MA): This is a non-linear MA. It calculates the "Fractal Dimension" of the price. When the market is ranging, the FRAMA slows down (filters noise). When the market trends, it speeds up.
SuperSmoother (2-Pole Ehlers): Based on John Ehlers' digital signal processing (DSP) work, this filter removes aliasing noise from price data, leaving only the "true" spectral component of the trend.
2. The Innovation: Dynamic Length Optimization
In V2.0, the script introduces a brute-force optimization layer rarely seen in Pine Script due to computational limits.
Most traders ask: "Should I use the 9 MA or the 21 MA?"
This system asks: "Why guess?"
The script pre-computes all 8 MAs at 10 different lengths simultaneously:
3, 5, 8, 10, 12, 14, 16, 20, 21, 25
The Optimization Loop:
Normalization: The script normalizes the current price return using ATR (Average True Range) to create a standardized "Target."
Error Calculation: On every bar, the script calculates the prediction error (Mean Absolute Error) for every MA at every length (80 combinations total).
Selection: It identifies which length is currently minimizing error for each specific MA type.
Adaptation: If the market speeds up, the optimal length might shift from 21 to 5 automatically. If the market becomes choppy, it might extend to 25 to smooth out the noise.
3. The "Brain": Gradient Boosting Machine (GBM) Weighting
Once the system has determined the optimal length for each MA, it must determine how much trust (Weight) to place in each MA type.
Inputs: The deviation of each MA from the price (Signals) and the recent normalized price returns.
The Learning Rate (gbmLearningRate): This determines how quickly the model adapts. A rate of 0.05 implies the model shifts its bias slowly, preserving stability.
The Process:
The script maintains an array of weights (initially 0.125 or 12.5% per MA).
It compares the composite signal against the actual price movement.
MAs that correctly predicted the move have their weights increased.
MAs that failed are penalized (weights decreased).
Result: A "Composite MA" is drawn. This is a weighted average of the 8 MAs. In a specific market condition, the Composite might be composed of 40% JMA, 30% HMA, and 0% of the others, depending on what is winning at that moment.
Part 2: Signal Generation and Confluence
The system does not rely on a single trigger. It employs a Multi-Confluence logic engine to filter false positives common in high-volatility environments.
The Confluence Score
The script calculates a "Bull Count" and "Bear Count" on every bar.
It checks the slope of all 8 optimized MAs individually.
If the JMA is rising, +1 Bull. If the HMA is falling, +1 Bear.
Score: A score of 8/8 indicates "Strong Confluence." This means every distinct mathematical calculation agrees on the direction.
Signal Modes
The user can select how the script generates entry/exit icons:
Composite Cross: Standard crossover of Price vs. the Composite MA.
Price Cross: Crossover confirmed by Slope (Price crosses up AND Slope is positive).
Slope Change (Recommended for Scalping): Signals are generated when the derivative of the MA changes. If the MA is falling, flattens, and turns up (V-Shape), a signal acts immediately, often before price crosses the MA.
Multi-Confluence: A signal is only printed if a crossover occurs AND the Confluence Score is > 6 (75% agreement among the ensemble).
Volatility Filter
The script calculates a VolatilityFactor (Current ATR / 50-period SMA of ATR).
If volatility is too low (dead market), signals are suppressed to prevent chop.
If volatility is extremely high (news event spikes), signals are filtered to prevent buying the top of a wick.
Part 3: Operational Guide for High-Momentum Trading
This system is specifically tuned for Alpha Generation in fast-moving markets. It is distinct from Beta capture (market riding).
1. Asset Selection
This script fails in low-volatility, ranging environments (e.g., EURUSD during the Asian session). It thrives on assets with high variance and directional inertia.
Crypto: Bitcoin (BTC), Ethereum (ETH), Solana (SOL), and high-beta Altcoins.
Indices: Nasdaq 100 (NQ/US100), DAX40.
Commodities: Gold (XAUUSD), Crude Oil.
Forex: GBPJPY, EURJPY (The "Guppy" pairs).
2. Timeframe Selection
The max_bars_back and lookback periods (3 to 25) dictate that this is a Short-Duration tool.
1-Minute / 5-Minute: Ideal for Scalping. The "Slope Change" signal mode works best here to catch the immediate turn of the trend.
15-Minute: Ideal for Intraday swing trading.
3. The "Slope Scalp" Strategy
The most effective way to use this script is not to wait for crosses, but to trade the Slope Color.
The Setup: Wait for the Price to pull back into the "MA Cloud" (the gray shaded area between the highest and lowest MA).
The Trigger: Watch the Composite MA line.
Gray: Neutral/Flat.
Teal: Slope has turned Positive.
Red: Slope has turned Negative.
The Entry: As soon as the line turns from Red to Gray/Teal inside the cloud, initiate a trade in the direction of the higher timeframe trend. This captures the exact moment momentum shifts back in favor of the trend.
4. Interpretation of the Tables
Info Table: Displays the current "Trend Status," "Confluence Score" (e.g., 7/8 Bull), and the "GBM Accuracy" (how well the model has predicted the last 50 bars).
GBM Weights Table: This is your "Under the Hood" view. It shows which MA is currently dominating the weightings.
Insight: If FRAMA has the highest weight, the market is fractal/choppy.
Insight: If JMA or HMA has the highest weight, the market is trending smoothly.
Part 4: Why This Is NOT for Investing
It is critical to understand the distinction between Signal Processing and Investment Analysis.
1. The Length Constraint
The maximum length calculated by this script is 25 bars. In an investment context (Daily/Weekly charts), a 25-period MA is still considered a short-term trend filter. Investors typically look at the 50, 100, or 200 SMA to determine macro bias.
The Risk: Using this script on a Weekly chart for investing will result in "whipsawing." Because the MAs are so reactive, a standard 5% correction in a Bull Market will trigger a "Sell" signal, causing the investor to exit a profitable long-term position prematurely.
2. Noise Sensitivity
The algorithms (JMA, HMA, etc.) are designed to react to immediate price physics.
Investing: Requires ignoring noise. You want to stay in Apple stock despite a bad earnings report drop, provided the yearly trend is up.
This Script: Is designed to exploit noise. It detects the earnings drop instantly and signals a short to profit from the panic, then signals a buy at the bottom.
Conclusion: An investor using this tool will over-trade, accruing massive commission fees and tax liabilities, while likely underperforming a simple "Buy and Hold" strategy due to constant entries and exits.
Part 5: Advantages of the V2.0 System
1. Zero-Lag Responsiveness
By using the JMA and GBM weighting, the Composite line frequently moves with price rather than behind it. This allows for tighter Stop Losses. In scalping, a tight stop loss is the difference between a high Risk:Reward ratio and a blown account.
2. Adaptation to Market Phase
Standard indicators fail because they are static. An RSI(14) is always 14 bars.
In a Parabolic Trend, this system shortens its lengths (to e.g., 3 or 5) to keep you in the trade until the very top.
In a Consolidation, it lengthens itself (to 20-25) and lowers the weights of reactive MAs to prevent false breakouts.
3. Psychological Confirmation
The "Confluence" logic provides objective data for trade execution. Seeing that "7 out of 8" algorithms agree on a direction gives the trader the conviction to execute the trade immediately, reducing hesitation.
4. Quantitative Edge
The "GBM Improvement" metric in the dashboard shows exactly how much better the ML-Composite is performing compared to a simple average. This allows the trader to know when the "Smart" logic is working and when the market is too random for even ML to predict (at which point the trader should sit on hands).
Conclusion
The Institutional Adaptive MA Intelligence System V2.0 is a high-performance Formula 1 car of technical indicators. It requires a skilled driver who understands high-momentum assets.
It abstracts away the complexity of choosing the "right" indicator settings by brute-forcing the math in real-time. For the scalper and intraday momentum trader, it offers a distinct edge: the ability to visualize the true, noise-filtered trajectory of price action with the lowest mathematically possible latency. However, for the long-term investor, it is a tool of distraction; its hyper-sensitivity is a liability in strategies requiring patience and duration. Use this tool to snipe entries in volatile markets, take quick profits, and exit before the trend reversal becomes obvious to the rest of the market.
EMA and Dow Theory Strategies V2 DOGE Current Optimum Value
📘 Overview
These are the current optimal values for DOGE.
They are intended for use on the 2‑hour timeframe.
This script requires complex configuration, but there is an optimal set of values somewhere.
Here, I’m sharing the settings that I personally use at the moment.
Turning Take Profit off can lead to higher profits, but it also increases risks such as a lower win rate.
With Take Profit on, you can adjust the settings by increasing the values.
I have been trading using Dow Theory for many years.
Trading with Dow Theory and EMA has been my main strategy.
Although it has been profitable, I have long struggled with its low win rate.
The issue lies in the immaturity of the exit strategy, and I’m currently experimenting to see if I can solve that.
In V2, I added three take‑profit lines, securing 30% of the profit at each level to ensure a minimum level of gain.
Additionally, when the trend weakens, half of the position is closed.
In all scenarios, the remaining position is held until the trend reverses.
The system provides precise entries, adaptive exits, and highly visual guidance that helps traders understand trend structure at a glance.
🧠 Key Features
🔹 1. Dual‑EMA Trend Logic (Symbol + External Index)
Both the chart symbol and an external index (OTHERS.D) are evaluated using fast/slow EMAs to determine correlation‑based trend bias.
🔹 2. Dow Theory Swing Detection (Real‑time)
The script identifies swing highs/lows and updates trend direction when price breaks them. This creates a structural trend model that reacts faster than EMAs alone.
🔹 3. Gradient Trend Zones (Visual Trend Strength)
When trend is up or down, the area between price and the latest swing level is filled with a multi‑step gradient. This makes trend strength and distance-to-structure visually intuitive.
🔹 4. Higher‑Timeframe Swing Trend (htfTrend)
Swing highs/lows from a higher timeframe (e.g., 4H) are plotted to show macro structure. Used only for visual context, not for filtering entries.
🔹 5. RSI‑Based Entry Protection
RSI prevents entries during extreme overbought/oversold conditions.
🔹 6. Dynamic Exit System
Includes:
Custom stop‑loss (%)
Partial take‑profit (TP1/TP2/TP3)
Automatic scale‑out when trend color weakens
“Color‑change lockout” to prevent immediate re‑entry
Real‑time PnL tracking and labels
🔹 7. Alerts for All Key Events
Entry, stop‑loss, partial exits, and trend‑change exits all generate structured JSON alerts.
🔹 8. Visual PnL Labels & Equity Tracking
PnL for the latest trade is displayed directly on the chart, including scale‑out adjustments.
⚙️ Input Parameters
Parameter Description
Fast EMA / Slow EMA EMAs used for symbol trend detection
Index Fast / Slow EMA EMAs applied to external index
StopLoss (%) Custom stop‑loss threshold
Scale‑Out % Portion to exit when trend color weakens
RSI Period / Levels Overbought/oversold filters
Swing Detection Length Bars used to detect swing highs/lows
Stats Display Position of statistics table
🧭 About htfTrend (Higher Timeframe Trend)
The higher‑timeframe swing trend is displayed visually but not used for entry logic.
Why? Strict HTF filtering reduces trade frequency and often removes profitable setups. By keeping it visual‑only, traders retain flexibility while still benefiting from macro structure awareness.
Use it as a contextual guide, not a constraint.
📘 概要
DOGEの現在の最適値です。
2時間足での使用を想定しています。
このスクリプトは複雑な設定が必要ですが、どこかに最適値が存在します。
今回は現在私が個人的に使っている設定値の公開です。
Take ProfitをOFFにするとさらなる利益が望めますが、勝率が下がるなどのリスクが上がります。
ONにした状態で数値を上げることによって調整することが可能です。
私はダウ理論を使ったトレードを長年続けてきました。
ダウ理論とEMAを使ったトレードが私の主力です。
しかし利益は出るものの、長年その勝率の低さに悩んでいました。
問題は出口戦略が未熟なためで、現在はそれらの解決ができないかと試行錯誤を続けています。
V2では3本の利益確定ラインを引き、それぞれ30%ずつ利益を確定し、最低限の利益がでるようにしました。
それ以外にはトレンドが弱まったタイミングで半分の利益確定をし、どのパターンでも残ったポジションはトレンド転換まで持ち続けます。
🧠 主な機能
🔹 1. 銘柄+外部インデックスの EMA クロス判定
対象銘柄と OTHERS.D の EMA を比較し、相関を考慮したトレンド方向を判定します。
🔹 2. ダウ理論に基づくスイング高値・安値の自動検出
スイング更新によりトレンド方向を切り替える、構造ベースのトレンド判定を採用。
🔹 3. グラデーション背景によるトレンド強度の可視化
スイングラインから現在価格までを段階的に塗り分け、 「どれだけトレンドが伸びているか」を直感的に把握できます。
🔹 4. 上位足スイングトレンド(htfTrend)の表示
4H などの上位足でのスイング高値・安値を表示し、 大局的なトレンド構造を視覚的に把握できます(ロジックには未使用)。
🔹 5. RSI による過熱・売られすぎフィルター
極端な RSI 状態でのエントリーを防止。
🔹 6. 動的イグジットシステム
カスタム損切り(%)
TP1/TP2/TP3 の段階的利確
トレンド色の弱まりによる自動スケールアウト
色変化後の再エントリー制限(waitForColorChange)
リアルタイム PnL の追跡とラベル表示
🔹 7. アラート完備(JSON 形式)
エントリー、損切り、部分利確、トレンド反転などすべてに対応。
🔹 8. 損益ラベル・統計表示
直近トレードの損益をチャート上に表示し、視覚的に把握できます。
⚙️ 設定項目
設定項目名 説明
Fast / Slow EMA 銘柄の EMA 設定
Index Fast / Slow EMA 外部インデックスの EMA 設定
損切り(%) カスタム損切りライン
部分利確割合 トレンド弱化時のスケールアウト割合
RSI 期間・水準 過熱/売られすぎフィルター
スイング検出期間 スイング高値・安値の検出に使用
統計表示位置 テーブルの表示位置
🧭 上位足トレンド(htfTrend)について
上位足スイングの更新に基づくトレンド判定を表示しますが、 エントリー条件には使用していません。
理由: 上位足を厳密にロジックへ組み込むと、トレード機会が大幅に減るためです。
本ストラテジーでは、 「大局の把握は視覚で、エントリーは柔軟に」 という設計思想を採用しています。
→ 裁量で利確判断や逆張り回避に活用できます。
Price % Distance from 52 Weeks High, and EMAs"Stop guessing how far extended the price is—measure it instantly."
As a swing trader, knowing the exact distance between the current price and your key moving averages is critical. It tells you if a stock is overextended (too far) or offering a low-risk pullback entry (near 0%).
This lightweight utility script calculates the real-time percentage distance of the closing price from three critical levels:
10 EMA (Short-term momentum)
20 EMA (Swing trend baseline)
52-Week High (Major structural resistance)
It displays this data in a single, clean Smart Label attached to the latest candle, keeping your chart clutter-free.
Key Features
📊 Instant Calculation: See exactly how far (%) the price is from the 10 EMA, 20 EMA, and 52-Week High without using a measuring tool.
🧠 Intelligent Trend Coloring: The text color changes dynamically based on the immediate trend:
🟢 Green Text: Price is ABOVE both 10 & 20 EMAs (Bullish / Buy-the-dip zone).
🔴 Red Text: Price is BELOW both 10 & 20 EMAs (Bearish / Caution).
⚪ White Text: Price is mixed/choppy (between the EMAs).
👁️ High Contrast Design: Uses a semi-transparent dark background that ensures the data is clearly visible on both Light and Dark mode charts.
How to Use for Swing Trading
Pullback Entries: In a strong uptrend (Green Text), watch for the 10 EMA or 20 EMA % value to drop near 0.0% to 0.5%. This indicates a pullback to the average—often a high-probability entry point.
Overextension Warning: If the % distance becomes unusually large (e.g., Price is +5% above the 10 EMA), the move may be overextended, signaling to tighten stops or take profit.
52-Week Breakouts: Monitor the 52W % distance. As it approaches 0.0%, the stock is challenging its yearly high, alerting you to potential breakout plays.
Settings
EMA Lengths: Fully customizable (Default: 10 & 20).
Lookback: Adjust the high lookback period (Default: 260 bars for 52 Weeks).
Position: Toggle the label to appear Above or Below the candle.
THE ELVINATORTHE ELVINATOR is my trend-following momentum indicator built on the 20 EMA, 50 EMA, and 200 EMA, designed for trading **XAUUSD during the New York session (9:30–17:00 NY time), Monday through Friday**.
**How to trade it:**
* **Trend filter:** Only take **longs above the 200 EMA** and **shorts below the 200 EMA**. This keeps trades aligned with Gold’s dominant direction.
* **Long setups:** A **20 EMA cross above the 50 EMA** signals bullish momentum. Best entries come after a pullback into the 20–50 EMA zone followed by strong continuation candles.
* **Short setups:** A **20 EMA cross below the 50 EMA** signals bearish momentum. Look for pullbacks into the EMA zone and rejection before continuation lower.
* **Timing:** Focus on NY open and high-volume moves. Avoid choppy conditions and late-session exhaustion.
* **Risk & exits:** Place stops beyond recent swings or EMA structure. Targets can be prior highs/lows or scaled with trend continuation.
THE ELVINATOR is built for **structure, patience, and disciplined execution**, allowing traders to capitalize on Gold’s volatility without chasing noise.
Simple ema and sma cross
A simple EMA and SMA cross is an indicator that uses alpha from two moving averages: SMA (simple moving average) and EMA (exponential moving average).
The point where the EMA and SMA cross is usually a good place to enter a position.
The indicator includes smoothing settings to help you find the right calibration for your trading needs.
It also marks signals with triangles for easier use and includes alerts so you never miss a cross.
ATR Bands (MA Distance)ATR Bands (MA Distance) plots volatility-based bands at a multiple of ATR away from a selected moving average.
Unlike percentage envelopes or standard deviation bands, this indicator measures distance from the moving average using ATR, representing the market’s normal “breathing range” rather than statistical probability.
Key Features
The center line is a selectable moving average (EMA, SMA, RMA/Wilder, or WMA).
Upper and lower bands are calculated as:
Moving Average ± ATR × Multiplier
Band width automatically adapts to changing market volatility.
Designed for consistent use across different markets and timeframes without parameter re-optimization.
Non-repainting: all values are calculated only from confirmed historical bars.
Intended Use
ATR Bands (MA Distance) is best used as a context and preparation tool , not as a direct entry or exit signal.
Typical use cases include:
Identifying areas where price is extended relative to its recent volatility.
Visualizing normal vs. stretched price distance from the moving average.
Supporting range-based analysis or trade preparation when combined with other indicators (e.g., oscillators).
Important Notes / How NOT to Use
This indicator does NOT generate buy or sell signals by itself .
Touching or crossing a band does not imply an automatic reversal.
In strong trending markets, price may stay outside the bands for extended periods.
ATR Bands should not be interpreted as overbought/oversold levels on their own.
This indicator does NOT repaint. Once a bar is closed, its values will not change.
For best results:
Use ATR Bands as a preparation zone, then wait for confirmation from your own entry logic.
Disable or ignore band-based mean-reversion ideas during strong trend conditions.
Concept Summary (Short)
ATR Bands (MA Distance) visualize how far price has moved from its moving average in terms of volatility, without repainting and without relying on percentage deviation or statistical assumptions.
Optional Short Description (Preview)
Volatility-based, non-repainting ATR bands plotted at a distance from a moving average.
Designed for market context and trade preparation — not standalone signals.
%R Exhaustion + VixFix with 200MA Regime%R Exhaustion + VixFix with 200MA Regime Strategy
A momentum-based trading strategy that combines regime filtering,
volatility analysis, and oversold/overbought conditions for
optimal entry and exit timing.
Key Components:
• MA 200 Regime Filter: Identifies bearish market regimes when
price stays below MA 200 for extended periods, preventing longs
during downtrends
• Percent R Exhaustion: Uses dual-timeframe Williams %R to detect
oversold reversals and overbought exhaustion zones
• Williams VixFix: Volatility-based indicator that identifies
market bottoms and filtered entry conditions during panic selling
• Matrix Oscillator: Confirms exit signals when market becomes
overbought
Entry Logic:
- Long entries trigger when: (1) Not in bearish regime, (2) %R
shows oversold or reversal, (3) VixFix filtered entry confirms
- Position pyramiding with scaling: Initial entry at configured %
of equity, subsequent entries match current position size
(doubling effect)
Exit Logic:
- Partial sells when both overbought conditions and Matrix sell
signal align
- Breakeven stop loss activates after profitable partial sells or
when entering bearish regime
- Gradual profit-taking using configurable portion percentages
Position Management:
- Configurable initial entry size and sell portions
- Pyramiding up to 5 entries with exponential position sizing
- Dynamic stop loss management for capital preservation
LevelsAutomatic levels with alerts, based on:
1) SMAs
2) Anchored Volume Profile (AVP)
3) Pivot Points Standard
Use this to set automated alerts in conjunction with manually added levels
Quality-Controlled Trend Strategy v2 (Expectancy Focused)This script focuses on quality control rather than curve-fitting.
No repainting, no intrabar tricks, no fake equity curves.
It uses confirmed-bar entries, ATR-based risk, and clean trend logic so backtests reflect what could actually be traded live.
If you publish scripts, this is the minimum structure worth sharing.
Why this script exists
TradingView’s public scripts are flooded with:
repainting indicators
no stop-loss logic
curve-fit entries that collapse live
strategies that look good only in hindsight
This script is intentionally boring but honest.
No repainting.
No intrabar tricks.
No fake equity curves
The goal is quality control, not hype.
What this strategy enforces
✔ Confirmed bars only
✔ Single source of truth for indicators
✔ Fixed risk structure
✔ No signal repainting
✔ Clean exits with unique IDs
✔ Works on any liquid market
Trading Logic (simple & auditable)
Trend filter
EMA 50 vs EMA 200
Entry
Pullback to EMA 50
RSI confirms momentum (not oversold/overbought)
Risk
ATR-based stop
Fixed R:R
One position at a time
This is the minimum bar for a strategy to be considered publish-worthy.
Why this helps TradingView quality
Most low-value scripts fail because they:
hide repainting logic
skip exits entirely
use inconsistent calculations
rely on hindsight candles
This strategy forces discipline:
every signal is confirmed
every trade has defined risk
behavior is repeatable across symbols & timeframes
If more scripts followed this baseline, TradingView’s public library would be far more usable.






















