ICT/SMC Holy GrailThe Holy Grail, with its backtesting feature to check win rates, is all you need to do when placing orders!
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Dual MTF Confirmed Trend Strategy (5m Entry / 15m MACD & RSI) v1That is a detailed Dual Multi-Timeframe (MTF) Confirmed Trend Strategy written in Pine Script for TradingView. The core idea of this strategy is to only take entry signals on a faster timeframe (5-minute) when the trend is strongly confirmed on a slower, higher timeframe (15-minute). This aims to reduce false signals and trade in the direction of the dominant trend. Here is an explanation of how the strategy works, broken down by section:
1. 5-Minute Entry Filters ๐This section calculates several indicators on the current 5-minute chart to identify potential trade setups. A position is only considered if all 5-minute conditions align.
Supertrend: A trend-following indicator based on Average True Range (ATR).
Long Condition: The closing price must be above the Supertrend line.
Short Condition: The closing price must be below the Supertrend line.
Gann Hi-Lo (GHL): A trend indicator using Simple Moving Averages (SMA) of the high and low prices. GHL Line: Switches between the SMA of the Highs and the SMA of the Lows based on price action.
Long Condition: The closing price must be above the GHL line.
Short Condition: The closing price must be below the GHL line.
Exponential Moving Averages (EMAs): It uses a 50-period EMA and a 100-period EMA to confirm the short-term trend direction.
Long Condition: The closing price must be above both the 50 EMA and the 100 EMA.
Short Condition: The closing price must be below both the 50 EMA and the 100 EMA.
2. 15-Minute MTF Confirmation Filters โณThis is the crucial step where the strategy verifies the trend on the slower, 15-minute timeframe using the request security function. This step acts as a gatekeeper to ensure the 5-minute trade aligns with the larger trend.
MACD Histogram (12, 26, 9): The difference between the MACD Line and the Signal Line.
Long Confirmation: The 15m MACD Histogram must be greater than 0 (MACD line is above the Signal line, indicating bullish momentum).
Short Confirmation: The 15m MACD Histogram must be less than 0 (MACD line is below the Signal line, indicating bearish momentum).
RSI (Relative Strength Index) (14): A momentum oscillator. The 50 level is often used to determine the general market trend.
Long Confirmation: The 15m RSI must be greater than 50 (indicating stronger bullish momentum).
Short Confirmation: The 15m RSI must be less than 50 (indicating stronger bearish momentum).
The Total 15m Confirmation is only true if both the MACD and the RSI confirmation signals align.
3. Trade Orders (Entry Logic) โ๏ธ
The strategy only executes a trade when the 5-minute entry conditions are met AND the 15-minute confirmation conditions are met.
Final Long Condition:
5m Conditions (Supertrend, GHL, EMA alignment) AND
15m Confirmation (MACD Hist > 0 AND RSI > 50)
Final Short Condition:
5m Conditions (Supertrend, GHL, EMA alignment) AND
15m Confirmation (MACD Hist < 0 AND RSI < 50)
When a trade signal is generated, the strategy:
Closes any opposite position (e.g., closes a "Short" trade if a "Long" signal appears).
Enters the new position (e.g., enters a "Long" trade).
This is designed as a reversal strategy where a new entry automatically closes the previous opposing trade.
In Summary
The strategy operates on a principle of Trend Alignment:
5-Minute Chart: Is used for Signal Timing (when exactly to enter the market).
15-Minute Chart: Is used for Trend Validation (is the overall market momentum supporting the signal?).
It's an attempt to capture short-term moves (5m signals) that are backed by strong medium-term momentum (15m confirmation), thereby aiming for higher probability trades.
This is not investment advice; it is recommended to perform optimization and backtesting for the assets intended for implementation.
Omega Correlation [OmegaTools]Omega Correlation (ฮฉ CRR) is a cross-asset analytics tool designed to quantify both the strength of the relationship between two instruments and the tendency of one to move ahead of the other. It is intended for traders who work with indices, futures, FX, commodities, equities and ETFs, and who require something more robust than a simple linear correlation line.
The indicator operates in two distinct modes, selected via the โShowโ parameter: Correlation and Anticipation. In Correlation mode, the script focuses on how tightly the current chart and the chosen second asset move together. In Anticipation mode, it shifts to a leadโlag perspective and estimates whether the second asset tends to behave as a leader or a follower relative to the symbol on the chart.
In both modes, the core inputs are the chart symbol and a user-selected second symbol. Internally, both assets are transformed into normalized log-returns: the script computes logarithmic returns, removes short-term mean and scales by realized volatility, then clips extreme values. This normalisation allows the tool to compare behaviour across assets with different price levels and volatility profiles.
In Correlation mode, the indicator computes a composite correlation score that typically ranges between โ1 and +1. Values near +1 indicate strong and persistent positive co-movement, values near zero indicate an unstable or weak link, and values near โ1 indicate a stable anti-correlation regime. The composite score is constructed from three components.
The first component is a normalized return co-movement measure. After transforming both instruments into normalized returns, the script evaluates how similar those returns are bar by bar. When the two assets consistently deliver returns of similar sign and magnitude, this component is high and positive. When they frequently diverge or move in opposite directions, it becomes negative. This captures short-term co-movement in a volatility-adjusted way.
The second component focuses on highโlow swing alignment. Rather than looking only at closes, it examines the direction of changes in highs and lows for each bar. If both instruments are printing higher highs and higher lows together, or lower highs and lower lows together, the swing structure is considered aligned. Persistent alignment contributes positively to the correlation score, while repeated mismatches between the swing directions reduce it. This helps differentiate between superficial price noise and structural similarity in trend behaviour.
The third component is a classical Pearson correlation on closing prices, computed over a longer lookback. This serves as a stabilising backbone that summarises general co-movement over a broader window. By combining normalized return co-movement, swing alignment and standard price correlation with calibrated weights, the Correlation mode provides a richer view than a single linear measure, capturing both short-term dynamic interaction and longer-term structural linkage.
In Anticipation mode, Omega Correlation estimates whether the second asset tends to lead or lag the current chart. The output is again a continuous score around the range. Positive values suggest that the second asset is acting more as a leader, with its past moves bearing informative value for subsequent moves of the chart symbol. Negative values indicate that the second asset behaves more like a laggard or follower. Values near zero suggest that no stable leadโlag structure can be identified.
The anticipation score is built from four elements inspired by quantitative leadโlag and price discovery analysis. The first element is a residual lead correlation, conceptually similar to Granger-style logic. The script first measures how much of the chart symbolโs normalized returns can be explained by its own lagged values. It then removes that component and studies the correlation between the residuals and lagged returns of the second asset. If the second assetโs past returns consistently explain what the chart symbol does beyond its own autoregressive behaviour, this residual correlation becomes significantly positive.
The second element is an asymmetric leadโlag structure measure. It compares the strength of relationships in both directions across multiple lags: the correlation of the current symbol with lagged versions of the second asset (candidate leader) versus the correlation of lagged values of the current symbol with the present values of the second asset. If the forward direction (second asset leading the first) is systematically stronger than the backward direction, the structure is skewed toward genuine leadership of the second asset.
The third element is a relative price discovery score, constructed by building a dynamic hedge ratio between the two prices and defining a spread. The indicator looks at how changes in each asset contribute to correcting deviations in this spread over time. When the chart symbol tends to do most of the adjustment while the second asset remains relatively stable, it suggests that the second asset is taking a greater role in determining the equilibrium price and the chart symbol is adjusting to it. The difference in adjustment intensity between the two instruments is summarised into a single score.
The fourth element is a breakout follow-through causality component. The script scans for breakout events on the second asset, where its price breaks out of a recent high or low range while the chart symbol has not yet done so. It then evaluates whether the chart symbol subsequently confirms the breakout direction, remains neutral, or moves against it. Events where the second asset breaks and the first asset later follows in the same direction add positive contribution, while failed or contrarian follow-through reduce this component. The contribution is also lightly modulated by the strength of the breakout, via the underlying normalized return.
The four elements of the Anticipation mode are combined into a single leading correlation score, providing a compact and interpretable measure of whether the second asset currently behaves as an effective early signal for the symbol you trade.
To aid interpretation, Omega Correlation builds dynamic bands around the active series (correlation or anticipation). It estimates a long-term central tendency and a typical deviation around it, plotting upper and lower bands that highlight unusually high or low values relative to recent history. These bands can be used to distinguish routine fluctuations from genuinely extreme regimes.
The script also computes percentile-based levels for the correlation series and uses them to track two special price levels on the main chart: lost correlation levels and gained correlation levels. When the correlation drops below an upper percentile threshold, the current price is stored as a lost correlation level and plotted as a horizontal line. When the correlation rises above a lower percentile threshold, the current price is stored as a gained correlation level. These levels mark zones where a historically strong relationship between the two markets broke down or re-emerged, and can be used to frame divergence, convergence and spread opportunities.
An information panel summarises, in real time, whether the second asset is behaving more as a leading, lagging or independent instrument according to the anticipation score, and suggests whether the current environment is more conducive to de-alignment, re-alignment or classic spread behaviour based on the correlation regime. This makes the tool directly interpretable even for users who are not familiar with all the underlying statistical details.
Typical applications for Omega Correlation include intermarket analysis (for example, index vs index, commodity vs related equity sector, FX vs bonds), dynamic hedge sizing, regime detection for algorithmic strategies, and the identification of leadโlag structures where a macro driver or benchmark can be monitored as an early signal for the instrument actually traded. The indicator can be applied across intraday and higher timeframes, with the understanding that the strength and nature of relationships will differ across horizons.
Omega Correlation is designed as an advanced analytical framework, not as a standalone trading system. Correlation and leadโlag relationships are statistical in nature and can change abruptly, especially around macro events, regime shifts or liquidity shocks. A positive anticipation reading does not guarantee that the second asset will always move first, and a high correlation regime can break without warning. All outputs of this tool should be combined with independent analysis, sound risk management and, when appropriate, backtesting or forward testing on the userโs specific instruments and timeframes.
The intention behind Omega Correlation is to bring techniques inspired by quantitative research, such as normalized return analysis, residual correlation, asymmetric leadโlag structure, price discovery logic and breakout event studies, into an accessible TradingView indicator. It is intended for traders who want a structured, professional way to understand how markets interact and to incorporate that information into their discretionary or systematic decision-making processes.
FPT - Key Levels with VWAP๐ถ FPT โ Key Levels with VWAP
This indicator combines multi-session VWAP, higher-timeframe key levels, market structure (HH/HL/LH/LL), and liquidity zones into one clean intraday tool.
Designed for scalping, day-trading, and session-based strategies such as Asia โ London โ New York flows.
๐ต Features
1. Multi-Session VWAP
Asia VWAP
London VWAP
New York VWAP
Daily reset
Optional deviations & clean mode
2. Key Levels (HTF SR Zones)
Automatically detects:
Previous Day High / Low
4H / 1H Key Levels
Session High / Low
Midpoints
Equal Highs & Equal Lows (liquidity lines)
3. Market Structure Engine
Swing points (HH, HL, LH, LL)
Break of Structure (BOS)
Market Structure Shift (MSS)
Optional minimal mode showing only breaks
4. Liquidity Tools
Buyside & sellside liquidity zones
Range high / low liquidity
Optional void / imbalance zones
5. Clean Visualization Mode
Removes unnecessary text
Shows only the essential levels
Perfect for chart posting or backtesting
๐ฉ Use Cases
Intraday key level mapping
VWAP deviation โ mean reversion setups
Liquidity sweep โ BOS/MSS setups
Session volatility filtering
Scalping and fast execution planning
โ ๏ธ Disclaimer
This script does not provide financial advice.
It is for educational and analytical purposes only.
All trading decisions are solely your responsibility.
Simple Grid Trading v1.0 [PUCHON]Simple Grid Trading v1.0
Overview
This is a Long-Only Grid Trading Strategy developed in Pine Script v6 for TradingView. It is designed to profit from market volatility by placing a series of Buy Limit orders at predefined price levels. As the price drops, the strategy accumulates positions. As the price rises, it sells these positions at a profit.
Features
Grid Types : Supports both Arithmetic (equal price spacing) and Geometric (equal percentage spacing) grids.
Flexible Order Management : Uses strategy.order for precise control and prevents duplicate orders at the same level.
Performance Dashboard : A real-time table displaying key metrics like Capital, Cashflow, and Drawdown.
Advanced Metrics : Includes Max Drawdown (MaxDD) , Avg Monthly Return , and CAGR calculations.
Customizable : Fully adjustable price range, grid lines, and lot size.
Dashboard Metrics
The dashboard (default: Bottom Right) provides a quick snapshot of the strategy's performance:
Initial Capital : The starting capital defined in the strategy settings.
Lot Size : The fixed quantity of assets purchased per grid level.
Avg. Profit per Grid : The average realized profit for each closed trade.
Cashflow : The total realized net profit (closed trades only).
MaxDD : Maximum Drawdown . The largest percentage drop in equity (realized + unrealized) from a peak.
Avg Monthly Return : The average percentage return generated per month.
CAGR : Compound Annual Growth Rate . The mean annual growth rate of the investment over the specified time period.
Strategy Settings (Inputs)
Grid Settings
Upper Price : The highest price level for the grid.
Lower Price : The lowest price level for the grid.
Number of Grid Lines : The total number of levels (lines) in the grid.
Grid Type :
Arithmetic: Distance between lines is fixed in price terms (e.g., $10, $20, $30).
Geometric: Distance between lines is fixed in percentage terms (e.g., 1%, 2%, 3%).
Lot Size : The fixed amount of the asset to buy at each level.
Dashboard Settings
Show Dashboard : Toggle to hide/show the performance table.
Position : Choose where the dashboard appears on the chart (e.g., Bottom Right, Top Left).
How It Works
Initialization : On the first bar, the script calculates the price levels based on your Upper/Lower price and Grid Type.
Entry Logic :
The strategy places Buy Limit orders at every grid level below the current price.
It checks if a position already exists at a specific level to avoid "stacking" multiple orders on the same line.
Exit Logic :
For every Buy order, a corresponding Sell Limit (Take Profit) order is placed at the next higher grid level.
MaxDD Calculation :
The script continuously tracks the highest equity peak.
It calculates the drawdown on every bar (including intra-bar movements) to ensure accuracy.
Displayed as a percentage (e.g., 5.25%).
Disclaimer
This script is for educational and backtesting purposes only. Grid trading involves significant risk, especially in strong trending markets where the price may move outside your grid range. Always use proper risk management.
SPY/QQQ Customizable Price ConverterThis is a minimalist utility tool designed for Index traders (SPX, NDX, RUT). It allows you to monitor the price of a reference asset (like SPY, QQQ) directly on your main chart without cluttering your screen.
Key Features:
1.๐ฑ๏ธ Crosshair Sync for Historical Data (Highlight): Unlike simple info tables that only show the latest price, this script allows for historical inspection.
ยท How it works: Simply move your mouse crosshair over ANY historical candle on your chart.
ยท The script will instantly display the closing price of the reference asset (e.g., SPY) for that specific time in the Status Line (top-left) or the Data Window. Perfect for backtesting and reviewing price action.
2.๐ Fully Customizable Ticker: Default is set to SPY, but you can change it to anything in the settings.
e.g.
ยท Trading NDX Change it to QQQ.
ยท Trading RUT Change it to IWM.
3.๐ Clean Real-Time Dashboard:
ยท A floating table displays the current real-time price of your reference asset.
ยท Color-coded text (Green/Red) indicates price movement.
ยท Fully customizable size, position, and colors to fit your layout.
15m ORB Breakout NAS100 (5m Mgmt) v6 - OptimizedOpening Range Breakout Strategy
Buy and sell signals are given upon break of market session opening range. Best utilized for 30 minute NY opening range, managed on 5 min timeframe on NAS100. Tweak the settings for higher win rate on backtesting dashboard before implementing strategy.
Delta Signals NO REPINTA (FINAL)๐ข New Indicator: Delta Signals NO REPAINT ๐ฅ
Introducing my new indicator based on Order Flow Delta, designed to provide buy and sell signals with absolutely NO repainting โ perfect for scalping, day trading, or swing trading.
This tool combines two powerful components:
โ
Order Flow Delta โ Measures the real strength between buyers and sellers
โ
Smart Trend Filter โ Only shows signals in the direction of the dominant trend
Together, they deliver cleaner, more accurate and more reliable signals, with clear entry markers on the chart and a delta histogram revealing real market pressure.
๐ Whatโs Included?
๐น Buy/Sell signals with NO repaint
๐น Intelligent delta calculation
๐น Trend filter using moving average
๐น Clear labels on entry points
๐น Visual delta histogram
๐น Works great on Crypto, Forex, Indices & Stocks
๐น Very lightweight and fast on TradingView
๐ฏ Why is it powerful?
Because it doesn't rely on lagging indicators โ it reads the actual imbalance between buyers and sellers, often detecting strong moves before traditional indicators do.
This type of analysis is used by professional order flow traders, but now you have it on your TradingView chart in a simple, visual format.
๐ฅ Perfect for:
Scalpers who need precision
Day traders working breakouts and pullbacks
Swing traders seeking strong confirmations
Traders who want clean, NO-repaint signals
If you want a version with automatic TP/SL, alerts, or full backtesting, I can publish that as well.
Just let me know. ๐๐
BybitMinOrderSizeBybit Order Quantity Compliance Library
This library provides all utility functions required for TradingView strategies
that execute orders on Bybit via webhooks.
Problem:
Bybit enforces two strict rules on every order submitted:
Minimum Order Size โ each symbol has its own minimum quantity.
Quantity Precision โ each symbol requires rounding to the correct number of decimals.
TradingView does not expose this metadata, so strategies can easily submit
quantities that Bybit rejects as invalid.
Solution (This Library):
This library embeds full Bybit contract metadata, including:
A complete mapping of Bybit symbols โ minimum order size
A complete mapping of Bybit symbols โ allowed precision (decimal places)
A helper to normalize tickers (removing `.P` suffix for Bybit perpetuals)
It also exposes utility functions to automatically make your quantities valid:
`normalizeTicker()` โ removes `.P` for consistent lookup
`getMinOrderSize()` โ returns the correct minimum order size
`getPrecisionForTicker()` โ returns required quantity precision
`floorQty()` โ floors quantities to valid minimum increments
`roundQty()` โ rounds quantities to valid decimal precision
Use Cases:
Ensuring webhook strategies never send too-small orders
Rounding limit/market orders correctly before execution
Making Pine strategies execution-accurate for Bybit
Avoiding "order rejected: qty too small / invalid precision" errors
This library is recommended for:
Live trading via TradingView โ Bybit webhooks
Backtesting strategies that simulate real Bybit constraints
Source: www.bybit.com
Updated: 2025-11-25 โ Bybit contract metadata
normalizeTicker(symbol)
โโNormalizes Bybit perpetual tickers by removing the ".P" suffix.
precisionFromMinOrder(minOrder)
โโDerives precision (decimal places) from minimum order size.
getMinOrderSize(symbol)
โโRetrieves the minimum order size for the current or given symbol.
getPrecisionForTicker(symbol)
โโRetrieves the required quantity precision (decimal places) for a given Bybit symbol.
floorQty(qty, symbol)
โโRounds a quantity down to the nearest valid minimum order size for a given symbol.
roundQty(qty, symbol)
โโRounds a quantity to the valid precision for the specified symbol.
Marcaj Ore 07:00 ศi 18:00 (Stabil v2)For backtesting and remember times that you can be active in the market.
Oracle Protocol โ Arch Public (Testing Clone) Oracle Protocol โ Arch Public Series (testing clone)
This model implements the Arch Public Oracle structure: a systematic accumulation-and-distribution engine built around a dynamic Accumulation Cost Base (ACB), strict profit-gate exit logic, and a capital-bounded flywheel reinvestment system.
It is designed for transparent execution, deterministic behaviour, and rule-based position management.
Core Function Set
1. Accumulation Framework (ACB-Driven)
The accumulation engine evaluates market movement against defined entry conditions, including:
Percentage-based entry-drop triggers
Optional buy-below-ACB mode
Capital-gated entries tied to available ledger balance
Fixed-dollar and min-dollar entry rules (as seen in Arch public materials)
Automated sizing through flywheel capital
Range-bounded ledger for controlled backtesting input
Each qualifying buy updates the live ACB, maintains the internal ledger, and forms the next reference point for exit evaluation.
No forecasting mechanisms are included.
2. Profit-Gate Exit System
Exits are governed by the standard Arch public approach:
A sealed ACB reference for threshold evaluation
Optional live-ACB visibility
Profit-gate triggers defined per asset class
Candle-confirmation integration (โProfitGate + Candleโ mode)
Distribution only when the smallest active threshold is met
This provides a consistent cadence with published Arch diagrams and PDFs.
3. Once-Per-Rally Governance
After a distribution, the algorithm locks until price retraces below the most recent accumulation base.
Only after re-arming can the next profit gate activate.
This prevents over-frequency selling and aligns with the public-domain Oracle behaviour.
4. Quiet-Bars & Threshold Cluster Control
A volatility-stabilisation layer prevents multiple exits from micro-fluctuations or transient spikes.
This ensures clean execution during fast markets and high volatility.
5. Flywheel Reinvestment
Distribution proceeds automatically return to the capital pool where permitted, creating a closed system of:
Entry sizing
Exit proceeds
Ledger-managed capital state
All sizing respects capital boundaries and does not breach dollar floors or overrides.
6. Automation Hooks and Integration
The script exposes:
3Commas-compatible JSON sizing
Entry/exit signalling via alertcondition()
Deterministic event reporting suitable for external automation
This allows consistent deployment across automated execution environments.
7. Visual Tooling
Optional displays include:
Live ACB line
Exit-guide markers
Capital, state, and ledger panels
Realized/unrealized outcome tracking based on internal logic only
Visual components do not influence execution rules.
Operating Notes
This model is rule-based, deterministic, and non-predictive.
It executes only according to the explicit thresholds, capital limits, and state transitions defined within the script.
No discretionary or forward-looking logic is included.
Simple Line๐ Understanding the Basic Concept
The trend reverses only when the price moves up or down by a fixed filter size.
It ignores normal volatility and noise, recognizing a trend change only when price moves beyond a specified threshold.
Trend direction is visually intuitive through line colors (green: uptrend, red: downtrend).
โ๏ธ Explanation of Settings
Auto Brick Size: Automatically determines the brick/filter size.
Fixed Brick Size: Manually set the size (e.g., 15, 30, 50, 100, etc.).
Volatility Length: The lookback period used for calculations (default: 14).
๐ Example of Identifying Buy Timing
When the line changes from gray or red to green, it signals the start of an uptrend.
This indicates that the price has moved upward by more than the required threshold.
๐ Example of Identifying Sell Timing
When the line changes from green to red, it suggests a possible downtrend reversal.
At this point, consider closing long positions or evaluating short entries.
๐งช Recommended Use Cases
Use as a trend filter to enhance the accuracy of existing strategies.
Can be used alone as a clean directional indicator without complex oscillators.
Works synergistically with trend-following strategies, breakout strategies, and more.
๐ Notes & Cautions
More suitable for medium- to long-term trend trading than for fast scalping.
If the brick size is too small, the indicator may react to noise.
Sensitivity varies greatly depending on the selected brick size, so backtesting is essential to determine optimal values.
โ The Trend Simple Line focuses solely on directionโremove the noise and focus purely on the trend.
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Paulinho Signals โ Cripto 5m/15m com Filtro de LateralidadeThis script is an automated Pine Script v6 strategy designed for short-term cryptocurrency trading, especially on 5-minute and 15-minute timeframes. It combines moving average crossovers, trend strength (ADX), volatility (ATR), and candlestick patterns to generate buy and sell signals with a fixed risk/reward management system.
How to Use:
- Apply to cryptocurrency charts on 5m or 15m timeframes.
- Adjust parameters to fit your preferences (EMA, RSI, ADX, ATR).
- Use for backtesting or as a decision-support tool.
Disclaimer:
This script is for educational purposes only and does not constitute financial advice. Always test on demo accounts before applying to live trading.
Multi Timeframe Bollinger Bands Spectrum [Ata]Multi-Timeframe Bollinger Bands Spectrum
Technical Overview
This script integrates multi-timeframe volatility analysis with volume-derived order flow estimation. By combining Bollinger Bands (statistical deviation) with internal candle volume logic, the indicator qualifies price movements to differentiate between sustained trends, reversals, and exhaustion events.
The system is designed to provide a structural context for price action, visualizing market regimes through a dual-zone spectrum and filtering signals based on the interaction between price location and specific volume thresholds.
Core Logic & Calculation
1. Volume Decomposition Algorithm
Instead of using total volume, the script estimates Buying Pressure vs. Selling Pressure based on the close position relative to the candle's High/Low range:
- Buying Volume (vb): Increases as the close approaches the High.
- Selling Volume (vs): Increases as the close approaches the Low.
This logic allows the detection of directional flow even within standard volume bars.
2. Statistical Spectrum
The indicator renders deviations from the Basis (SMA) as two distinct zones:
- Bullish Zone (Blue): Price positioning between the Basis and Upper Band.
- Bearish Zone (Red): Price positioning between the Basis and Lower Band.
This structure is applied across multiple timeframes (overlay) to visualize the macro trend context without noise.
3. Non-Repainting Execution
To ensure historical accuracy and reliability for backtesting, all higher-timeframe data is requested using "lookahead_off". Signals are confirmed only upon the closure of the respective timeframe's candle.
Signal Definitions
Signals are generated only when specific Volatility and Volume conditions intersect:
Reversal Setups (Reaction to Liquidity)
- WALL: Triggered when price rejects the Upper Band accompanied by Extreme Selling Volume (vs > Limit). This suggests active limit sell orders absorbing the rally.
- FLOOR: Triggered when price rejects the Lower Band accompanied by Extreme Buying Volume (vb > Limit). This suggests active limit buy orders absorbing the drop.
- ABSORP: Identifies absorption near the lower bands where selling pressure is met with passive buying (indicated by lower wicks and relative buy volume).
Momentum Setups (Trend Continuation)
- POWER: Validates a breakout above the Upper Band only if supported by Dominant Buying Volume and a strong candle body.
- PANIC: Validates a breakdown below the Lower Band only if supported by Dominant Selling Volume.
- TRAP: Marks failed breakouts where price exits the bands but volume analysis contradicts the move (e.g., low directional volume).
Exhaustion Setups (Statistical Extremes)
- CLIMAX/CRASH: Identifies anomalies where price deviates significantly from the mean (Extreme Deviation) or when volume reaches unsustainable levels relative to the average, often preceding a mean reversion.
Input Parameters
- Bollinger Logic: Configuration for Length and Standard Deviation Multiplier.
- Volume Thresholds: Adjustable factors for Minimum Volume (Trend) and Extreme Volume (Reversal/Climax).
- Timeframe Layers: Toggle visibility for up to 5 higher timeframes.
- Theme: Adjusts label contrast for Dark/Light backgrounds.
Disclaimer
This indicator is strictly for analytical purposes. It provides a visualization of past market data based on statistical and volumetric formulas. Users should apply their own risk management protocols.
MTF Scalper - alemicihanMulti-Timeframe Scalper Strategy: Aligning the Big Picture for Quick Gains
This article presents a robust futures trading strategy designed for high-frequency scalping in the crypto market. Itโs built on the principle of minimizing risk by ensuring that short-term entries are always aligned with the dominant, higher-timeframe trend.
The Core Concept: Alignment is Key
A Balanced Trend Follower approach, now refined for rapid scalping, uses a Multi-Timeframe (MTF) confirmation system to filter out market noise and increase the probability of a successful trade.
The strategy operates on a Low Timeframe (LTF) chart (e.g., 3m, 5m, or 15m) but only executes trades if the direction is validated by three Higher Timeframes (HTF).
ComponentPurposeFunctionHTF (D, 4h, 1h) EMA => Trend Confirmation =>Checks if the current price is above/below all three Exponential Moving Averages (EMA 20). This provides a strong directional bias.
LTF (5m) Stochastic RSI => Momentum Entry => Generates the actual buy/sell signal by spotting a swift crossover, indicating fresh momentum in the direction of the confirmed HTF trend.
How The Signal Is Generated
Trend Alignment: The system first confirms the trend. If the price is trading above the Daily, 4-Hour, and 1-Hour EMAs, the market is deemed to be in a Strong LONG Trend. Only LONG signals are permitted.
Momentum Trigger: Once the trend is confirmed, a Long Signal is generated only when the Stochastic K-Line crosses above the D-Line, indicating a momentum shift (a pullback ending) towards the main trend direction.
Short Signal: The inverse logic applies to the Short Trend confirmation and entry signal.
Mandatory Risk Management: ATR-Based Exit
Given the high leverage nature of futures and scalping, static Stop-Loss (SL) and Take-Profit (TP) levels are inefficient. This strategy uses the Average True Range (ATR) indicator to dynamically set profit and loss targets based on current market volatility.
Stop Loss (SL): Set dynamically at 1.5 x ATR below (for long) or above (for short) the entry price. This gives the trade enough room to breathe without risking excessive capital.
Take Profit (TP): Set dynamically at 3.0 x ATR, establishing a robust Risk-to-Reward Ratio of 1:2.
Final Thoughts on Testing
This sophisticated approach combines the reliability of MTF analysis with the speed of momentum indicators. However, data analysis is key. Backtesting these parameters (EMA, ATR Multipliers, RSI/Stochastic lengths) on your chosen asset (like BTC/USDT or ETH/USDT) and timeframe is crucial to achieving optimal performance.
Multi-Timeframe TTM Squeeze Pro with alerts and screenersBased of John Carters TTM Squeeze. Must open the settings and select wether you want to match the timeframe in your chart. This must be done in the pinescreener as well otherwise results will not be correct.
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# **Squeeze Momentum Pro โ Enhanced Screener + EMA Cross Alerts**
This custom version of the Squeeze Momentum indicator expands the standard TTM-style squeeze with screening and automated alert logic so you can quickly find high-quality setups across many tickers.
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## **What This Script Does**
This indicator plots a three-level squeeze visual similar to TTM Squeeze:
Dot meanings in this indicator
Orange dot:
Strongest squeeze โ Bollinger Bands are inside the tightest Keltner level (highest volatility compression).
Red dot:
Medium squeeze โ still compressed, but not as tight as orange.
Black dot:
Weak squeeze / lowest level of volatility compression.
Price is coiling, but not as tight as the higher levels.
Green dot (โFiredโ):
Squeeze has released โ Bollinger Bands have expanded out of the channels and momentum is moving.
A momentum histogram is plotted to show directional pressure during the squeeze.
---
## **Major Improvements Added**
### **โ Screenable Conditions for Stock Scanners**
This version includes multiple `alertcondition()` flags so the script can be used as a **Pine Screener inside TradingView**.
Currently it can screen for:
โ Price closing above the 50-SMA
โ Presence of an **orange (strong) squeeze dot**
โ 6/20 EMA crossover signals inside a squeeze
These can be used inside the TradingView Screener or in watchlists to automatically highlight qualifying tickers.
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### **โก 6/20 EMA Trend Signals (Filtered by Squeeze)**
A crossover system was added:
* **Bullish Signal:** 6 EMA crosses above 20 EMA
* **Bearish Signal:** 6 EMA crosses below 20 EMA
But **these signals only trigger if the market is in a red or orange squeeze**, which helps remove noise and focus on valid setups.
---
### **โข Visual Markers Under the Histogram**
Whenever an EMA crossover occurs during a squeeze:
* A **green up-triangle** is plotted for a bullish cross
* A **red down-triangle** for a bearish cross
These markers are drawn **below the histogram**, keeping the display clean while still providing quick visual cues.
---
### **โฃ Fully Non-Repainting Logic**
All signals and squeeze calculations are based on standard fully-resolved `ta.*` functions, making the results stable both in backtesting and real-time.
---
## **Who This Script Helps**
This version is ideal for:
* Traders who use TradingViewโs screener and want automated breakout/continuation filtering
* Traders who scan large watchlists for squeeze setups
* Users who want trend confirmation during volatility compression
---
## **How to Use It**
1. Add the script to your chart
2. Open TradingView Alerts or Screener
3. Select the conditions you want, for example:
* *โOrange Squeeze Detectedโ*
* *โSqueeze Fire after 3 squeeze dots*
* *โ4 REd Dots in a row.โ*
* *โBuy Alertโ*
* *โEMA 6/20 Bullish Crossover (Squeeze Only)โ*
* *โClose Above 50 SMAโ*
Once active, TradingView will automatically flag symbols that meet the criteria.
---
## **Summary**
This enhanced Squeeze Momentum indicator turns the standard TTM-style visual into a **true screening and alert system** by adding:
* Multi-level squeezes
* EMA trend signals
* Screener-compatible alert conditions
* Clean visual signals
* Non-repainting logic
It helps traders quickly locate high-probability setups across any watchlist or market.
Hash Momentum IndicatorHash Momentum Indicator
Overview
The Hash Momentum Indicator provides real-time momentum-based trading signals with visual entry/exit markers and automatic risk management levels. This is the indicator version of the popular Hash Momentum Strategy, designed for traders who want signal alerts without backtesting functionality.
Perfect for: Live trading, automation via alerts, multi-indicator setups, and clean chart visualization.
What Makes This Indicator Special
1. Pure Momentum-Based Signals
Captures price acceleration in real-time - not lagging moving average crossovers. Enters when momentum exceeds a dynamic ATR-based threshold, catching moves as they begin accelerating.
2. Automatic Risk Management Visualization
Every signal automatically displays:
Entry level (white dashed line)
Stop loss level (red line)
Take profit target (green line)
Partial TP levels (dotted green lines)
3. Smart Trade Management
Trade Cooldown: Prevents overtrading by enforcing waiting period between signals
EMA Trend Filter: Only trades with the trend (optional)
Session Filters: Trade only during Tokyo/London/New York sessions (optional)
Weekend Toggle: Avoid low-liquidity weekend periods (optional)
4. Clean Visual Design
๐ข Tiny green dot = Long entry signal
๐ด Tiny red dot = Short entry signal
๐ต Blue X = Long exit
๐ Orange X = Short exit
No cluttered labels or dashboard - just clean signals
5. Professional Alerts Ready
Set up TradingView alerts for:
Long signals
Short signals
Long exits
Short exits
How It Works
Step 1: Calculate Momentum
Momentum = Current Price - Price
Normalized by standard deviation for consistency
Must exceed ATR ร Threshold to trigger
Step 2: Confirm Acceleration
Momentum must be increasing (positive momentum change)
Price must be moving in signal direction
Step 3: Apply Filters
EMA Filter: Long only above EMA, short only below EMA (if enabled)
Session Filter: Check if in allowed trading session (if enabled)
Weekend Filter: Block signals on Sat/Sun (if enabled)
Cooldown: Ensure minimum bars passed since last signal
Step 4: Generate Signal
All conditions met = Entry signal fires
Lines automatically drawn for entry, stop, and targets
Step 5: Exit Detection
Opposite momentum detected = Exit signal
Stop loss or take profit hit = Exit signal
Lines removed from chart
โ๏ธ Settings Guide
Core Strategy
Momentum Length (Default: 13)
Number of bars for momentum calculation. Higher values = stronger signals but fewer trades.
Aggressive: 10
Balanced: 13
Conservative: 18-24
Momentum Threshold (Default: 2.25)
ATR multiplier for signal generation. Higher values = only trade the biggest momentum moves.
Aggressive: 2.0
Balanced: 2.25
Conservative: 2.5-3.0
Risk:Reward Ratio (Default: 2.5)
Your target profit as a multiple of your risk. With 2.2% stop and 2.5 R:R, your target is 5.5% profit.
Conservative: 3.0+ (need 25% win rate to profit)
Balanced: 2.5 (need 29% win rate to profit)
Aggressive: 2.0 (need 33% win rate to profit)
Macketings 1min ScalpingThis is a hyper-reactive scalping strategy designed for the 1-minute chart. It utilizes a strict four-EMA hierarchy (80/90/340/500) to ensure trades are only taken in the strongest aligned market trend. The strategy is built to be extremely tight on risk and focuses on capturing the immediate, high-momentum swing that follows a confirmed EMA retest or breakout.
Key Mechanics (How it Works):
Strict Trend Alignment: Entry is only permitted when the faster EMA band (80/90) and the price action are correctly aligned with the slow trend (340/500).
Long: EMA 80/90 must be above EMA 340/500, AND EMA 340 must be above EMA 500. (And vice-versa for Short.)
Expanded Retest Entry: The strategy waits for the price to retest or briefly enter the 80/90 band, then immediately enters upon the confirmed momentum breakout from that band.
Dynamic Risk Management (Tight Ride): The strategy is engineered to ride the wave aggressively while protecting capital immediately:
Extremely Tight Initial Stop Loss (0.2% default): Limits initial risk instantly.
Break-Even Security: Once profit hits 0.3%, the Stop Loss is automatically trailed to secure 0.2% profit (a risk-free trade).
Aggressive Exit Logic: Positions are closed not only upon hitting the Take Profit target (2.5%) but also immediately if the 80/90 EMA band crosses the 340 EMA, signaling a critical loss of momentum.
Disclaimer:
This strategy requires high-liquidity instruments and is best used on low timeframes (1-minute) due to its dependency on fast momentum shifts and tight stops. Backtesting and forward testing are crucial before deployment.
90D High % Pullback Lines (Hybrid 10 Lines)90D High % Pullback Lines (Hybrid 10 Lines) visualizes drawdown levels from the 90-day high, with up to 10 fully customizable percentage-based lines.
This tool makes it easy to identify pullbacks, dip-buy zones, trend continuation points, and discount regions in any market.
๐ Features
โ
Up to 10 customizable pullback levels
Each line has its own % drop setting
Turn any line ON/OFF individually
Example presets: โ10%, โ20%, โ30%, โฆ โ95%
โ
Two rendering modes
1. Hybrid Fixed Line Mode (Stable / Anti-Shift)
Prevents line drift caused by chart updates
Keeps horizontal levels synchronized on every bar
Best stability for intraday & real-time use
2. Lightweight plot (stepline) Mode
Ideal for backtesting
Fully compatible with alerts
Clean and fast rendering
โ
Supports daily-based 90-day high
Even on lower timeframes, the indicator can use the daily 90-day high
Ideal for MTF (multi-timeframe) analysis
๐ฏ Use Cases
Instantly see how far price has pulled back (%) from the 90-day high
Build systematic dip-buy / trend-follow setups
Identify discount zones during volatility
Monitor recovery signals after strong sell-offs
Works great for crypto, FX, indices, and stocks
๐จ Alerts Included
Alerts trigger when closing price crosses any selected pullback line
Useful for automated dip-buy alerts, breakout alerts, etc.
๐ Notes
Due to internal TradingView behavior, public indicators may behave slightly differently from real-time script editing mode.
The Hybrid Line Mode is designed to provide the most stable and drift-free line display.
7/21 EMA ADX Pro After many months (actually years) of intense research, countless hours of testing different approaches, and rigorous backtesting, Iโve finally developed this indicator/strategy based on moving average crossovers enhanced with power-based filtering to significantly reduce false signals and whipsaws. This is not just another basic MA crossover system. The core idea revolves around applying mathematical powers (exponents) to the moving averages and combining them with additional confirmation filters, creating a much more robust and reliable signal generation mechanism. Iโm sharing it with the community in the hope that it can be useful to someone else who, like me, has spent endless nights trying to find an edge in the markets. Feel free to test it, modify it, or improve it. Feedback, suggestions, and constructive criticism are always welcome. If you find it helpful, a simple like or comment would mean a lot โ itโs the result of a huge amount of work and passion. Happy trading! (Full Pine Script code will be posted below or in the next update โ stay tuned!
14:30 New York OpenRed dotted line at NY open. Shows new traders where NY opens. Helpful for backtesting and when trading that session where it starts very quickly
Any Strategy BacktestA simple script for backtesting your strategies with TP and SL settings. For this to work, your indicators must have sources for long and short conditions.
Nadaraya-Watson: Rational Quadratic Kernel (Opening Gap Shift)What we did to fix it: We didn't throw out the old data (that made it too jumpy early in the day).
Instead, we "tricked" the kernel by shifting all the previous day's prices up or down by the exact gap amount (e.g., if it gapped up 50 points, add 50 to every old price point). This makes the history "line up" with the new day's starting level.
Created so with a fresh session the Nadaraya-Watson Regression Kernel is relevant from the get go - no catch up on opening gaps.
All credit to jdehorty his full description is below.
What is NadarayaโWatson Regression?
NadarayaโWatson Regression is a type of Kernel Regression, which is a non-parametric method for estimating the curve of best fit for a dataset. Unlike Linear Regression or Polynomial Regression, Kernel Regression does not assume any underlying distribution of the data. For estimation, it uses a kernel function, which is a weighting function that assigns a weight to each data point based on how close it is to the current point. The computed weights are then used to calculate the weighted average of the data points.
How is this different from using a Moving Average?
A Simple Moving Average is actually a special type of Kernel Regression that uses a Uniform (Retangular) Kernel function. This means that all data points in the specified lookback window are weighted equally. In contrast, the Rational Quadratic Kernel function used in this indicator assigns a higher weight to data points that are closer to the current point. This means that the indicator will react more quickly to changes in the data.
Why use the Rational Quadratic Kernel over the Gaussian Kernel?
The Gaussian Kernel is one of the most commonly used Kernel functions and is used extensively in many Machine Learning algorithms due to its general applicability across a wide variety of datasets. The Rational Quadratic Kernel can be thought of as a Gaussian Kernel on steroids; it is equivalent to adding together many Gaussian Kernels of differing length scales. This allows the user even more freedom to tune the indicator to their specific needs.
The formula for the Rational Quadratic function is:
K(x, x') = (1 + ||x - x'||^2 / (2 * alpha * h^2))^(-alpha)
where x and x' data are points, alpha is a hyperparameter that controls the smoothness (i.e. overall "wiggle") of the curve, and h is the band length of the kernel.
Does this Indicator Repaint?
No, this indicator has been intentionally designed to NOT repaint. This means that once a bar has closed, the indicator will never change the values in its plot. This is useful for backtesting and for trading strategies that require a non-repainting indicator.
Settings:
Bandwidth. This is the number of bars that the indicator will use as a lookback window.
Relative Weighting Parameter. The alpha parameter for the Rational Quadratic Kernel function. This is a hyperparameter that controls the smoothness of the curve. A lower value of alpha will result in a smoother, more stretched-out curve, while a lower value will result in a more wiggly curve with a tighter fit to the data. As this parameter approaches 0, the longer time frames will exert more influence on the estimation, and as it approaches infinity, the curve will become identical to the one produced by the Gaussian Kernel.
Color Smoothing. Toggles the mechanism for coloring the estimation plot between rate of change and cross over modes.
