Signalgo MASignalgo MA
Signalgo MA is a next-generation indicator for TradingView that redefines moving average (MA) trading by combining multi-timeframe logic, trend strength filtering, and adaptive trade management. Here’s a deep dive into how it works, its unique features, and why it stands apart from traditional MA indicators.
How Signalgo MA Works
1. Multi-Timeframe Moving Average Analysis
Simultaneous EMA & SMA Tracking: Signalgo MA calculates exponential (EMA) and simple (SMA) moving averages across a wide range of timeframes—from 1 minute to 3 months.
Layered Cross Detection: It detects crossovers and crossunders on each timeframe, allowing for both micro and macro trend detection.
Synchronized Signal Mapping: Instead of acting on a single crossover, the indicator requires agreement across multiple timeframes to trigger meaningful signals, filtering out noise and false positives.
2. Trend Strength & Quality Filtering
ADX Trend Filter: Trades are only considered when the Average Directional Index (ADX) confirms a strong trend, ensuring signals are not triggered during choppy or directionless markets.
Volume & Momentum Confirmation: For the strongest signals, the system requires:
A significant volume spike
Price above/below a longer-term EMA (for buys/sells)
RSI momentum confirmation
One-Time Event Detection: Each crossover event is flagged only once per occurrence, preventing repeated signals from the same move.
Inputs & User Controls
Preset Parameters:
EMA & SMA Lengths: Optimized for both short-term and long-term analysis.
ADX Length & Minimum: Sets the threshold for what is considered a “strong” trend.
Show Labels/Table: Visual toggles for displaying signal and trade management information.
Trade Management:
Show TP/SL Logic: Toggle to display or hide take-profit (TP) and stop-loss (SL) levels.
ATR Length & Multipliers: Fine-tune how SL and TP levels adapt to market volatility.
Enable Trailing Stop: Option to activate dynamic stop movement after TP1.
Entry & Exit Strategy
Entry Logic
Long (Buy) Entry: Triggered when multiple timeframes confirm bullish EMA/SMA crossovers, ADX confirms trend strength, and all volume/momentum filters align.
Short (Sell) Entry: Triggered when multiple timeframes confirm bearish crossunders, with the same strict filtering.
Exit & Trade Management
Stop Loss (SL): Automatically set based on recent volatility (ATR), adapting to current market conditions.
Take Profits (TP1, TP2, TP3): Three profit targets at increasing reward multiples, allowing for flexible trade management.
Trailing Stop: After TP1 is hit, the stop loss moves to breakeven and a trailing stop is activated to lock in further gains.
Event Markers: Each time a TP or SL is hit, a visual label is placed on the chart for full transparency.
Strict Signal Quality Filters: Signals are only generated when volume spikes, momentum, and trend strength all align—dramatically reducing false positives.
Adaptive, Automated Trade Management: Built-in TP/SL and trailing logic mean you get not just signals, but a full trade management suite—rarely found in standard MA indicators.
Event-Driven, Not Static: Each signal is triggered only once per event, eliminating repetitive or redundant entries.
Visual & Alert Integration: Every signal and trade event is visually marked and can trigger TradingView alerts, keeping you informed in real time.
Trading Strategy Application
Versatility: Suitable for scalping, day trading, swing trading, and longer-term positions thanks to its multi-timeframe logic.
Systematic Execution: By automating entries, exits, and risk management, Signalgo MA helps you trade with discipline and confidence, minimizing emotional bias.
Noise Reduction: The advanced, layered filtering logic means you only see the highest-probability setups, helping you avoid common MA “fakeouts” and overtrading.
Moving_average
The Multi Crossover Strategy [BoyaSignals]
📄 OVERVIEW
This strategy combines a layered entry system and adaptive risk management to capture opportunities across different market phases. Entries progress from deep reversals to momentum breakouts, using filters that adjust to trend, consolidation, or reversal conditions.
Advanced risk management features are built in, including a dynamic trailing stop and dynamic stop loss that adapt to volatility and trend conditions. These mechanisms are designed to help manage open positions more effectively than using fixed ATR multipliers alone.
The system includes enhanced backtesting statistics to help evaluate how changes in configuration affect historical performance. All backtesting results are for evaluation purposes only and should not be relied upon as an indicator of future performance.
For transparency, the strategy provides detailed chart labels showing the type of entry triggered, the entry filter number, real-time profit and loss percentages, and the reason for position closure. Display options allow users to show or hide labels and to overlay decision-related moving averages and Bollinger Bands for further context.
Alerts generated by this strategy can be used for discretionary entries or connected to automated trading platforms that accept TradingView webhook signals, such as Coinbase, Binance, and others. Some traders choose to integrate this setup with third-party services like Cryptohopper to automate execution, though this is entirely optional.
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🔍 HOW DOES IT WORK
Signals are generated through a combination of momentum crossovers that pinpoint different stages of market movement. Each entry undergoes a series of checks across multiple indicators—including RSI, CCI, ADX, Bollinger Bands, moving averages, and volume—to confirm alignment with the strategy’s criteria.
Optional divergence detection across ten indicators can further strengthen signal quality and reduce the chance of false entries. In addition, global filters enforce conditions like minimum retracements, distance from key averages, and sufficient volatility before any trade is allowed.
Once an entry is active, stop losses and trailing stops adjust automatically in response to current volatility, momentum shifts, and recent price behavior. By sequencing filters and confirmations, the strategy aims to avoid chasing late moves while systematically identifying setups with the highest potential.
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🎯 ENTRY TYPES
This strategy combines multiple entry methods to help identify potential opportunities across a variety of price conditions. Each entry type can be enabled or disabled individually and is evaluated using configurable filters and confirmation tools.
Stochastic RSI Crossover
Triggers when the Stochastic RSI K line crosses above the D line, often in oversold areas.
9-Period Moving Average Crossover
Triggers when price crosses the 9-period simple moving average.
MACD Crossover
Triggers when the MACD line crosses the signal line.
Big Bottom Entry
Designed to catch deep reversals before a Stochastic RSI crossover has formed.
Breakout Entry
Triggers when price exceeds recent high levels.
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📊 MULTI-INDICATOR EVALUATION
Every entry signal is assessed using conditions including RSI, ADX, Stochastic, CCI, volume, volatility, price position relative to Bollinger Bands, proximity to the 50 and 200 moving averages, and additional proprietary filters. These filters help align entries with broader market context and avoid signals during unfavorable conditions.
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🧭 DIVERGENCE CONFIRMATION
An additional confirmation layer can be added by checking for divergences around entry bar.
Settings let users customize how strict the divergence confirmation should be:
Specify the minimum number of divergences required
Allow divergence count overrides when volume is elevated
Require divergence on the crossover bar (stricter) or accept the nearest pivot (more flexible)
Enable divergence only when the market is not in an uptrend
Apply divergence checks selectively to specific entry types
Disable divergence validation entirely
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🧩 ENTRY FILTERS
Filters Adapted To Price Context
Each entry method uses filters tailored to price conditions. For example, Stochastic RSI has distinct filters for downtrends, sideways moves, and retracements. 9MA and MACD entries check if price is above or below the basis line. You can enable or disable these filters to create stricter or more flexible entry criteria.
This is a layered approach that identifies opportunities progressively—from deep reversals to Stoch entries below the 9MA, then 9MA and MACD setups between averages and the upper Bollinger Band, and finally breakout entries at new highs. If one entry (e.g., a Stoch Crossover) doesn’t trigger, the strategy evaluates the next crossover filters as price rises.
Global Entry Filters
In addition to specific entry conditions, the strategy includes global filters to improve signal quality. These can:
Require a minimum distance above or below the 50 and 200 moving averages.
Define minimum and maximum retracement percentages in an uptrend.
Specify minimum distances from recent swing highs, swing lows, or resistance.
Set a minimum Bollinger Band width for entries.
Optionally disable entries entirely if the price is below key moving averages.
These filters can be adjusted or turned off to fine-tune selectivity.
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🟢 DYNAMIC TRAILING STOPS
The strategy includes an advanced trailing stop mechanism that adapts to market conditions. Unlike a fixed ATR stop, this system evaluates multiple criteria to determine how aggressively or loosely to trail price.
The trailing stop becomes active only after price has reached a minimum profit level to avoid early tightening.
Dynamic ATR multipliers adjust between tight, narrow, and wide modes:
Wide trailing is used when strong bullish momentum, breakouts, or support above moving averages are detected.
Narrow trailing is applied during low volatility and early momentum loss.
Tight trailing activates if reversal signals appear, such as bearish divergences or trend exhaustion.
Evaluation factors include volatility, Bollinger Band compression, momentum slope and exhaustion patterns, price position relative to moving averages and bands, divergence signals, and recent swing levels.
You can define ATR multipliers, enable or disable tightening conditions, and choose adaptive or fixed trailing behavior.
Labels show when the trailing stop is armed and when adjustments occur.
Entry Label – In the snapshot above, you can see a Stoch Entry with the number 1 displayed below the “Stoch” label, indicating that Entry Filter 1 was the specific condition that triggered this trade.
Divergence Label – The entry was confirmed by divergences detected on four indicators at the entry bar: Stoch, CCI, CMF, and MFI. A green divergence label means regular divergences were found (hidden divergences are shown in orange).
Percentage Label – Where a position closes, you’ll see a percentage label showing the profit or loss achieved—green for profit, red for loss.
Trail Stop Label – The light blue label identifies which trailing stop rule closed the trade. In this snapshot, it was a tight stop loss triggered by bearish divergence.
Notice: A few bars to the left of this entry, there is another green divergence label without a corresponding entry signal. This indicates that although a divergence was detected, none of the entry filter criteria were met, so no trade was initiated.
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🔴 DYNAMIC STOP LOSS
This strategy includes a comprehensive stop loss system that adapts as the market evolves. The stop loss can:
Use ATR-based or fixed percentage distance.
Tighten if early reversal risk appears , such as minor bearish movement or early trend shifts.
Tighten further if stronger bearish reversal signals confirm , including failed bounce attempts, rejection at resistance, or lower highs.
Define a maximum allowable loss per trade . By default, max stop loss is set to 3.5% below entry.
Allow a temporary extension beyond the max loss cap if bullish recovery signals appear, such as deep oversold conditions with momentum shift or successful bounces. By default, extended stop loss is enabled with 1.2% additional loss allowed.
Adjust to breakeven after reaching a defined profit.
Additional settings define how many bars must pass before certain stops activate, how long extended stops remain active, and what triggers a final exit. Labels show which stop type was triggered and why.
Examples to the use of extended SL:
A Reduced Loss Example:
A Reduced Loss Example 2:
Loss Turned Into Profit:
The “+” mark at the bottom of a bar indicates that the extended stop loss feature kept the position open due to detected reversal signals.
The “T” mark shows that the tight stop loss was triggered at that bar.
The red stop loss label above the closing bar displays the type of stop loss activated (e.g., Extended SL) and the reason for the exit (e.g., Breakdown).
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STATISTICS AND BACKTESTING
The statistics provided in this strategy, help you analyze historical performance and see how changing the settings affects results .
Statistics include net profit, win rate, average win and loss size, maximum drawdown, risk/reward ratio, counts of each stop loss and trailing stop type, performance by entry method, filter-specific results, and monthly and yearly profit distributions.
The strategy was developed over the course of a full year, with extensive evaluation and testing on multiple coins and market conditions. By default all entry types and their related filters are activated. The default settings works well with many symbols but you will always need to fine-tune them in order to achieve best results for each symbol. Optimized results were found with DOGEUSDT on the 15 minute chart .
Although default settings can deliver strong performance on some symbols, it may produce poor results on others if left unadjusted. Tips for quickly tuning the configuration to different coins are provided at the end of this description.
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ADDITIONAL LABELS
Skipped Divergence Labels
In the snapshot above, you can see an example of a label showing a skipped divergence. This means a divergence was detected on that bar but was not considered valid. A divergence will not be treated as valid if the number of divergences on that bar is less than the minimum defined in the settings, or if the type of divergence does not match the expected type for the current trend. Hidden divergences are used to confirm retracements during uptrends, while regular divergences are used to identify potential bottom reversals.
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🧮 RISK ASSUMPTIONS AND DEFAULT SETTINGS
This strategy backtest uses a starting balance of $10,000 with 1 tick slippage and 0.075% commission. Position size defaults to 100% per trade to clearly measure the impact of each entry without partial allocations. The maximum stop loss is set at 3.5% below entry to limit downside risk, while an extended stop is activated by default (optional) and can widen losses by up to an additional 1.2%.
Why 100% Position Size is Used
This strategy defaults to allocating 100% of available equity per trade to simplify performance measurement and scaling. Because all entries are protected by defined stop loss levels (by default, maximum 3.5% of entry price + Extended stop loss % if activated), the actual risk per trade remains capped and does not exceed a sustainable portion of account equity. Users who prefer a different allocation can easily adjust position sizing in the Properties tab to match their preferred risk tolerance.
NOTICE & DISCLAIMER
This material is provided solely for personal study and demonstration. Redistribution, resale, modification, or any other use of these files or ideas is strictly prohibited. This tool does not provide financial advice or recommendations. Trading involves substantial risk and should be based on your own judgment. You are solely responsible for any decisions and outcomes.
No representation is made that the strategy will perform as intended in all situations. Automated systems may occasionally exit positions too early or too late, or extend trades when they should not. Use this information carefully and at your own discretion. No guarantees of performance or results are given.
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TIPS FOR ADJUSTING SETTINGS TO VARIOUS SYMBOLS
There are a few simple steps I recommend when adapting the strategy to other coins or symbols:
1. Review the backtesting results.
Check whether there’s a healthy balance between wins and losses across most entry filters. If not, continue with the adjustments below.
2. Adjust divergence confirmation strictness.
For example, by default, Stoch Entries use the “Divergence / Uptrend” setting, requiring divergence only when an uptrend isn’t detected. Changing this to “After Divergence” forces every entry to confirm with divergence. Refer to the tooltips for each option to see how they impact signals.
3. Refine divergence settings.
Try adjusting the minimum number of divergences required to validate a signal and toggle the override divergence count switch. You can also experiment with enabling or disabling the other divergence-related toggles to see how they affect performance.
4. Deactivate specific entry filters.
If some filters still show a weak win/loss ratio after refining divergence criteria, consider turning them off to improve overall results.
5. Modify Narrow Trailing Stop behavior.
You can choose when the Narrow Trailing Stop should engage—either when bandwidth drops below 3% or when it falls under the average bandwidth of recent bars.
6. Adjust Global Entry Filters
Fine-tune the global filters to change thresholds for defining uptrends, retracements, minimum volatility, and conditions around key moving averages.
ADEDA v3ADEDA v3 - Advanced Divergence and Extended Distance Analysis
ADEDA v3 is a versatile TradingView indicator primarily focused on identifying profitable short duration trades by attempting to signal imminent contrarian moves in established price trends. It combines popular technical tools like RSI, MACD, and CCI with unique relativity settings, comparing the current symbol to major index ETFs (SPY, QQQ, IWM, RSP). With customizable trading modes and settings, ADEDA v3 can adapt to various trading styles and markets.
ADEDA v3 overlays five moving averages on your chart and provides visual signals through indicator shapes and detailed tables. It’s designed to help traders of all levels identify overextended market conditions and make informed decisions.
Key Features
Moving Average Analysis:
Plots EMA9, EMA21, EMA34, SMA50, and SMA200. Measures the percentage distance of the price from EMA9 and EMA21 to detect overextension.
Technical Indicators:
Uses RSI, MACD, and optional CCI to confirm signals.
Relativity Settings:
Compares the symbol’s performance to SPY, QQQ, IWM, and RSP using RSI, highlighting overbought or oversold conditions relative to the market.
Customizable Modes:
Offers four modes—Normal, Loose, Strict, and Daytrading—with tailored settings for different strategies.
Volatility Spike Detection (experimental):
Attempts to filter out signals during high volatility periods using ATR and volume analysis, reducing false positives.
Visual Tools:
Displays divergence shapes (! marks) and tables for distances, RSI, and moving average RSI values.
Input Parameters
Customize ADEDA v3 to fit your trading needs with these settings:
Lookback Period (40 default):
Number of bars to calculate historical high absolute distances from EMA9 and EMA21. Increase for more reliability, decrease for faster signals.
Threshold (75 default):
Percentage of the historical high distance that the current distance must exceed to trigger an "extended" signal. Higher values mean fewer, stronger signals.
Mode (Normal default):
Normal: Balanced for most markets.
Loose: More signals, less strict.
Strict: Fewer, high-confidence signals.
Daytrading: Optimized for 5-minute intervals for intraday trading.
CCI Length (20 default):
Adjusts CCI sensitivity (1-2000). *IMPORTANT* -- This setting must be adjusted individually to each symbol for best results.
Use CCI (true default):
Toggle CCI on or off in signal calculations.
Show Divergence Shapes (true default):
Displays buy/sell shapes on the chart.
Show Distance Table (true default):
Shows price distances from EMA9/EMA21 and their status.
Show RSI Table (true default):
Displays RSI of relativities to SPY, QQQ, IWM, RSP.
Show MA RSI Table (true default):
Shows moving averages of relativity RSI values.
Exclude Open & Close (Daytrading) (false default):
In Daytrading mode, skips signals in the first/last 15 minutes of the day.
Relativity Settings:
RSI Length (14): Length for relativity RSI.
MA Length (14): Moving average length for RSI.
Overbought Threshold (70): RSI level for overbought.
Oversold Threshold (35): RSI level for oversold.
Volatility Spike Detection (experimental):
Use Volatility Spike Detection (default false): Enable to filter out signals during periods of high volatility.
ATR Length (8): ATR calculation period.
Baseline Length (50): Baseline for ATR/volume.
ATR Spike Threshold (1.3): Multiplier for ATR spikes.
Volume Spike Threshold (1.2): Multiplier for volume spikes.
How to Interpret Signals
Divergence Shapes:
Downward (!): Potential sell signal (red).
Upward (!): Potential buy signal (green).
Purple (!): Conditions met for 4+ bars. A purple signal indicates unusual momentum/volatility. It is a warning that previous signals have a higher chance of being incorrect/false.
Distance Table:
Shows current distances from EMA9/EMA21 vs. historical highs. "Extended" in red (upside) or green (downside) when the threshold is crossed.
RSI Table:
RSI values for relativities. Red = overbought, green = oversold.
MA RSI Table:
Moving averages of relativity RSI. Same color coding as RSI table.
Volatility Spike:
Red background highlights high volatility periods (if enabled).
Usage Tips
Given the nature of the design of the indicator to signal potential short-term contrarian price action, repeated signaling of overbought or oversold conditions can indicate that the symbol is in a longer-term trend that is opposite to individual signaling. In these cases, intrepid users may use the indicator to execute complementary strategies, e.g. selling short-term covered calls against a long term held position when overbought signals appear.
Also, please keep in mind that ADEDA v3 is not designed to provide exit signaling.
Alerts
Set up alerts in TradingView’s "Alerts" tab:
Current Bar: Triggers on new buy/sell signals.
Last 2 Bars: Triggers if conditions met in the past two bars (great for screeners).
Data Requirements
ADEDA v3 fetches SPY, QQQ, IWM, and RSP data for relativity. These index ETFs have been chosen rather than the indexes themselves as most TradingView users should have access to price data for these ETFs without extra add-ons.
Legal Disclaimer
This script is provided "as is," without any warranties or guarantees of any kind, either express or implied. The author is not a financial advisor, and this script should not be considered financial advice. Users are solely responsible for their own trading decisions and should not rely on this script as the basis for any financial actions. The author shall not be held liable for any losses, damages, or claims arising from the use of this script. By using this script, you agree to assume all risks associated with its use and hold the author harmless from any consequences that may result.
AI Smart Liquidity Signal 🚀
The "AI Smart Liquidity Signal" indicator is an advanced technical analysis tool designed for traders on TradingView. It aims to identify high-probability trading opportunities by analyzing liquidity dynamics and integrating a comprehensive suite of intelligent filters. This indicator provides precise entry and exit signals, complete with defined take-profit and stop-loss levels, helping traders make informed decisions.
Key Features:
Advanced Liquidity Analysis: The indicator identifies and plots liquidity trendlines based on key pivot points (Pivot High/Low), revealing "liquidity breakouts" that often precede significant price movements. This analysis offers unique insights into hidden supply and demand zones in the market.
Comprehensive Signal Filtering System: To ensure the highest quality signals, the indicator incorporates a robust filtering system, including:
Trend Filters: General and Smart Trend analysis using Moving Averages (SMA, EMA) to determine market strength and direction.
Momentum and Volatility Filters: Utilizing indicators like RSI, MACD, and ATR to assess momentum and price volatility, helping to avoid false signals in choppy markets.
Candle Body Strength Filters: Evaluating the strength of candle bodies to confirm signal validity.
Support & Resistance Filters: Identifying dynamic and retested support and resistance zones, and filtering signals that might be trapped within these areas.
Higher Timeframe Filters: Ability to enable trend filters from higher timeframes (e.g., 30-minute, 1-hour, 4-hour) to ensure signal confluence with larger trends.
Session Filter: Trade only during specific market sessions (Asian, London, New York) to focus trading on the most active periods.
Integrated Risk Management: The indicator provides automatic Take Profit (TP1, TP2, TP3) and Stop Loss (SL) levels based on Average True Range (ATR), helping traders effectively manage their trades and set realistic targets.
Multi-Timeframe (MTF) Scanner: The indicator allows you to monitor buy and sell signals across multiple timeframes simultaneously (from 1-minute to 1-day), providing a holistic market view and helping to identify the best entry opportunities.
Customizable Alerts: Set up instant alerts for buy/sell signals, entry/exit levels, or when price touches support/resistance zones, to stay informed about trading opportunities without constant chart monitoring.
Clear Visual Representation: All signals, trendlines, take-profit/stop-loss levels, and support/resistance zones are clearly and intuitively displayed on the chart, facilitating visual analysis.
How It Works:
The indicator employs a sophisticated algorithm that combines liquidity analysis with signal confirmation through a customizable set of filters. It identifies potential reversal points in the market (pivot points) and draws liquidity trendlines that represent areas of price attraction or rejection. When these lines are broken, an initial signal is generated. This signal then passes through a series of filters (such as RSI, MACD, ATR, trend analysis, support and resistance) to enhance its accuracy and reduce false positives. The final signals are displayed with dynamically calculated take-profit and stop-loss levels.
Why Choose AI Smart Liquidity Signal?
Enhanced Accuracy: Thanks to its multi-layered filtering system, the indicator aims to provide more precise and reliable signals.
Effective Risk Management: Integrated take-profit and stop-loss levels help you protect your capital and maximize profitable trades.
Comprehensive Market View: The multi-timeframe scanner gives you a broad market perspective, helping you identify the strongest trends and opportunities.
User-Friendly: Despite its internal complexity, the indicator is designed to be user-friendly, with clear input options allowing you to customize it to fit your trading style.
Whether you are a novice or an experienced trader, the "AI Smart Liquidity Signal" indicator provides you with the necessary tools to enhance your trading strategy and improve your results.
Convergence [by Oberlunar]
The Convergence Indicator by Oberlunar is a multi-timeframe analysis tool that identifies and visualizes trend convergence across up to 10 configurable timeframes using advanced customizable moving averages, including Hull, OberX (a Hull mod), THMA, EMA, and SMA, with an optional pseudo-Hilbert Transform.
It provides a clear visual overlay through gradual fill areas that highlight bullish and bearish trends while offering a fully configurable dynamic table to monitor live trend states across all selected timeframes with user-defined colors and positioning.
This tool is designed for traders who seek to pinpoint multi-timeframe convergence points to enhance their decision-making process in trend-following and breakout strategies.
Oberlunar 👁️⭐
Smart Gap Indicator + EMAs📈 Smart Gap Indicator + EMAs
Spot high-impact gaps with precision and confidence.
🔍 What it does:
This tool identifies and highlights strategic price gaps that often precede strong directional moves. It filters out noise by combining advanced logic with volume activity and trend bias, helping you focus on the most relevant setups.
📊 Key Features:
Smart Gap Detection – Automatically detects meaningful gap up/down events based on dynamic thresholds.
EMA Trend Filter – Optional multi-EMA filter (10, 21, 50) to help align trades with the prevailing market trend.
Volume Spike Signal – Highlights volume surges that may indicate institutional involvement.
Clean Visuals – Configurable labels, shapes, and optional gap fill lines to aid quick interpretation.
Gap Performance Table – Summarizes recent gap activity to assess directional bias.
⚠️ Built-in Alerts:
Gap Up
Gap Down
Gap + Volume Spike
💡 Made by a trader, for traders.
Whether you're a swing trader, gap hunter, or momentum follower—this tool was crafted to give you an edge where it matters most: timing.
Dynamic Gap Probability ToolDynamic Gap Probability Tool measures the percentage gap between price and a chosen moving average, then analyzes your chart history to estimate the likelihood of the next candle moving up or down. It dynamically adjusts its sample size to ensure statistical robustness while focusing on the exact deviation level.
Originality and Value:
• Combines gap-based analysis with dynamic sample aggregation to balance precision and reliability.
• Automatically extends the sample when exact matches are scarce, avoiding misleading signals on rare extreme moves.
• Provides real “next-candle” probabilities based on historical occurrences rather than fixed thresholds or untested heuristics.
• Adds value by giving traders an evidence-based edge: you see how similar past deviations actually played out.
How It Works:
1. Calculate gap = (close – moving average) / moving average * 100.
2. Round the absolute gap to nearest percent (X%).
3. Count historical bars where gap ≥ X% above or ≤ –X% below.
4. If exact X% count is below the minimum occurrences threshold, include gaps at X+1%, X+2%, etc., until threshold is reached.
5. Compute “next-candle” green vs. red probabilities from the aggregated sample.
6. Display current gap, sample size, green probability, and red probability in a table.
Inputs:
• Moving Average Type (SMA, EMA, WMA, VWMA, HMA, SMMA, TMA)
• Moving Average Period (default 200)
• Minimum Occurrences Threshold (default 50)
• Table position and styling options
Examples:
• If price is 3% above the 200-period SMA and 120 occurrences ≥3% are found, with 84 green next candles (70%) and 36 red (30%), the script displays “3% | 120 | 70% green | 30% red.”
• If price is 8% below the SMA but only 20 exact matches exist, the script will include 9% and 10% gaps until it reaches 50 samples, then calculate probabilities from that broader set.
Why It’s Useful:
• Mean-reversion traders see green-probability signals at extreme overbought or oversold levels.
• Trend-followers identify continuation likelihood when red probability is high.
• Risk managers gauge reliability by inspecting sample size before acting on any signal.
Limitations:
• Historical probabilities do not guarantee future performance.
• Results depend on timeframe and symbol, backtest with your data before trading.
• Use realistic slippage and commission when overlaying on strategy scripts.
SMA Crossing Background Color (Multi-Timeframe)When day trading or scalping on lower timeframes, it’s often difficult to determine whether the broader market trend is moving upward or downward. To address this, I usually check higher timeframes. However, splitting the layout makes the charts too small and hard to read.
To solve this issue, I created an indicator that uses the background color to show whether the current price is above or below a moving average from a higher timeframe.
For example, if you set the SMA Length to 200 and the MT Timeframe to 5 minutes, the indicator will display a red background on the 1-minute chart when the price drops below the 200 SMA on the 5-minute chart. This helps you quickly recognize that the trend on the higher timeframe has turned bearish—without having to open a separate chart.
デイトレード、スキャルピングで短いタイムフレームでトレードをするときに、大きな動きは上に向いているのか下に向いているのかトレンドがわからなくなることがあります。
その時に上位足を確認するのですが、レイアウトをスプリットすると画面が小さくて見えにくくなるので、バックグラウンドの色で上位足の移動平均線では価格が上なのか下なのかを表示させるインジケーターを作りました。
例えば、SMA Length で200を選び、MT Timeframeで5分を選べば、1分足タイムフレームでトレードしていて雲行きが怪しくなってくるとBGが赤になり、5分足では200線以下に突入しているようだと把握することができます。
VEP - Volume Explosion Predictor💥 VEP - Volume Explosion Predictor
General Overview
The Volume Explosion Predictor (VEP) is an advanced indicator that analyzes volume peaks to predict when the next volume explosion might occur. Using statistical analysis on historical patterns, it provides accurate probabilities on moments of greater trading activity.
MAIN FEATURES
🎯 Intelligent volume peak detection
Automatically identifies significant volume peaks
Anti-consecutive filter to avoid redundant signals
Customizable threshold for detection sensitivity
📊 Advanced statistical analysis
Calculates the average distance between volume peaks
Monitors the number of sessions without peaks
Tracks the maximum historical range without activity
🔮 Predictive system
Dynamic probability: Calculates the probability of an imminent peak
Visual indicators: Background colors that change based on probability
Time forecasts: Estimates remaining sessions to the next peak
📈 Visual signals
Colored arrows: Green for bullish peaks, red for bearish peaks
Statistics table: Complete real-time overview
ALERT SYSTEM
🚨 Three Alert Levels
New Valid Volume Peak: New peak detected
Approaching Prediction: Increasing probability
High Peak Probability: High probability of explosion
HOW TO USE IT
📋 Recommended setup
Timeframe : Works on all timeframes but daily, weekly or monthly timeframe usage is recommended. In any case, it should always be used consistently with your time horizon
Markets : Stocks, crypto, forex, commodities
Threshold for volume peak realization : It's recommended to start with 2.0x (i.e., twice the volume average) for normal markets, 1.5x for more volatile markets. This parameter can be set in the settings as desired
🎨 Visual interpretation
Green Arrows : Peak during bullish candle
Red Arrows : Peak during bearish candle
Red Background : High probability (>90%) of new peak
Yellow Background : Medium probability (50-70%)
📊 STATISTICS TABLE
The table shows:
Total peaks analyzed
Average distance between peaks
Current sessions without peaks
Forecast remaining sessions
Percentage probability
Volume threshold needed for peak realization
STRATEGIC ADVANTAGES
🎯 For Day Traders
Anticipates moments of greater volatility for analysis, supporting the evaluation of trading setups and providing context on low volume periods
📈 For Swing Traders
Identifies high-probability volume patterns, supporting breakout analysis with volume and improving understanding of market timing
🔍 For Technical Analysts
Understands the stock's volume patterns.
Helps evaluate the historical market interest and supports quantitative research and analysis
OTHER THINGS TO KNOW...
A) Anti-Consecutive Algorithm : allows to avoid multiple and consecutive volume signals and peaks at close range
B) Statistical Validation : Uses standard deviation for accuracy
C) Memory Management : Limits historical data for optimal performance
D) Compatibility : Works with all TradingView chart types
⚠️ IMPORTANT DISCLAIMER
This indicator is exclusively a technical analysis tool for studying volume patterns. It does not provide investment advice, trading signals or entry/exit points. All trading decisions are at the complete discretion and responsibility of the user. Always use in combination with other technical and fundamental analysis and proper risk management.
DESCRIZIONE IN ITALIANO
💥 VEP - Volume Explosion Predictor
Panoramica Generale
Il Volume Explosion Predictor (VEP) è un indicatore avanzato che analizza i picchi di volume per prevedere quando potrebbe verificarsi la prossima esplosione di volume. Utilizzando analisi statistiche sui pattern storici, fornisce probabilità accurate sui momenti di maggiore attività di trading.
CARATTERISTICHE PRINCIPALI
🎯 Rilevamento intelligente dei picchi di volume
- Identifica automaticamente i picchi di volume significativi
- Filtro anti-consecutivo per evitare segnali ridondanti
- Soglia personalizzabile per la sensibilità del rilevamento
📊 Analisi statistica avanzata
Calcola la distanza media tra i picchi di volume
Monitora il numero di sessioni senza picchi
Traccia il range massimo storico senza attività
🔮 Sistema predittivo
Probabilità dinamica: Calcola la probabilità di un imminente picco
Indicatori visivi: Colori di sfondo che cambiano in base alla probabilità
Previsioni temporali: Stima delle sessioni rimanenti al prossimo picco
📈 Segnali visivi
1) Frecce colorate: Verdi per picchi rialzisti, rosse per ribassisti
2) Tabella statistiche: Panoramica completa in tempo reale
SISTEMA DI ALERT
🚨 Tre Livelli di Alert
1) New Valid Volume Peak: Nuovo picco rilevato
2) Approaching Prediction: Probabilità in aumento
3) High Peak Probability: Alta probabilità di esplosione
COME UTILIZZARLO
📋 Setup consigliato
- Timeframe : Funziona su tutti i timeframe ma è consigliabile un utilizzo su timeframe giornaliero, settimanale o mensile. In ogni caso va sempre utilizzato coerentemente con il proprio orizzonte temporale
- Mercati : Azioni, crypto, forex, commodities
- Limite affinché si realizzi il picco di volumi : Si consiglia di iniziare con 2.0x (ovvero due volte la media dei volumi) per mercati normali, 1.5x per mercati più volatili. Questo parametro può essere settato nelle impostazioni a proprio piacimento
🎨 Interpretazione visuale
Frecce Verdi : Picco durante candela rialzista
Frecce Rosse : Picco durante candela ribassista
Sfondo Rosso : Alta probabilità (>90%) di nuovo picco
Sfondo Giallo : Probabilità media (50-70%)
📊 TABELLA STATISTICHE
La tabella mostra:
1. Totale picchi analizzati
2. Distanza media tra picchi
3. Sessioni attuali senza picchi
4. Previsione sessioni rimanenti
5. Probabilità percentuale
6. Soglia volume necessaria affinché si realizzi il picco di volumi
VANTAGGI STRATEGICI
🎯 Per Day Traders
Anticipa i momenti di maggiore volatilità per analisi, supportando la valutazione dei setup di trading e fornendo al contempo un contesto sui periodi di basso volume
📈 Per Swing Traders
1. Identifica pattern di volume ad alta probabilità, supportando l'analisi dei breakout con volume e migliorando la comprensione dei tempi di mercato
🔍 Per Analisti Tecnici
Comprende i pattern di volume del titolo.
Aiuta a fare una valutazione dell'interesse storico del mercato ed è di supporto alla ricerca e analisi quantitativa
ALTRE COSE DA SAPERE...
A) Algoritmo Anti-Consecutivo : permette di evitare segnali e picchi di volume multipli e consecutivi multipli a distanza ravvicinata
B) Validazione Statistica : Utilizza deviazione standard per l'accuratezza
C) Gestione Memoria : Limita i dati storici per performance ottimali
D) Compatibilità : Funziona con tutti i tipi di grafico TradingView
⚠️ DISCLAIMER IMPORTANTE
Questo indicatore è esclusivamente uno strumento di analisi tecnica per lo studio dei pattern di volume. Non fornisce consigli di investimento, segnali di trading o punti di ingresso/uscita. Tutte le decisioni di trading sono a completa discrezione e responsabilità dell'utente. Utilizzare sempre in combinazione con altre analisi tecniche, fondamentali e una adeguata gestione del rischio.
Volumen Consolidado Exchanges [JoseMetal]============
ENGLISH
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- General description:
This is a consolidated volume indicator that allows you to pick up to 10 exchanges to consolidate volume, which can be displayed split or merged.
- Features:
Shows per-exchange volume with custom exchange selection.
Able to toggle on/off each exchange.
Able to customize color for each exchange.
Toggleable total (sum) volume with custom SMA.
- Visual:
Volume is sorted from highest to lowest, so you can see every single exchange's color volume.
Accumulated volume is white, and SMA is red.
- Recommendations:
Perfect for trading with volume strategies or using as confirmation with order blocks or FVGs.
============
ESPAÑOL
============
- Descripción general:
Este es un indicador de volumen consolidado que permite seleccionar hasta 10 exchanges para consolidar el volumen, el cual puede mostrarse dividido o fusionado.
- Características:
Muestra el volumen por exchange con selección personalizada de exchanges.
Posibilidad de activar/desactivar cada exchange.
Posibilidad de personalizar el color de cada exchange.
Volumen total (suma) activable/desactivable con SMA personalizable.
- Visual:
El volumen se ordena de mayor a menor, de forma que puedes ver el volumen de color de cada exchange individual.
El volumen acumulado es blanco, y la SMA es roja.
- Recomendaciones:
Perfecto para operar con estrategias de volumen o usar como confirmación con order blocks o FVGs.
KST Strategy [Skyrexio]Overview
KST Strategy leverages Know Sure Thing (KST) indicator in conjunction with the Williams Alligator and Moving average to obtain the high probability setups. KST is used for for having the high probability to enter in the direction of a current trend when momentum is rising, Alligator is used as a short term trend filter, while Moving average approximates the long term trend and allows trades only in its direction. Also strategy has the additional optional filter on Choppiness Index which does not allow trades if market is choppy, above the user-specified threshold. Strategy has the user specified take profit and stop-loss numbers, but multiplied by Average True Range (ATR) value on the moment when trade is open. The strategy opens only long trades.
Unique Features
ATR based stop-loss and take profit. Instead of fixed take profit and stop-loss percentage strategy utilizes user chosen numbers multiplied by ATR for its calculation.
Configurable Trading Periods. Users can tailor the strategy to specific market windows, adapting to different market conditions.
Optional Choppiness Index filter. Strategy allows to choose if it will use the filter trades with Choppiness Index and set up its threshold.
Methodology
The strategy opens long trade when the following price met the conditions:
Close price is above the Alligator's jaw line
Close price is above the filtering Moving average
KST line of Know Sure Thing indicator shall cross over its signal line (details in justification of methodology)
If the Choppiness Index filter is enabled its value shall be less than user defined threshold
When the long trade is executed algorithm defines the stop-loss level as the low minus user defined number, multiplied by ATR at the trade open candle. Also it defines take profit with close price plus user defined number, multiplied by ATR at the trade open candle. While trade is in progress, if high price on any candle above the calculated take profit level or low price is below the calculated stop loss level, trade is closed.
Strategy settings
In the inputs window user can setup the following strategy settings:
ATR Stop Loss (by default = 1.5, number of ATRs to calculate stop-loss level)
ATR Take Profit (by default = 3.5, number of ATRs to calculate take profit level)
Filter MA Type (by default = Least Squares MA, type of moving average which is used for filter MA)
Filter MA Length (by default = 200, length for filter MA calculation)
Enable Choppiness Index Filter (by default = true, setting to choose the optional filtering using Choppiness index)
Choppiness Index Threshold (by default = 50, Choppiness Index threshold, its value shall be below it to allow trades execution)
Choppiness Index Length (by default = 14, length used in Choppiness index calculation)
KST ROC Length #1 (by default = 10, value used in KST indicator calculation, more information in Justification of Methodology)
KST ROC Length #2 (by default = 15, value used in KST indicator calculation, more information in Justification of Methodology)
KST ROC Length #3 (by default = 20, value used in KST indicator calculation, more information in Justification of Methodology)
KST ROC Length #4 (by default = 30, value used in KST indicator calculation, more information in Justification of Methodology)
KST SMA Length #1 (by default = 10, value used in KST indicator calculation, more information in Justification of Methodology)
KST SMA Length #2 (by default = 10, value used in KST indicator calculation, more information in Justification of Methodology)
KST SMA Length #3 (by default = 10, value used in KST indicator calculation, more information in Justification of Methodology)
KST SMA Length #4 (by default = 15, value used in KST indicator calculation, more information in Justification of Methodology)
KST Signal Line Length (by default = 10, value used in KST indicator calculation, more information in Justification of Methodology)
User can choose the optimal parameters during backtesting on certain price chart.
Justification of Methodology
Before understanding why this particular combination of indicator has been chosen let's briefly explain what is KST, Williams Alligator, Moving Average, ATR and Choppiness Index.
The KST (Know Sure Thing) is a momentum oscillator developed by Martin Pring. It combines multiple Rate of Change (ROC) values, smoothed over different timeframes, to identify trend direction and momentum strength. First of all, what is ROC? ROC (Rate of Change) is a momentum indicator that measures the percentage change in price between the current price and the price a set number of periods ago.
ROC = 100 * (Current Price - Price N Periods Ago) / Price N Periods Ago
In our case N is the KST ROC Length inputs from settings, here we will calculate 4 different ROCs to obtain KST value:
KST = ROC1_smooth × 1 + ROC2_smooth × 2 + ROC3_smooth × 3 + ROC4_smooth × 4
ROC1 = ROC(close, KST ROC Length #1), smoothed by KST SMA Length #1,
ROC2 = ROC(close, KST ROC Length #2), smoothed by KST SMA Length #2,
ROC3 = ROC(close, KST ROC Length #3), smoothed by KST SMA Length #3,
ROC4 = ROC(close, KST ROC Length #4), smoothed by KST SMA Length #4
Also for this indicator the signal line is calculated:
Signal = SMA(KST, KST Signal Line Length)
When the KST line rises, it indicates increasing momentum and suggests that an upward trend may be developing. Conversely, when the KST line declines, it reflects weakening momentum and a potential downward trend. A crossover of the KST line above its signal line is considered a buy signal, while a crossover below the signal line is viewed as a sell signal. If the KST stays above zero, it indicates overall bullish momentum; if it remains below zero, it points to bearish momentum. The KST indicator smooths momentum across multiple timeframes, helping to reduce noise and provide clearer signals for medium- to long-term trends.
Next, let’s discuss the short-term trend filter, which combines the Williams Alligator and Williams Fractals. Williams Alligator
Developed by Bill Williams, the Alligator is a technical indicator that identifies trends and potential market reversals. It consists of three smoothed moving averages:
Jaw (Blue Line): The slowest of the three, based on a 13-period smoothed moving average shifted 8 bars ahead.
Teeth (Red Line): The medium-speed line, derived from an 8-period smoothed moving average shifted 5 bars forward.
Lips (Green Line): The fastest line, calculated using a 5-period smoothed moving average shifted 3 bars forward.
When the lines diverge and align in order, the "Alligator" is "awake," signaling a strong trend. When the lines overlap or intertwine, the "Alligator" is "asleep," indicating a range-bound or sideways market. This indicator helps traders determine when to enter or avoid trades.
The next indicator is Moving Average. It has a lot of different types which can be chosen to filter trades and the Least Squares MA is used by default settings. Let's briefly explain what is it.
The Least Squares Moving Average (LSMA) — also known as Linear Regression Moving Average — is a trend-following indicator that uses the least squares method to fit a straight line to the price data over a given period, then plots the value of that line at the most recent point. It draws the best-fitting straight line through the past N prices (using linear regression), and then takes the endpoint of that line as the value of the moving average for that bar. The LSMA aims to reduce lag and highlight the current trend more accurately than traditional moving averages like SMA or EMA.
Key Features:
It reacts faster to price changes than most moving averages.
It is smoother and less noisy than short-term EMAs.
It can be used to identify trend direction, momentum, and potential reversal points.
ATR (Average True Range) is a volatility indicator that measures how much an asset typically moves during a given period. It was introduced by J. Welles Wilder and is widely used to assess market volatility, not direction.
To calculate it first of all we need to get True Range (TR), this is the greatest value among:
High - Low
abs(High - Previous Close)
abs(Low - Previous Close)
ATR = MA(TR, n) , where n is number of periods for moving average, in our case equals 14.
ATR shows how much an asset moves on average per candle/bar. A higher ATR means more volatility; a lower ATR means a calmer market.
The Choppiness Index is a technical indicator that quantifies whether the market is trending or choppy (sideways). It doesn't indicate trend direction — only the strength or weakness of a trend. Higher Choppiness Index usually approximates the sideways market, while its low value tells us that there is a high probability of a trend.
Choppiness Index = 100 × log10(ΣATR(n) / (MaxHigh(n) - MinLow(n))) / log10(n)
where:
ΣATR(n) = sum of the Average True Range over n periods
MaxHigh(n) = highest high over n periods
MinLow(n) = lowest low over n periods
log10 = base-10 logarithm
Now let's understand how these indicators work in conjunction and why they were chosen for this strategy. KST indicator approximates current momentum, when it is rising and KST line crosses over the signal line there is high probability that short term trend is reversing to the upside and strategy allows to take part in this potential move. Alligator's jaw (blue) line is used as an approximation of a short term trend, taking trades only above it we want to avoid trading against trend to increase probability that long trade is going to be winning.
Almost the same for Moving Average, but it approximates the long term trend, this is just the additional filter. If we trade in the direction of the long term trend we increase probability that higher risk to reward trade will hit the take profit. Choppiness index is the optional filter, but if it turned on it is used for approximating if now market is in sideways or in trend. On the range bounded market the potential moves are restricted. We want to decrease probability opening trades in such condition avoiding trades if this index is above threshold value.
When trade is open script sets the stop loss and take profit targets. ATR approximates the current volatility, so we can make a decision when to exit a trade based on current market condition, it can increase the probability that strategy will avoid the excessive stop loss hits, but anyway user can setup how many ATRs to use as a stop loss and take profit target. As was said in the Methodology stop loss level is obtained by subtracting number of ATRs from trade opening candle low, while take profit by adding to this candle's close.
Backtest Results
Operating window: Date range of backtests is 2023.01.01 - 2025.05.01. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Initial capital: 10000 USDT
Percent of capital used in every trade: 60%
Maximum Single Position Loss: -5.53%
Maximum Single Profit: +8.35%
Net Profit: +5175.20 USDT (+51.75%)
Total Trades: 120 (56.67% win rate)
Profit Factor: 1.747
Maximum Accumulated Loss: 1039.89 USDT (-9.1%)
Average Profit per Trade: 43.13 USDT (+0.6%)
Average Trade Duration: 27 hours
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters.
How to Use
Add the script to favorites for easy access.
Apply to the desired timeframe and chart (optimal performance observed on 1h BTC/USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrexio commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation.
Quantum Fibonacci Flow
Quantum Fib Ribbon (QFLOW)
📖 How It Works
A three-band ribbon built from Fibonacci-scaled moving averages, filled and colored to reflect current momentum strength and direction.
Green when bullish flow is strong, red when bearish flow dominates, and orange in between to highlight slowing momentum.
⚙️ Key Controls
* Base Length: Adjusts the ribbon’s overall lookback.
* Ribbon Opacity: How solid or translucent the fill appears.
* Momentum Scale & Exponent: Fine-tune how sensitively the ribbon reacts to price speed versus volatility.
* Override Threshold: Determines at what momentum level the ribbon “snaps” to full green or red.
🚨 Over-Extension Logic
When price extends significantly above or below the ribbon, it often signals exhaustion.
The first return to the ribbon after such an extension frequently acts as strong support or resistance — offering high-probability trade setups.
🔺 Optional Trade Signals
Enable the over-extension alert to mark these key areas:
* A green triangle shows price extended below the ribbon, then retested → potential long.
* A red triangle shows price extended above, then retested → potential short.
🎯 How to Trade
• Breakout-Retest Setup: Watch for over-extended price moves. The first comeback to the ribbon often marks key levels of interest for a reversal or continuation.
Fourier Weighted Moving Average-(FWMA)Fourier Weighted Moving Average (FWMA)
About Fourier and His Theory
Joseph Fourier (1768–1830) was a French mathematician and physicist best known for his work on heat transfer and periodic functions. His most significant contribution to science is what we now call Fourier Analysis.
What Is Fourier's Theory?
Fourier’s theory states that:
Any repeating (periodic) signal or pattern can be broken down into a sum of simple sine and cosine waves.
This idea became the foundation of signal processing, modern physics, and data smoothing techniques — including those used in financial markets.
Key Concepts of Fourier’s Theory
1. Decomposition of Signals
Complex waveforms can be expressed as combinations of basic sine waves with different frequencies and amplitudes.
2. Frequency Domain View
Instead of viewing data in time (or price), you can analyze its frequency — how often certain movements repeat.
3. Smoothing and Filtering
By focusing only on certain frequencies (e.g., slower or longer cycles), Fourier methods allow you to filter out short-term noise and focus on the trend.
4. Applications in Finance
In trading, Fourier principles help design indicators that:
* Remove short-term market noise
* Emphasize dominant cycles
* Provide cleaner trend direction
Why It Matters for This Indicator
The Fourier Weighted Moving Average (FWMA) used in this indicator applies a custom weight derived from a sin² function, inspired by Fourier’s work on wave behavior. This gives more influence to the mid-section of the price data, making the average line smoother and more stable than traditional methods like SMA or EMA.
Unlike basic moving averages, the FWMA reacts to price changes more fluidly while reducing whipsaws, which is especially useful for trend-following strategies.
Input Settings and Controls
This section outlines all configurable fields and buttons available in the indicator, grouped for clarity:
Main Settings
* Source
Defines the price source used in the FWMA calculation. Options typically include close, open, hl2, etc.
* FWMA – 1 (Length)
Sets the period for the first Fourier Weighted Moving Average. Shorter lengths produce faster, more sensitive lines.
* FWMA – 2 (Length)
Sets the period for the second FWMA, typically used as a slower or long-term trend filter.
* Weight Epsilon
A small constant added to the weight formula to prevent division by zero and improve numeric stability in the FWMA formula.
Slope Sensitivity
* Slope Sensitivity (Bars)
This field defines the number of bars used to calculate the slope of each FWMA. The slope determines whether the line is rising or falling and is used to change the line color accordingly.
* Enable Slope Coloring (Toggle)
When enabled, both FWMA lines change color based on their slope:
* Positive slope = trend up color
* Negative slope = trend down color
If disabled, lines are shown in a neutral (gray) color.
Ribbon Settings (Group: Ribbon)
* Enable Ribbon for FWMA-2 (Toggle)
Turns the ribbon feature on or off. When enabled, the script plots two additional lines slightly above and below FWMA-2.
* Ribbon Thickness
Controls the line width of the ribbon above and below FWMA-2. Values from 1 to 100 are allowed, giving full control over ribbon visual prominence.
Contrarian 100 MAPairs nicely with Enhanced-Stock-Ticker-with-50MA-vs-200MA located here:
Description
The Contrarian 100 MA is a sophisticated Pine Script v6 indicator designed for traders seeking to identify key market structure shifts and trend reversals using a combination of a 100-period Simple Moving Average (SMA) envelope and Inner Circle Trader (ICT) Break of Structure (BoS) and Market Structure Shift (MSS) logic. By overlaying a semi-transparent SMA-based shadow on the price chart and plotting bullish and bearish structure signals, this indicator helps traders visualize critical price levels and potential trend changes. It leverages higher timeframe (HTF) pivot points and dynamic logic to adapt to various chart timeframes, making it ideal for swing and contrarian trading strategies. Customizable colors, timeframes, and alert conditions enhance its versatility for manual and automated trading setups.
Key Features
SMA Envelope: Plots a 100-period SMA for high and low prices, creating a semi-transparent (50% opacity) purple shadow to highlight the price range and provide context for price movements.
ICT BoS/MSS Logic: Identifies Break of Structure (BoS) and Market Structure Shift (MSS) signals for both bullish and bearish conditions, based on HTF pivot points.
Dynamic Timeframe Support: Adjusts pivot detection based on user-selected HTF (default: 1D) and chart timeframe (1M, 5M, 15M, 30M, 1H, 4H, 1D), ensuring adaptability across markets.
Visual Signals: Draws dotted lines for BoS (bullish/bearish) and MSS (bullish/bearish) signals at pivot levels, with customizable colors for easy identification.
Contrarian Approach: Signals potential reversals by combining SMA context with ICT structure breaks, ideal for traders looking to capitalize on trend shifts.
Alert Conditions: Supports alerts for bullish/bearish BoS and MSS signals, enabling integration with TradingView’s alert system for automated trading.
Performance Optimization: Uses efficient pivot detection and line management to minimize resource usage while maintaining accuracy.
Technical Details
SMA Calculation:
Computes 100-period SMAs for high (smaHigh) and low (smaLow) prices.
Plots invisible SMAs (fully transparent) and fills the area between them with 50% transparent purple for visual context.
Pivot Detection:
Uses ta.pivothigh and ta.pivotlow to identify HTF swing points, with dynamic lookback periods (rlBars: 5 for daily, 2 for intraday).
Tracks pivot highs (pH, nPh) and lows (pL, nPl) using a custom piv type for price and time.
BoS/MSS Logic:
Bullish BoS: Triggered when price breaks above a pivot high in a bullish trend, drawing a line at the pivot level.
Bearish BoS: Triggered when price breaks below a pivot low in a bearish trend.
Bullish MSS: Occurs when price breaks a pivot high in a bearish trend, signaling a potential trend reversal.
Bearish MSS: Occurs when price breaks a pivot low in a bullish trend.
Lines are drawn using line.new with xloc.bar_time for precise alignment, styled as dotted with customizable colors.
HTF Integration: Fetches HTF close prices and pivot data using request.security with lookahead_on for accurate signal timing.
Line Management: Maintains an array of lines (lin), removing outdated lines when new MSS signals occur to keep the chart clean.
Pivot Reset: Clears broken pivots (e.g., when price exceeds a pivot high or falls below a pivot low) to ensure fresh signal generation.
How to Use
Add to Chart:
Copy the script into TradingView’s Pine Editor and apply it to your chart.
Configure Settings:
SMA Length: Adjust the SMA period (default: 100 bars) to suit your trading style.
Structure Timeframe: Set the HTF for pivot detection (default: 1D).
Chart Timeframe: Select the chart timeframe (1M, 5M, 15M, 30M, 1H, 4H, 1D) to adjust pivot sensitivity.
Colors: Customize bullish/bearish BoS and MSS line colors via input settings.
Interpret Signals:
Bullish BoS: White dotted line (default) at a broken pivot high in a bullish trend, indicating trend continuation.
Bearish BoS: White dotted line at a broken pivot low in a bearish trend.
Bullish MSS: White dotted line at a broken pivot high in a bearish trend, suggesting a reversal to bullish.
Bearish MSS: White dotted line at a broken pivot low in a bullish trend, suggesting a reversal to bearish.
Use the SMA shadow to gauge price position within the recent range.
Set Alerts:
Create alerts for bullish/bearish BoS and MSS signals using TradingView’s alert system.
Customize Visuals:
Adjust line colors or SMA fill transparency via TradingView’s settings for better visibility.
Example Use Cases
Swing Trading: Use MSS signals to enter trades at potential trend reversals, with the SMA envelope confirming price extremes.
Contrarian Trading: Capitalize on BoS and MSS signals to trade against prevailing trends, using the SMA shadow for context.
Automated Trading: Integrate BoS/MSS alerts with trading bots for systematic entries and exits.
Multi-Timeframe Analysis: Combine HTF signals (e.g., 1D) with lower timeframe charts (e.g., 1H) for precise entries.
Notes
Testing: Backtest the indicator on your chosen market and timeframe to validate performance.
Compatibility: Built for Pine Script v6 and tested on TradingView as of June 19, 2025.
Limitations: Signals rely on HTF pivot accuracy, which may lag in fast-moving markets. Adjust rlBars or timeframe for sensitivity.
Optional Enhancements: Consider uncommenting or adding a histogram for SMA divergence (e.g., smaHigh - smaLow) for additional insights.
Acknowledgments
This indicator combines ICT’s market structure concepts with a dynamic SMA envelope to provide a unique contrarian trading tool. Share your feedback or suggestions in the TradingView comments, and happy trading!
Trend Blend
Trend blend is my new indicator. I use it to identify my bias when trading and filter out fake setups that are going in the wrong direction.
Trend blend utilises the 9 EMA (Red), 21 EMA (Black), and if you trade futures or Bitcoin, you can also use the VWAP (Blue).
There is also a table at the top right that displays the chart time frame bias
I prefer to use the 1-hour time frame for bias and execute the trades on 5-minute charts, mainly, and sometimes on the 1-minute for a smaller stoploss.
Here's an example of the trade I took during the London session on XAU/USD
1 hour bias was Bearish
Price broke out of the range
I waited for the London session to open, where I ended up taking a short on the 5-minute time frame as we broke out of the pre-London range
Entry was at the Fair Value Gap (5-minute bias was also Bearish as price traded into the FVG)
Stoploss was at the last high
Take Profit was the next major support level
Another set that I like to trade with the Trend blend is when price is trending bullish and price trades inside the 9 and 21 EMA, and there is a bullish candle closer above the 9 EMA with Stoploss below the low of the bullish candle and Take profit between 1-2 Risk to Reward
Same when there's a bearish trend, I wait for price to trade inside the 9 and 21 EMA, and I'll take sells when a bearish candle closes below the 9 EMA.
This setup works best in strong trends, or it can be used to enter a trade on a pullback or to scale into an existing trade.
PRO Investing - LevelPRO Investing - Level
📊 Dynamic Support/Resistance
This indicator plots the PRO Investing Level, defined as the midpoint between the highest high and lowest low over the past 252 trading days (default lookback period, equivalent to ~1 year). It acts as a key mean-reversion reference level, useful for identifying potential support/resistance zones or market equilibrium levels.
Features:
🕰️ Option to display only today’s level or historical levels.
⚙️ Customizable lookback period for flexibility across timeframes and strategies.
📉 Teal line plotted directly on the chart, highlighting this institutional-grade level.
Ideal for traders looking to anchor price action to significant historical ranges—particularly useful in mean-reversion, breakout, or volatility compression strategies.
OBV with MA & Bollinger Bands by Marius1032OBV with MA & Bollinger Bands by Marius1032
This script adds customizable moving averages and Bollinger Bands to the classic OBV (On Balance Volume) indicator. It helps identify volume-driven momentum and trend strength.
Features:
OBV-based trend tracking
Optional smoothing: SMA, EMA, RMA, WMA, VWMA
Optional Bollinger Bands with SMA
Potential Combinations and Trading Strategies:
Breakouts: Look for price breakouts from the Bollinger Bands, and confirm with a rising OBV for an uptrend or falling OBV for a downtrend.
Trend Reversals: When the price touches a Bollinger Band, examine the OBV for divergence. A bullish divergence (price lower low, OBV higher low) near the lower band could signal a reversal.
Volume Confirmation: Use OBV to confirm the strength of the trend indicated by Bollinger Bands. For example, if the BBs indicate an uptrend and OBV is also rising, it reinforces the bullish signal.
1. On-Balance Volume (OBV):
Purpose: OBV is a momentum indicator that uses volume flow to predict price movements.
Calculation: Volume is added on up days and subtracted on down days.
Interpretation: Rising OBV suggests potential upward price movement. Falling OBV suggests potential lower prices.
Divergence: Divergence between OBV and price can signal potential trend reversals.
2. Moving Average (MA):
Purpose: Moving Averages smooth price fluctuations and help identify trends.
Combination with OBV: Pairing OBV with MAs helps confirm trends and identify potential reversals. A crossover of the OBV line and its MA can signal a trend reversal or continuation.
3. Bollinger Bands (BB):
Purpose: BBs measure market volatility and help identify potential breakouts and trend reversals.
Structure: They consist of a moving average (typically 20-period) and two standard deviation bands.
Combination with OBV: Combining BBs with OBV allows for a multifaceted approach to market analysis. For example, a stock hitting the lower BB with a rising OBV could indicate accumulation and a potential upward reversal.
Created by: Marius1032
Chebyshev-Gauss Convergence DivergenceThe Chebyshev-Gauss Convergence Divergence is a momentum indicator that leverages the Chebyshev-Gauss Moving Average (CG-MA) to provide a smoother and more responsive alternative to traditional oscillators like the MACD. For more information see the moving average script:
How it works:
It calculates a fast CG-MA and a slow CG-MA. The CG-MA uses Gauss-Chebyshev quadrature to compute a weighted average, which can offer a better trade-off between lag and smoothness compared to simple or exponential MAs.
The Oscillator line is the difference between the fast CG-MA and the slow CG-MA.
A Signal Line, which is a simple moving average of the Oscillator line, is plotted to show the average trend of the oscillator.
A Histogram is plotted, representing the difference between the Oscillator and the Signal Line. The color of the histogram bars changes to indicate whether momentum is strengthening or weakening.
How to use:
Crossovers: A buy signal can be generated when the Oscillator line crosses above the Signal line. A sell signal can be generated when it crosses below.
Zero Line: When the Oscillator crosses above the zero line, it indicates upward momentum (fast MA is above slow MA).When it crosses below zero, it indicates downward momentum.
Divergence: Like with the MACD, look for divergences between the oscillator and price action to spot potential reversals.
Histogram: The histogram provides a visual representation of the momentum. When the bars are growing, momentum is increasing. When they are shrinking, momentum is fading.
CGMALibrary "CGMA"
This library provides a function to calculate a moving average based on Chebyshev-Gauss Quadrature. This method samples price data more intensely from the beginning and end of the lookback window, giving it a unique character that responds quickly to recent changes while also having a long "memory" of the trend's start. Inspired by reading rohangautam.github.io
What is Chebyshev-Gauss Quadrature?
It's a numerical method to approximate the integral of a function f(x) that is weighted by 1/sqrt(1-x^2) over the interval . The approximation is a simple sum: ∫ f(x)/sqrt(1-x^2) dx ≈ (π/n) * Σ f(xᵢ) where xᵢ are special points called Chebyshev nodes.
How is this applied to a Moving Average?
A moving average can be seen as the "mean value" of the price over a lookback window. The mean value of a function with the Chebyshev weight is calculated as:
Mean = /
The math simplifies beautifully, resulting in the mean being the simple arithmetic average of the function evaluated at the Chebyshev nodes:
Mean = (1/n) * Σ f(xᵢ)
What's unique about this MA?
The Chebyshev nodes xᵢ are not evenly spaced. They are clustered towards the ends of the interval . We map this interval to our lookback period. This means the moving average samples prices more intensely from the beginning and the end of the lookback window, and less intensely from the middle. This gives it a unique character, responding quickly to recent changes while also having a long "memory" of the start of the trend.
Chebyshev-Gauss Moving AverageThis indicator applies the principles of Chebyshev-Gauss Quadrature to create a novel type of moving average. Inspired by reading rohangautam.github.io
What is Chebyshev-Gauss Quadrature?
It's a numerical method to approximate the integral of a function f(x) that is weighted by 1/sqrt(1-x^2) over the interval . The approximation is a simple sum: ∫ f(x)/sqrt(1-x^2) dx ≈ (π/n) * Σ f(xᵢ) where xᵢ are special points called Chebyshev nodes.
How is this applied to a Moving Average?
A moving average can be seen as the "mean value" of the price over a lookback window. The mean value of a function with the Chebyshev weight is calculated as:
Mean = /
The math simplifies beautifully, resulting in the mean being the simple arithmetic average of the function evaluated at the Chebyshev nodes:
Mean = (1/n) * Σ f(xᵢ)
What's unique about this MA?
The Chebyshev nodes xᵢ are not evenly spaced. They are clustered towards the ends of the interval . We map this interval to our lookback period. This means the moving average samples prices more intensely from the beginning and the end of the lookback window, and less intensely from the middle. This gives it a unique character, responding quickly to recent changes while also having a long "memory" of the start of the trend.
ATR% Multiple from MAThis indicator builds upon the original idea by jfsrevg of using the ATR% multiple from a daily 50-period moving average to highlight when a stock or instrument is extended relative to its own volatility. My version expands on this by incorporating an ADR% (Average Daily Range percentage) volatility filter, which helps refine the signals to adapt better to different instruments and timeframes.
What it does:
• Calculates the 50-period simple moving average (SMA) using daily data as the baseline trend reference.
• Measures the instrument’s Average True Range (ATR) relative to the current close (ATR%).
• Uses this ratio to identify when an instrument is significantly extended above its average volatility-based range.
• Adds a dynamic ADR% filter — computed as the average daily range divided by the daily close — to adjust the extension threshold dynamically based on recent price volatility.
• Plots small circles above price bars when extension conditions are met, signaling potential overbought conditions.
•The script works on both daily and weekly timeframes, but all volatility calculations are based on daily data to ensure consistency.
How to use:
• Traders can use this indicator to spot when a stock or instrument is significantly stretched relative to its own volatility, which may signal a good time to scale out or manage risk.
• The dynamic ADR% filter helps reduce false positives by adjusting thresholds based on market conditions.
• Use the customizable settings for ATR length, SMA length, and ADR length to fine-tune the indicator for your preferred instruments.
Original Contributions:
• Integrated an ADR% filter that refines the extension threshold based on real-time volatility.
• Added dynamic thresholds that adapt to market conditions, making the indicator more reliable across different instruments and timeframes.
• Maintained daily volatility calculations while allowing signals to appear on both daily and weekly charts.
Advanced Moving Average ChannelAdvanced Moving Average Channel (MAC) is a comprehensive technical analysis tool that combines multiple moving average types with volume analysis to provide a complete market perspective.
Key Features:
1. Dynamic Channel Formation
- Configurable moving average types (SMA, EMA, WMA, VWMA, HMA, TEMA)
- Separate upper and lower band calculations
- Customizable band offsets for precise channel adjustment
2. Volume Analysis Integration
- Multi-timeframe volume analysis (1H, 24H, 7D)
- Relative volume comparison against historical averages
- Volume trend detection with visual indicators
- Price-level volume distribution profile
3. Market Context Indicators
- RSI integration for overbought/oversold conditions
- Channel position percentage
- Volume-weighted price levels
- Breakout detection with visual signals
Usage Guidelines:
1. Channel Interpretation
- Price within channel: Normal market conditions
- Price above upper band: Potential overbought condition
- Price below lower band: Potential oversold condition
- Channel width: Indicates market volatility
2. Volume Analysis
- High relative volume (>150%): Strong market interest
- Low relative volume (<50%): Weak market interest
- Volume trend arrows: Indicate increasing/decreasing market participation
- Volume profile: Shows price levels with highest trading activity
3. Trading Signals
- Breakout arrows: Potential trend continuation
- RSI extremes: Confirmation of overbought/oversold conditions
- Volume confirmation: Validates price movements
Customization:
- Adjust MA length for different market conditions
- Modify band offsets for tighter/looser channels
- Fine-tune volume analysis parameters
- Customize visual appearance
This indicator is designed for traders who want to combine price action, volume analysis, and market structure in a single, comprehensive tool.
