Moving Average Channel Avancé# Moving Average Channel Avancé (MAC)
This versatile TradingView indicator provides a dynamic channel around a central moving average, offering a comprehensive tool for trend identification, volatility assessment, and potential entry/exit signals.
## Key Features:
* **Flexible Moving Average Core:** Choose from a variety of popular moving average types (SMA, EMA, WMA, VWMA, HMA, TEMA) to serve as the baseline for your channel. Customize the length and price source for tailored analysis.
* **Multiple Channel Calculation Methods:**
* **Standard Deviation:** Creates Bollinger Band-like channels based on price volatility.
* **ATR (Average True Range):** Generates Keltner Channel-style bands that adapt to market volatility.
* **Percentage:** Defines channel width as a fixed percentage of the moving average.
* **Donchian:** Uses highest highs and lowest lows over a specified period to form the channel.
* **Visual Customization:**
* Toggle visibility of the midline, channel fill, and breakout signals.
* Full color customization for upper/lower bands, midline, channel fill, and bullish/bearish breakout signals.
* **Breakout Signals:** Displays arrows when the price crosses above the lower band (potential buy) or below the upper band (potential sell).
* **Overbought/Oversold Visualization:** Bar coloring highlights potential overbought (price near upper band) and oversold (price near lower band) conditions.
* **Information Panel:** A convenient on-chart table displays the selected MA type and the current price position within the channel as a percentage.
* **Alert Conditions:** Set up alerts for:
* Price crossing above/below the upper band.
* Price crossing above/below the lower band.
* Overbought and oversold conditions.
## How to Use:
The Moving Average Channel Avancé can be used in various ways:
* **Trend Following:** Trade in the direction of the channel. When the price is consistently above the midline and respecting the lower band as support, it can indicate an uptrend. Conversely, price action below the midline, with the upper band acting as resistance, can suggest a downtrend.
* **Volatility Breakouts:** Look for price breakouts above the upper band or below the lower band as potential entry signals, especially when accompanied by increased volume.
* **Mean Reversion:** In ranging markets, prices may tend to revert towards the central moving average after touching the outer bands.
* **Support and Resistance:** The channel bands can act as dynamic levels of support and resistance.
This indicator is designed to be intuitive for novice traders while offering the depth of customization that experienced analysts require. Experiment with different settings and MA types to find what best suits your trading style and the specific market you are analyzing.
Moving_average
Custom MAs (Multi-Timeframe, 5x MA, EMA/SMA/WMA/RMA)Multi-Timeframe Moving Averages (Per-TF, Per-Type, Clean Labels)
This script allows you to plot up to five customizable moving averages, each with:
✅ Independent timeframe (chart or fixed)
✅ Independent MA type (EMA, SMA, WMA, RMA)
✅ Custom color, length, and visibility
✅ Optional visual smoothing using a second MA layer
✅ Clean, informative labels (e.g. EMA 50 @ 1D)
✅ Grouped settings for ease of use
Use this to track key MAs from higher or lower timeframes without switching charts, build trend overlays, or monitor cross-timeframe confluence zones.
Designed to be clean, accurate, and highly flexible — no clutter, no unnecessary features.
wealthwalk📊 Key Features in This Script
Smart Signals (Buy/Sell Alerts)
Market Structure (CHoCH/BOS)
Identifies swing highs/lows (HH, LH, HL, LL).
Detects Break of Structure (BOS) and Change of Character (CHoCH).
🔰 BUY Signal Guidance
You should consider BUYING when:
Bullish Signal Appears:
A "Buy" label is plotted on the chart (enabled via Smart Signals).
This implies a bullish crossover, signaling upward momentum.
Multi-Timeframe Table is Bullish (if enabled):
If the majority of the trends in the table (5min, 15min, 1h, etc.) are green ("Bullish"), it adds strength to the BUY signal.
SELL Signal Guidance
You should consider SELLING (or SHORTING) when:
✅ Confirmation Tips
To improve reliability of your entries:
Wait for candle close confirmation above/below bands.
Use swing points & BOS/CHoCH labels (if enabled) to spot higher highs/lower lows.
Combine signals with basic volume or candlestick patterns for better accuracy.
Always set stop-loss beyond recent swing points or bands.
MA Dispersion+MA Dispersion+ — read the “breathing space” between your moving-averages
Get instant feedback on trend strength, volatility expansion and mean-reversion — across any timeframe.
MA Dispersion+ turns the humble moving-average stack into a single, easy-to-read oscillator that tells you at a glance whether price is coiling or fanning out.
🧩 What it does
Plugs into your favourite MA setup
• Pick the classic 5 / 20 / 50 / 200 lengths or disable any combination with one click.
• Choose the MA engine you trust — SMA, EMA, RMA, VWMA or WMA.
• Works on any timeframe thanks to TradingView’s security() engine.
Measures “spread”
For every bar it calculates the absolute distance of each selected MA from their average.
The tighter the stack, the lower the value; the wider the fan, the higher the value.
Adds professional-grade controls
• Weighting — let short-term MAs dominate (Inverse Length), keep everything equal, or dial in your own custom weights.
• Normalisation — convert the raw distance into a percentage of price, ATR multiples, or scale by the MAs’ own mean so you can compare symbols of any price or volatility.
🔍 How traders use it
Trend confirmation – rising dispersion while price breaks out = momentum is genuine.
Volatility squeeze – dispersion parking near zero warns that a big move is loading.
Multi-TF outlook – drop one pane per timeframe (e.g. 5 m, 1 h, 1 D) and see which layer of the market is driving.
Mean-reversion plays – spikes that fade quickly often coincide with exhaustion and snap-backs.
⚙️ Quick-start
Add MA Dispersion+ to your chart.
Set the pane’s timeframe in the first input.
Tick the MA lengths you actually use.
(Optional) Pick a weighting scheme and a normaliser.
Repeat the indicator for as many timeframes as you like — each instance keeps its own settings.
✨ Why you’ll love it
Zero clutter – one orange line tells you what four separate MAs whisper.
Configurable yet bullet-proof – all lengths are hard-coded constants, so Pine never complains.
Context aware – normalisation lets you compare BTC’s $60 000 chaos with EURUSD’s four--decimals calm.
Lightweight – no labels, no drawings, no background processing — perfect for mobile and multi-pane layouts.
Give MA Dispersion+ a try and let your charts breathe — you’ll never look at moving-average ribbons the same way again.
Happy trading!
fxdeal delta zoneescription:
The "Delta Zones Buy/Sell Pressure" indicator, created by the original author "scarf", is a technical tool that unveils key areas of buying and selling pressure in the market. This indicator utilizes the concept of Delta, calculating differences between open, close, high, and low prices. When these differences exceed a threshold determined by the user-defined standard deviation, areas of intense buying (indicated by green boxes) and selling pressure (indicated by red boxes) on the chart are identified.
How It Works:
The indicator calculates Delta using various combinations of candle prices to determine buying and selling pressure. When Delta surpasses a certain level, indicated by the user-defined standard deviation, visual signals in the form of boxes on the chart are generated. These boxes highlight specific areas where buying or selling pressure is particularly strong, aiding traders in identifying potential entry and exit points in the market.
CAN INDICATORCAN Moving Averages Indicator - Feature Guide
1. Multiple Moving Averages (20 MAs)
- Supports up to 20 individual moving averages
- Each MA can be independently configured:
- Enable/Disable toggle
- Length (period) setting
- Type selection (SMA, EMA, DEMA, VWMA, RMA, WMA)
- Color customization
- Individual timeframe settings when global timeframe is disabled
Pre-configured MA Settings:
1. MA1-8: SMA type
- Lengths: 20, 50, 100, 200, 365, 489, 600, 1460
2. MA9-20: EMA type
- Lengths: 30, 60, 120, 240, 300, 400, 500, 700, 800, 900, 1000, 2000
2. Global Timeframe Settings
Location: Global Settings group
Features:
- Use Global Timeframe: Toggle to use one timeframe for all MAs
- Global Timeframe: Select the timeframe to apply globally
3. Label Display Options
Location: Main Inputs section
Controls:
- Show MA Type: Display MA type (SMA, EMA, etc.)
- Show MA Length: Display period length
- Show Resolution: Display timeframe
- Label Offset: Adjust label position
4. Cross Alerts System
Location: Cross Alerts group
Features:
1. Price Crosses:
- Alerts when price crosses any selected MA
- Select MA to monitor (1-20)
- Triggers on crossover/crossunder
2. MA Crosses:
- Alerts when one MA crosses another
- Select fast MA (1-20)
- Select slow MA (1-20)
- Triggers on crossover/crossunder
5. Relative Strength (RS) Analysis
Location: Relative Strength group
Features:
- Select any MA to monitor (1-20)
- Compares MA to its own average
- Adjustable RS Length (default 14)
- Visual feedback via background color:
- Green: MA above its average (uptrend)
- Red: MA below its average (downtrend)
- Customizable colors and transparency
6. Moving Average Types Available
1. **SMA** (Simple Moving Average)
- Equal weight to all prices
2. **EMA** (Exponential Moving Average)
- More weight to recent prices
3. **DEMA** (Double Exponential Moving Average)
- Reduced lag compared to EMA
4. **VWMA** (Volume Weighted Moving Average)
- Incorporates volume data
5. **RMA** (Running Moving Average)
- Smoother than EMA
6. **WMA** (Weighted Moving Average)
- Linear weight distribution
Usage Tips
1. **For Trend Following:**
- Enable longer-period MAs (MA4-MA8)
- Use cross alerts between long-term MAs
- Monitor RS for trend strength
2. **For Short-term Trading:**
- Focus on shorter-period MAs (MA1-MA3, MA9-MA11)
- Enable price cross alerts
- Use multiple timeframe analysis
3. **For Multiple Timeframe Analysis:**
- Disable global timeframe
- Set different timeframes for each MA
- Compare MA relationships across timeframes
4. **For Performance:**
- Disable unused MAs
- Limit active alerts to necessary pairs
- Use RS selectively on key MAs
Dumb Money ConceptUse in 1 minute timeframe
1. Strategy setup
Name & sizing: Trades 25% of your account on each signal, assumes 0.04% commission + 2‑tick slippage, starts with a notional 10 million.
Timing: Only makes decisions at each 1‑minute bar close, and processes orders at bar‑close.
2. Optional filters (both default to off)
Volatility filter : when on, requires that yesterday’s ATR (average true range) ≥ your threshold before even placing an entry.
Trend filter : when on, only allows a “long” if yesterday’s close was above its daily MA, or a “short” if below.
You can toggle each filter on/off and adjust ATR period, ATR threshold, and MA length through the inputs at the top.
3. Signal logic (“dumb money” wicks)
At today’s first minute, the script pulls yesterday’s open, high, low, close, ATR and MA—using only completed daily bars so nothing repaints.
It measures the size of yesterday’s upper wick (close→high) vs. lower wick (open→low).
If the upper wick was longer, that sets a long bias (“dumb money” got shaken out at the top). Otherwise it sets a short bias.
4. Calculate where to place orders
On that same first minute of day:
Entry: a limit order at half of yesterday’s range away from today’s open (below the open for longs, above for shorts).
Stop‑loss: one full‑range (×1.0) below today’s open for longs (and above for shorts).
Take‑profit: 1.236× yesterday’s range above today’s open for longs (and below for shorts).
5. Apply filters before sending entry
Before actually placing that limit order, it checks:
Volatility: if enabled, requires yesterday’s ATR ≥ your “Min Daily ATR.”
Trend: if enabled, requires yesterday’s close to lie on the same side of its daily MA as your signal.
If either filter fails, no order is sent.
6. Give the limit order up to 24 hours to fill
The code remembers the bar‑index when the order went live.
If 1440 one‑minute bars pass (≈24 h) without a fill, it automatically cancels the unfilled entry—so stale orders don’t hang around.
7. Once filled, TP/SL manage the trade
As soon as your limit order executes, two opposite orders are placed:
A take‑profit at the 1.236× range level
A stop‑loss at the –1.0× range level
One cancels the other when triggered.
8. No overnight risk
On the very first minute of the next daily bar, any position still open is force‑closed (“Time Exit”)
Multi-Symbol Trend DashboardMulti-Symbol Trend Dashboard - MA Cross Trend Monitor
Short Description
A customizable dashboard that displays trend direction across multiple symbols and timeframes using moving average crossovers.
Full Description
Overview
This Multi-Symbol Trend Dashboard allows you to monitor trend direction across 7 different symbols and 5 timeframes simultaneously in a single view. The dashboard uses moving average crossovers to determine trend direction, displaying bullish trends in green and bearish trends in red.
Key Features
Multi-Symbol Monitoring : Track up to 7 different trading instruments at once
Multi-Timeframe Analysis: View 5 different timeframes simultaneously for each instrument
Customizable Moving Averages: Choose between SMA, EMA, or WMA with adjustable periods
Visual Clarity: Color-coded cells provide immediate trend identification
Flexible Positioning: Place the dashboard anywhere on your chart
Customizable Appearance: Adjust sizes, colors, and text formatting
How It Works
The dashboard calculates a fast MA and slow MA for each symbol-timeframe combination. When the fast MA is above the slow MA, the cell shows green (bullish). When the fast MA is below the slow MA, the cell shows red (bearish).
Use Cases
Get a bird's-eye view of market trends across multiple instruments
Identify potential trading opportunities where multiple timeframes align
Monitor your watchlist without switching between charts
Spot divergences between related instruments
Track market breadth across sectors or related instruments
Notes and Limitations
Limited to 7 symbols and 5 timeframes due to TradingView's security request limits
Uses simple MA crossover as trend determination method
Dashboard is most effective when displayed on a dedicated chart
Performance may vary on lower-end devices due to multiple security requests
Settings Explanation
MA Settings: Configure the periods and types of moving averages
Display Settings: Adjust dashboard positioning and visual elements
Trading Instruments: Select which symbols to monitor (defaults to major forex pairs)
Timeframes: Choose which timeframes to display (default: M15, H1, H4, D1, W1)
Colors: Customize the color scheme for bullish/bearish indications and headers
This dashboard provides a straightforward way to maintain situational awareness across multiple markets and timeframes, helping traders identify potential setups and market conditions at a glance.
Moving Average ToolkitMoving Average Toolkit - Advanced MA Analysis with Flexible Source Input
A powerful and versatile moving average indicator designed for maximum flexibility. Its unique source input feature allows you to analyze moving averages of ANY indicator or price data, making it perfect for creating custom combinations with RSI, Volume, OBV, or any other technical indicator.
Key Features:
• Universal Source Input:
- Analyze moving averages of any data: Price, Volume, RSI, MACD, Custom Indicators
- Perfect for creating advanced technical setups
- Identify trends in any technical data
• 13 Moving Average Types:
- Traditional: SMA, EMA, WMA, RMA, VWMA
- Advanced: HMA, T3, DEMA, TEMA, KAMA, ZLEMA, McGinley, EPMA
• Dual MA System:
- Compare two different moving averages
- Independent settings for each MA
- Perfect for multiple timeframe analysis
• Visual Offset Analysis:
- Dynamic color changes based on momentum
- Fill between current and offset values
- Clear visualization of trend strength
Usage Examples:
• Price Trend: Traditional MA analysis using price data
• Volume Trend: Apply MA to volume for volume trend analysis
• RSI Trend: Smooth RSI movements for clearer signals
• Custom: Apply to any indicator output for unique insights
Settings:
• Fully customizable colors for bull/bear conditions
• Adjustable offset periods
• Independent length settings
• Optional second MA for comparison
Perfect for:
• Advanced technical analysts
• Multi-indicator strategy developers
• Custom indicator creators
• Traders seeking flexible analysis tools
This versatile toolkit goes beyond traditional moving averages by allowing you to apply sophisticated MA analysis to any technical data, creating endless possibilities for custom technical analysis strategies.
Semaphore📌 Indicator Description: Semaphore
The Semaphore indicator plots three key moving averages on the current asset's price, allowing users to select between SMA (Simple Moving Average) or EMA (Exponential Moving Average), and to choose whether the calculation should be based on the daily timeframe or the current chart timeframe.
🔧 Customizable Parameters:
Moving average type: SMA or EMA.
Data source: Daily timeframe or current chart timeframe.
Fixed lengths: 10 (short-term), 21 (medium-term), and 50 (long-term).
🎯 What does it do?
Calculates and plots the three selected moving averages.
Automatically adapts to the chosen timeframe (e.g., display daily averages on a 1h chart).
Color-coded lines for easy visual distinction:
🔵 Blue for the 10-period MA
🟡 Yellow for the 21-period MA
🔴 Red for the 50-period MA
🌟 Benefits and Advantages:
Timeframe flexibility: Follow higher timeframe trends (daily) while trading on lower timeframes.
Clean and quick visual reference: With just three colored lines, you get a clear view of short, medium, and long-term trends.
Perfect for “traffic light” strategies: For example, all MAs aligned in one direction can indicate strong trend confirmation.
Universal use: Works seamlessly with any asset — stocks, crypto, forex, indices, and more.
AllMA Trend Radar [trade_lexx]📈 AllMA Trend Radar is your universal trend analysis tool!
📊 What is AllMA Trend Radar?
AllMA Trend Radar is a powerful indicator that uses various types of Moving Averages (MA) to analyze trends and generate trading signals. The indicator allows you to choose from more than 30 different types of moving averages and adjust their parameters to suit your trading style.
💡 The main components of the indicator
📈 Fast and slow moving averages
The indicator uses two main lines:
- Fast MA (blue line): reacts faster to price changes
- Slow MA (red line): smoother, reflects a long-term trend
The combined use of fast and slow MA allows you to get trend confirmation and entry/exit points from the market.
🔄 Wide range of moving averages
There are more than 30 types of moving averages at your disposal:
- SMA: Simple moving average
- EMA: Exponential moving average
- WMA: Weighted moving average
- DEMA: double exponential MA
- TEMA: triple exponential MA
- HMA: Hull Moving Average
- LSMA: Moving average of least squares
- JMA: Eureka Moving Average
- ALMA: Arnaud Legoux Moving Average
- ZLEMA: moving average with zero delay
- And many others!
🔍 Indicator signals
1️⃣ Fast 🆚 Slow MA signals (intersection and ratio of fast and slow MA)
Up/Down signals (intersection)
- Buy (Up) signal:
- What happens: the fast MA crosses the slow MA from bottom to top
- What does the green triangle with the "Buy" label under the candle look
like - What does it mean: a likely upward trend reversal or an uptrend strengthening
- Sell signal (Down):
- What happens: the fast MA crosses the slow MA from top to bottom
- What does it look like: a red triangle with a "Sell" mark above the candle
- What does it mean: a likely downtrend reversal or an increase in the downtrend
Greater/Less signals (ratio)
- Buy signal (Greater):
- What happens: the fast MA becomes higher than the slow MA
- What does it look like: a green triangle with a "Buy" label under the candle
- What does it mean: the formation or confirmation of an uptrend
- Sell signal (Less):
- What happens: the fast MA becomes lower than the slow MA
- What does it look like: a red triangle with a "Sell" mark above the candle
- What does it mean: the formation or confirmation of a downtrend
2️⃣ Signals ⚡️ Fast MA (fast MA and price)
Up/Down signals (intersection)
- Buy signal (Up Fast):
- What happens: the price crosses the fast MA from bottom to top
- What does it look like: a green triangle with a "Buy" label under the candle
- What does it mean: a short-term price growth signal
- Sell signal (Down Fast):
- What happens: the price crosses the fast MA from top to bottom
- What does it look like: a red triangle with a "Sell" label above the candle
- What does it mean: a short-term price drop signal
Greater/Less signals (ratio)
- Buy signal (Greater Fast):
- What happens: the price is getting higher than the fast MA
- What does it look like: a green triangle with a "Buy" label under the candle
- What does it mean: the price is above the fast MA, which indicates an upward movement
- Sell signal (Less Fast):
- What happens: the price is getting lower than the fast MA
- What does it look like: a red triangle with a "Sell" mark above the candle
- What does it mean: the price is under the fast MA, which indicates a downward movement
3️⃣ Signals 🐢 Slow MA (slow MA and price)
Up/Down signals (intersection)
- Buy signal (Up Slow):
- What happens: the price crosses the slow MA from bottom to top
- What does it look like: a green triangle with a "Buy" label under the candle
- What does it mean: a potential medium-term upward trend reversal
- Sell signal (Down Slow):
- What happens: the price crosses the slow MA from top to bottom
- What does it look like: a red triangle with a "Sell" label above the candle
- What does it mean: a potential medium-term downward trend reversal
Greater/Less signals (ratio)
- Buy signal (Greater Slow):
- What happens: the price is getting above the slow MA
- What does it look like: a green triangle with a "Buy" label under the candle
- What does it mean: the price is above the slow MA, which indicates a strong upward movement
- Sell signal (Less Slow):
- What is happening: the price is getting below the slow MA
- What does it look like: a red triangle with a "Sell" mark above the candle
- What does it mean: the price is under the slow MA, which indicates a strong downward movement
🛠 Filters to filter out false signals
1️⃣ Minimum distance between the signals
- What it does: sets the minimum number of candles between signals of the same type
- Why it is needed: it prevents the appearance of too frequent signals, especially during periods of high volatility
- How to set it up: Set a different value for each signal type (default: 3-5 bars)
- Example: if the value is 3 for Up/Down signals, after the buy signal appears, the next buy signal may appear no earlier than 3 bars later
2️⃣ Advanced indicator filters
🔍 RSI Filter
- What it does: Checks the Relative Strength Index (RSI) value before generating a signal
- Why it is needed: it helps to avoid countertrend entries and catch reversal points
- How to set up:
- For buy signals (🔋 Buy): set the RSI range, usually in the oversold zone (for example, 1-30)
- For sell signals (🪫 Sell): set the RSI range, usually in the overbought zone (for example, 70-100)
- Example: if the RSI = 25 (in the range 1-30), the buy signal will be confirmed
📊 MFI Filter (Cash Flow Index)
- What it does: analyzes volumes and the direction of price movement
- Why it is needed: confirms signals with data on the activity of cash flows
- How to set up:
- For buy signals (🔋 Buy): set the MFI range in the oversold zone (for example, 1-25)
- For sell signals (🪫 Sell): set the MFI range in the overbought zone (for example, 75-100)
- Example: if MFI = 80 (in the range of 75-100), the sell signal will be confirmed
📈 Stochastic Filter
- What it does: analyzes the position of the current price relative to the price range
- Why it is needed: confirms signals based on overbought/oversold conditions
- How to configure:
- You can configure the K Length, D Length and Smoothing parameters
- For buy signals (🔋 Buy): set the stochastic range in the oversold zone (for example, 1-20)
- For sell signals (🪫 Sell): set the stochastic range in the overbought zone (for example, 80-100)
- Example: if stochastic = 15 (is in the range of 1-20), the buy signal will be confirmed
🔌 Connecting to trading strategies
The indicator provides various connectors to connect to your trading strategies.:
1️⃣ Individual connectors for each type of signal
- 🔌Fast vs Slow Up/Down MA Signal🔌: signals for the intersection of fast and slow MA
- 🔌Fast vs Slow Greater/Less MA Signal🔌: signals of the ratio of fast and slow MA
- 🔌Fast Up/Down MA Signal🔌: signals of the intersection of price and fast MA
- 🔌Fast Greater/Less MA Signal🔌: signals of the ratio of price and fast MA
- 🔌Slow Up/Down MA Signal🔌: signals of the intersection of price and slow MA
- 🔌Slow Greater/Less MA Signal🔌: Price versus slow MA signals
2️⃣ Combined connectors
- 🔌Combined Up/Down MA Signal🔌: combines all the crossing signals (Up/Down)
- 🔌Combined Greater/Less MA Signal🔌: combines all the signals of the ratio (Greater/Less)
- 🔌Combined All MA Signals🔌: combines all signals (Up/Down and Greater/Less)
❗️ All connectors return values:
- 1: buy signal
- -1: sell signal
- 0: no signal
📚 How to start using AllMA Trend Radar
1️⃣ Selection of types of moving averages
- Add an indicator to the chart
- Select the type and period for the fast MA (default: DEMA with a period of 14)
- Select the type and period for the slow MA (default: SMA with a period of 14)
- Experiment with different types of MA to find the best combination for your trading style
2️⃣ Signal settings
- Turn on the desired signal types (Up/Down, Greater/Less)
- Set the minimum distance between the signals
- Activate and configure the necessary filters (RSI, MFI, Stochastic)
3️⃣ Checking on historical data
- Analyze how the indicator works based on historical data
- Pay attention to the accuracy of the signals and the presence of false alarms
- Adjust the settings if necessary
4️⃣ Introduction to the trading strategy
- Decide which signals will be used to enter the position.
- Determine which signals will be used to exit the position.
- Connect the indicator to your trading strategy through the appropriate connectors
🌟 Practical application examples
Scalping strategy
- Fast MA: TEMA with a period of 8
- Slow MA: EMA with a period of 21
- Active signals: Fast MA Up/Down
- Filters: RSI (range 1-40 for purchases, 60-100 for sales)
- Signal spacing: 3 bars
Strategy for day trading
- Fast MA: TEMA with a period of 10
- Slow MA: SMA with a period of 20
- Active signals: Fast MA Up/Down and Fast vs Slow Greater/Less
- Filters: MFI (range 1-25 for purchases, 75-100 for sales)
- Signal spacing: 5 bars
Swing Trading Strategy
- Fast MA: DEMA with a period of 14
- Slow MA: VWMA with a period of 30
- Active signals: Fast vs Slow Up/Down and Slow MA Greater/Less
- Filters: Stochastic (range 1-20 for purchases, 80-100 for sales)
- Signal spacing: 8 bars
A strategy for positional trading
- Fast MA: HMA with a period of 21
- Slow MA: SMA with a period of 50
- Active signals: Slow MA Up/Down and Fast vs Slow Greater/Less
- Filters: RSI and MFI at the same time
- The distance between the signals: 10 bars
💡 Tips for using AllMA Trend Radar
1. Select the types of MA for market conditions:
- For trending markets: DEMA, TEMA, HMA (fast MA)
- For sideways markets: SMA, WMA, VWMA (smoothed MA)
- For volatile markets: KAMA, AMA, VAMA (adaptive MA)
2. Combine different types of signals:
- Up/Down signals work better when moving from a sideways trend to a directional
one - Greater/Less signals are optimal for fixing a stable trend
3. Use filters effectively:
- The RSI filter works great in trending markets
- MFI filter helps to confirm the strength of volume movement
- Stochastic filter works well in lateral ranges
4. Adjust the minimum distance between the signals:
- Small values (2-3 bars) for short-term trading
- Average values (5-8 bars) for medium-term trading
- Large values (10+ bars) for long-term trading
5. Use combination connectors:
- For more reliable signals, connect the indicator through the combined connectors
💰 With the AllMA Trend Radar indicator, you get a universal trend analysis tool that can be customized for any trading style and timeframe. The combination of different types of moving averages and advanced filters allows you to significantly improve the accuracy of signals and the effectiveness of your trading strategy!
Oil/gas ratio MAOil/Gas Ratio-Based Equivalent Price
This indicator calculates the gas-equivalent price based on the current oil price and a defined oil/gas ratio. It helps identify relative overvaluation or undervaluation of natural gas compared to oil.
Features:
- Choose between a static or dynamic (SMA-based) oil/gas ratio
- Displays the fair value of gas derived from oil prices
- Works with any oil ticker symbol (e.g. BRENT, USOIL, etc.)
Useful for traders analyzing intermarket relationships and looking for relative value signals between energy commodities.
PineVersatilitiesBundleLibrary "PineVersatilitiesBundle"
Versatilities (aka, Versatile Utilities) Pack includes:
- Eighteen Price Variants bundled in a Map,
- Nine Smoothing Variants bundled in a Map,
- Visualisations that indicate on both - pane and chart.
price_variants(lb)
Computes Several different averages using current and previous OHLC values
Parameters:
lb (int) : - lookback distance for combining OHLC values from the past with the present
Returns: Map of Eighteen Uncommon Combinations of single and two-bar OHLC averages (rounded-to-mintick)
dynamic_MA(masrc, malen, lsmaoff, almasgm, almaoff, almaflr)
Dynamically computes Eight different MAs and returns a Map containing Nine MAs
Parameters:
masrc (float) : source series to compute MA
malen (simple int) : lookback distance for MA
lsmaoff (simple int) : optional LSMA offset - default is 0
almasgm (simple float) : optional ALMA sigma - default is 5
almaoff (simple float) : optional ALMA offset - default is 0.5
almaflr (simple bool) : optional ALMA floor flag - default is false
Returns: Map of MAs - 'ALMA', 'EMA', 'HMA', 'LSMA', 'RMA', 'SMA', 'SWMA', 'WMA', 'ALL' (rounded-to-mintick)
Qullamaggie [Modified] | FractalystWhat's the purpose of this strategy?
The strategy aims to identify high-probability breakout setups in trending markets, inspired by Kristjan "Qullamaggie" Kullamägi’s approach.
It focuses on capturing explosive price moves after periods of consolidation, using technical criteria like moving averages, breakouts, trailing stop-loss and momentum confirmation.
Ideal for swing traders seeking to ride strong trends while managing risk.
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How does the strategy work?
The strategy follows a systematic process to capture high-momentum breakouts:
Pre-Breakout Criteria:
Prior Price Surge: Identifies stocks that have rallied 30-100%+ in recent month(s), signaling strong underlying momentum (per Qullamaggie’s volatility expansion principles).
Consolidation Phase: Looks for a tightening price range (e.g., flag, pennant, or tight base), indicating a potential "coiling" before continuation.
Trend Confirmation: Uses moving averages (e.g., 20/50/200 EMA) to ensure the stock is trading above key averages on the daily chart, confirming an uptrend.
Price Break: Enters when price clears the consolidation high with conviction.
Risk Management:
Initial Stop Loss: Placed below the consolidation low or a recent swing point to limit downside.
Break-Even Adjustment: Moves stop loss to breakeven once the trade reaches 1.5x risk-to-reward (RR), securing a "free trade" while letting winners run.
Trailing Stop (Unique Edge):
Market Structure Trailing: Instead of trailing via moving averages, the stop is dynamically adjusted using structural invalidation level. This adapts to price action, allowing the trade to stay open during volatile retracements while locking in gains as new structure forms.
Why This Matters: Most strategies use rigid trailing stops (e.g., below the 10EMA), which often exit prematurely in choppy markets. By trailing based on structure, this strategy avoids "noise" and captures larger trends, directly boosting overall returns.
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What markets or timeframes is this suited for?
This is a long-only strategy designed for trending markets, and it performs best in:
Markets: Stocks (especially high-growth, liquid equities), cryptocurrencies (major pairs with strong volatility), commodities (e.g., oil, gold), and futures (index/commodity futures).
Timeframes: Primarily daily charts for swing trades (1-30 day holds), though weekly charts can help confirm broader trends.
Key Advantage: The TradingView script allows instant backtesting with adjustable parameters
You can:
- Test historical performance across multiple markets to identify which assets align best with the strategy.
- Optimize settings (e.g., trailing stop sensitivity, moving averages etc.) to match a market’s volatility profile.
Build a diversified portfolio by filtering for markets that show consistent profitability in backtests.
For example, you might discover cryptos require tighter trailing stops due to volatility, while stocks thrive with wider structural stops. The script automates this analysis, letting you to trade confidently.
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What indicators or tools does the strategy use?
The strategy combines customizable technical tools with strict anti-lookahead safeguards:
Core Indicators:
Moving Averages: Adjustable periods (e.g., 20/50/200 EMA or SMA) and timeframes (daily/weekly) to confirm trend alignment. Users can test combinations (e.g., 10EMA vs. 20EMA) to optimize for specific markets.
Breakout Parameters:
Consolidation Length: Adjustable window to define the "tightness" of the pre-breakout pattern.
Entry Models: Flexible entry logics (Breakouts and fractals)
Anti-Lookahead Design:
All calculations (e.g., moving averages, consolidation ranges, volume averages) use only closed/confirmed data available at the time of the signal.
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How do I manage risk with this strategy?
The strategy prioritizes customizable risk controls to align with your trading style and account size:
User-Defined Risk Inputs:
Risk Per Trade: Set a % of Equity (e.g., 1-2%) to determine position size. The strategy auto-calculates shares/contracts to match your selected risk per trade.
Flexibility: Choose between fixed risk or equity-based scaling.
The script adjusts position sizing dynamically based on your selection.
Pyramiding Feature:
Customizable Entries: Adjust the number of pyramiding trades allowed (e.g., 1-3 additional positions) in the strategy settings. Each new entry is triggered only if the prior trade hits its 1.5x RR target and the trend remains intact.
Risk-Scaled Additions: New positions use profits from prior trades, compounding gains without increasing initial risk.
Risk-Free Trade Mechanic:
Once a trade reaches 1.5x RR, the stop loss is moved to breakeven, eliminating downside risk.
The strategy then opens a new position (if pyramiding is enabled) using a portion of the locked-in profit. This "snowballs" winners while keeping total capital exposure stable.
Impact on Net Profit & Drawdown:
Net Profit Boost: Pyramiding lets you ride multi-leg trends aggressively. For example, a 100% runner could generate 2-3x more profit vs. a single-entry approach.
Controlled Drawdowns: Since new positions are funded by profits (not initial capital), max drawdown stays anchored to your original risk per trade (e.g., 1-2% of account). Even if later entries fail, the breakeven stop on prior trades protects overall equity.
Why This Works: Most strategies either over-leverage (increasing drawdowns) or exit too early. By recycling profits into new positions only after securing risk-free capital, this approach mimics hedge fund "scaling in" tactics while staying retail-trader friendly.
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How does the strategy identify market structure for its trailing stoploss?
The strategy identifies market structure by utilizing an efficient logic with for loops to pinpoint the first swing candle that features a pivot of 2. This marks the beginning of the break of structure, where the market's previous trend or pattern is considered invalidated or changed.
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What are the underlying calculations?
The underlying calculations involve:
Identifying Swing Points: The strategy looks for swing highs (marked with blue Xs) and swing lows (marked with red Xs). A swing high is identified when a candle's high is higher than the highs of the candles before and after it. Conversely, a swing low is when a candle's low is lower than the lows of the candles before and after it.
Break of Structure (BOS):
Bullish BOS: This occurs when the price breaks above the swing high level of the previous structure, indicating a potential shift to a bullish trend.
Bearish BOS: This happens when the price breaks below the swing low level of the previous structure, signaling a potential shift to a bearish trend.
Structural Liquidity and Invalidation:
Structural Liquidity: After a break of structure, liquidity levels are updated to the first swing high in a bullish BOS or the first swing low in a bearish BOS.
Structural Invalidation: If the price moves back to the level of the first swing low before the bullish BOS or the first swing high before the bearish BOS, it invalidates the break of structure, suggesting a potential reversal or continuation of the previous trend.
This method provides users with a technical approach to filter market regimes, offering an advantage by minimizing the risk of overfitting to historical data, which is often a concern with traditional indicators like moving averages.
By focusing on identifying pivotal swing points and the subsequent breaks of structure, the strategy maintains a balance between sensitivity to market changes and robustness against historical data anomalies, ensuring a more adaptable and potentially more reliable market analysis tool.
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What entry criteria are used in this script?
The script uses two entry models for trading decisions: BreakOut and Fractal.
Underlying Calculations:
Breakout: The script records the most recent swing high by storing it in a variable. When the price closes above this recorded level, and all other predefined conditions are satisfied, the script triggers a breakout entry. This approach is considered conservative because it waits for the price to confirm a breakout above the previous high before entering a trade. As shown in the image, as soon as the price closes above the new candle (first tick), the long entry gets taken. The stop-loss is initially set and then moved to break-even once the price moves in favor of the trade.
Fractal: This method involves identifying a swing low with a period of 2, which means it looks for a low point where the price is lower than the two candles before and after it. Once this pattern is detected, the script executes the trade. This is an aggressive approach since it doesn't wait for further price confirmation. In the image, this is represented by the 'Fractal 2' label where the script identifies and acts on the swing low pattern.
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What type of stop-loss identification method are used in this strategy?
This strategy employs two types of stop-loss methods: Initial Stop-loss and Trailing Stop-Loss.
Underlying Calculations:
Initial Stop-loss:
ATR Based: The strategy uses the Average True Range (ATR) to set an initial stop-loss, which helps in accounting for market volatility without predicting price direction.
Calculation:
- First, the True Range (TR) is calculated for each period, which is the greatest of:
- Current Period High - Current Period Low
- Absolute Value of Current Period High - Previous Period Close
- Absolute Value of Current Period Low - Previous Period Close
- The ATR is then the moving average of these TR values over a specified period, typically 14 periods by default. This ATR value can be used to set the stop-loss at a distance from the entry price that reflects the current market volatility.
Swing Low Based:
For this method, the stop-loss is set based on the most recent swing low identified in the market structure analysis. This approach uses the lowest point of the recent price action as a reference for setting the stop-loss.
Trailing Stop-Loss:
The strategy uses structural liquidity and structural invalidation levels across multiple timeframes to adjust the stop-loss once the trade is profitable. This method involves:
Detecting Structural Liquidity: After a break of structure, the liquidity levels are updated to the first swing high in a bullish scenario or the first swing low in a bearish scenario. These levels serve as potential areas where the price might find support or resistance, allowing the stop-loss to trail the price movement.
Detecting Structural Invalidation: If the price returns to the level of the first swing low before a bullish break of structure or the first swing high before a bearish break of structure, it suggests the trend might be reversing or invalidating, prompting the adjustment of the stop-loss to lock in profits or minimize losses.
By using these methods, the strategy dynamically adjusts the initial stop-loss based on market volatility, helping to protect against adverse price movements while allowing for enough room for trades to develop. The ATR-based stop-loss adapts to the current market conditions by considering the volatility, ensuring that the stop-loss is not too tight during volatile periods, which could lead to premature exits, nor too loose during calm markets, which might result in larger losses. Similarly, the swing low based stop-loss provides a logical exit point if the market structure changes unfavorably.
Each market behaves differently across various timeframes, and it is essential to test different parameters and optimizations to find out which trailing stop-loss method gives you the desired results and performance. This involves backtesting the strategy with different settings for the ATR period, the distance from the swing low, and how the trailing stop-loss reacts to structural liquidity and invalidation levels.
Through this process, you can tailor the strategy to perform optimally in different market environments, ensuring that the stop-loss mechanism supports the trade's longevity while safeguarding against significant drawdowns.
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What type of break-even method is used in this strategy? What are the underlying calculations?
Moves the initial stop-loss to the entry price when the price reaches a certain RR ratio.
Calculation:
Break-even level = Entry Price + (Initial Risk * RR Ratio)
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What tables are available in this script?
- Summary: Provides a general overview, displaying key performance parameters such as Net Profit, Profit Factor, Max Drawdown, Average Trade, Closed Trades and more.
Total Commission: Displays the cumulative commissions incurred from all trades executed within the selected backtesting window. This value is derived by summing the commission fees for each trade on your chart.
Average Commission: Represents the average commission per trade, calculated by dividing the Total Commission by the total number of closed trades. This metric is crucial for assessing the impact of trading costs on overall profitability.
Avg Trade: The sum of money gained or lost by the average trade generated by a strategy. Calculated by dividing the Net Profit by the overall number of closed trades. An important value since it must be large enough to cover the commission and slippage costs of trading the strategy and still bring a profit.
MaxDD: Displays the largest drawdown of losses, i.e., the maximum possible loss that the strategy could have incurred among all of the trades it has made. This value is calculated separately for every bar that the strategy spends with an open position.
Profit Factor: The amount of money a trading strategy made for every unit of money it lost (in the selected currency). This value is calculated by dividing gross profits by gross losses.
Avg RR: This is calculated by dividing the average winning trade by the average losing trade. This field is not a very meaningful value by itself because it does not take into account the ratio of the number of winning vs losing trades, and strategies can have different approaches to profitability. A strategy may trade at every possibility in order to capture many small profits, yet have an average losing trade greater than the average winning trade. The higher this value is, the better, but it should be considered together with the percentage of winning trades and the net profit.
Winrate: The percentage of winning trades generated by a strategy. Calculated by dividing the number of winning trades by the total number of closed trades generated by a strategy. Percent profitable is not a very reliable measure by itself. A strategy could have many small winning trades, making the percent profitable high with a small average winning trade, or a few big winning trades accounting for a low percent profitable and a big average winning trade. Most mean-reversion successful strategies have a percent profitability of 40-80% but are profitable due to risk management control.
BE Trades: Number of break-even trades, excluding commission/slippage.
Losing Trades: The total number of losing trades generated by the strategy.
Winning Trades: The total number of winning trades generated by the strategy.
Total Trades: Total number of taken traders visible your charts.
Net Profit: The overall profit or loss (in the selected currency) achieved by the trading strategy in the test period. The value is the sum of all values from the Profit column (on the List of Trades tab), taking into account the sign.
- Monthly: Displays performance data on a month-by-month basis, allowing users to analyze performance trends over each month and year.
- Weekly: Displays performance data on a week-by-week basis, helping users to understand weekly performance variations.
- UI Table: A user-friendly table that allows users to view and save the selected strategy parameters from user inputs. This table enables easy access to key settings and configurations, providing a straightforward solution for saving strategy parameters by simply taking a screenshot with Alt + S or ⌥ + S.
User-input styles and customizations:
Please note that all background colors in the style are disabled by default to enhance visualization.
How to Use This Strategy to Create a Profitable Edge and Systems?
Choose Your Strategy mode:
- Decide whether you are creating an investing strategy or a trading strategy.
Select a Market:
- Choose a one-sided market such as stocks, indices, or cryptocurrencies.
Historical Data:
- Ensure the historical data covers at least 10 years of price action for robust backtesting.
Timeframe Selection:
- Choose the timeframe you are comfortable trading with. It is strongly recommended to use a timeframe above 15 minutes to minimize the impact of commissions/slippage on your profits.
Set Commission and Slippage:
- Properly set the commission and slippage in the strategy properties according to your broker/prop firm specifications.
Parameter Optimization:
- Use trial and error to test different parameters until you find the performance results you are looking for in the summary table or, preferably, through deep backtesting using the strategy tester.
Trade Count:
- Ensure the number of trades is 200 or more; the higher, the better for statistical significance.
Positive Average Trade:
- Make sure the average trade is above zero.
(An important value since it must be large enough to cover the commission and slippage costs of trading the strategy and still bring a profit.)
Performance Metrics:
- Look for a high profit factor, and net profit with minimum drawdown.
- Ideally, aim for a drawdown under 20-30%, depending on your risk tolerance.
Refinement and Optimization:
- Try out different markets and timeframes.
- Continue working on refining your edge using the available filters and components to further optimize your strategy.
What Makes This Strategy Unique?
This strategy combines flexibility, smart risk management, and momentum focus in a way that’s rare and practical:
1. Adapts to Any Market Rhythm
Works on daily, weekly, or intraday charts without code changes.
Uses two entry types: classic breakouts (like trending stocks) or fractal patterns (to avoid false starts).
2. Smarter Stop-Loss System
No rigid rules: Stops adjust based on price structure (e.g., new “higher lows”), not fixed percentages.
Avoids whipsaws: Tightens stops only when the trend strengthens, not in choppy markets.
3. Safe Profit-Boosting Pyramiding
Adds new positions only after prior trades are risk-free (stops moved above breakeven).
Scales up using locked-in profits, not new capital, to grow gains safely.
4. Built-In Momentum Check
Tracks 1/3/6-month price growth to spotlight stocks with strong, lasting momentum.
Terms and Conditions | Disclaimer
Our charting tools are provided for informational and educational purposes only and should not be construed as financial, investment, or trading advice. They are not intended to forecast market movements or offer specific recommendations. Users should understand that past performance does not guarantee future results and should not base financial decisions solely on historical data.
Built-in components, features, and functionalities of our charting tools are the intellectual property of @Fractalyst Unauthorized use, reproduction, or distribution of these proprietary elements is prohibited.
- By continuing to use our charting tools, the user acknowledges and accepts the Terms and Conditions outlined in this legal disclaimer and agrees to respect our intellectual property rights and comply with all applicable laws and regulations.
Enhanced Fuzzy SMA Analyzer (Multi-Output Proxy) [FibonacciFlux]EFzSMA: Decode Trend Quality, Conviction & Risk Beyond Simple Averages
Stop Relying on Lagging Averages Alone. Gain a Multi-Dimensional Edge.
The Challenge: Simple Moving Averages (SMAs) tell you where the price was , but they fail to capture the true quality, conviction, and sustainability of a trend. Relying solely on price crossing an average often leads to chasing weak moves, getting caught in choppy markets, or missing critical signs of trend exhaustion. Advanced traders need a more sophisticated lens to navigate complex market dynamics.
The Solution: Enhanced Fuzzy SMA Analyzer (EFzSMA)
EFzSMA is engineered to address these limitations head-on. It moves beyond simple price-average comparisons by employing a sophisticated Fuzzy Inference System (FIS) that intelligently integrates multiple critical market factors:
Price deviation from the SMA ( adaptively normalized for market volatility)
Momentum (Rate of Change - ROC)
Market Sentiment/Overheat (Relative Strength Index - RSI)
Market Volatility Context (Average True Range - ATR, optional)
Volume Dynamics (Volume relative to its MA, optional)
Instead of just a line on a chart, EFzSMA delivers a multi-dimensional assessment designed to give you deeper insights and a quantifiable edge.
Why EFzSMA? Gain Deeper Market Insights
EFzSMA empowers you to make more informed decisions by providing insights that simple averages cannot:
Assess True Trend Quality, Not Just Location: Is the price above the SMA simply because of a temporary spike, or is it supported by strong momentum, confirming volume, and stable volatility? EFzSMA's core fuzzyTrendScore (-1 to +1) evaluates the health of the trend, helping you distinguish robust moves from noise.
Quantify Signal Conviction: How reliable is the current trend signal? The Conviction Proxy (0 to 1) measures the internal consistency among the different market factors analyzed by the FIS. High conviction suggests factors are aligned, boosting confidence in the trend signal. Low conviction warns of conflicting signals, uncertainty, or potential consolidation – acting as a powerful filter against chasing weak moves.
// Simplified Concept: Conviction reflects agreement vs. conflict among fuzzy inputs
bullStrength = strength_SB + strength_WB
bearStrength = strength_SBe + strength_WBe
dominantStrength = max(bullStrength, bearStrength)
conflictingStrength = min(bullStrength, bearStrength) + strength_N
convictionProxy := (dominantStrength - conflictingStrength) / (dominantStrength + conflictingStrength + 1e-10)
// Modifiers (Volatility/Volume) applied...
Anticipate Potential Reversals: Trends don't last forever. The Reversal Risk Proxy (0 to 1) synthesizes multiple warning signs – like extreme RSI readings, surging volatility, or diverging volume – into a single, actionable metric. High reversal risk flags conditions often associated with trend exhaustion, providing early warnings to protect profits or consider counter-trend opportunities.
Adapt to Changing Market Regimes: Markets shift between high and low volatility. EFzSMA's unique Adaptive Deviation Normalization adjusts how it perceives price deviations based on recent market behavior (percentile rank). This ensures more consistent analysis whether the market is quiet or chaotic.
// Core Idea: Normalize deviation by recent volatility (percentile)
diff_abs_percentile = ta.percentile_linear_interpolation(abs(raw_diff), normLookback, percRank) + 1e-10
normalized_diff := raw_diff / diff_abs_percentile
// Fuzzy sets for 'normalized_diff' are thus adaptive to volatility
Integrate Complexity, Output Clarity: EFzSMA distills complex, multi-factor analysis into clear, interpretable outputs, helping you cut through market noise and focus on what truly matters for your decision-making process.
Interpreting the Multi-Dimensional Output
The true power of EFzSMA lies in analyzing its outputs together:
A high Trend Score (+0.8) is significant, but its reliability is amplified by high Conviction (0.9) and low Reversal Risk (0.2) . This indicates a strong, well-supported trend.
Conversely, the same high Trend Score (+0.8) coupled with low Conviction (0.3) and high Reversal Risk (0.7) signals caution – the trend might look strong superficially, but internal factors suggest weakness or impending exhaustion.
Use these combined insights to:
Filter Entry Signals: Require minimum Trend Score and Conviction levels.
Manage Risk: Consider reducing exposure or tightening stops when Reversal Risk climbs significantly, especially if Conviction drops.
Time Exits: Use rising Reversal Risk and falling Conviction as potential signals to take profits.
Identify Regime Shifts: Monitor how the relationship between the outputs changes over time.
Core Technology (Briefly)
EFzSMA leverages a Mamdani-style Fuzzy Inference System. Crisp inputs (normalized deviation, ROC, RSI, ATR%, Vol Ratio) are mapped to linguistic fuzzy sets ("Low", "High", "Positive", etc.). A rules engine evaluates combinations (e.g., "IF Deviation is LargePositive AND Momentum is StrongPositive THEN Trend is StrongBullish"). Modifiers based on Volatility and Volume context adjust rule strengths. Finally, the system aggregates these and defuzzifies them into the Trend Score, Conviction Proxy, and Reversal Risk Proxy. The key is the system's ability to handle ambiguity and combine multiple, potentially conflicting factors in a nuanced way, much like human expert reasoning.
Customization
While designed with robust defaults, EFzSMA offers granular control:
Adjust SMA, ROC, RSI, ATR, Volume MA lengths.
Fine-tune Normalization parameters (lookback, percentile). Note: Fuzzy set definitions for deviation are tuned for the normalized range.
Configure Volatility and Volume thresholds for fuzzy sets. Tuning these is crucial for specific assets/timeframes.
Toggle visual elements (Proxies, BG Color, Risk Shapes, Volatility-based Transparency).
Recommended Use & Caveats
EFzSMA is a sophisticated analytical tool, not a standalone "buy/sell" signal generator.
Use it to complement your existing strategy and analysis.
Always validate signals with price action, market structure, and other confirming factors.
Thorough backtesting and forward testing are essential to understand its behavior and tune parameters for your specific instruments and timeframes.
Fuzzy logic parameters (membership functions, rules) are based on general heuristics and may require optimization for specific market niches.
Disclaimer
Trading involves substantial risk. EFzSMA is provided for informational and analytical purposes only and does not constitute financial advice. No guarantee of profit is made or implied. Past performance is not indicative of future results. Use rigorous risk management practices.
EMA Clouds with Strict Buy/Sell SignalsEMA Clouds with Strict Buy/Sell Signals - Precision Trading Unleashed
Unlock the power of trend-following precision with the EMA Clouds with Strict Buy/Sell Signals indicator, a sophisticated tool built for traders who demand reliability and clarity in their decision-making. Inspired by the legendary Ripster EMA Clouds, this indicator takes the classic cloud concept to the next level by incorporating stricter, high-confidence signals—perfect for navigating the markets on 15-minute or higher timeframes.
Why You’ll Want This on Your Chart:
Dual EMA Clouds for Crystal-Clear Trends: Watch as two dynamic clouds—formed by carefully paired Exponential Moving Averages (8/21 and 34/50)—paint a vivid picture of market momentum. The green short-term cloud and red long-term cloud provide an intuitive, at-a-glance view of trend direction and strength.
Stricter Signals, Fewer False Moves: Tired of chasing weak signals? This indicator only triggers buy and sell signals when the stars align: a cloud crossover (short-term crossing above or below long-term) and price confirmation above or below both clouds. The result? Fewer trades, higher conviction, and a cleaner chart.
Customizable Timeframe Power: Whether you’re a scalper on the 15-minute chart or a swing trader on the daily, tailor the clouds to your preferred higher timeframe (15min, 30min, 1hr, 4hr, or daily) for seamless integration into your strategy.
Visual Mastery Meets Actionable Alerts: Green buy triangles below the bars and red sell triangles above them make spotting opportunities effortless. Pair this with built-in alerts, and you’ll never miss a high-probability trade again.
How It Works:
Buy Signal: Triggers when the short-term cloud crosses above the long-term cloud and the price surges above both, signaling a robust bullish breakout.
Sell Signal: Activates when the short-term cloud dips below the long-term cloud and the price falls beneath both, confirming bearish dominance.
Cloud Visualization: The green cloud (8/21 EMA) tracks fast-moving trends, while the red cloud (34/50 EMA) anchors the broader market direction—together, they filter noise and spotlight tradable moves.
Why Traders Will Love It:
Designed for those who value precision over guesswork, this indicator cuts through market clutter to deliver signals you can trust. Whether you’re trading stocks, forex, crypto, or futures, its adaptability and strict logic make it a must-have tool for serious traders. Customize the EMA lengths, tweak the timeframe, and watch your edge sharpen.
Add EMA Clouds with Strict Buy/Sell Signals to your chart today and experience the confidence of trading with a tool that’s as disciplined as you are. Your next big move is waiting—don’t let it slip away.
RSI + Stochastic + WMA StrategyThis script is designed for TradingView and serves as a trading strategy (not just a visual indicator). It's intended for backtesting, strategy optimization, or live trading signal generation using a combination of popular technical indicators.
📊 Indicators Used in the Strategy:
Indicator Description
RSI (Relative Strength Index) Measures momentum; identifies overbought (>70) or oversold (<30) conditions.
Stochastic Oscillator (%K & %D) Detects momentum reversal points via crossovers. Useful for timing entries.
WMA (Weighted Moving Average) Identifies the trend direction (used as a trend filter).
📈 Trading Logic / Strategy Rules:
📌 Long Entry Condition (Buy Signal):
All 3 conditions must be true:
RSI is Oversold → RSI < 30
Stochastic Crossover Upward → %K crosses above %D
Price is above WMA → Confirms uptrend direction
👉 Interpretation: Market was oversold, momentum is turning up, and price confirms uptrend — bullish entry.
📌 Short Entry Condition (Sell Signal):
All 3 conditions must be true:
RSI is Overbought → RSI > 70
Stochastic Crossover Downward → %K crosses below %D
Price is below WMA → Confirms downtrend direction
👉 Interpretation: Market is overbought, momentum is turning down, and price confirms downtrend — bearish entry.
🔄 Strategy Execution (Backtesting Logic):
The script uses:
pinescript
Copy
Edit
strategy.entry("LONG", strategy.long)
strategy.entry("SHORT", strategy.short)
These are Pine Script functions to place buy and sell orders automatically when the above conditions are met. This allows you to:
Backtest the strategy
Measure win/loss ratio, drawdown, and profitability
Optimize indicator settings using TradingView Strategy Tester
📊 Visual Aids (Charts):
Plots WMA Line: Orange line for trend direction
Overbought/Oversold Zones: Horizontal lines at 70 (red) and 30 (green) for RSI visualization
⚡ Strategy Type Summary:
Category Setting
Strategy Type Momentum Reversal + Trend Filter
Timeframe Flexible (Works best on 1H, 4H, Daily)
Trading Style Swing/Intraday
Risk Profile Medium to High (due to momentum triggers)
Uses Leverage Possible (adjust risk accordingly)
Maxima MAX1📌 Overview:
This strategy is a Simple Moving Average (SMA) Crossover system with an optional Relative Strength Index (RSI) filter for better trade confirmation. It allows traders to customize key parameters and backtest results within a specific date range.
📊 How It Works:
✅ Entry Conditions:
The closing price must be above both the Fast SMA and Slow SMA.
(Optional) RSI must be above a threshold (default: 50) for additional confirmation.
❌ Exit Condition:
The closing price drops below the Fast SMA, signaling an exit.
🔧 Customizable Inputs:
SMA Lengths: Adjust both Fast and Slow SMA values.
RSI Filter: Enable/disable RSI confirmation with a custom length & threshold.
Backtest Date Range: Choose a start and end date for testing historical performance.
🚀 Why Use This Strategy?
✔ Ideal for trend-following traders looking for momentum-based entries.
✔ Provides an additional RSI filter to reduce false signals.
✔ Helps traders refine their strategy by testing different parameters.
📢 How to Use:
1️⃣ Customize the SMA lengths, RSI settings, and date range.
2️⃣ Enable/Disable the RSI filter as needed.
3️⃣ Analyze historical performance and optimize for different markets.
⚠ Disclaimer:
This strategy is for educational purposes only. Always backtest thoroughly before using it in live trading.
Color Themed Guppy Multiple Moving Average
========== TLDR ==========
The "Color Themed Guppy Multiple Moving Average" plots a group of 6 Moving Averages on your chart with a selection of color themes to automatically style the different length Moving Average lines. As someone who struggles with screens and colors on a busy chart, this indicator has helped me a lot in quickly identifying which Moving Average price is respecting the most - giving me better signals for trade entries and trend loss.
========== Key Features and Advantages ==========
- Show different length Moving Averages with a single indicator
- quickly make your chart more readable with 12 different color themes
- The themes will color the Moving Averages with a gradient (light - dark), with a lighter color indicating a shorter length or 'faster' Moving Average
- Select the type of Moving Average you would like to use
========== Use Cases ==========
Identify Specific Length Moving Averages That are Acting as Support or Resistance:
Having each Moving Average coloured by a theme makes it easier to track each individual line with your eyes, making it easier to quickly find the Moving Averages that price is respecting the most for a given asset and/or trend.
Get Bias Quickly:
When all 6 of the Moving Averages are 'stacked' on top of each other in order, and all are angled either up or down, it can provide a useful bias for the market on your timeframe.
For example, If the fastest (smallest length) Moving Averages are angled up and sitting above the slower (largest length) Moving Averages, it may indicate that a 'long' bias would be preferable for any trades.
Having a color gradient from the themes makes it much easier to see when the Moving Average lines are "stacked" in order.
Identify Turning Points:
When the faster (smallest length) Moving Averages start to cross over the slower (largest length) Moving Averages, it may indicate a potential price/trend reversal.
Again, having a color gradient from the themes makes it much easier to spot this
========== Theme Options ==========
- Red
- Orange
- Yellow
- Green
- Teal
- Light Blue
- Blue
- Violet
- Purple
- Pink
- Rainbow - Solid
- Rainbow - Light
If you'd like other themes added feel free to request them in the comments and I can try to add more.
Breakouts With Timefilter Strategy [LuciTech]This strategy captures breakout opportunities using pivot high/low breakouts while managing risk through dynamic stop-loss placement and position sizing. It includes a time filter to limit trades to specific sessions.
How It Works
A long trade is triggered when price closes above a pivot high, and a short trade when price closes below a pivot low.
Stop-loss can be set using ATR, prior candle high/low, or a fixed point value. Take-profit is based on a risk-reward multiplier.
Position size adjusts based on the percentage of equity risked.
Breakout signals are marked with triangles, and entry, stop-loss, and take-profit levels are plotted.
moving average filter: Bullish breakouts only trigger above the MA, bearish breakouts below.
The time filter shades the background during active trading hours.
Customization:
Adjustable pivot length for breakout sensitivity.
Risk settings: percentage risked, risk-reward ratio, and stop-loss type.
ATR settings: length, smoothing method (RMA, SMA, EMA, WMA).
Moving average filter (SMA, EMA, WMA, VWMA, HMA) to confirm breakouts.
Anchored Powered KAMA [LuxAlgo]The Anchored Powered KAMA tool is a new flavor of the famous Kaufman's Adaptive Moving Average (KAMA).
It adds 5 different anchoring periods, a power exponent to the original KAMA calculation to increase the degree of filtering during ranging trends, and standard deviation bands calculated against the KAMA itself.
🔶 USAGE
In the image above we can see the different parts of the tool, it displays the Anchored Powered KAMA surrounded by standard deviation bands at 2x (solid) and 1x (dashed) by default.
This tool provides a simple and easy way to determine if the current market is ranging or trending and where the market extremes are in the current period.
As a rule of thumb, traders may want to trade extremes in ranges and pullbacks in trends.
When the KAMA is flat, a range is in place, so traders may want to wait for the price to reach an extreme before opening a trade in the other direction.
Conversely, if the KAMA is moving up or down, a trend is in place and traders may want to wait for the price to pull back to the KAMA before opening a trade in the direction of the trend.
🔹 Anchor Period
On the above chart, we can see different anchor periods on different chart timeframes.
This option is very useful for those traders who use multi-timeframe analysis, allowing them to see how the market behaves over different timeframes.
The valid values for this parameter are:
Hourly
Daily
Weekly
Monthly
Yearly
The tool has a built-in Auto feature for traders convenience, it automatically selects the optimal Anchor Period in function of the chart timeframe.
timeframes up to 2m: Hourly
timeframes up to 15m: Daily
timeframes up to 1H: Weekly
timeframes up to 4H: Monthly
larger timeframes: Yearly
🔹 Choosing the Right Anchor Period
In the chart above we can see the custom error message that the tool displays when the Auto feature is disabled and the Anchor Period is too large for the current chart timeframe.
Traders can select a smaller Anchor Period or a larger chart timeframe for the tool to display correctly.
🔶 DETAILS
The tool uses Welford's algorithm to calculate the KAMA's standard deviation, then plots the outer bands at the multiplier specified in the settings panel, and the inner bands at the multiplier specified minus 1.
🔹 Power Exponent
The graph above shows how different values of this parameter can affect the output.
To display the original KAMA a value of 1 must be set, by default this parameter is set to 2.
The higher the value, the better the tool's ability to detect ranges.
🔶 SETTINGS
Anchor Period: Select up to 5 different time periods from Hourly, Daily, Weekly, Monthly, and Yearly.
Source: Choose the source for all calculations.
Power Exponent: Fine-tune the KAMA calculation, a value of 1 will output the original KAMA, and is set to 2 by default.
Band Multiplier: Select the multiplier for the standard deviation bands.
DynamicMALibrary "DynamicMA"
Dynamic Moving Averages Library
Introduction
The Dynamic Moving Averages Library is a specialized collection of custom built functions designed to calculate moving averages dynamically, beginning from the first available bar. Unlike standard moving averages, which rely on fixed length lookbacks, this library ensures that indicators remain fully functional from the very first data point, making it an essential tool for analysing assets with short time series or limited historical data.
This approach allows traders and developers to build robust indicators that do not require a preset amount of historical data before generating meaningful outputs. It is particularly advantageous for:
Newly listed assets with minimal price history.
High-timeframe trading, where large lookback periods can lead to delayed or missing data.
By eliminating the constraints of fixed lookback periods, this library enables the seamless construction of trend indicators, smoothing functions, and hybrid models that adapt instantly to market conditions.
Comprehensive Set of Custom Moving Averages
The library includes a wide range of custom dynamic moving averages, each designed for specific analytical use cases:
SMA (Simple Moving Average) – The fundamental moving average, dynamically computed.
EMA (Exponential Moving Average) – Adaptive smoothing for better trend tracking.
DEMA (Double Exponential Moving Average) – Faster trend detection with reduced lag.
TEMA (Triple Exponential Moving Average) – Even more responsive than DEMA.
WMA (Weighted Moving Average) – Emphasizes recent price action while reducing noise.
VWMA (Volume Weighted Moving Average) – Accounts for volume to give more weight to high-volume periods.
HMA (Hull Moving Average) – A superior smoothing method with low lag.
SMMA (Smoothed Moving Average) – A hybrid approach between SMA and EMA.
LSMA (Least Squares Moving Average) – Uses linear regression for trend detection.
RMA (Relative Moving Average) – Used in RSI-based calculations for smooth momentum readings.
ALMA (Arnaud Legoux Moving Average) – A Gaussian-weighted MA for superior signal clarity.
Hyperbolic MA (HyperMA) – A mathematically optimized averaging method with dynamic weighting.
Each function dynamically adjusts its calculation length to match the available bar count, ensuring instant functionality on all assets.
Fully Optimized for Pine Script v6
This library is built on Pine Script v6, ensuring compatibility with modern TradingView indicators and scripts. It includes exportable functions for seamless integration into custom indicators, making it easy to develop trend-following models, volatility filters, and adaptive risk-management systems.
Why Use Dynamic Moving Averages?
Traditional moving averages suffer from a common limitation: they require a fixed historical window to generate meaningful values. This poses several problems:
New Assets Have No Historical Data - If an asset has only been trading for a short period, traditional moving averages may not be able to generate valid signals.
High Timeframes Require Massive Lookbacks - On 1W or 1M charts, a 200-period SMA would require 200 weeks or months of data, making it unusable on newer assets.
Delayed Signal Initialization - Standard indicators often take dozens of bars to stabilize, reducing effectiveness when trading new trends.
The Dynamic Moving Averages Library eliminates these issues by ensuring that every function:
Starts calculation from bar one, using available data instead of waiting for a lookback period.
Adapts dynamically across timeframes, making it equally effective on low or high timeframes.
Allows smoother, more responsive trend tracking, particularly useful for volatile or low-liquidity assets.
This flexibility makes it indispensable for custom script developers, quantitative analysts, and discretionary traders looking to build more adaptive and resilient indicators.
Final Summary
The Dynamic Moving Averages Library is a versatile and powerful set of functions designed to overcome the limitations of fixed-lookback indicators. By dynamically adjusting the calculation length from the first bar, this library ensures that moving averages remain fully functional across all timeframes and asset types, making it an essential tool for traders and developers alike.
With built-in adaptability, low-lag smoothing, and support for multiple moving average types, this library unlocks new possibilities for quantitative trading and strategy development - especially for assets with short price histories or those traded on higher timeframes.
For traders looking to enhance signal reliability, minimize lag, and build adaptable trading systems, the Dynamic Moving Averages Library provides an efficient and flexible solution.
SMA(sourceData, maxLength)
Dynamic SMA
Parameters:
sourceData (float)
maxLength (int)
EMA(src, length)
Dynamic EMA
Parameters:
src (float)
length (int)
DEMA(src, length)
Dynamic DEMA
Parameters:
src (float)
length (int)
TEMA(src, length)
Dynamic TEMA
Parameters:
src (float)
length (int)
WMA(src, length)
Dynamic WMA
Parameters:
src (float)
length (int)
HMA(src, length)
Dynamic HMA
Parameters:
src (float)
length (int)
VWMA(src, volsrc, length)
Dynamic VWMA
Parameters:
src (float)
volsrc (float)
length (int)
SMMA(src, length)
Dynamic SMMA
Parameters:
src (float)
length (int)
LSMA(src, length, offset)
Dynamic LSMA
Parameters:
src (float)
length (int)
offset (int)
RMA(src, length)
Dynamic RMA
Parameters:
src (float)
length (int)
ALMA(src, length, offset_sigma, sigma)
Dynamic ALMA
Parameters:
src (float)
length (int)
offset_sigma (float)
sigma (float)
HyperMA(src, length)
Dynamic HyperbolicMA
Parameters:
src (float)
length (int)
[TehThomas] - MA Cross with DisplacementThis TradingView script, "MA Cross with Displacement," is designed to detect potential long and short trade opportunities based on moving average (MA) crossovers combined with price displacement confirmation. The script utilizes two simple moving averages (SMA) and highlights potential trade signals when a crossover occurs alongside a strong price movement (displacement).
Why This Indicator is Useful
This indicator enhances the standard moving average crossover strategy by incorporating a displacement condition, making trade signals more reliable. Many traders rely on moving average crossovers to determine trend reversals, but false signals often occur due to minor price fluctuations. By requiring a significant price movement (displacement), this indicator helps filter out weak or insignificant crossovers, leading to more high-probability trade opportunities.
How It Works
Calculates Two Moving Averages (MA)
The user can set two different MA periods:
MA 1 (blue line): Default period is 9 (shorter-term trend).
MA 2 (red line): Default period is 21 (longer-term trend).
These moving averages smooth out price fluctuations to identify overall trends.
Detects Crossovers
Bullish crossover: The blue MA crosses above the red MA + displacement candle → Potential long signal.
Example of bullish cross with displacement:
Bearish crossover: The blue MA crosses below the red MA + displacement candle → Potential short signal.
Example of bearish cross with displacement:
Confirms Displacement (Strong Price Move)
A price displacement threshold is used (default: 1.1% of the previous candle size).
For a valid trade signal, a crossover must occur alongside a strong price movement.
Bullish Displacement Condition: Price increased by more than the threshold.
Bearish Displacement Condition: Price decreased by more than the threshold.
Visual Indicators on the Chart
Bars are colored green when there is a bullish displacement.
Bars are colored red when there is a bearish displacement.
These color changes help traders quickly identify potential trade setups.
How to Use the Indicator
Add the Script to Your Chart
Copy and paste the script into TradingView's Pine Script Editor.
Click "Add to Chart" to activate it.
Customize the Settings
Adjust the moving average periods to fit your trading strategy.
Modify the displacement threshold based on market volatility.
Change the bar colors for better visualization.
Look for Trade Signals
Long Trade (Buy Signal)
The blue MA crosses above the red MA (bullish crossover).
A green bar appears, confirming bullish displacement.
Short Trade (Sell Signal)
The blue MA crosses below the red MA (bearish crossover).
A red bar appears, confirming bearish displacement.
Use in Conjunction with Other Indicators
This indicator works best when combined with support & resistance levels, RSI, MACD, or volume analysis to improve trade accuracy.
Final Thoughts
The MA Cross with Displacement Indicator improves the reliability of moving average crossovers by requiring strong price movements to confirm a trade signal. This helps traders avoid false breakouts and weak trends, making it a powerful tool for identifying high-probability trades.
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