BTC Transaction Indicator Name: "Bitcoin On-Chain Volume & Dynamic Parabolic Curve Signals"
Purpose:
This indicator is designed for Bitcoin traders and long-term holders. It combines the analysis of Bitcoin's on-chain transaction volume with price action to generate "Whale" and "Bear" signals. Additionally, it features a unique dynamic parabolic curve that acts as a visual support line, adapting its visibility based on price interaction with a key Exponential Moving Average (EMA).
Key Components:
On-Chain Volume Analysis:
Utilizes Estimated Transaction Volume (ETRAV) data from the Bitcoin blockchain.
Calculates fast and slow Simple Moving Averages (SMAs) of this volume.
Identifies volume trends (up/down) and significant volume increases/decreases.
Employs fixed thresholds (2,500,000 for low volume and 25,000,000 for high volume) to define key activity levels, similar to how historical on-chain analysis defined accumulation and distribution zones.
Price Action Analysis:
Calculates fast and slow SMAs of the price.
Detects price trends (up/down), recoveries, and declines based on these price SMAs.
"Whale" and "Bear" Signals:
Whale Signals (Buy-side): Generated when there's an upward volume trend, significant volume increase, and a downward price trend followed by price recovery. These indicate potential accumulation phases.
Bear Signals (Sell-side): Generated when there's a downward volume trend, significant volume decrease, and an upward price trend followed by price decline. These indicate potential distribution phases.
Visuals: Both types of signals are plotted as small, colored circles directly on the price chart, with corresponding text labels ("Whale," "Buy," "Bear," "Sell," "Price Recovering," "Price Declining").
Dynamic Parabolic Curve:
Concept: A green parabolic (exponential) curve that serves as a dynamic visual support line.
Activation: The curve starts drawing automatically only when the price crosses over the EMA 500 (Exponential Moving Average of 500 periods). The curve's starting point is set at a user-defined percentage below the EMA 500 value at that exact crossover point.
Visibility: The curve remains visible and continues its trajectory only as long as the price stays above the EMA 500.
Deactivation: The curve disappears instantly if the price falls below or equals the EMA 500. It will only reappear if the price crosses above the EMA 500 again.
Customization: The curve's steepness (Tasa Crecimiento Curva) and its initial distance from the EMA 500 (Inicio Curva % por debajo de EMA500) are adjustable.
Dynamic Label: A "Parabólico" text label is plotted near the center of the active curve segment, with an adjustable vertical offset to ensure it stays visually appealing below the curve.
What is PLOTTED on the chart:
The small, colored circle signals for Whale/Buy and Bear/Sell activity.
The green dynamic parabolic curve.
What is NOT PLOTTED:
EMA 200, EMA 500 lines (though they are calculated internally for logic).
Raw volume data or volume Moving Averages (these are only used for signal calculation, not plotted).
Ideal for:
Bitcoin traders and investors focused on long-term trends and cycle analysis, who want visual cues for accumulation/distribution phases based on on-chain activity, complemented by a unique, dynamically appearing parabolic support curve.
Important Notes:
Relies on the availability of external on-chain data (QUANDL:BCHAIN) within TradingView.
Functions best on a daily timeframe for optimal on-chain data relevance.
Cerca negli script per "Exponential"
Momentum ScopeOverview
Momentum Scope is a Pine Script™ v6 study that renders a –1 to +1 momentum heatmap across up to 32 lookback periods in its own pane. Using an Augmented Relative Momentum Index (ARMI) and color shading, it highlights where momentum strengthens, weakens, or stays flat over time—across any asset and timeframe.
Key Features
Full-Spectrum Momentum Map : Computes ARMI for 1–32 lookbacks, indexed from –1 (strong bearish) to +1 (strong bullish).
Flexible Scale Gradation : Choose Linear or Exponential spacing, with adjustable expansion ratio and maximum depth.
Trending Bias Control : Apply a contrast-style curve transform to emphasize trending vs. mean-reverting behavior.
Duotone & Tritone Palettes : Select between two vivid color styles, with user-definable hues for bearish, bullish, and neutral momentum.
Compact, Overlay-Free Display : Renders solely in its own pane—keeping your price chart clean.
Inputs & Customization
Scale Gradation : Linear or Exponential spacing of intervals
Scale Expansion : Ratio governing step-size between successive lookbacks
Scale Maximum : Maximum lookback period (and highest interval)
Trending Bias : Curve-transform bias to tilt the –1 … +1 grid
Color Style : Duotone or Tritone rendering modes
Reducing / Increasing / Neutral Colors : Pick your own hues for bearish, bullish, and flat zones
How to Use
Add to Chart : Apply “Momentum Scope” as a separate indicator.
Adjust Scale : For exponential spacing, switch your indicator Y-axis to Logarithmic .
Set Bias & Colors : Tweak Trending Bias and choose a palette that stands out on your layout.
Interpret the Heatmap :
Red tones = weakening/bearish momentum
Green tones = strengthening/bullish momentum
Neutral hues = indecision or flat momentum
Copyright © 2025 MVPMC. Licensed under MIT. For full license see opensource.org
Vix_Fix Enhanced MTF [Cometreon]The VIX Fix Enhanced is designed to detect market bottoms and spikes in volatility, helping traders anticipate major reversals with precision. Unlike standard VIX Fix tools, this version allows you to control the standard deviation logic, switch between chart styles, customize visual outputs, and set up advanced alerts — all with no repainting.
🧠 Logic and Calculation
This indicator is based on Larry Williams' VIX Fix and integrates features derived from community requests/advice, such as inverse VIX logic.
It calculates volatility spikes using a customizable standard deviation of the lows and compares it to a moving high to identify potential reversal points.
All moving average logic is based on Cometreon's proprietary library, ensuring accurate and optimized calculations on all 15 moving average types.
🔷 New Features and Improvements
🟩 Custom Visual Styles
Choose how you want your VIX data displayed:
Line
Step Line
Histogram
Area
Column
You can also flip the orientation (bottom-up or top-down), change the source ticker, and tailor the display to match your charting preferences.
🟩 Multi-MA Standard Deviation Calculation
Customize the standard deviation formula by selecting from 15 different moving averages:
SMA (Simple Moving Average)
EMA (Exponential Moving Average)
WMA (Weighted Moving Average)
RMA (Smoothed Moving Average)
HMA (Hull Moving Average)
JMA (Jurik Moving Average)
DEMA (Double Exponential Moving Average)
TEMA (Triple Exponential Moving Average)
LSMA (Least Squares Moving Average)
VWMA (Volume-Weighted Moving Average)
SMMA (Smoothed Moving Average)
KAMA (Kaufman’s Adaptive Moving Average)
ALMA (Arnaud Legoux Moving Average)
FRAMA (Fractal Adaptive Moving Average)
VIDYA (Variable Index Dynamic Average)
This gives you fine control over how volatility is measured and allows tuning the sensitivity for different market conditions.
🟩 Full Control Over Percentile and Deviation Conditions
You can enable or disable lines for standard deviation and percentile conditions, and define whether you want to trigger on over or under levels — adapting the indicator to your exact logic and style.
🟩 Chart Type Selection
You're no longer limited to candlestick charts! Now you can use Vix_Fix with different chart formats, including:
Candlestick
Heikin Ashi
Renko
Kagi
Line Break
Point & Figure
🟩 Multi-Timeframe Compatibility Without Repainting
Use a different timeframe from your chart with confidence. Signals remain stable and do not repaint. Perfect for spotting long-term reversal setups on lower timeframes.
🟩 Alert System Ready
Configure alerts directly from the indicator’s panel when conditions for over/under signals are met. Stay informed without needing to monitor the chart constantly.
🔷 Technical Details and Customizable Inputs
This indicator includes full control over the logic and appearance:
1️⃣ Length Deviation High - Adjusts the lookback period used to calculate the high deviation level of the VIX logic. Shorter values make it more reactive; longer values smooth out the signal.
2️⃣ Ticker - Choose a different chart type for the calculation, including Heikin Ashi, Renko, Kagi, Line Break, and Point & Figure.
3️⃣ Style VIX - Change the visual style (Line, Histogram, Column, etc.), adjust line width, and optionally invert the display (bottom-to-top).
📌 Fill zones for deviation and percentile are active only in Line and Step Line modes
4️⃣ Use Standard Deviation Up / Down - Enable the overbought and oversold zone logic based on upper and lower standard deviation bands.
5️⃣ Different Type MA (for StdDev) - Choose from 15 different moving averages to define the calculation method for standard deviation (SMA, EMA, HMA, JMA, etc.), with dedicated parameters like Phase, Sigma, and Offset for optimized responsiveness.
6️⃣ BB Length & Multiplier - Adjust the period and multiplier for the standard deviation bands, similar to how Bollinger Bands work.
7️⃣ Show StdDev Up / Down Line - Enable or disable the visibility of upper and lower standard deviation boundaries.
8️⃣ Use Percentile & Length High - Activate the percentile-based logic to detect extreme values in historical volatility using a customizable lookback length.
9️⃣ Highest % / Lowest % - Set the high and low percentile thresholds (e.g., 85 for high, 99 for low) that will be used to trigger over/under signals.
🔟 Show High / Low Percentile Line - Toggle the visual display of the percentile boundaries directly on the chart for clearer signal reference.
1️⃣1️⃣ Ticker Settings – Customize parameters for special chart types such as Renko, Heikin Ashi, Kagi, Line Break, and Point & Figure, adjusting reversal, number of lines, ATR length, etc.
1️⃣2️⃣ Timeframe – Enables using SuperTrend on a higher timeframe.
1️⃣3️⃣ Wait for Timeframe Closes -
✅ Enabled – Displays Vix_Fix smoothly with interruptions.
❌ Disabled – Displays Vix_Fix smoothly without interruptions.
☄️ If you find this indicator useful, leave a Boost to support its development!
Every feedback helps to continuously improve the tool, offering an even more effective trading experience. Share your thoughts in the comments! 🚀🔥
Demand Index (Hybrid Sibbet) by TradeQUODemand Index (Hybrid Sibbet) by TradeQUO \
\Overview\
The Demand Index (DI) was introduced by James Sibbet in the early 1990s to gauge “real” buying versus selling pressure by combining price‐change information with volume intensity. Unlike pure price‐based oscillators (e.g. RSI or MACD), the DI highlights moves backed by above‐average volume—helping traders distinguish genuine demand/supply from false breakouts or low‐liquidity noise.
\Calculation\
\
\ \Step 1: Weighted Price (P)\
For each bar t, compute a weighted price:
```
Pₜ = Hₜ + Lₜ + 2·Cₜ
```
where Hₜ=High, Lₜ=Low, Cₜ=Close of bar t.
Also compute Pₜ₋₁ for the prior bar.
\ \Step 2: Raw Range (R)\
Calculate the two‐bar range:
```
Rₜ = max(Hₜ, Hₜ₋₁) – min(Lₜ, Lₜ₋₁)
```
This Rₜ is used indirectly in the exponential dampener below.
\ \Step 3: Normalize Volume (VolNorm)\
Compute an EMA of volume over n₁ bars (e.g. n₁=13):
```
EMA_Volₜ = EMA(Volume, n₁)ₜ
```
Then
```
VolNormₜ = Volumeₜ / EMA_Volₜ
```
If EMA\_Volₜ ≈ 0, set VolNormₜ to a small default (e.g. 0.0001) to avoid division‐by‐zero.
\ \Step 4: BuyPower vs. SellPower\
Calculate “raw” BuyPowerₜ and SellPowerₜ depending on whether Pₜ > Pₜ₋₁ (bullish) or Pₜ < Pₜ₋₁ (bearish). Use an exponential dampener factor Dₜ to moderate extreme moves when true range is small. Specifically:
• If Pₜ > Pₜ₋₁,
```
BuyPowerₜ = (VolNormₜ) / exp
```
otherwise
```
BuyPowerₜ = VolNormₜ.
```
• If Pₜ < Pₜ₋₁,
```
SellPowerₜ = (VolNormₜ) / exp
```
otherwise
```
SellPowerₜ = VolNormₜ.
```
Here, H₀ and L₀ are the very first bar’s High/Low—used to calibrate the scale of the dampening. If the denominator of the exponential is near zero, substitute a small epsilon (e.g. 1e-10).
\ \Step 5: Smooth Buy/Sell Power\
Apply a short EMA (n₂ bars, typically n₂=2) to each:
```
EMA_Buyₜ = EMA(BuyPower, n₂)ₜ
EMA_Sellₜ = EMA(SellPower, n₂)ₜ
```
\ \Step 6: Raw Demand Index (DI\_raw)\
```
DI_rawₜ = EMA_Buyₜ – EMA_Sellₜ
```
A positive DI\_raw indicates that buying force (normalized by volume) exceeds selling force; a negative value indicates the opposite.
\ \Step 7: Optional EMA Smoothing on DI (DI)\
To reduce choppiness, compute an EMA over DI\_raw (n₃ bars, e.g. n₃ = 1–5):
```
DIₜ = EMA(DI_raw, n₃)ₜ.
```
If n₃ = 1, DI = DI\_raw (no further smoothing).
\
\Interpretation\
\
\ \Crossing Zero Line\
• DI\_raw (or DI) crossing from below to above zero signals that cumulative buying pressure (over the chosen smoothing window) has overcome selling pressure—potential Long signal.
• Crossing from above to below zero signals dominant selling pressure—potential Short signal.
\ \DI\_raw vs. DI (EMA)\
• When DI\_raw > DI (the EMA of DI\_raw), bullish momentum is accelerating.
• When DI\_raw < DI, bullish momentum is weakening (or bearish acceleration).
\ \Divergences\
• If price makes new highs while DI fails to make higher highs (DI\_raw or DI declining), this hints at weakening buying power (“bearish divergence”), possibly preceding a reversal.
• If price makes new lows while DI fails to make lower lows (“bullish divergence”), this may signal waning selling pressure and a potential bounce.
\ \Volume Confirmation\
• A strong price move without a corresponding rise in DI often indicates low‐volume “fake” moves.
• Conversely, a modest price move with a large DI spike suggests true institutional participation—often a more reliable breakout.
\
\Usage Notes & Warnings\
\
\ \Never Use DI in Isolation\
It is a \filter\ and \confirmation\ tool—combine with price‐action (trendlines, support/resistance, candlestick patterns) and risk management (stop‐losses) before executing trades.
\ \Parameter Selection\
• \Vol EMA length (n₁)\: Commonly 13–20 bars. Shorter → more responsive to volume spikes, but noisier.
• \Buy/Sell EMA length (n₂)\: Typically 2 bars for fast smoothing.
• \DI smoothing (n₃)\: Usually 1 (no smoothing) or 3–5 for moderate smoothing. Long DI\_EMA (e.g. 20–50) gives a slower signal.
\ \Market Adaptation\
Works well in liquid futures, indices, and heavily traded stocks. In thinly traded or highly erratic markets, adjust n₁ upward (e.g., 20–30) to reduce noise.
---
\In Summary\
The Demand Index (James Sibbet) uses a three‐stage smoothing (volume → Buy/Sell Power → DI) to reveal true demand/supply imbalance. By combining normalized volume with price change, Sibbet’s DI helps traders identify momentum backed by real participation—filtering out “empty” moves and spotting early divergences. Always confirm DI signals with price action and sound risk controls before trading.
TrueTrend MaxRThe TrueTrend MaxR indicator is designed to identify the most consistent exponential price trend over extended periods. It uses statistical analysis on log-transformed prices to find the trendline that best fits historical price action, and highlights the most frequently tested or traded level within that trend channel.
For optimal results, especially on high timeframes such as weekly or monthly, it is recommended to use this indicator on charts set to logarithmic scale. This ensures proper visual alignment with the exponential nature of long-term price movements.
How it works
The indicator tests 50 different lookback periods, ranging from 300 to 1280 bars. For each period, it:
- Applies a linear regression on the natural logarithm of the price
- Computes the slope and intercept of the trendline
- Calculates the unbiased standard deviation from the regression line
- Measures the correlation strength using Pearson's R coefficient
The period with the highest Pearson R value is selected, meaning the trendline drawn corresponds to the log-scale trend with the best statistical fit.
Trendline and deviation bands
Once the optimal period is identified, the indicator plots:
- A main log-scale trendline
- Upper and lower bands, based on a user-defined multiple of the standard deviation
These bands help visualize how far price deviates from its core trend, and define the range of typical fluctuations.
Point of Control (POC)
Inside the trend channel, the space between upper and lower bands is divided into 15 logarithmic levels. The script evaluates how often price has interacted with each level, using one of two selectable methods:
- Touches: Counts the number of candles crossing each level
- Volume: Weighs each touch by the traded volume at that candle
The level with the highest cumulative interaction is considered the dynamic Point of Control (POC), and is plotted as a line.
Annualized performance and confidence display
When used on daily or weekly timeframes, the script also calculates the annualized return (CAGR) based on the detected trend, and displays:
- A performance estimate in percentage terms
- A textual label describing the confidence level based on the Pearson R value
Why this indicator is useful
- Automatically detects the most statistically consistent exponential trendline
- Designed for log-scale analysis, suited to long-term investment charts
- Highlights key price levels frequently visited or traded within the trend
- Provides objective, data-based trend and volatility insights
- Displays annualized growth rate and correlation strength for quick evaluation
Notes
- All calculations are performed only on the last bar
- No future data is used, and the script does not repaint
- Works on any instrument or timeframe, with optimal use on higher timeframes and logarithmic scaling
Heikinisi Candle (With MA + Smoothing + Buy/Sell with Cooldown)This custom Heikinisi Candle (With MA + Smoothing + Buy/Sell with Cooldown) indicator combines the advantages of Heikin-Ashi candles with the flexibility of multiple moving averages and smoothing options. The built-in buy/sell signals with cooldown functionality help traders avoid overtrading while capturing trend reversals and momentum shifts. Whether you're a day trader, swing trader, or long-term investor, this indicator offers powerful tools for analyzing price action and making informed trading decisions.
Note: Disable the regular candle to get better visualization.
Key Features:
Custom Heikin-Ashi Candles:
The core feature of this script is the Heikin-Ashi candles, which are known for smoothing price action and helping traders identify market trends more clearly.
Unlike traditional Heikin-Ashi, this version adjusts the Heikin-Ashi close based on specific price action patterns, including rejection signals and engulfing patterns.
The custom Heikin-Ashi open also incorporates momentum, adjusting dynamically based on recent price changes.
Price Action Measurements:
The indicator measures key price action components, including:
Body: The absolute difference between the open and close.
Candle Range: The total range from high to low.
Upper Wick: The distance from the highest price to the maximum of open or close.
Lower Wick: The distance from the lowest price to the minimum of open or close.
These measurements help detect bullish and bearish conditions, as well as price rejection signals.
Buy/Sell Signal Logic:
Buy Signal: Triggered when the Heikin-Ashi close is above the chosen moving average (MA1), with a cooldown period to avoid too frequent signals.
Sell Signal: Triggered when the Heikin-Ashi close falls below the MA1 after a buy signal has already been issued.
The cooldown period ensures that buy and sell signals are spaced apart by a specific number of bars, preventing excessive signal generation during periods of price consolidation.
Multiple Moving Averages (MA):
This script supports up to three customizable moving averages (MA1, MA2, MA3), each of which can be set to different types and lengths, including:
Simple Moving Average (SMA)
Exponential Moving Average (EMA)
Weighted Moving Average (WMA)
Volume Weighted Moving Average (VWMA)
Volume Weighted Moving Price (VWMP)
Least Squares Moving Average (LSMA)
Hull Moving Average (HMA)
Double Exponential Moving Average (DEMA)
Triple Exponential Moving Average (TEMA)
Users can adjust the length and type of each MA for tailored analysis.
Smoothing Options for MAs:
Users can smooth the output of MAs using various types of smoothing algorithms (SMA, EMA, LSMA, WMA, Gaussian) and a customizable length. This helps to reduce noise in the moving average lines and provides clearer signals.
Gaussian Filter (Advanced Smoothing):
A Gaussian Filter is available as a smoothing option for MAs. This filter reduces noise and makes the moving averages smoother, which can be particularly helpful in volatile or choppy markets.
Alerts and Visualization:
The script allows users to plot buy and sell signals on the chart with distinctive markers. A Buy Signal is shown below the bar with a lime green marker and text "Buy," while a Sell Signal is shown above the bar with a red marker and text "Sell."
Traders can also set up alerts based on the buy/sell signals to get notified in real time.
Indicator Configuration:
Heikin-Ashi Candle Configuration:
Automatically adjusts Heikin-Ashi candles based on rejection signals, engulfing patterns, and momentum. It uses custom formulas for the Heikin-Ashi open and close, making it more sensitive to price action than standard Heikin-Ashi candles.
Moving Averages (MA) Configuration:
You can select from multiple moving average types and lengths (MA1, MA2, MA3) for trend-following analysis.
Choose between SMA, EMA, WMA, VWMA, VWMP, LSMA, HMA, DEMA, and TEMA.
Smoothing Options:
Enable or disable smoothing for the moving averages.
Select from different smoothing types, including SMA, EMA, RMA, WMA, LSMA, and Gaussian.
Cooldown Period:
Control the number of bars that must pass before a new buy/sell signal is triggered. This cooldown period helps prevent excessive trading signals in quick succession.
How to Use:
Analyze Price Action with Heikin-Ashi Candles:
The custom Heikin-Ashi candles are ideal for spotting market trends, reversals, and price rejection. Use the candle patterns to gauge the market sentiment.
Use MAs for Trend Confirmation:
The moving averages (MA1, MA2, MA3) can help identify the prevailing trend. A price above a rising MA indicates an uptrend, while a price below a falling MA suggests a downtrend.
Trigger Buy and Sell Signals:
When the Heikin-Ashi close crosses above MA1, a buy signal is triggered.
When the Heikin-Ashi close crosses below MA1 after a buy signal, a sell signal is triggered.
The cooldown period ensures that signals are spaced out, preventing overtrading.
Use Smoothing for Clearer Signals:
If you are trading in a volatile market, you can use the smoothing options to make the MAs smoother and reduce noise.
Weekly Moving Averages (MAs) to Intraday ChartThis indicator overlays key weekly timeframe moving averages onto your intraday chart, allowing you to visualize important long-term support and resistance levels while trading shorter timeframes. The indicator includes:
330-period Simple Moving Average (white): Ultra long-term trend indicator
200-period Simple Moving Average (fuchsia): Major long-term trend indicator often watched by institutional traders
100-period Simple Moving Average (purple): Medium-to-long term trend indicator
50-period Exponential Moving Average (blue): Medium-term trend indicator, more responsive to recent price action
21-period Exponential Moving Average (teal): Short-to-medium term trend indicator
9-period Exponential Moving Average (aqua): Short-term trend indicator, highly responsive to recent price movements
This multi-timeframe approach helps identify significant support/resistance zones that might not be visible on your current timeframe. When price interacts with these weekly moving averages during intraday trading, it often signals important areas where institutional orders may be placed.
The indicator uses color-coding with increasing line thickness to help you quickly distinguish between different moving averages. Consider areas where multiple MAs cluster together as particularly strong support/resistance zones.
Perfect for day traders and swing traders who want to maintain awareness of the bigger picture while focusing on shorter-term price action.
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!
Dskyz (DAFE) MAtrix with ATR-Powered Precision Dskyz (DAFE) MAtrix with ATR-Powered Precision
This cutting‐edge futures trading strategy built to thrive in rapidly changing market conditions. Developed for high-frequency futures trading on instruments such as the CME Mini MNQ, this strategy leverages a matrix of sophisticated moving averages combined with ATR-based filters to pinpoint high-probability entries and exits. Its unique combination of adaptable technical indicators and multi-timeframe trend filtering sets it apart from standard strategies, providing enhanced precision and dynamic responsiveness.
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Core Functional Components
1. Advanced Moving Averages
A distinguishing feature of the DAFE strategy is its robust, multi-choice moving averages (MAs). Clients can choose from a wide array of MAs—each with specific strengths—in order to fine-tune their trading signals. The code includes user-defined functions for the following MAs:
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Hull Moving Average (HMA):
The hma(src, len) function calculates the HMA by using weighted moving averages (WMAs) to reduce lag considerably while smoothing price data. This function computes an intermediate WMA of half the specified length, then a full-length WMA, and finally applies a further WMA over the square root of the length. This design allows for rapid adaptation to price changes without the typical delays of traditional moving averages.
Triple Exponential Moving Average (TEMA):
Implemented via tema(src, len), TEMA uses three consecutive exponential moving averages (EMAs) to effectively cancel out lag and capture price momentum. The final formula—3 * (ema1 - ema2) + ema3—produces a highly responsive indicator that filters out short-term noise.
Double Exponential Moving Average (DEMA):
Through the dema(src, len) function, DEMA calculates an EMA and then a second EMA on top of it. Its simplified formula of 2 * ema1 - ema2 provides a smoother curve than a single EMA while maintaining enhanced responsiveness.
Volume Weighted Moving Average (VWMA):
With vwma(src, len), this MA accounts for trading volume by weighting the price, thereby offering a more contextual picture of market activity. This is crucial when volume spikes indicate significant moves.
Zero Lag EMA (ZLEMA):
The zlema(src, len) function applies a correction to reduce the inherent lag found in EMAs. By subtracting a calculated lag (based on half the moving average window), ZLEMA is exceptionally attuned to recent price movements.
Arnaud Legoux Moving Average (ALMA):
The alma(src, len, offset, sigma) function introduces ALMA—a type of moving average designed to be less affected by outliers. With parameters for offset and sigma, it allows customization of the degree to which the MA reacts to market noise.
Kaufman Adaptive Moving Average (KAMA):
The custom kama(src, len) function is noteworthy for its adaptive nature. It computes an efficiency ratio by comparing price change against volatility, then dynamically adjusts its smoothing constant. This results in an MA that quickly responds during trending periods while remaining smoothed during consolidation.
Each of these functions—integrated into the strategy—is selectable by the trader (via the fastMAType and slowMAType inputs). This flexibility permits the tailored application of the MA most suited to current market dynamics and individual risk management preferences.
2. ATR-Based Filters and Risk Controls
ATR Calculation and Volatility Filter:
The strategy computes the Average True Range (ATR) over a user-defined period (atrPeriod). ATR is then used to derive both:
Volatility Assessment: Expressed as a ratio of ATR to closing price, ensuring that trades are taken only when volatility remains within a safe, predefined threshold (volatilityThreshold).
ATR-Based Entry Filters: Implemented as atrFilterLong and atrFilterShort, these conditions ensure that for long entries the price is sufficiently above the slow MA and vice versa for shorts. This acts as an additional confirmation filter.
Dynamic Exit Management:
The exit logic employs a dual approach:
Fixed Stop and Profit Target: Stops and targets are set at multiples of ATR (fixedStopMultiplier and profitTargetATRMult), helping manage risk in volatile markets.
Trailing Stop Adjustments: A trailing stop is calculated using the ATR multiplied by a user-defined offset (trailOffset), which captures additional profits as the trade moves favorably while protecting against reversals.
3. Multi-Timeframe Trend Filtering
The strategy enhances its signal reliability by leveraging a secondary, higher timeframe analysis:
15-Minute Trend Analysis:
By retrieving 15-minute moving averages (fastMA15m and slowMA15m) via request.security, the strategy determines the broader market trend. This secondary filter (enabled or disabled through useTrendFilter) ensures that entries are aligned with the prevailing market direction, thereby reducing the incidence of false signals.
4. Signal and Execution Logic
Combined MA Alignment:
The entry conditions are based primarily on the alignment of the fast and slow MAs. A long condition is triggered when the current price is above both MAs and the fast MA is above the slow MA—complemented by the ATR filter and volume conditions. The reverse applies for a short condition.
Volume and Time Window Validation:
Trades are permitted only if the current volume exceeds a minimum (minVolume) and the current hour falls within the predefined trading window (tradingStartHour to tradingEndHour). An additional volume spike check (comparing current volume to a moving average of past volumes) further filters for optimal market conditions.
Comprehensive Order Execution:
The strategy utilizes flexible order execution functions that allow pyramiding (up to 10 positions), ensuring that it can scale into positions as favorable conditions persist. The use of both market entries and automated exits (with profit targets, stop-losses, and trailing stops) ensures that risk is managed at every step.
5. Integrated Dashboard and Metrics
For transparency and real-time analysis, the strategy includes:
On-Chart Visualizations:
Both fast and slow MAs are plotted on the chart, making it easy to see the market’s technical foundation.
Dynamic Metrics Dashboard:
A built-in table displays crucial performance statistics—including current profit/loss, equity, ATR (both raw and as a percentage), and the percentage gap between the moving averages. These metrics offer immediate insight into the health and performance of the strategy.
Input Parameters: Detailed Breakdown
Every input is meticulously designed to offer granular control:
Fast & Slow Lengths:
Determine the window size for the fast and slow moving averages. Smaller values yield more sensitivity, while larger values provide a smoother, delayed response.
Fast/Slow MA Types:
Choose the type of moving average for fast and slow signals. The versatility—from basic SMA and EMA to more complex ones like HMA, TEMA, ZLEMA, ALMA, and KAMA—allows customization to fit different market scenarios.
ATR Parameters:
atrPeriod and atrMultiplier shape the volatility assessment, directly affecting entry filters and risk management through stop-loss and profit target levels.
Trend and Volume Filters:
Inputs such as useTrendFilter, minVolume, and the volume spike condition help confirm that a trade occurs in active, trending markets rather than during periods of low liquidity or market noise.
Trading Hours:
Restricting trade execution to specific hours (tradingStartHour and tradingEndHour) helps avoid illiquid or choppy markets outside of prime trading sessions.
Exit Strategies:
Parameters like trailOffset, profitTargetATRMult, and fixedStopMultiplier provide multiple layers of risk management and profit protection by tailoring how exits are generated relative to current market conditions.
Pyramiding and Fixed Trade Quantity:
The strategy supports multiple entries within a trend (up to 10 positions) and sets a predefined trade quantity (fixedQuantity) to maintain consistent exposure and risk per trade.
Dashboard Controls:
The resetDashboard input allows for on-the-fly resetting of performance metrics, keeping the strategy’s performance dashboard accurate and up-to-date.
Why This Strategy is Truly Exceptional
Multi-Faceted Adaptability:
The ability to switch seamlessly between various moving average types—each suited to particular market conditions—enables the strategy to adapt dynamically. This is a testament to the high level of coding sophistication and market insight infused within the system.
Robust Risk Management:
The integration of ATR-based stops, profit targets, and trailing stops ensures that every trade is executed with well-defined risk parameters. The system is designed to mitigate unexpected market swings while optimizing profit capture.
Comprehensive Market Filtering:
By combining moving average crossovers with volume analysis, volatility thresholds, and multi-timeframe trend filters, the strategy only enters trades under the most favorable conditions. This multi-layered filtering reduces noise and enhances signal quality.
-Final Thoughts-
The Dskyz Adaptive Futures Elite (DAFE) MAtrix with ATR-Powered Precision strategy is not just another trading algorithm—it is a multi-dimensional, fully customizable system built on advanced technical principles and sophisticated risk management techniques. Every function and input parameter has been carefully engineered to provide traders with a system that is both powerful and transparent.
For clients seeking a state-of-the-art trading solution that adapts dynamically to market conditions while maintaining strict discipline in risk management, this strategy truly stands in a class of its own.
****Please show support if you enjoyed this strategy. I'll have more coming out in the near future!!
-Dskyz
Caution
DAFE is experimental, not a profit guarantee. Futures trading risks significant losses due to leverage. Backtest, simulate, and monitor actively before live use. All trading decisions are your responsibility.
Volume Flow with Bollinger Bands and EMA Cross SignalsThe Volume Flow with Bollinger Bands and EMA Cross Signals indicator is a custom technical analysis tool designed to identify potential buy and sell signals based on several key components:
Volume Flow: This component combines price movement and trading volume to create a signal that indicates the strength or weakness of price movements. When the price is rising with increasing volume, it suggests strong buying activity, whereas falling prices with increasing volume indicate strong selling pressure.
Bollinger Bands: Bollinger Bands consist of three lines:
The Basis (middle line), which is a Simple Moving Average (SMA) of the price over a set period.
The Upper Band, which is the Basis plus a multiple of the standard deviation (typically 2).
The Lower Band, which is the Basis minus a multiple of the standard deviation. Bollinger Bands help identify periods of high volatility and potential overbought/oversold conditions. When the price touches the upper band, it might indicate that the market is overbought, while touching the lower band might indicate oversold conditions.
EMA Crossovers: The script includes two Exponential Moving Averages (EMAs):
Fast EMA: A shorter-term EMA, typically more sensitive to price changes.
Slow EMA: A longer-term EMA, responding slower to price changes. The crossover of the Fast EMA crossing above the Slow EMA (bullish crossover) signals a potential buy opportunity, while the Fast EMA crossing below the Slow EMA (bearish crossover) signals a potential sell opportunity.
Background Color and Candle Color: The indicator highlights the chart's background with specific colors based on the signals:
Green background for buy signals.
Yellow background for sell signals. Additionally, the candles are colored green for buy signals and yellow for sell signals to visually reinforce the trade opportunities.
Buy/Sell Labels: Small labels are placed on the chart:
"BUY" label in green is placed below the bar when a buy signal is generated.
"SELL" label in yellow is placed above the bar when a sell signal is generated.
Working of the Indicator:
Volume Flow Calculation: The Volume Flow is calculated by multiplying the price change (current close minus the previous close) with the volume. This product is then smoothed with a Simple Moving Average (SMA) over a user-defined period (length). The result is then multiplied by a multiplier to adjust its sensitivity.
Price Change = close - close
Volume Flow = Price Change * Volume
Smoothed Volume Flow = SMA(Volume Flow, length)
The Volume Flow Signal is then: Smooth Volume Flow * Multiplier
This calculation represents the buying or selling pressure in the market.
Bollinger Bands: Bollinger Bands are calculated using the Simple Moving Average (SMA) of the closing price (basis) and the Standard Deviation (stdev) of the price over a period defined by the user (bb_length).
Basis (Middle Band) = SMA(close, bb_length)
Upper Band = Basis + (bb_std_dev * Stdev)
Lower Band = Basis - (bb_std_dev * Stdev)
The upper and lower bands are plotted alongside the price to identify the price's volatility. When the price is near the upper band, it could be overbought, and near the lower band, it could be oversold.
EMA Crossovers: The Fast EMA and Slow EMA are calculated using the Exponential Moving Average (EMA) function. The crossovers are detected by checking:
Buy Signal (Bullish Crossover): When the Fast EMA crosses above the Slow EMA.
Sell Signal (Bearish Crossover): When the Fast EMA crosses below the Slow EMA.
The long_condition variable checks if the Fast EMA crosses above the Slow EMA, and the short_condition checks if it crosses below.
Visual Signals:
Background Color: The background is colored green for a buy signal and yellow for a sell signal. This gives an immediate visual cue to the trader.
Bar Color: The candles are colored green for buy signals and yellow for sell signals.
Labels:
A "BUY" label in green appears below the bar when the Fast EMA crosses above the Slow EMA.
A "SELL" label in yellow appears above the bar when the Fast EMA crosses below the Slow EMA.
Summary of Buy/Sell Logic:
Buy Signal:
The Fast EMA crosses above the Slow EMA (bullish crossover).
Volume flow is positive, indicating buying pressure.
Background turns green and candles are colored green.
A "BUY" label appears below the bar.
Sell Signal:
The Fast EMA crosses below the Slow EMA (bearish crossover).
Volume flow is negative, indicating selling pressure.
Background turns yellow and candles are colored yellow.
A "SELL" label appears above the bar.
Usage of the Indicator:
This indicator is designed to help traders identify potential entry (buy) and exit (sell) points based on:
The interaction of Exponential Moving Averages (EMAs).
The strength and direction of Volume Flow.
Price volatility using Bollinger Bands.
By combining these components, the indicator provides a comprehensive view of market conditions, helping traders make informed decisions on when to enter and exit trades.
TTM Squeeze Momentum MTF [Cometreon]TTM Squeeze Momentum MTF combines the core logic of both the Squeeze Momentum by LazyBear and the TTM Squeeze by John Carter into a single, unified indicator. It offers a complete system to analyze the phase, direction, and strength of market movements.
Unlike the original versions, this indicator allows you to choose how to calculate the trend, select from 15 different types of moving averages, customize every parameter, and adapt the visual style to your trading preferences.
If you are looking for a powerful, flexible and highly configurable tool, this is the perfect choice for you.
🔷 New Features and Improvements
🟩 Unified System: Trend Detection + Visual Style
You can decide which logic to use for the trend via the "Show TTM Squeeze Trend" input:
✅ Enabled → Trend calculated using TTM Squeeze
❌ Disabled → Trend based on Squeeze Momentum
You can also customize the visual style of the indicator:
✅ Enable "Show Histogram" for a visual mode using Histogram, Area, or Column
❌ Disable it to display the classic LazyBear-style line
Everything updates automatically and dynamically based on your selection.
🟩 Full Customization
Every base parameter of the original indicator is now fully configurable: lengths, sources, moving average types, and more.
You can finally adapt the squeeze logic to your strategy — not the other way around.
🟩 Multi-MA Engine
Choose from 15 different Moving Averages for each part of the calculation:
SMA (Simple Moving Average)
EMA (Exponential Moving Average)
WMA (Weighted Moving Average)
RMA (Smoothed Moving Average)
HMA (Hull Moving Average)
JMA (Jurik Moving Average)
DEMA (Double Exponential Moving Average)
TEMA (Triple Exponential Moving Average)
LSMA (Least Squares Moving Average)
VWMA (Volume-Weighted Moving Average)
SMMA (Smoothed Moving Average)
KAMA (Kaufman’s Adaptive Moving Average)
ALMA (Arnaud Legoux Moving Average)
FRAMA (Fractal Adaptive Moving Average)
VIDYA (Variable Index Dynamic Average)
🟩 Dynamic Signal Line
Apply a moving average to the momentum for real-time cross signals, with full control over its length and type.
🟩 Multi-Timeframe & Multi-Ticker Support
You're no longer limited to the chart's current timeframe or ticker. Apply the squeeze to any symbol or timeframe without repainting.
🔷 Technical Details and Customizable Inputs
This indicator offers a fully modular structure with configurable parameters for every component:
1️⃣ Squeeze Momentum Settings – Choose the source, length, and type of moving average used to calculate the base momentum.
2️⃣ Trend Mode Selector – Toggle "Show TTM Squeeze Trend" to select the trend logic displayed on the chart:
✅ Enabled – Shows the trend based on TTM Squeeze (Bollinger Bands inside/outside Keltner Channel)
❌ Disabled – Displays the trend based on Squeeze Momentum logic
🔁 The moving average type for the Keltner Channel is handled automatically, so you don't need to select it manually, even if the custom input is disabled.
3️⃣ Signal Line – Toggle the Signal Line on the Squeeze Momentum. Select its length and MA type to generate visual cross signals.
4️⃣ Bollinger Bands – Configure the length, multiplier, source, and MA type used in the bands.
5️⃣ Keltner Channel – Adjust the length, multiplier, source, and MA type. You can also enable or disable the True Range option.
6️⃣ Advanced MA Parameters – Customize the parameters for advanced MAs (JMA, ALMA, FRAMA, VIDYA), including Phase, Power, Offset, Sigma, and Shift values.
7️⃣ Ticker & Input Source – Select the ticker and manage inputs for alternative chart types like Renko, Kagi, Line Break, and Point & Figure.
8️⃣ Style Settings – Choose how the squeeze is displayed:
Enable "Show Histogram" for Histogram, Area, or Column style
Disable it to show the classic LazyBear-style line
Use Reverse Color to invert line colors
Toggle Show Label to highlight Signal Line cross signals
Customize trend colors to suit your preferences
9️⃣ Multi-Timeframe Options - Timeframe – Use the squeeze on higher timeframes for stronger confirmation
🔟 Wait for Timeframe Closes -
✅ Enabled – Prevents multiple signals within the same candle
❌ Disabled – Displays the indicator smoothly without delay
🔧 Default Settings Reference
To replicate the default settings of the original indicators as they appear when first applied to the chart, use the following configurations:
🟩 TTM Squeeze (John Carter Style)
Squeeze
Length: 20
MA Type: SMA
Show TTM Squeeze Trend: Enabled
Bollinger Bands
Length: 20
Multiplier: 2.0
MA Type: SMA
Keltner Channel
Length: 20
Multiplier: 1.0
Use True Range: ON
MA Type: EMA
Style
Show Histogram: Enabled
Reverse Color: Enabled
🟩 Squeeze Momentum (LazyBear Style)
Squeeze
Length: 10
MA Type: SMA
Show TTM Squeeze Trend: Disabled
Bollinger Bands
Length: 20
Multiplier: 1.5
MA Type: SMA
Keltner Channel
Length: 10
Multiplier: 1.5
Use True Range: ON
MA Type: SMA
Style
Show Histogram: Disabled
Reverse Color: Disabled
⚠️ These values are intended as a starting point. The Cometreon indicator lets you fully customize every input to fit your trading style.
🔷 How to Use Squeeze Momentum Pro
🔍 Identifying Trends
Squeeze Momentum Pro supports two different methods for identifying the trend visually, each based on a distinct logic:
Squeeze Momentum Trend (LazyBear-style):
Displays 3 states based on the position of the Bollinger Bands relative to the Keltner Channel:
🔵 Blue = No Squeeze (BB outside KC and KC outside BB)
⚪️ White = Squeeze Active (BB fully inside KC)
⚫️ Gray = Neutral state (none of the above)
TTM Squeeze Trend (John Carter-style):
Calculates the difference in width between the Bollinger Bands and the Keltner Channel:
🟩 Green = BB width is greater than KC → potential expansion phase
🟥 Red = BB are tighter than KC → possible compression or pre-breakout
📈 Interpreting Signals
Depending on the active configuration, the indicator can provide various signals, including:
Trend color → Reflects the current compression/expansion state (based on selected mode)
Momentum value (above or below 0) → May indicate directional pressure
Signal Line cross → Can highlight momentum shifts
Color change in the momentum → May suggest a potential trend reversal
🛠 Integration with Other Tools
Squeeze Momentum Pro works well alongside other indicators to strengthen market context:
✅ Volume Profile / OBV – Helps confirm accumulation or distribution during squeezes
✅ RSI – Useful to detect divergence between momentum and price
✅ Moving Averages – Ideal for defining primary trend direction and filtering signals
☄️ If you find this indicator useful, leave a Boost to support its development!
Every piece of feedback helps improve the tool and deliver an even better trading experience.
🔥 Share your ideas or feature requests in the comments!
SuperTrend MTF Pro [Cometreon]The SuperTrend MTF Pro takes the classic SuperTrend to a whole new level of customization and accuracy. Unlike the standard version, this indicator allows you to select different moving averages, apply it to various chart types, and fine-tune every key parameter.
If you're looking for an advanced, non-repainting, and highly configurable SuperTrend, this is the right choice for you.
🔷 New Features and Improvements
🟩 Multi-MA SuperTrend
Now you can customize the SuperTrend calculation by choosing from 15 different moving averages:
SMA (Simple Moving Average)
EMA (Exponential Moving Average)
WMA (Weighted Moving Average)
RMA (Smoothed Moving Average)
HMA (Hull Moving Average)
JMA (Jurik Moving Average)
DEMA (Double Exponential Moving Average)
TEMA (Triple Exponential Moving Average)
LSMA (Least Squares Moving Average)
VWMA (Volume-Weighted Moving Average)
SMMA (Smoothed Moving Average)
KAMA (Kaufman’s Adaptive Moving Average)
ALMA (Arnaud Legoux Moving Average)
FRAMA (Fractal Adaptive Moving Average)
VIDYA (Variable Index Dynamic Average)
🟩 Multiple Chart Types
You're no longer limited to candlestick charts! Now you can use SuperTrend with different chart formats, including:
Heikin Ashi
Renko
Kagi
Line Break
Point & Figure
🟩 Customizable Timeframe
Now you can adjust the SuperTrend timeframe without repainting issues, avoiding signal distortions.
🔷 Technical Details and Customizable Inputs
SuperTrend offers multiple customization options to fit any trading strategy:
1️⃣ ATR Period – Defines the ATR length, affecting the indicator’s sensitivity.
2️⃣ Source – Selects the price value used for calculations (Close, HL2, Open, etc.).
3️⃣ ATR Mult – Multiplies the ATR to determine band distance. Higher values reduce false signals, lower values make it more reactive.
4️⃣ Change ATR Calculation Method – When enabled, uses the default ATR method; when disabled, allows selecting another Moving Average with "Use Different Type".
5️⃣ Source Break – Defines the price source for trend changes (Close for more stability, High/Low for more reactivity).
6️⃣ Use Different Type – Allows selecting an alternative Moving Average for ATR calculation if "Change ATR Calculation Method" is disabled.
7️⃣ SuperTrend Type – Advanced options for specific MAs (JMA, ALMA, FRAMA, VIDYA), with dedicated parameters like Phase, Sigma, and Offset for optimized responsiveness.
8️⃣ Ticker Settings – Customize parameters for special chart types such as Renko, Heikin Ashi, Kagi, Line Break, and Point & Figure, adjusting reversal, number of lines, and ATR length.
9️⃣ Timeframe – Enables using SuperTrend on a higher timeframe.
🔟 Wait for Timeframe Closes -
✅ Enabled – Prevents multiple signals, useful for precise alerts.
❌ Disabled – Displays SuperTrend smoothly without interruptions.
🔷 How to Use SuperTrend MTF Pro
🔍 Identifying Trends
SuperTrend follows the ongoing trend and provides clear visual signals:
When the price is above the line, the trend is bullish.
When the price is below the line, the trend is bearish.
📈 Interpreting Signals
Line color and position change → Possible trend reversal
Bounce off the line → Potential trend continuation
Strong breakout of the line → Possible reversal
🛠 Integration with Other Tools
RSI or MACD to filter false signals
Moving Averages to confirm trend direction
Support and Resistance to improve entry points
☄️ If you find this indicator useful, leave a Boost to support its development!
Every feedback helps to continuously improve the tool, offering an even more effective trading experience. Share your thoughts in the comments! 🚀🔥
[F.B]_ZLEMA MACD ZLEMA MACD – A Zero-Lag Variant of the Classic MACD
Introduction & Motivation
The Moving Average Convergence Divergence (MACD) is a standard indicator for measuring trend strength and momentum. However, it suffers from the latency of traditional Exponential Moving Averages (EMAs).
This variant replaces EMAs with Zero Lag Exponential Moving Averages (ZLEMA), reducing delay and increasing the indicator’s responsiveness. This can potentially lead to earlier trend change detection, especially in highly volatile markets.
Calculation Methodology
2.1 Zero-Lag Exponential Moving Average (ZLEMA)
The classic EMA formula is extended with a correction factor:
ZLEMA_t = EMA(2 * P_t - EMA(P_t, L), L)
where:
P_t is the closing price,
L is the smoothing period length.
2.2 MACD Calculation Using ZLEMA
MACD_t = ZLEMA_short,t - ZLEMA_long,t
with standard parameters of 12 and 26 periods.
2.3 Signal Line with Adaptive Methodology
The signal line can be calculated using ZLEMA, EMA, or SMA:
Signal_t = f(MACD, S)
where f is the chosen smoothing function and S is the period length.
2.4 Histogram as a Measure of Momentum Changes
Histogram_t = MACD_t - Signal_t
An increasing histogram indicates a relative acceleration in trend strength.
Potential Applications in Data Analysis
Since the indicator is based solely on price time series, its effectiveness as a standalone trading signal is limited. However, in quantitative models, it can be used as a feature for trend quantification or for filtering market phases with strong trend dynamics.
Potential use cases include:
Trend Classification: Segmenting market phases into "trend" vs. "mean reversion."
Momentum Regime Identification: Analyzing histogram dynamics to detect increasing or decreasing trend strength.
Signal Smoothing: An alternative to classic EMA smoothing in more complex multi-factor models.
Important: Using this as a standalone trading indicator without additional confirmation mechanisms is not recommended, as it does not demonstrate statistical superiority over other momentum indicators.
Evaluation & Limitations
✅ Advantages:
Reduced lag compared to the classic MACD.
Customizable signal line smoothing for different applications.
Easy integration into existing analytical pipelines.
⚠️ Limitations:
Not a standalone trading system: Like any moving average, this indicator is susceptible to noise and false signals in sideways markets.
Parameter sensitivity: Small changes in period lengths can lead to significant signal deviations, requiring robust optimization.
Conclusion
The ZLEMA MACD is a variant of the classic MACD with reduced latency, making it particularly useful for analytical purposes where faster adaptation to price movements is required.
Its application in trading strategies should be limited to multi-factor models with rigorous evaluation. Backtests and out-of-sample analyses are essential to avoid overfitting to past market data.
Disclaimer: This indicator is provided for informational and educational purposes only and does not constitute financial advice. The author assumes no responsibility for any trading decisions made based on this indicator. Trading involves significant risk, and past performance is not indicative of future results.
MACD with Holt–Winters Smoothing [AIBitcoinTrend]👽 MACD with Holt–Winters Smoothing (AIBitcoinTrend)
The MACD with Holt–Winters Smoothing is an momentum indicator that enhances traditional MACD analysis by incorporating Holt–Winters exponential smoothing. This adaptation reduces lag while maintaining trend sensitivity, making it more effective for detecting trend reversals and sustained momentum shifts. Additionally, the indicator includes real-time divergence detection and an ATR-based trailing stop system, helping traders manage risk dynamically.
👽 What Makes the MACD with Holt–Winters Smoothing Unique?
Unlike the standard MACD, which relies on simple exponential moving averages, this version applies Holt–Winters smoothing to better capture trends while filtering out market noise. Combined with real-time divergence detection and a trailing stop system, this indicator allows traders to:
✅ Identify trend strength with a dynamically smoothed MACD signal.
✅ Detect bullish and bearish divergences in real time.
✅Implement Crossover/Crossunder signals tied to ATR-based trailing stops for risk management
👽 The Math Behind the Indicator
👾 Holt–Winters Smoothing for MACD
Traditional MACD calculations use exponential moving averages (EMA) to identify momentum. This indicator improves upon it by applying Holt’s linear trend equations, which enhance signal accuracy by reducing lag and smoothing out fluctuations.
Key Features:
Alpha (α) - Controls the weight of the new data in smoothing.
Beta (β) - Determines how fast the trend component adapts to new changes.
The Holt–Winters Signal Line provides a refined MACD crossover system for better trade execution.
👾 Real-Time Divergence Detection
The indicator identifies bullish and bearish divergences between MACD and price action.
Bullish Divergence: Occurs when price makes a lower low, but MACD makes a higher low – signaling potential upward momentum.
Bearish Divergence: Occurs when price makes a higher high, but MACD makes a lower high – signaling potential downward momentum.
👾 Dynamic ATR-Based Trailing Stop
The indicator includes a trailing stop system based on ATR (Average True Range). This allows traders to manage positions dynamically based on volatility.
Bullish Trailing Stop: Triggers when MACD crosses above the Holt–Winters signal, with a stop placed at low - (ATR × Multiplier).
Bearish Trailing Stop: Triggers when MACD crosses below the Holt–Winters signal, with a stop placed at high + (ATR × Multiplier).
Trailing Stop Adjustments: Expands or contracts dynamically with market conditions, reducing premature exits while securing profits.
👽 How Traders Can Use This Indicator
👾 Divergence Trading
Traders can use real-time divergence detection to anticipate trend reversals before they occur.
Bullish Divergence Setup:
Look for MACD making a higher low, while price makes a lower low.
Enter long when MACD confirms upward momentum.
Bearish Divergence Setup:
Look for MACD making a lower high, while price makes a higher high.
Enter short when MACD confirms downward momentum.
👾 Trailing Stop & Signal-Based Trading
Bullish Setup:
✅ MACD crosses above the Holt–Winters signal.
✅ A bullish trailing stop is placed using low - ATR × Multiplier.
✅ Exit if the price crosses below the stop.
Bearish Setup:
✅ MACD crosses below the Holt–Winters signal.
✅ A bearish trailing stop is placed using high + ATR × Multiplier.
✅ Exit if the price crosses above the stop.
This systematic trade management approach helps traders lock in profits while reducing drawdowns.
👽 Why It’s Useful for Traders
Lag Reduction: Holt–Winters smoothing ensures faster and more reliable trend detection.
Real-Time Divergence Alerts: Identify potential reversals before they happen.
Adaptive Risk Management: ATR-based trailing stops adjust to volatility dynamically.
Works Across Markets & Timeframes: Effective for stocks, forex, crypto, and futures trading.
👽 Indicator Settings
MACD Fast & Slow Lengths: Adjust the MACD short- and long-term EMA periods.
Holt–Winters Alpha & Beta: Fine-tune the smoothing sensitivity.
Enable Divergence Detection: Toggle real-time divergence analysis.
Lookback Period for Divergences: Configure how far back pivot points are detected.
ATR Multiplier for Trailing Stops: Adjust stop-loss sensitivity to market volatility.
Trend Filtering: Enable signal filtering based on trend direction.
Disclaimer: This indicator is designed for educational purposes and does not constitute financial advice. Please consult a qualified financial advisor before making investment decisions.
Cometreon_Public📚 Cometreon Public Library – Advanced Functions for Pine Script
This library contains advanced functions used in my public indicators on TradingView. The goal is to make the code more modular and efficient, allowing users to call pre-built functions for complex calculations without rewriting them from scratch.
🔹 Currently Available Functions:
1️⃣ Moving Average Function – Provides multiple types of moving averages to choose from, including:
SMA (Simple Moving Average)
EMA (Exponential Moving Average)
WMA (Weighted Moving Average)
RMA (Smoothed Moving Average)
HMA (Hull Moving Average)
JMA (Jurik Moving Average)
DEMA (Double Exponential Moving Average)
TEMA (Triple Exponential Moving Average)
LSMA (Least Squares Moving Average)
VWMA (Volume-Weighted Moving Average)
SMMA (Smoothed Moving Average)
KAMA (Kaufman’s Adaptive Moving Average)
ALMA (Arnaud Legoux Moving Average)
FRAMA (Fractal Adaptive Moving Average)
VIDYA (Variable Index Dynamic Average)
2️⃣ Custom RSI – Uses the Moving Average function to modify the calculation method, with an additional option for a dynamic version.
3️⃣ Custom MACD – Uses the Moving Average function to modify the calculation method, with an additional option for a dynamic version.
4️⃣ Custom Alligator – Uses the Moving Average function to modify generic calculations, allowing users to change the calculation method.
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)
MA RSI MACD Signal SuiteThis Pine Script™ is designed for use in Trading View and generates trading signals based on moving average (MA) crossovers, RSI (Relative Strength Index) signals, and MACD (Moving Average Convergence Divergence) indicators. It provides visual markers on the chart and can be configured to suit various trading strategies.
1. Indicator Overview
The indicator includes signals for:
Moving Averages (MA): It tracks crossovers between different types of moving averages.
RSI: Signals based on RSI crossing certain levels or its signal line.
MACD: Buy and sell signals generated by MACD crossovers.
2. Inputs and Customization
Moving Averages (MAs):
You can customize up to 6 moving averages with different types, lengths, and colors.
MA Type: Choose from different types of moving averages:
SMA (Simple Moving Average)
EMA (Exponential Moving Average)
HMA (Hull Moving Average)
SMMA (RMA) (Smoothed Moving Average)
WMA (Weighted Moving Average)
VWMA (Volume Weighted Moving Average)
T3, DEMA, TEMA
Source: Select the price to base the MA on (e.g., close, open, high, low).
Length: Define the number of periods for each moving average.
Examples:
MA1: Exponential Moving Average (EMA) with a period of 9
MA2: Exponential Moving Average (EMA) with a period of 21
RSI Settings:
RSI is calculated based on a user-defined period and is used to identify potential overbought or oversold conditions.
RSI Length: Lookback period for RSI (default 14).
Overbought Level: Defines the overbought threshold for RSI (default 70).
Oversold Level: Defines the oversold threshold for RSI (default 30).
You can also adjust the smoothing for the RSI signal line and customize when to trigger buy and sell signals based on the RSI crossing these levels.
MACD Settings:
MACD is used for identifying changes in momentum and trends.
Fast Length: The period for the fast moving average (default 12).
Slow Length: The period for the slow moving average (default 26).
Signal Length: The period for the signal line (default 9).
Smoothing Method: Choose between SMA or EMA for both the MACD and the signal line.
3. Signal Logic
Moving Average (MA) Crossover Signals:
Crossover: A bullish signal is generated when a fast MA crosses above a slow MA.
Crossunder: A bearish signal is generated when a fast MA crosses below a slow MA.
The crossovers are plotted with distinct colors, and the chart will display markers for these crossover events.
RSI Signals:
Oversold Crossover: A bullish signal when RSI crosses over its signal line below the oversold level (30).
Overbought Crossunder: A bearish signal when RSI crosses under its signal line above the overbought level (70).
RSI signals are divided into:
Aggressive (Early) Entries: Signals when RSI is crossing the oversold/overbought levels.
Conservative Entries: Signals when RSI confirms a reversal after crossing these levels.
MACD Signals:
Buy Signal: Generated when the MACD line crosses above the signal line (bullish crossover).
Sell Signal: Generated when the MACD line crosses below the signal line (bearish crossunder).
Additionally, the MACD histogram is used to identify momentum shifts:
Rising to Falling Histogram: Alerts when the MACD histogram switches from rising to falling.
Falling to Rising Histogram: Alerts when the MACD histogram switches from falling to rising.
4. Visuals and Alerts
Plotting:
The script plots the following on the price chart:
Moving Averages (MA): The selected MAs are plotted as lines.
Buy/Sell Shapes: Triangular markers are displayed for buy and sell signals generated by RSI and MACD.
Crossover and Crossunder Markers: Crosses are shown when two MAs crossover or crossunder.
Alerts:
Alerts can be configured based on the following conditions:
RSI Signals: Alerts for oversold or overbought crossover and crossunder events.
MACD Signals: Alerts for MACD line crossovers or momentum shifts in the MACD histogram.
Alerts are triggered when specific conditions are met, such as:
RSI crosses over or under the oversold/overbought levels.
MACD crosses the signal line.
Changes in the MACD histogram.
5. Example Usage
1. Trend Reversal Setup:
Buy Signal: Use the RSI oversold crossover and MACD bullish crossover to identify potential entry points in a downtrend.
Sell Signal: Use the RSI overbought crossunder and MACD bearish crossunder to identify potential exit points or short entries in an uptrend.
2. Momentum Strategy:
Combine MACD and RSI signals to identify the strength of a trend. Use MACD histogram analysis and RSI levels for confirmation.
3. Moving Average Crossover Strategy:
Focus on specific MA crossovers, such as the 9-period EMA crossing above the 21-period EMA, for buy signals. When a longer-term MA (e.g., 50-period) crosses a shorter-term MA, it may indicate a strong trend change.
6. Alerts Conditions
The script includes several alert conditions, which can be triggered and customized based on the user’s preferences:
RSI Oversold Crossover: Alerts when RSI crosses over the signal line below the oversold level (30).
RSI Overbought Crossunder: Alerts when RSI crosses under the signal line above the overbought level (70).
MACD Buy/Sell Crossover: Alerts when the MACD line crosses the signal line for a buy or sell signal.
7. Conclusion
This script is highly customizable and can be adjusted to suit different trading strategies. By combining MAs, RSI, and MACD, traders can gain multiple perspectives on the market, enhancing their ability to identify potential buy and sell opportunities.
Supertrend with EMAs (288 & 50)This indicator combines the Supertrend with two key Exponential Moving Averages (EMAs) — the 50 EMA and the 288 EMA — to help traders identify trends and possible entry or exit points in the market.
Key Features:
Supertrend Indicator:
The Supertrend indicator is a widely used trend-following tool. It helps determine whether the market is in an uptrend or downtrend by adjusting based on the Average True Range (ATR).
In this indicator, green represents an uptrend, and red represents a downtrend.
288 EMA:
The 288-period Exponential Moving Average is plotted to show the long-term market trend. It reacts more quickly to recent price changes than a simple moving average, offering an effective way to gauge long-term market direction.
50 EMA:
The 50-period Exponential Moving Average is commonly used as a short-term trend indicator. It helps identify shorter-term trends and serves as a dynamic support/resistance level.
EMA Crossover Alerts:
This indicator includes alerts for when the 50 EMA crosses above the 288 EMA (bullish signal) and when it crosses below (bearish signal), helping traders catch trend reversals or confirmation of current trends.
Supertrend Alerts:
Alerts are triggered when the Supertrend indicator switches from uptrend to downtrend or downtrend to uptrend, indicating a potential shift in market direction.
Usage:
Uptrend Confirmation: When the Supertrend is green and the 50 EMA is above the 288 EMA, it signals that the market is in a strong bullish trend.
Downtrend Confirmation: When the Supertrend is red and the 50 EMA is below the 288 EMA, it indicates that the market is in a bearish trend.
Crossover Signals: The indicator provides alerts when the 50 EMA crosses above or below the 288 EMA, helping traders spot trend changes.
Best For:
Trend-following strategies
Identifying potential trend reversals and market shifts
Traders looking for a combination of short-term and long-term trend analysis
Note: This indicator is most effective when used in conjunction with other technical analysis tools and should be considered alongside other factors such as volume, support/resistance levels, and price action.
Volume Delta Candles HTF [TradingFinder] LTF Volume Candles 🔵 Introduction
In financial markets, understanding the concepts of supply and demand and their impact on price movements is of paramount importance. Supply and demand, as fundamental pillars of economics, reflect the interaction between buyers and sellers.
When buyers' strength surpasses that of sellers, demand increases, and prices tend to rise. Conversely, when sellers dominate buyers, supply overtakes demand, causing prices to drop. These interactions play a crucial role in determining market trends, price reversal points, and trading decisions.
Volume Delta Candles offer traders a practical way to visualize trading activity within each candlestick. By integrating data from lower timeframes or live market feeds, these candles eliminate the need for standalone volume indicators.
They present the proportions of buying and selling volume as intuitive colored bars, making it easier to interpret market dynamics at a glance. Additionally, they encapsulate critical metrics like peak delta, lowest delta, and net delta, allowing traders to grasp the market's internal order flow with greater precision.
In financial markets, grasping the interplay between supply and demand and its influence on price movements is crucial for successful trading. These fundamental economic forces reflect the ongoing balance between buyers and sellers in the market.
When buyers exert greater strength than sellers, demand dominates, driving prices upward. Conversely, when sellers take control, supply surpasses demand, and prices decline. Understanding these dynamics is essential for identifying market trends, pinpointing reversal points, and making informed trading decisions.
Volume Delta Candles provide an innovative method for evaluating trading activity within individual candlesticks, offering a simplified view without relying on separate volume indicators. By leveraging lower timeframe or real-time data, this tool visualizes the distribution of buying and selling volumes within a candle through color-coded bars.
This visual representation enables traders to quickly assess market sentiment and understand the forces driving price action. Buyer and seller strength is a critical concept that focuses on the ratio of buying to selling volumes. This ratio not only provides insights into the market's current state but also serves as a leading indicator for detecting potential shifts in trends.
Traders often rely on volume analysis to identify significant supply and demand zones, guiding their entry and exit strategies. Delta Candles translate these complex metrics, such as Maximum Delta, Minimum Delta, and Final Delta, into an easy-to-read visual format using Japanese candlestick structures, making them an invaluable resource for analyzing order flows and market momentum.
By merging the principles of supply and demand with comprehensive volume analysis, tools like the indicator introduced here offer unparalleled clarity into market behavior. This indicator calculates the relative strength of supply and demand for each candlestick by analyzing the ratio of buyers to sellers.
🔵 How to Use
The presented indicator is a powerful tool for analyzing supply and demand strength in financial markets. It helps traders identify the strengths and weaknesses of buyers and sellers and utilize this information for better decision-making.
🟣 Analyzing the Highest Volume Trades on Candles
A unique feature of this indicator is the visualization of price levels with the highest trade volume for each candlestick. These levels are marked as black lines on the candles, indicating prices where most trades occurred. This information is invaluable for identifying key supply and demand zones, which often act as support or resistance levels.
🟣 Trend Confirmation
The indicator enables traders to confirm bullish or bearish trends by observing changes in buyer and seller strength. When buyer strength increases and demand surpasses supply, the likelihood of a bullish trend continuation grows. Conversely, decreasing buyer strength and increasing seller strength may signal a potential bearish trend reversal.
🟣 Adjusting Timeframes and Calculation Methods
Users can customize the indicator's candlestick timeframe to align with their trading strategy. Additionally, they can switch between moving average and current candle modes to achieve more precise market analysis.
This indicator, with its accurate and visual data display, is a practical and reliable tool for market analysts and traders. Using it can help traders make better decisions and identify optimal entry and exit points.
🔵 Settings
Lower Time Frame Volume : This setting determines which timeframe the indicator should use to identify the price levels with the highest trade volume. These levels, displayed as black lines on the candlesticks, indicate prices where the most trades occurred.
It is recommended that users align this timeframe with their primary chart’s timeframe.
As a general rule :
If the main chart’s timeframe is low (e.g., 1-minute or 5-minute), it is better to keep this setting at a similarly low timeframe.
As the main chart’s timeframe increases (e.g., daily or weekly), it is advisable to set this parameter to a higher timeframe for more aligned data analysis.
Cumulative Mode :
Current Candle : Strength is calculated only for the current candlestick.
EMA (Exponential Moving Average) : The strength is calculated using an exponential moving average, suitable for identifying longer-term trends.
Calculation Period : The default period for the exponential moving average (EMA) is set to 21. Users can modify this value for more precise analysis based on their specific requirements.
Ultra Data : This option enables users to view more detailed data from various market sources, such as Forex, Crypto, or Stocks. When activated, the indicator aggregates and displays volume data from multiple sources.
🟣 Table Settings
Show Info Table : This option determines whether the information table is displayed on the chart. When enabled, the table appears in a corner of the chart and provides details about the strength of buyers and sellers.
Table Size : Users can adjust the size of the text within the table to improve readability.
Table Position : This setting defines the table’s placement on the chart.
🔵 Conclusion
The indicator introduced in this article is designed as an advanced tool for analyzing supply and demand dynamics in financial markets. By leveraging buyer and seller strength ratios and visually highlighting price levels with the highest trade volume, it aids traders in identifying key market zones.
Key features, such as adjustable analysis timeframes, customizable calculation methods, and precise volume data display, allow users to tailor their analyses to market conditions.
This indicator is invaluable for analyzing support and resistance levels derived from trade volumes, enabling traders to make more accurate decisions about entering or exiting trades.
By utilizing real market data and displaying the highest trade volume lines directly on the chart, it provides a precise perspective on market behavior. These features make it suitable for both novice and professional traders aiming to enhance their analysis and trading strategies.
With this indicator, traders can gain a better understanding of supply and demand dynamics and operate more intelligently in financial markets. By combining volume data with visual analysis, this tool provides a solid foundation for effective decision-making and improved trading performance. Choosing this indicator is a significant step toward refining analysis and achieving success in complex financial markets.
Median Deviation Suite [InvestorUnknown]The Median Deviation Suite uses a median-based baseline derived from a Double Exponential Moving Average (DEMA) and layers multiple deviation measures around it. By comparing price to these deviation-based ranges, it attempts to identify trends and potential turning points in the market. The indicator also incorporates several deviation types—Average Absolute Deviation (AAD), Median Absolute Deviation (MAD), Standard Deviation (STDEV), and Average True Range (ATR)—allowing traders to visualize different forms of volatility and dispersion. Users should calibrate the settings to suit their specific trading approach, as the default values are not optimized.
Core Components
Median of a DEMA:
The foundation of the indicator is a Median applied to the 7-day DEMA (Double Exponential Moving Average). DEMA aims to reduce lag compared to simple or exponential moving averages. By then taking a median over median_len periods of the DEMA values, the indicator creates a robust and stable central tendency line.
float dema = ta.dema(src, 7)
float median = ta.median(dema, median_len)
Multiple Deviation Measures:
Around this median, the indicator calculates several measures of dispersion:
ATR (Average True Range): A popular volatility measure.
STDEV (Standard Deviation): Measures the spread of price data from its mean.
MAD (Median Absolute Deviation): A robust measure of variability less influenced by outliers.
AAD (Average Absolute Deviation): Similar to MAD, but uses the mean absolute deviation instead of median.
Average of Deviations (avg_dev): The average of the above four measures (ATR, STDEV, MAD, AAD), providing a combined sense of volatility.
Each measure is multiplied by a user-defined multiplier (dev_mul) to scale the width of the bands.
aad = f_aad(src, dev_len, median) * dev_mul
mad = f_mad(src, dev_len, median) * dev_mul
stdev = ta.stdev(src, dev_len) * dev_mul
atr = ta.atr(dev_len) * dev_mul
avg_dev = math.avg(aad, mad, stdev, atr)
Deviation-Based Bands:
The indicator creates multiple upper and lower lines based on each deviation type. For example, using MAD:
float mad_p = median + mad // already multiplied by dev_mul
float mad_m = median - mad
Similar calculations are done for AAD, STDEV, ATR, and the average of these deviations. The indicator then determines the overall upper and lower boundaries by combining these lines:
float upper = f_max4(aad_p, mad_p, stdev_p, atr_p)
float lower = f_min4(aad_m, mad_m, stdev_m, atr_m)
float upper2 = f_min4(aad_p, mad_p, stdev_p, atr_p)
float lower2 = f_max4(aad_m, mad_m, stdev_m, atr_m)
This creates a layered structure of volatility envelopes. Traders can observe which layers price interacts with to gauge trend strength.
Determining Trend
The indicator generates trend signals by assessing where price stands relative to these deviation-based lines. It assigns a trend score by summing individual signals from each deviation measure. For instance, if price crosses above the MAD-based upper line, it contributes a bullish point; crossing below an ATR-based lower line contributes a bearish point.
When the aggregated trend score crosses above zero, it suggests a shift towards a bullish environment; crossing below zero indicates a bearish bias.
// Define Trend scores
var int aad_t = 0
if ta.crossover(src, aad_p)
aad_t := 1
if ta.crossunder(src, aad_m)
aad_t := -1
var int mad_t = 0
if ta.crossover(src, mad_p)
mad_t := 1
if ta.crossunder(src, mad_m)
mad_t := -1
var int stdev_t = 0
if ta.crossover(src, stdev_p)
stdev_t := 1
if ta.crossunder(src, stdev_m)
stdev_t := -1
var int atr_t = 0
if ta.crossover(src, atr_p)
atr_t := 1
if ta.crossunder(src, atr_m)
atr_t := -1
var int adev_t = 0
if ta.crossover(src, adev_p)
adev_t := 1
if ta.crossunder(src, adev_m)
adev_t := -1
int upper_t = src > upper ? 3 : 0
int lower_t = src < lower ? 0 : -3
int upper2_t = src > upper2 ? 1 : 0
int lower2_t = src < lower2 ? 0 : -1
float trend = aad_t + mad_t + stdev_t + atr_t + adev_t + upper_t + lower_t + upper2_t + lower2_t
var float sig = 0
if ta.crossover(trend, 0)
sig := 1
else if ta.crossunder(trend, 0)
sig := -1
Practical Usage and Calibration
Default settings are not optimized: The given parameters serve as a starting point for demonstration. Users should adjust:
median_len: Affects how smooth and lagging the median of the DEMA is.
dev_len and dev_mul: Influence the sensitivity of the deviation measures. Larger multipliers widen the bands, potentially reducing false signals but introducing more lag. Smaller multipliers tighten the bands, producing quicker signals but potentially more whipsaws.
This flexibility allows the trader to tailor the indicator for various markets (stocks, forex, crypto) and time frames.
Backtesting and Performance Metrics
The code integrates with a backtesting library that allows traders to:
Evaluate the strategy historically
Compare the indicator’s signals with a simple buy-and-hold approach
Generate performance metrics (e.g., mean returns, Sharpe Ratio, Sortino Ratio) to assess historical effectiveness.
Disclaimer
No guaranteed results: Historical performance does not guarantee future outcomes. Market conditions can vary widely.
User responsibility: Traders should combine this indicator with other forms of analysis, appropriate risk management, and careful calibration of parameters.
300-Candle Weighted Average Zones w/50 EMA SignalsThis indicator is designed to deliver a more nuanced view of price dynamics by combining a custom, weighted price average with a volatility-based zone and a trend filter (in this case, a 50-period exponential moving average). The core concept revolves around capturing the overall price level over a relatively large lookback window (300 candles) but with an intentional bias toward recent market activity (the most recent 20 candles), thereby offering a balance between long-term context and short-term responsiveness. By smoothing this weighted average and establishing a “zone” of standard deviation bands around it, the indicator provides a refined visualization of both average price and its recent volatility envelope. Traders can then look for confluence with a standard trend filter, such as the 50 EMA, to identify meaningful crossover signals that may represent trend shifts or opportunities for entry and exit.
What the Indicator Does:
Weighted Price Average:
Instead of using a simple or exponential moving average, this indicator calculates a custom weighted average price over the past 300 candles. Most historical candles receive a base weight of 1.0, but the most recent 20 candles are assigned a higher weight (for example, a weight of 2.0). This weighting scheme ensures that the calculation is not simply a static lookback average; it actively emphasizes current market conditions. The effect is to generate an average line that is more sensitive to the most recent price swings while still maintaining the historical context of the previous 280 candles.
Smoothing of the Weighted Average:
Once the raw weighted average is computed, an exponential smoothing function (EMA) is applied to reduce noise and produce a cleaner, more stable average line. This smoothing helps traders avoid reacting prematurely to minor price fluctuations. By stabilizing the average line, traders can more confidently identify actual shifts in market direction.
Volatility Zone via Standard Deviation Bands:
To contextualize how far price can deviate from this weighted average, the indicator uses standard deviation. Standard deviation is a statistical measure of volatility—how spread out the price values are around the mean. By adding and subtracting one standard deviation from the smoothed weighted average, the indicator plots an upper band and a lower band, creating a zone or channel. The area between these bands is filled, often with a semi-transparent color, highlighting a volatility corridor within which price and the EMA might oscillate.
This zone is invaluable in visualizing “normal” price behavior. When the 50 EMA line and the weighted average line are both within this volatility zone, it indicates that the market’s short- to mid-term trend and its average pricing are aligned well within typical volatility bounds.
Incorporation of a 50-Period EMA:
The inclusion of a commonly used trend filter, the 50 EMA, adds another layer of context to the analysis. The 50 EMA, being a widely recognized moving average length, is often considered a baseline for intermediate trend bias. It reacts faster than a long-term average (like a 200 EMA) but is still stable enough to filter out the market “chop” seen in very short-term averages.
By overlaying the 50 EMA on this custom weighted average and the surrounding volatility zone, the trader gains a dual-dimensional perspective:
Trend Direction: If the 50 EMA is generally above the weighted average, the short-term trend is gaining bullish momentum; if it’s below, the short-term trend has a bearish tilt.
Volatility Normalization: The bands, constructed from standard deviations, provide a sense of whether the price and the 50 EMA are operating within a statistically “normal” range. If the EMA crosses the weighted average within this zone, it signals a potential trend initiation or meaningful shift, as opposed to a random price spike outside normal volatility boundaries.
Why a Trader Would Want to Use This Indicator:
Contextualized Price Level:
Standard MAs may not fully incorporate the most recent price dynamics in a large lookback window. By weighting the most recent candles more heavily, this indicator ensures that the trader is always anchored to what the market is currently doing, not just what it did 100 or 200 candles ago.
Reduced Whipsaw with Smoothing:
The smoothed weighted average line reduces noise, helping traders filter out inconsequential price movements. This makes it easier to spot genuine changes in trend or sentiment.
Visual Volatility Gauge:
The standard deviation bands create a visual representation of “normal” price movement. Traders can quickly assess if a breakout or breakdown is statistically significant or just another oscillation within the expected volatility range.
Clear Trade Signals with Confirmation:
By integrating the 50 EMA and designing signals that trigger only when the 50 EMA crosses above or below the weighted average while inside the zone, the indicator provides a refined entry/exit criterion. This avoids chasing breakouts that occur in abnormal volatility conditions and focuses on those crossovers likely to have staying power.
How to Use It in an Example Strategy:
Imagine you are a swing trader looking to identify medium-term trend changes. You apply this indicator to a chart of a popular currency pair or a leading tech stock. Over the past few days, the 50 EMA has been meandering around the weighted average line, both confined within the standard deviation zone.
Bullish Example:
Suddenly, the 50 EMA crosses decisively above the weighted average line while both are still hovering within the volatility zone. This might be your cue: you interpret this crossover as the 50 EMA acknowledging the recent upward shift in price dynamics that the weighted average has highlighted. Since it occurred inside the normal volatility range, it’s less likely to be a head-fake. You place a long position, setting an initial stop just below the lower band to protect against volatility.
If the price continues to rise and the EMA stays above the average, you have confirmation to hold the trade. As the price moves higher, the weighted average may follow, reinforcing your bullish stance.
Bearish Example:
On the flip side, if the 50 EMA crosses below the weighted average line within the zone, it suggests a subtle but meaningful change in trend direction to the downside. You might short the asset, placing your protective stop just above the upper band, expecting that the statistically “normal” level of volatility will contain the price action. If the price does break above those bands later, it’s a sign your trade may not work out as planned.
Other Indicators for Confluence:
To strengthen the reliability of the signals generated by this weighted average zone approach, traders may want to combine it with other technical studies:
Volume Indicators (e.g., Volume Profile, OBV):
Confirm that the trend crossover inside the volatility zone is supported by volume. For instance, an uptrend crossover combined with increasing On-Balance Volume (OBV) or volume spikes on up candles signals stronger buying pressure behind the price action.
Momentum Oscillators (e.g., RSI, Stochastics):
Before taking a crossover signal, check if the RSI is above 50 and rising for bullish entries, or if the Stochastics have turned down from overbought levels for bearish entries. Momentum confirmation can help ensure that the trend change is not just an isolated random event.
Market Structure Tools (e.g., Pivot Points, Swing High/Low Analysis):
Identify if the crossover event coincides with a break of a previous pivot high or low. A bullish crossover inside the zone aligned with a break above a recent swing high adds further strength to your conviction. Conversely, a bearish crossover confirmed by a breakdown below a previous swing low can make a short trade setup more compelling.
Volume-Weighted Average Price (VWAP):
Comparing where the weighted average zone lies relative to VWAP can provide institutional insight. If the bullish crossover happens while the price is also holding above VWAP, it can mean that the average participant in the market is in profit and that the trend is likely supported by strong hands.
This indicator serves as a tool to balance long-term perspective, short-term adaptability, and volatility normalization. It can be a valuable addition to a trader’s toolkit, offering enhanced clarity and precision in detecting meaningful shifts in trend, especially when combined with other technical indicators and robust risk management principles.
Turtle Trade Channels Indicator with EMATurtle Trade Channels Indicator with EMA (TuTCI + EMA)
This custom indicator combines the classic Turtle Trading Channel strategy with an Exponential Moving Average (EMA) filter to provide clear entry and exit signals, as well as trend direction guidance.
Features:
Turtle Channels: The indicator calculates the upper and lower Turtle Trading Channels based on the highest and lowest values over a user-defined period ( Entry Length for the channel).
Entry/Exit Signals: Alerts you to potential buy and sell opportunities with visual signals on the chart.
Long Entry: When the price crosses above the upper channel.
Short Entry: When the price crosses below the lower channel.
Long Exit: When the price breaks below the exit line.
Short Exit: When the price breaks above the exit line.
EMA Filter: A 50-period Exponential Moving Average (EMA) is included to identify the overall trend. The background color turns green when the price is above the EMA (bullish trend) and red when the price is below the EMA (bearish trend).
Highlighter: Optional background highlighting for the most relevant signals, such as when the price crosses the upper or lower Turtle Channel. This feature helps to easily identify key market movements.
Visual Customization: Customize the EMA length, Entry/Exit lengths, and toggle signals and highlighting to suit your preferences.
How It Works:
The Turtle Trade Channels are designed to capture breakouts by identifying key price levels (highest high and lowest low) over a specified period. By combining this strategy with an EMA, the indicator ensures trades are aligned with the broader trend, increasing the probability of successful trades.
Uptrend: When the price is above the EMA, the indicator considers the trend to be bullish, and it highlights long entry signals.
Downtrend: When the price is below the EMA, the trend is considered bearish, and short entries are emphasized.
Customization:
Entry Length: Adjusts the period for calculating the Turtle Channel's entry levels.
Exit Length: Defines the period for calculating the exit levels.
EMA Length: The period for the Exponential Moving Average (default is set to 50).
Show Entry/Exit Signals: Toggle the visibility of entry/exit signals on the chart.
Highlighter On/Off: Toggle background highlighting for key signals.
This indicator is suitable for traders who follow trend-following strategies, particularly those influenced by the Turtle Trading methodology, and wish to use an EMA filter for better trend confirmation.
Use Cases:
Trend-following traders looking for clear entry/exit signals.
Breakout traders using the Turtle Trading concept to identify price breakouts.
Swing traders who want to incorporate trend analysis with price levels.
AadTrend [InvestorUnknown]The AadTrend indicator is an experimental trading tool that combines a user-selected moving average with the Average Absolute Deviation (AAD) from this moving average. This combination works similarly to the Supertrend indicator but offers additional flexibility and insights. In addition to generating Long and Short signals, the AadTrend indicator identifies RISK-ON and RISK-OFF states for each trade direction, highlighting areas where taking on more risk may be considered.
Core Concepts and Features
Moving Average (User-Selected Type)
The indicator allows users to select from various types of moving averages to suit different trading styles and market conditions:
Simple Moving Average (SMA)
Exponential Moving Average (EMA)
Hull Moving Average (HMA)
Double Exponential Moving Average (DEMA)
Triple Exponential Moving Average (TEMA)
Relative Moving Average (RMA)
Fractal Adaptive Moving Average (FRAMA)
Average Absolute Deviation (AAD)
The Average Absolute Deviation measures the average distance between each data point and the mean, providing a robust estimation of volatility.
aad(series float src, simple int length, simple string avg_type) =>
avg = // Moving average as selected by the user
abs_deviations = math.abs(src - avg)
ta.sma(abs_deviations, length)
This provides a volatility measure that adapts to recent market conditions.
Combining Moving Average and AAD
The indicator creates upper and lower bands around the moving average using the AAD, similar to how the Supertrend indicator uses Average True Range (ATR) for its bands.
AadTrend(series float src, simple int length, simple float aad_mult, simple string avg_type) =>
// Calculate AAD (volatility measure)
aad_value = aad(src, length, avg_type)
// Calculate the AAD-based moving average by scaling the price data with AAD
avg = switch avg_type
"SMA" => ta.sma(src, length)
"EMA" => ta.ema(src, length)
"HMA" => ta.hma(src, length)
"DEMA" => ta.dema(src, length)
"TEMA" => ta.tema(src, length)
"RMA" => ta.rma(src, length)
"FRAMA" => ta.frama(src, length)
avg_p = avg + (aad_value * aad_mult)
avg_m = avg - (aad_value * aad_mult)
var direction = 0
if ta.crossover(src, avg_p)
direction := 1
else if ta.crossunder(src, avg_m)
direction := -1
A chart displaying the moving average with upper and lower AAD bands enveloping the price action.
Signals and Trade States
1. Long and Short Signals
Long Signal: Generated when the price crosses above the upper AAD band,
Short Signal: Generated when the price crosses below the lower AAD band.
2. RISK-ON and RISK-OFF States
These states provide additional insight into the strength of the current trend and potential opportunities for taking on more risk.
RISK-ON Long: When the price moves significantly above the upper AAD band after a Long signal.
RISK-OFF Long: When the price moves back below the upper AAD band, suggesting caution.
RISK-ON Short: When the price moves significantly below the lower AAD band after a Short signal.
RISK-OFF Short: When the price moves back above the lower AAD band.
Highlighted areas on the chart representing RISK-ON and RISK-OFF zones for both Long and Short positions.
A chart showing the filled areas corresponding to trend directions and RISK-ON zones
Backtesting and Performance Metrics
While the AadTrend indicator focuses on generating signals and highlighting risk areas, it can be integrated with backtesting frameworks to evaluate performance over historical data.
Integration with Backtest Library:
import InvestorUnknown/BacktestLibrary/1 as backtestlib
Customization and Calibration
1. Importance of Calibration
Default Settings Are Experimental: The default parameters are not optimized for any specific market condition or asset.
User Calibration: Traders should adjust the length, aad_mult, and avg_type parameters to align the indicator with their trading strategy and the characteristics of the asset being analyzed.
2. Factors to Consider
Market Volatility: Higher volatility may require adjustments to the aad_mult to avoid false signals.
Trading Style: Short-term traders might prefer faster-moving averages like EMA or HMA, while long-term traders might opt for SMA or FRAMA.
Alerts and Notifications
The AadTrend indicator includes built-in alert conditions to notify traders of significant market events:
Long and Short Alerts:
alertcondition(long_alert, "LONG (AadTrend)", "AadTrend flipped ⬆LONG⬆")
alertcondition(short_alert, "SHORT (AadTrend)", "AadTrend flipped ⬇Short⬇")
RISK-ON and RISK-OFF Alerts:
alertcondition(risk_on_long, "RISK-ON LONG (AadTrend)", "RISK-ON LONG (AadTrend)")
alertcondition(risk_off_long, "RISK-OFF LONG (AadTrend)", "RISK-OFF LONG (AadTrend)")
alertcondition(risk_on_short, "RISK-ON SHORT (AadTrend)", "RISK-ON SHORT (AadTrend)")
alertcondition(risk_off_short, "RISK-OFF SHORT (AadTrend)", "RISK-OFF SHORT (AadTrend)")
Important Notes and Disclaimer
Experimental Nature: The AadTrend indicator is experimental and should be used with caution.
No Guaranteed Performance: Past performance is not indicative of future results. Backtesting results may not reflect real trading conditions.
User Responsibility: Traders and investors should thoroughly test and calibrate the indicator settings before applying it to live trading.
Risk Management: Always use proper risk management techniques, including stop-loss orders and position sizing.
