Momentum Regression [BackQuant]Momentum Regression
The Momentum Regression is an advanced statistical indicator built to empower quants, strategists, and technically inclined traders with a robust visual and quantitative framework for analyzing momentum effects in financial markets. Unlike traditional momentum indicators that rely on raw price movements or moving averages, this tool leverages a volatility-adjusted linear regression model (y ~ x) to uncover and validate momentum behavior over a user-defined lookback window.
Purpose & Design Philosophy
Momentum is a core anomaly in quantitative finance — an effect where assets that have performed well (or poorly) continue to do so over short to medium-term horizons. However, this effect can be noisy, regime-dependent, and sometimes spurious.
The Momentum Regression is designed as a pre-strategy analytical tool to help you filter and verify whether statistically meaningful and tradable momentum exists in a given asset. Its architecture includes:
Volatility normalization to account for differences in scale and distribution.
Regression analysis to model the relationship between past and present standardized returns.
Deviation bands to highlight overbought/oversold zones around the predicted trendline.
Statistical summary tables to assess the reliability of the detected momentum.
Core Concepts and Calculations
The model uses the following:
Independent variable (x): The volatility-adjusted return over the chosen momentum period.
Dependent variable (y): The 1-bar lagged log return, also adjusted for volatility.
A simple linear regression is performed over a large lookback window (default: 1000 bars), which reveals the slope and intercept of the momentum line. These values are then used to construct:
A predicted momentum trendline across time.
Upper and lower deviation bands , representing ±n standard deviations of the regression residuals (errors).
These visual elements help traders judge how far current returns deviate from the modeled momentum trend, similar to Bollinger Bands but derived from a regression model rather than a moving average.
Key Metrics Provided
On each update, the indicator dynamically displays:
Momentum Slope (β₁): Indicates trend direction and strength. A higher absolute value implies a stronger effect.
Intercept (β₀): The predicted return when x = 0.
Pearson’s R: Correlation coefficient between x and y.
R² (Coefficient of Determination): Indicates how well the regression line explains the variance in y.
Standard Error of Residuals: Measures dispersion around the trendline.
t-Statistic of β₁: Used to evaluate statistical significance of the momentum slope.
These statistics are presented in a top-right summary table for immediate interpretation. A bottom-right signal table also summarizes key takeaways with visual indicators.
Features and Inputs
✅ Volatility-Adjusted Momentum : Reduces distortions from noisy price spikes.
✅ Custom Lookback Control : Set the number of bars to analyze regression.
✅ Extendable Trendlines : For continuous visualization into the future.
✅ Deviation Bands : Optional ±σ multipliers to detect abnormal price action.
✅ Contextual Tables : Help determine strength, direction, and significance of momentum.
✅ Separate Pane Design : Cleanly isolates statistical momentum from price chart.
How It Helps Traders
📉 Quantitative Strategy Validation:
Use the regression results to confirm whether a momentum-based strategy is worth pursuing on a specific asset or timeframe.
🔍 Regime Detection:
Track when momentum breaks down or reverses. Slope changes, drops in R², or weak t-stats can signal regime shifts.
📊 Trade Filtering:
Avoid false positives by entering trades only when momentum is both statistically significant and directionally favorable.
📈 Backtest Preparation:
Before running costly simulations, use this tool to pre-screen assets for exploitable return structures.
When to Use It
Before building or deploying a momentum strategy : Test if momentum exists and is statistically reliable.
During market transitions : Detect early signs of fading strength or reversal.
As part of an edge-stacking framework : Combine with other filters such as volatility compression, volume surges, or macro filters.
Conclusion
The Momentum Regression indicator offers a powerful fusion of statistical analysis and visual interpretation. By combining volatility-adjusted returns with real-time linear regression modeling, it helps quantify and qualify one of the most studied and traded anomalies in finance: momentum.
在脚本中搜索"TRENDLINES"
Contrarian RSIContrarian RSI Indicator
Pairs nicely with Contrarian 100 MA (optional hide/unhide buy/sell signals)
Description
The Contrarian RSI is a momentum-based technical indicator designed to identify potential reversal points in price action by combining a unique RSI calculation with a predictive range model inspired by the "Contrarian 5 Levels" logic. Unlike traditional RSI, which measures price momentum based solely on price changes, this indicator integrates a smoothed, weighted momentum calculation and predictive price ranges to generate contrarian signals. It is particularly suited for traders looking to capture reversals in trending or range-bound markets.
This indicator is versatile and can be used across various timeframes, though it performs best on higher timeframes (e.g., 1H, 4H, or Daily) due to reduced noise and more reliable signals. Lower timeframes may require additional testing and careful parameter tuning to optimize performance.
How It Works
The Contrarian RSI combines two primary components:
Predictive Ranges (5 Levels Logic): This calculates a smoothed price average that adapts to market volatility using an ATR-based mechanism. It helps identify significant price levels that act as potential support or resistance zones.
Contrarian RSI Calculation: A modified RSI calculation that uses weighted momentum from the predictive ranges to measure buying and selling pressure. The result is smoothed and paired with a user-defined moving average to generate clear signals.
The indicator generates buy (long) and sell (exit) signals based on crossovers and crossunders of user-defined overbought and oversold levels, making it ideal for contrarian trading strategies.
Calculation Overview
Predictive Ranges (5 Levels Logic):
Uses a custom function (pred_ranges) to calculate a dynamic price average (avg) based on the ATR (Average True Range) multiplied by a user-defined factor (mult).
The average adjusts only when the price moves beyond the ATR threshold, ensuring responsiveness to significant price changes while filtering out noise.
This calculation is performed on a user-specified timeframe (tf5Levels) for multi-timeframe analysis.
Contrarian RSI:
Compares consecutive predictive range values to calculate gains (g) and losses (l) over a user-defined period (crsiLength).
Applies a Gaussian weighting function (weight = math.exp(-math.pow(i / crsiLength, 2))) to prioritize recent price movements.
Computes a "wave ratio" (net_momentum / total_energy) to normalize momentum, which is then scaled to a 0–100 range (qrsi = 50 + 50 * wave_ratio).
Smooths the result with a 2-period EMA (qrsi_smoothed) for stability.
Moving Average:
Applies a user-selected moving average (SMA, EMA, WMA, SMMA, or VWMA) with a customizable length (maLength) to the smoothed RSI (qrsi_smoothed) to generate the final indicator value (qrsi_ma).
Signal Generation:
Long Entry: Triggered when qrsi_ma crosses above the oversold level (oversoldLevel, default: 1).
Long Exit: Triggered when qrsi_ma crosses below the overbought level (overboughtLevel, default: 99).
Entry and Exit Rules
Long Entry: Enter a long position when the Contrarian RSI (qrsi_ma) crosses above the oversold level (default: 1). This suggests the asset is potentially oversold and due for a reversal.
Long Exit: Exit the long position when the Contrarian RSI (qrsi_ma) crosses below the overbought level (default: 99), indicating a potential overbought condition and a reversal to the downside.
Customization: Adjust overboughtLevel and oversoldLevel to fine-tune sensitivity. Lower timeframes may benefit from tighter levels (e.g., 20 for oversold, 80 for overbought), while higher timeframes can use extreme levels (e.g., 1 and 99) for stronger reversals.
Timeframe Considerations
Higher Timeframes (Recommended): The indicator is optimized for higher timeframes (e.g., 1H, 4H, Daily) due to its reliance on predictive ranges and smoothed momentum, which perform best with less market noise. These timeframes typically yield more reliable reversal signals.
Lower Timeframes: The indicator can be used on lower timeframes (e.g., 5M, 15M), but signals may be noisier and require additional confirmation (e.g., from price action or other indicators). Extensive backtesting and parameter optimization (e.g., adjusting crsiLength, maLength, or mult) are recommended for lower timeframes.
Inputs
Contrarian RSI Length (crsiLength): Length for RSI momentum calculation (default: 5).
RSI MA Length (maLength): Length of the moving average applied to the RSI (default: 1, effectively no MA).
MA Type (maType): Choose from SMA, EMA, WMA, SMMA, or VWMA (default: SMA).
Overbought Level (overboughtLevel): Upper threshold for exit signals (default: 99).
Oversold Level (oversoldLevel): Lower threshold for entry signals (default: 1).
Plot Signals on Main Chart (plotOnChart): Toggle to display signals on the price chart or the indicator panel (default: false).
Plotted on Lower:
Plotted on Chart:
5 Levels Length (length5Levels): Length for predictive range calculation (default: 200).
Factor (mult): ATR multiplier for predictive ranges (default: 6.0).
5 Levels Timeframe (tf5Levels): Timeframe for predictive range calculation (default: chart timeframe).
Visuals
Contrarian RSI MA: Plotted as a yellow line, representing the smoothed Contrarian RSI with the applied moving average.
Overbought/Oversold Lines: Red line for overbought (default: 99) and green line for oversold (default: 1).
Signals: Blue circles for long entries, white circles for long exits. Signals can be plotted on the main chart (plotOnChart = true) or the indicator panel (plotOnChart = false).
Usage Notes
Use the indicator in conjunction with other tools (e.g., support/resistance, trendlines, or volume) to confirm signals.
Test extensively on your chosen timeframe and asset to optimize parameters like crsiLength, maLength, and mult.
Be cautious with lower timeframes, as false signals may occur due to market noise.
The indicator is designed for contrarian strategies, so it works best in markets with clear reversal patterns.
Disclaimer
This indicator is provided for educational and informational purposes only. Always conduct thorough backtesting and risk management before using any indicator in live trading. The author is not responsible for any financial losses incurred.
Bollinger Bands Entry/Exit ThresholdsBollinger Bands Entry/Exit Thresholds
Author of enhancements: chuckaschultz
Inspired and adapted from the original 'Bollinger Bands Breakout Oscillator' by LuxAlgo
Overview
Pairs nicely with Contrarian 100 MA
The Bollinger Bands Entry/Exit Thresholds is a powerful momentum-based indicator designed to help traders identify potential entry and exit points in trending or breakout markets. By leveraging Bollinger Bands, this indicator quantifies price deviations from the bands to generate bullish and bearish momentum signals, displayed as an oscillator. It includes customizable entry and exit signals based on user-defined thresholds, with visual cues plotted either on the oscillator panel or directly on the price chart.
This indicator is ideal for traders looking to capture breakout opportunities or confirm trend strength, with flexible settings to adapt to various markets and trading styles.
How It Works
The Bollinger Bands Entry/Exit Thresholds calculates two key metrics:
Bullish Momentum (Bull): Measures the extent to which the price exceeds the upper Bollinger Band, expressed as a percentage (0–100).
Bearish Momentum (Bear): Measures the extent to which the price falls below the lower Bollinger Band, also expressed as a percentage (0–100).
The indicator generates:
Long Entry Signals: Triggered when the bearish momentum (bear) crosses below a user-defined Long Threshold (default: 40). This suggests weakening bearish pressure, potentially indicating a reversal or breakout to the upside.
Exit Signals: Triggered when the bullish momentum (bull) crosses below a user-defined Sell Threshold (default: 80), indicating a potential reduction in bullish momentum and a signal to exit long positions.
Signals are visualized as tiny colored dots:
Long Entry: Blue dots, plotted either at the bottom of the oscillator or below the price bar (depending on user settings).
Exit Signal: White dots, plotted either at the top of the oscillator or above the price bar.
Calculation Methodology
Bollinger Bands:
A user-defined Length (default: 14) is used to calculate an Exponential Moving Average (EMA) of the source price (default: close).
Standard deviation is computed over the same length, multiplied by a user-defined Multiplier (default: 1.0).
Upper Band = EMA + (Standard Deviation × Multiplier)
Lower Band = EMA - (Standard Deviation × Multiplier)
Bull and Bear Momentum:
For each bar in the lookback period (length), the indicator calculates:
Bullish Momentum: The sum of positive deviations of the price above the upper band, normalized by the total absolute deviation from the upper band, scaled to a 0–100 range.
Bearish Momentum: The sum of positive deviations of the price below the lower band, normalized by the total absolute deviation from the lower band, scaled to a 0–100 range.
Formula:
bull = (sum of max(price - upper, 0) / sum of abs(price - upper)) * 100
bear = (sum of max(lower - price, 0) / sum of abs(lower - price)) * 100
Signal Generation:
Long Entry: Triggered when bear crosses below the Long Threshold.
Exit: Triggered when bull crosses below the Sell Threshold.
Settings
Length: Lookback period for EMA and standard deviation (default: 14).
Multiplier: Multiplier for standard deviation to adjust Bollinger Band width (default: 1.0).
Source: Input price data (default: close).
Long Threshold: Bearish momentum level below which a long entry signal is generated (default: 40).
Sell Threshold: Bullish momentum level below which an exit signal is generated (default: 80).
Plot Signals on Main Chart: Option to display entry/exit signals on the price chart instead of the oscillator panel (default: false).
Style:
Bullish Color: Color for bullish momentum plot (default: #f23645).
Bearish Color: Color for bearish momentum plot (default: #089981).
Visual Features
Bull and Bear Plots: Displayed as colored lines with gradient fills for visual clarity.
Midline: Horizontal line at 50 for reference.
Threshold Lines: Dashed green line for Long Threshold and dashed red line for Sell Threshold.
Signal Dots:
Long Entry: Tiny blue dots (below price bar or at oscillator bottom).
Exit: Tiny white dots (above price bar or at oscillator top).
How to Use
Add to Chart: Apply the indicator to your TradingView chart.
Adjust Settings: Customize the Length, Multiplier, Long Threshold, and Sell Threshold to suit your trading strategy.
Interpret Signals:
Enter a long position when a blue dot appears, indicating bearish momentum dropping below the Long Threshold.
Exit the long position when a white dot appears, indicating bullish momentum dropping below the Sell Threshold.
Toggle Plot Location: Enable Plot Signals on Main Chart to display signals on the price chart for easier integration with price action analysis.
Combine with Other Tools: Use alongside other indicators (e.g., trendlines, support/resistance) to confirm signals.
Notes
This indicator is inspired by LuxAlgo’s Bollinger Bands Breakout Oscillator but has been enhanced with customizable entry/exit thresholds and signal plotting options.
Best used in conjunction with other technical analysis tools to filter false signals, especially in choppy or range-bound markets.
Adjust the Multiplier to make the Bollinger Bands wider or narrower, affecting the sensitivity of the momentum calculations.
Disclaimer
This indicator is provided for educational and informational purposes only.
Gann Support and Resistance LevelsThis indicator plots dynamic Gann Degree Levels as potential support and resistance zones around the current market price. You can fully customize the Gann degree step (e.g., 45°, 30°, 90°), the number of levels above and below the price, and the price movement per degree to fine-tune the levels to your strategy.
Key Features:
✅ Dynamic levels update automatically with the live price
✅ Adjustable degree intervals (Gann steps)
✅ User control over how many levels to display above and below
✅ Fully customizable label size, label color, and text color for mobile-friendly visibility
✅ Clean visual design for easy chart analysis
How to Use:
Gann levels can act as potential support and resistance zones.
Watch for price reactions at major degrees like 0°, 90°, 180°, and 270°.
Can be combined with other technical tools like price action, trendlines, or Gann fans for deeper analysis.
📌 This tool is perfect for traders using Gann theory, grid-based strategies, or those looking to enhance their visual trading setups with structured levels.
Cumulative Volume Delta📊 Indicator Name:
Cumulative Volume Delta (CVD) + Candle Divergence (Color DIfference)
📌 Purpose:
This indicator visualizes volume delta over a user-defined time anchor and highlights divergence between volume-based momentum and price movement. It's especially useful for identifying potential reversals, fakeouts, or hidden buying/selling pressure.
🔍 How It Works:
1. Volume Delta Calculation (CVD Candles):
The script uses ta.requestVolumeDelta() to approximate volume delta data over a chosen anchor period (e.g., 1D).
Volume delta = Buy Volume – Sell Volume
Each candle on the CVD chart represents changes in cumulative volume delta, with OHLC-style values:
openVolume: cumulative delta at the start of the bar
lastVolume: cumulative delta at the end of the bar
maxVolume, minVolume: intra-bar high and low
2. Visual Representation (CVD Candles):
Green/Teal candle: Delta is increasing (buying pressure dominates)
Red candle: Delta is decreasing (selling pressure dominates)
3. Divergence Detection:
The script compares the direction of the price candle with the direction of the CVD candle:
Price Up + CVD Down → Possible hidden selling (bearish divergence)
Price Down + CVD Up → Possible hidden buying (bullish divergence)
4. Color Highlighting:
Orange candle on the CVD chart signals divergence between price and volume delta.
This color override helps you quickly spot potential discrepancies between price movement and underlying volume pressure.
5. Alerting:
An alertcondition is added so you can receive a notification whenever a divergence occurs.
⚙️ User Inputs:
Anchor period (e.g., 1D): Timeframe over which the CVD is anchored.
Use custom timeframe: Allows you to override and define the internal lower timeframe used for volume estimation (e.g., 1-min).
📈 How to Use It:
✅ Bullish Divergence (Price down, CVD up)
This may indicate:
Buyers absorbing selling pressure.
A potential reversal to the upside.
Hidden accumulation.
🚫 Bearish Divergence (Price up, CVD down)
This may indicate:
Sellers stepping in despite upward price.
A potential reversal to the downside.
Hidden distribution.
🧠 Trading Insights:
CVD is often used by order flow traders or those analyzing market depth and volume imbalances.
This version lets you visually align price action with underlying volume, improving decision-making.
The divergence signal can be combined with other technical tools like support/resistance, candlestick patterns, or trendlines for confirmation.
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.
Adaptive Volume‐Demand‐Index (AVDI)Demand Index (according to James Sibbet) – Short Description
The Demand Index (DI) was developed by James Sibbet to measure real “buying” vs. “selling” strength (Demand vs. Supply) using price and volume data. It is not a standalone trading signal, but rather a filter and trend confirmer that should always be used together with chart structure and additional indicators.
---
\ 1. Calculation Basis\
1. Volume Normalization
$$
\text{normVol}_t
= \frac{\text{Volume}_t}{\mathrm{EMA}(\text{Volume},\,n_{\text{Vol}})_t}
\quad(\text{e.g., }n_{\text{Vol}} = 13)
$$
This smooths out extremely high volume spikes and compares them to the average (≈ 1 means “average volume”).
2. Price Factor
$$
\text{priceFactor}_t
= \frac{\text{Close}_t - \text{Open}_t}{\text{Open}_t}.
$$
Positive values for bullish bars, negative for bearish bars.
3. Component per Bar
$$
\text{component}_t
= \text{normVol}_t \times \text{priceFactor}_t.
$$
If volume is above average (> 1) and the price rises slightly, this yields a noticeably positive value; conversely if the price falls.
4. Raw DI (Rolling Sum)
Over a window of \$w\$ bars (e.g., 20):
$$
\text{RawDI}_t
= \sum_{i=0}^{w-1} \text{component}_{\,t-i}.
$$
Alternatively, recursively for \$t \ge w\$:
$$
\text{RawDI}_t
= \text{RawDI}_{t-1}
+ \text{component}_t
- \text{component}_{\,t-w}.
$$
5. Optional EMA Smoothing
An EMA over RawDI (e.g., \$n\_{\text{DI}} = 50\$) reduces short-term fluctuations and highlights medium-term trends:
$$
\text{EMA\_DI}_t
= \mathrm{EMA}(\text{RawDI},\,n_{\text{DI}})_t.
$$
6.Zero Line
Handy guideline:
RawDI > 0: Accumulated buying power dominates.
RawDI < 0: Accumulated selling power dominates.
2. Interpretation & Application
Crossing Zero
RawDI above zero → Indication of increasing buying pressure (potential long signal).
RawDI below zero → Indication of increasing selling pressure (potential short signal).
Not to be used alone for entry—always confirm with price action.
RawDI vs. EMA_DI
RawDI > EMA\_DI → Acceleration of demand.
RawDI < EMA\_DI → Weakening of demand.
Divergences
Price makes a new high, RawDI does not make a higher high → potential weakness in the uptrend.
Price makes a new low, RawDI does not make a lower low → potential exhaustion of the downtrend.
3. Typical Signals (for Beginners)
\ 1. Long Setup\
RawDI crosses zero from below,
RawDI > EMA\_DI (acceleration),
Price closes above a short-term swing high or resistance.
Stop-Loss: just below the last swing low, Take-Profit/Trailing: on reversal signals or fixed R\:R.
2. Short Setup
RawDI crosses zero from above,
RawDI < EMA\_DI (increased selling pressure),
Price closes below a short-term swing low or support.
Stop-Loss: just above the last swing high.
---
4. Notes and Parameters
Recommended Values (Beginners):
Volume EMA (n₍Vol₎) = 13
RawDI window (w) = 20
EMA over DI (n₍DI₎) = 50 (medium-term) or 1 (no smoothing)
Attention:\
NEVER use in isolation. Always in combination with price action analysis (trendlines, support/resistance, candlestick patterns).
Especially during volatile news phases, RawDI can fluctuate strongly → EMA\_DI helps to avoid false signals.
---
Conclusion The Demand Index by James Sibbet is a powerful filter to assess price movements by their volume backing. It shows whether a rally is truly driven by demand or merely a short-term volume anomaly. In combination with classic chart analysis and risk management, it helps to identify robust entry points and potential trend reversals earlier.
Gann Single SwingGann Single Swing Indicator
The Gann Single Swing indicator is a sophisticated tool rooted in the geometric and cyclical market analysis principles pioneered by William Delbert Gann. Designed for traders who value deep market structure analysis, this indicator leverages the interplay of price and time to identify key support and resistance zones, potential reversal points, and critical price-time synchronization areas. Its unique approach makes it an invaluable instrument for those employing Gann-based methodologies or seeking a systematic way to decode complex market dynamics.
What It Does
The Gann Single Swing indicator is built to pinpoint high-probability zones for price action, such as support and resistance levels, where traders can logically initiate long or short positions. By analyzing a user-defined price swing (a move between two selected points, such as a local high and low), the indicator constructs a geometric framework that reveals hidden patterns in market movements. It identifies:
Support and Resistance Zones: Key price levels where the market is likely to reverse or consolidate.
Temporal Reversal Zones: Specific time periods where price reversals are more probable due to time-price resonance.
Price-Time Synchronization Points: Areas where price and time align to signal potential market turning points.
How It Works
The indicator’s algorithm is grounded in Gann’s geometric principles, focusing on the relationship between price movements and time cycles. Here’s a high-level overview of its process:
Swing Selection: Traders select two key points on the chart (e.g., a local minimum and maximum) to define a price swing.
Channel Construction: The swing is encapsulated within a dynamic channel, forming the foundation of the geometric model.
Gann Fan Application: A Gann Fan is applied to the channel to calculate critical angles, representing the balance between price and time. These angles help identify resonant points that align with the channel’s central axis.
Squared Channel Analysis: The algorithm creates “squared” channels, geometrically derived sub-structures, analyzed for intersections and alignments to project external support and resistance zones beyond the base swing.
Internal Zone Mapping: Within the base swing, a reverse Gann Fan maps internal zones, highlighting areas of price-time convergence that may act as dynamic support or resistance.
Zone Projection: The indicator synthesizes these calculations to plot precise zones of support, resistance, and potential reversals, both spatially (price levels) and temporally (time-based zones).
While the exact mathematical formulations remain proprietary, the indicator relies on time-tested Gann techniques, such as angle-based analysis and cyclical resonance, to deliver actionable insights.
How to Use It
Select the Swing: Identify two significant points on the chart (e.g., a recent high and low) to define the swing. These points serve as the anchor for the indicator’s calculations.
Interpret the Zones: The indicator plots support and resistance zones (both price-based and time-based). Look for price action near these zones to identify potential entry or exit points.
Combine with Other Tools: For best results, use alongside other Gann-based tools (e.g., Gann Squares or Time Cycles) or traditional technical analysis (e.g., trendlines, Fibonacci levels) to confirm signals.
Monitor Temporal Zones: Pay attention to time-based reversal zones, as they may indicate when a price move is likely to occur, enhancing trade timing.
Why It’s Unique
Unlike conventional indicators that rely on moving averages, RSI, or other common metrics, the Gann Single Swing indicator offers a proprietary blend of Gann’s geometric and cyclical principles. Its ability to integrate price and time into a cohesive model sets it apart, providing traders with a deeper understanding of market structure. The indicator does not use public domain code or standard technical indicators, ensuring originality and value for traders seeking advanced tools.
Who It’s For
This indicator is ideal for:
Traders familiar with Gann’s methodologies who want to automate and enhance their geometric analysis.
Advanced traders looking to uncover hidden market patterns through price-time relationships.
Those seeking a robust, non-traditional tool for identifying high-probability trade setups.
The Gann Single Swing indicator is not a black-box forecasting tool but a powerful framework for dissecting market behavior. By combining user-defined inputs with sophisticated geometric calculations, it empowers traders to make informed decisions based on the timeless principles of Gann’s market philosophy.
Professional Candlestick + QQE Confirm v2.0 Professional Candlestick + QQE Confirm v1.0
This script combines powerful candlestick pattern detection with QQE momentum confirmation to improve signal reliability for swing trading and trend entries.
🔍 What It Does:
- Detects high-probability candlestick patterns (e.g. Pin Bars, Engulfing, Morning/Evening Stars)
- Confirms signals with the QQE indicator to reduce false entries
- Highlights buy/sell zones using combined logic
⚙️ Key Features:
- Multiple candlestick patterns, each toggleable
- QQE filtering to confirm valid breakouts or reversals
- Signal labels with strength grading
- Optional alert settings
📊 Best Use:
- Works well on 1H, 4H, and Daily charts
- Combine with trendlines or support/resistance for stronger entries
- Avoids signals in sideways/choppy markets
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This is a tool for traders who want to filter out weak candlestick signals using a trusted momentum indicator (QQE) for more accurate entries.
Simple Auto Trend LinesOpinionated way of drawing automatic trend lines. It draws automatically trend lines based on specified top/bottom strengths with multiple sets in order to keep track of multiple levels of interest.
Has the ability to hide invalidated trendlines if price moves away from it.
RSI Crossover Signal Companion - Alerts + Visuals🔷 RSI Crossover Signal Companion — Alerts + Visuals
The Relative Strength Index (RSI) is a momentum oscillator that measures the speed and change of recent price movements. It helps traders identify overbought or oversold conditions, possible trend reversals, and momentum strength.
This utility builds on TradingView’s classic Relative Strength Index (RSI) by adding real-time alerts and triangle markers when the RSI crosses its own moving average — a common technique for early momentum detection.
It is designed as a lightweight, visual companion tool for traders using RSI/MA crossover logic in manual or semi-automated strategies.
🔍 Features
✅ Preserves the full original RSI layout, including:
• Gradient fill and overbought/oversold zones
• Standard RSI input settings (length, source, etc.)
• MA smoothing options with user-defined type and length
🔺 Adds visual triangle markers:
🔼 Up triangle when RSI crosses above its MA
🔽 Down triangle when RSI crosses below its MA
📢 Built-in alerts for RSI/MA crosses:
“RSI Crossed Above MA”
“RSI Crossed Below MA”
📈 How to Use
This script is ideal for:
• Spotting early momentum shifts
• Confirming entries or exits in other systems (price action, trendlines, breakouts)
• Building alert-based automation (webhooks, bots, etc.)
Popular use cases:
• Combine with trend indicators like MA200 or MA12
• Use in confluence with price structure and divergence
• Validate breakout moves with momentum confirmation
⚙️ Customization
RSI length, MA length, MA type, and source are fully adjustable
Triangle marker size, shape, and color can be edited under Style
Alerts are pre-built and ready for use
Doji Candle with Horizontal Lines Raja Saien🔰 Doji Candle with Horizontal Lines By Raja Saien
Created by: Wasif Samejo
Script Type: Visual Doji Identifier with Key Level Markers
Overlay: Yes
📌 Description:
This indicator helps you visually identify Doji candles and automatically plots horizontal key levels based on their high, low, and a defined price zone.
A Doji candle is a powerful signal in price action trading that shows indecision in the market, often leading to strong reversals or breakouts. This script is especially useful for traders who want to mark such candles and prepare for possible trade setups.
📈 Features:
✅ Automatic Doji Detection – Based on customizable body size (20.0% of the total range).
✅ Highlights Doji Candle – Visually changes the bar color to yellow when a Doji is found.
✅ High/Low Horizontal Lines – Marks the candle's actual high and low for better visual analysis.
✅ Zone Lines Above/Below – Draws outer levels to form a zone around the Doji, helpful for breakout setups.
Zone Line Color – Set the color for the upper and lower zone lines.
High/Low Line Color – Set the color for the high and low candle levels.
💡 Combine this indicator with trendlines, volume, or Fibonacci tools for better confirmation.
Capitulation ScoutCapitulation Scout - Description
Overview
The Capitulation Scout is a streamlined technical indicator designed to identify potential market reversals by spotting moments of "capitulation" – extreme fear ( bearish capitulation ) or euphoria ( bullish capitulation ). It combines two independent filter groups to provide reliable reversal signals: an Extremes Filter (RSI + Bollinger Bands) and a Confirmation Filter (Volume Spike + MA Deviation). The indicator dynamically adapts to the current chart timeframe, making it versatile for day traders and long-term investors alike.
How It Works
This indicator uses two filter groups to detect capitulation, which can be enabled or disabled individually:
1. Extremes Filter (RSI + Bollinger Bands) : Identifies overbought (default: RSI > 70) or oversold (default: RSI < 30) conditions combined with price breaking through the Bollinger Bands (default: 200-period, 2x multiplier), indicating an extreme price movement.
2. Confirmation Filter (Volume Spike + MA Deviation) : Requires both a significant volume increase (default: 2x the 20-period average volume on lower timeframes, dynamically adjusted on higher timeframes) and a significant price deviation from a moving average (default: 5% deviation from a 50-period SMA) to confirm the capitulation event.
A signal is generated if at least one filter is enabled and all enabled filters meet their respective conditions.
Signals
- Bearish Capitulation : Marked with a red downward triangle (customizable in the "Style" tab) above the candle. Occurs when the enabled filters detect a potential top, e.g., overbought RSI and price above the upper Bollinger Band (if Extremes Filter enabled), and/or a volume spike combined with a significant upward deviation from the MA (if Confirmation Filter enabled).
- Bullish Capitulation : Marked with a green upward triangle (customizable in the "Style" tab) below the candle. Occurs when the enabled filters detect a potential bottom, e.g., oversold RSI and price below the lower Bollinger Band (if Extremes Filter enabled), and/or a volume spike combined with a significant downward deviation from the MA (if Confirmation Filter enabled).
Note : At least one filter must be enabled to generate signals. If both filters are disabled, no signals will be shown.
How to Use
1. Add the Capitulation Scout to your chart.
2. Look for red downward triangles ( bearish capitulation ) at market tops or green upward triangles ( bullish capitulation ) at market bottoms as potential reversal signals.
3. Use the signals in conjunction with other technical analysis tools (e.g., support/resistance levels, trendlines) to confirm trades.
4. Set up alerts for bearish or bullish capitulation signals to get real-time notifications.
5. Adjust the settings to suit your trading style and timeframe. For smaller timeframes (e.g., 5M or 15M), consider reducing the Bollinger Bands length for more sensitivity.
Settings
- Extremes Filter Settings
- Use Extremes Filter (RSI + Bollinger Bands) : Enable/disable the RSI and Bollinger Bands filter (default: enabled).
- RSI Length : Period for RSI calculation (default: 14 periods, relative to the chart timeframe).
- RSI Overbought/Oversold Levels : Thresholds for overbought/oversold conditions (default: 70/30).
- Bollinger Bands Length/Multiplier : Settings for Bollinger Bands (default: 200 periods, 2x multiplier).
- Confirmation Filter Settings
- Use Confirmation Filter (Volume Spike + MA Deviation) : Enable/disable the combined Volume Spike and MA Deviation filter (default: enabled). When enabled, both a volume spike and a significant MA deviation are required to meet the filter condition.
- Volume Spike Threshold (Base Multiplier) : Multiplier for detecting volume spikes on lower timeframes (default: 2x the 20-period average). On higher timeframes (e.g., weekly or monthly), the threshold is dynamically reduced to be more sensitive (e.g., 1.5x on weekly, 1x on monthly).
- Moving Average Length : Period for the SMA (default: 50 periods, relative to the chart timeframe).
- MA Deviation Threshold (%) : Percentage deviation from the MA to consider the price stretched (default: 5%).
Features
- MA Deviation Filter Visualization : The moving average used for the MA deviation filter can be enabled in the "Style" tab under "MA for Deviation Filter (Optional)" and is displayed in blue by default. It is disabled by default and must be manually enabled in the "Style" tab. Its color, line width, and style can be customized in the "Style" tab.
- Customizable Visuals : In the "Style" tab, you can toggle the visibility of signal markers and customize their colors, sizes, and styles.
- Alerts : Set up alerts for bearish or bullish capitulation signals to get real-time notifications.
Notes
- The indicator automatically adapts to the current chart timeframe (e.g., 1M, 15M, 1H, 1D, etc.). On smaller timeframes, consider reducing the RSI Length, Bollinger Bands Length, and Volume Period for better sensitivity. For example, on a 5-minute chart, a Bollinger Bands Length of 200 covers 1,000 minutes (over 16 hours), which might be too long – try lowering it to 50 or 100.
- Capitulation events are generally more reliable on higher timeframes (e.g., 1H, 4H, 1D), but the indicator can be used on any timeframe with proper adjustments. On weekly or monthly timeframes, the volume spike threshold is dynamically reduced to detect capitulation events more effectively.
- You can enable any combination of filters to generate signals. For example, disabling the Extremes Filter and enabling only the Confirmation Filter will generate signals based solely on volume spikes combined with MA deviation.
- Always combine with other analysis methods to reduce false signals.
- Test the indicator on your preferred markets (stocks, ETFs, crypto, etc.) and tweak the settings as needed.
Example
The thumbnail shows the Capitulation Scout on a daily chart of ETHUSD on Coinbase. Two red downward triangles ( bearish capitulation ) marked a major local top in early 2024, and from there, the ETH price started to correct. Two green upward triangles ( bullish capitulation ) marked a major bottom in April 2025, followed by a significant rally. For more examples, follow my account – I’ll aim to share and track such signals with you in the future.
Malama's Heikin CountMalama's Heikin Count is a Pine Script indicator designed to enhance price action analysis by combining Heikin Ashi candlestick calculations with a normalized measurement of upper and lower shadow sizes. The indicator overlays Heikin Ashi candles on the chart and displays the relative sizes of upper and lower shadows as numerical labels (scaled from 1 to 10) for candles within the last two days, starting from 9:00 AM each day. This tool aims to help traders identify the strength of price movements and potential reversals by quantifying the significance of candlestick shadows in the context of Heikin Ashi’s smoothed price data. It is particularly useful for day traders and swing traders who rely on candlestick patterns to gauge market sentiment and momentum.
The indicator solves the problem of interpreting raw candlestick data by providing a smoothed visualization through Heikin Ashi candles and a simplified, numerical representation of shadow sizes. This allows traders to quickly assess whether a candle’s upper or lower shadow indicates strong buying or selling pressure, aiding in decision-making for entries, exits, or reversals.
Originality and Usefulness
Originality: While Heikin Ashi candles are a well-known technique for smoothing price data and reducing noise, Malama's Heikin Count introduces a novel feature by calculating and normalizing the sizes of upper and lower shadows relative to the total candle height. Unlike standard Heikin Ashi implementations, which focus solely on candle body trends, this indicator quantifies shadow proportions and presents them on a standardized 1–10 scale. This normalization makes it easier for traders to compare shadow significance across different timeframes and assets without needing to manually interpret raw measurements. The restriction of shadow size labels to the last two days from 9:00 AM ensures relevance for active trading sessions, avoiding clutter from older data.
Usefulness: The indicator is particularly valuable for traders who combine candlestick pattern analysis with trend-following strategies. By integrating Heikin Ashi’s trend-smoothing capabilities with shadow size metrics, it provides a unique perspective on market dynamics. For example, large upper shadows (high normalized values) may indicate rejection at resistance levels, while large lower shadows may suggest support or buying pressure. Unlike other open-source Heikin Ashi indicators, which typically focus only on candle plotting, this script’s shadow size normalization and time-based filtering offer a distinctive tool for intraday and short-term trading strategies.
Detailed Methodology ("How It Works")
The core logic of Malama's Heikin Count revolves around three main components: Heikin Ashi candle calculations, shadow size analysis, and time-based filtering for label display. Below is a breakdown of how these components work together:
Heikin Ashi Candle Calculations:
The script calculates Heikin Ashi candles to smooth price data and reduce market noise, making trends easier to identify.
Formulas:
haClose = (open + high + low + close) / 4: The Heikin Ashi close is the average of the current bar’s open, high, low, and close prices.
haOpen = na(haOpen ) ? (open + close) / 2 : (haOpen + haClose ) / 2: The Heikin Ashi open is either the average of the current bar’s open and close (for the first bar) or the average of the previous Heikin Ashi open and close.
haHigh = max(high, max(haOpen, haClose)): The Heikin Ashi high is the maximum of the current bar’s high, Heikin Ashi open, and Heikin Ashi close.
haLow = min(low, min(haOpen, haClose)): The Heikin Ashi low is the minimum of the current bar’s low, Heikin Ashi open, and Heikin Ashi close.
These calculations produce smoothed candles that emphasize trend direction and reduce the impact of short-term price fluctuations.
Shadow Size Analysis:
The script calculates the upper and lower shadows of each Heikin Ashi candle to assess market sentiment.
Formulas:
upperShadow = haHigh - max(haClose, haOpen): Measures the length of the upper shadow (distance from the top of the candle body to the high).
lowerShadow = min(haClose, haOpen) - haLow: Measures the length of the lower shadow (distance from the bottom of the candle body to the low).
totalHeight = haHigh - haLow: Calculates the total height of the candle (from high to low).
upperShadowPercentage = (upperShadow / totalHeight) * 100: Converts the upper shadow length to a percentage of the total candle height.
lowerShadowPercentage = (lowerShadow / totalHeight) * 100: Converts the lower shadow length to a percentage of the total candle height.
Normalization: The normalizeShadowSize function scales the shadow percentages to a 1–10 range using math.round(value / 10). This ensures that shadow sizes are presented in an easily interpretable format, where 1 represents a very small shadow (less than 10% of the candle height) and 10 represents a very large shadow (90–100% of the candle height). The normalization caps values between 1 and 10 for consistency.
Time-Based Filtering:
The script only displays shadow size labels for candles within the last two days, starting from 9:00 AM each day. This is achieved by calculating a start timestamp using timestamp(year(timenow), month(timenow), dayofmonth(timenow) - daysBack, startHour, startMinute), where daysBack = 2, startHour = 9, and startMinute = 0.
The condition time >= startTime ensures that labels are only plotted for candles within this time window, keeping the chart relevant for recent trading activity and avoiding clutter from older data.
Signal Generation:
The script does not generate explicit buy or sell signals but provides visual cues through shadow size labels. Large upper shadow sizes (e.g., 8–10) may indicate selling pressure or resistance, while large lower shadow sizes may suggest buying pressure or support. Traders can use these metrics in conjunction with the Heikin Ashi candle colors (green for bullish, red for bearish) to make trading decisions.
Strategy Results and Risk Management
Backtesting: The script is an indicator and does not include built-in backtesting or strategy logic for generating buy/sell signals. As such, it does not assume specific commission, slippage, or account sizing parameters. Traders using this indicator should incorporate it into their existing strategies, applying their own risk management rules.
Risk Management Guidance:
Traders can use the shadow size labels to inform risk management decisions. For example, a large upper shadow (e.g., 8–10) at a resistance level may prompt a trader to set a tighter stop-loss above the candle’s high, anticipating a potential reversal. Conversely, a large lower shadow at a support level may suggest a wider stop-loss below the low to account for volatility.
Default settings (e.g., 2-day lookback, 9:00 AM start) are designed to focus on recent price action, which is suitable for intraday and short-term swing trading. Traders should combine the indicator with other tools (e.g., support/resistance levels, trendlines) to define risk limits, such as risking 5–10% of equity per trade.
The indicator does not enforce specific risk management settings, allowing traders to customize their approach based on their risk tolerance and trading style.
User Settings and Customization
The script includes the following user-customizable inputs:
Days Back (daysBack = 2):
Description: Controls the lookback period for displaying shadow size labels. The default value of 2 means labels are shown for candles within the last two days.
Impact: Increasing daysBack extends the time window for label display, which may be useful for longer-term analysis but could clutter the chart. Decreasing it focuses on more recent data, ideal for intraday trading.
Start Hour (startHour = 9) and Start Minute (startMinute = 0):
Description: Defines the start time of the trading day (default is 9:00 AM). Labels are only shown for candles after this time each day within the lookback period.
Impact: Traders can adjust these settings to align with their preferred trading session (e.g., 9:30 AM for U.S. market open). Changing the start time shifts the time window for label display, affecting which candles are analyzed.
These settings allow traders to tailor the indicator to their trading timeframe and session preferences, ensuring that the shadow size labels remain relevant to their analysis.
Visualizations and Chart Setup
The indicator plots the following elements on the chart:
Heikin Ashi Candles:
Plotted using plotcandle(haOpen, haClose, haHigh, haLow), these candles overlay the standard price chart.
Color Coding: Green candles indicate bullish momentum (Heikin Ashi close ≥ open), while red candles indicate bearish momentum (Heikin Ashi close < open).
These candles provide a smoothed view of price trends, making it easier to identify trend direction and continuations.
Shadow Size Labels:
Upper Shadow Labels: Displayed above each candle at the Heikin Ashi high, showing the normalized upper shadow size (1–10). These labels are green with white text and use the label.style_label_down style for clear visibility.
Lower Shadow Labels: Displayed below each candle at the Heikin Ashi low, showing the normalized lower shadow size (1–10). These labels are red with white text and use the label.style_label_up style.
Labels are only shown for candles within the last two days from 9:00 AM, ensuring that only recent and relevant data is visualized.
Debugging Labels (Optional):
A blue label at the bottom of the chart displays the text "Upper: Lower: " for each candle, showing both shadow sizes for debugging purposes. This can be removed or commented out if not needed, as it is primarily for development use.
The visualizations are designed to be minimal and focused, ensuring that traders can quickly interpret the Heikin Ashi trend and shadow size metrics without unnecessary clutter. The use of color-coded candles and labels enhances readability, while the time-based filtering keeps the chart clean and relevant.
ABC Trading ConceptOverview
ABC Trading Concept is a wave- and trend-based market structure indicator that identifies shifts in price behavior by analyzing impulse and correction patterns. It introduces a unique calculation method—Price-MAD-ATR Bands—to detect wave formation, trend reversals, and potential trade zones with dynamic adaptability to volatility and trend strength.
🔧 Core Logic and Calculations
1. Price-MAD-ATR Bands
At the heart of the script is a proprietary channel system based on:
MAD (MA Difference): Difference between fast and slow moving averages.
ATR (Average True Range): Measures current market volatility.
The bands are plotted as:
Upper Band = Price + MAD × ATR
Lower Band = Price − MAD × ATR
A breakout beyond these bands signals the formation of a new wave (up or down).
2. Wave Formation (A and B Waves)
Standard Method: A new wave forms when price breaks through a Price-MAD-ATR Band.
Extreme Method: A wave also forms when price breaks the passive extremum of an existing wave.
Wave A may be generated by a correction breaking the Reversal Point.
Wave B can be configured to form in three modes, including breakouts of internal or boosted counter-corrections.
3. Trend Structure
A trend is built from waves and includes:
Direction, active/passive extremums
Impulses and Corrections (each tracked independently)
Reversal Point: Defined by a boosted correction breakout
G-Point: Set at the active extremum of Wave A
Vic Line: A trendline derived from previous correction extremums (optional)
When price breaks above the G-point, a new trend may be initiated.
4. Correction Boost Logic
A correction becomes boosted when price exceeds a configurable multiple of the correction’s range. Boosted corrections define key zones and enable the creation of Reversal Points and Wave A setups.
5. Vic Sperandeo Line
Optionally used to enhance trend structure confirmation. Drawn between extremums of previous corrections and may act as a secondary condition for forming Wave A.
6. SL/TP Level Calculation
At the start of a new trend, SL and TP levels are automatically plotted based on:
The extremums of Wave A or Wave B (selectable)
Configurable ratios (e.g., 1.382, 2.0, 2.618 for TP levels)
📊 Visual Elements on the Chart
Bands: Price-MAD-ATR Bands as adaptive upper/lower thresholds
Waves: Yellow zigzag lines
Trends: Blue (or purple for hard-type) trendlines with directional arrow
Reversal Point: Dashed horizontal line (starts from key correction breakout)
Correction Zone: Shaded rectangle from boosted correction range
Vic Line: Dashed support/resistance trendline
TP/SL Levels: Dotted horizontal levels, plotted at trend origin
⚙️ Inputs and Customization
You can adjust:
ATR and MA parameters
Band width multiplier
Boost strength threshold for corrections
SL/TP levels and logic (by Wave A or B)
Vic Line usage and visual styles for each element
Over 40 configurable settings are available to adapt the indicator to your strategy.
🧠 How to Use
Look for a new trend start when G-point is broken.
Use Wave A/B structure and Reversal Point for setup planning.
Correction Zones help identify re-entry areas or stop placement.
Follow TP/SL levels to manage exits with structural targets.
The Vic Line can act as dynamic support/resistance in context.
The indicator provides analytical insights—it does not generate automatic signals.
💡 What Makes It Unique
Unlike typical wave or Zigzag indicators, ABC Trading Concept introduces a volatility-adjusted wave logic using Price-MAD-ATR Bands. This method combines trend momentum (MA differential) with market volatility (ATR), offering a more flexible and noise-resistant structure recognition system. The integration of Wave A/B logic, dynamic reversal zones, and Vic Line validation makes it a comprehensive tool for structural traders.
⚠️ Disclaimer
This tool is for technical analysis and educational purposes. It does not guarantee profit or forecast market direction. Trading involves risk—use this script as part of a larger strategy with proper risk management.
Tight Range Display with Background🌟 Tight Range Transparency Display with Background
What Is This Indicator?
Hey traders! Ever wanted a simple way to spot those quiet, low-volatility moments in the market that often signal a big move is coming? The Tight Range Transparency Display with Background does exactly that! This indicator highlights periods where the price is moving in a tight range—think of it as the calm before the storm. It paints the chart background blue to show these zones, with the shade getting darker the tighter the range becomes. It’s like having a visual cue to say, “Hey, something might be brewing here!”
Why You’ll Love It
Spot Key Moments Easily: The blue background makes it super easy to see when the market is in a tight range, which often happens before breakouts or big trends.
Customizable Settings: You can tweak the range thresholds to match your trading style—whether you’re looking for super tight zones or slightly broader ones.
Visual Clarity: The background gets darker when the range is tighter, giving you a quick sense of how compressed the price action is.
Perfect for Any Market: Works on stocks, forex, crypto, or any chart you trade, across any timeframe.
How to Use It
Add It to Your Chart:
Just copy this script into TradingView’s Pine Editor and hit "Add to Chart." It’ll overlay right on your price chart.
Tweak the Settings:
Open the indicator settings and use the dropdown menus to pick your preferred "Tight Range %" and "Wide Range %." For example, set a Tight Range % of 2.0% to catch smaller ranges, or go higher like 10.0% for broader ones.
You can also adjust the ATR Period (default is 5) to make the indicator more or less sensitive to recent price swings.
Watch for the Blue Background:
When the price enters a tight range, the chart background turns blue. The darker the blue, the tighter the range—meaning a potential breakout could be closer!
Trade Smarter:
Use these tight range zones to prepare for potential breakouts. For example, if you see a dark blue background, it might be a good time to watch for a big price move.
Pair this with other tools like support/resistance levels or volume spikes to confirm your trades.
Who Is This For?
Swing Traders: Perfect for spotting consolidation zones before a big swing.
Breakout Traders: Tight ranges often lead to breakouts—use this to time your entries.
Smart Money Followers: If you’re into smart money concepts, tight ranges can signal accumulation or distribution phases.
Beginners & Pros Alike: It’s easy to use for new traders but powerful enough for seasoned pros.
Real-World Example
Imagine you’re trading a stock on a 1-hour chart. You notice the background turns blue, and it’s getting darker over a few bars. This tells you the price range is tightening—maybe the stock is consolidating after a big move. You check your other indicators, see a volume spike, and spot a breakout above resistance. Boom! You catch the next big trend, all because this indicator helped you focus on the right moment.
Tips for Best Results
Try Different Timeframes: Tight ranges on a 15-minute chart might signal short-term moves, while a daily chart could highlight bigger trends.
Adjust for Your Market: For volatile markets like crypto, you might want a higher Tight Range % (e.g., 10.0%). For calmer markets like forex, try a lower setting (e.g., 2.0%).
Combine with Other Tools: Use this alongside trendlines, moving averages, or volume indicators to confirm your setups.
Why I Made This
I created this indicator because I wanted a simple, visual way to spot those critical low-volatility zones without cluttering my chart. The dynamic background color makes it intuitive to see when the market is “coiling up” for a potential move. I hope it helps you find better trading opportunities just like it does for me!
Let’s Connect
If you find this indicator helpful, I’d love to hear about it! Drop a comment or a rating to let me know how it’s working for you. Got ideas to make it even better? Feel free to message me on TradingView—I’m always open to suggestions.
Published On
Date: May 22, 2025
Happy trading, and may your charts always be in your favor! 🚀
How to Publish on TradingView
Open Pine Editor:
On TradingView, open a chart and go to the Pine Editor tab at the bottom.
Paste the Code:
Copy the script you provided and paste it into the Pine Editor.
Compile:
Click "Add to Chart" to ensure it compiles without errors.
Publish:
Click the "Publish Script" button (paper plane icon) in the Pine Editor.
Select "Publish New Script."
Add the Description:
Title: "Tight Range Transparency Display with Background"
Description: Copy the content above into the description field.
Visibility: Choose "Public" to share with everyone (or "Invite-Only" for restricted access).
Tags: Add tags like "tight range", "breakout", "smart money", "volatility", "swing trading".
Screenshot: Add a screenshot of the indicator on a chart, showing the blue background during a tight range.
Submit:
Click "Publish" to submit. TradingView will review it and make it live if it meets their guidelines.
Additional Notes
Screenshot Tip: Use a chart where the blue background is clearly visible (e.g., during a consolidation period) to make the indicator’s effect stand out.
Engage with Users: After publishing, respond to comments and feedback to build a positive reputation on TradingView.
This content is designed to be approachable and engaging, helping traders understand the value of your indicator and encouraging them to try it out.
(OFPI) Order Flow Polarity Index - Momentum Gauge (DAFE) (OFPI) Order Flow Polarity Index - Momentum Gauge: Decode Market Aggression
The (OFPI) Gauge Bar is your front-row seat to the battle between buyers and sellers. This isn’t just another indicator—it’s a momentum tracker that reveals market aggression through a sleek, centered gauge bar and a smart dashboard. Built for traders who want clarity without clutter, it’s your edge for spotting who’s driving price, bar by bar.
What Makes It Unique?
Order Flow Pressure Index (OFPI): Splits volume into buy vs. sell pressure based on candle body position. It’s not just volume—it’s intent, showing who’s got the upper hand.
T3 Smoothing Magic: Uses a Tilson T3 moving average to keep signals smooth yet responsive. No laggy SMA nonsense here.
Centered Gauge Bar: A 20-segment bar splits bullish (lime) and bearish (red) momentum around a neutral center. Empty segments scream indecision—it’s like a visual heartbeat of the market.
Momentum Shift Alerts: Catches reversals with “Momentum Shift” flags when the OFPI crests, so you’re not caught off guard.
Clean Dashboard: A compact, bottom-left table shows momentum status, the gauge bar, and the OFPI value. Color-coded, transparent, and no chart clutter.
Inputs & Customization
Lookback Length (default 10): Set the window for pressure calculations. Short for scalps, long for trends.
T3 Smoothing Length (default 5): Tune the smoothness. Tight for fast markets, relaxed for chill ones.
T3 Volume Factor (default 0.7): Crank it up for snappy signals or down for silky trends.
Toggle the dashboard for minimalist setups or mobile trading.
How to Use It
Bullish Momentum (Lime, Right-Filled): Buyers are flexing. Look for breakouts or trend continuations. Pair with support levels.
Bearish Momentum (Red, Left-Filled): Sellers are in charge. Scout for breakdowns or shorts. Check resistance zones.
Neutral (Orange, Near Center): Market’s chilling. Avoid big bets—wait for a breakout or play the range.
Momentum Shift: A reversal might be brewing. Confirm with price action before jumping in.
Not a Solo Act: Combine with your strategy—trendlines, RSI, whatever. It’s a momentum lens, not a buy/sell bot.
Why Use the OFPI Gauge?
See the Fight: Most tools just count volume. OFPI shows who’s winning with a visual that slaps.
Works Anywhere: Crypto, stocks, forex, any timeframe. Tune it to your style.
Clean & Pro: No chart spam, just a sharp gauge and a dashboard that delivers.
Unique Edge: No other indicator blends body-based pressure, T3 smoothing, and a centered gauge like this.
The OFPI Gauge catches the market’s pulse so you can trade with confidence. It’s not about predicting the future—it’s about knowing who’s in control right now.
For educational purposes only. Not financial advice. Always use proper risk management.
Use with discipline. Trade your edge.
— Dskyz , for DAFE Trading Systems
Why EMA Isn't What You Think It IsMany new traders adopt the Exponential Moving Average (EMA) believing it's simply a "better Simple Moving Average (SMA)". This common misconception leads to fundamental misunderstandings about how EMA works and when to use it.
EMA and SMA differ at their core. SMA use a window of finite number of data points, giving equal weight to each data point in the calculation period. This makes SMA a Finite Impulse Response (FIR) filter in signal processing terms. Remember that FIR means that "all that we need is the 'period' number of data points" to calculate the filter value. Anything beyond the given period is not relevant to FIR filters – much like how a security camera with 14-day storage automatically overwrites older footage, making last month's activity completely invisible regardless of how important it might have been.
EMA, however, is an Infinite Impulse Response (IIR) filter. It uses ALL historical data, with each past price having a diminishing - but never zero - influence on the calculated value. This creates an EMA response that extends infinitely into the past—not just for the last N periods. IIR filters cannot be precise if we give them only a 'period' number of data to work on - they will be off-target significantly due to lack of context, like trying to understand Game of Thrones by watching only the final season and wondering why everyone's so upset about that dragon lady going full pyromaniac.
If we only consider a number of data points equal to the EMA's period, we are capturing no more than 86.5% of the total weight of the EMA calculation. Relying on he period window alone (the warm-up period) will provide only 1 - (1 / e^2) weights, which is approximately 1−0.1353 = 0.8647 = 86.5%. That's like claiming you've read a book when you've skipped the first few chapters – technically, you got most of it, but you probably miss some crucial early context.
▶️ What is period in EMA used for?
What does a period parameter really mean for EMA? When we select a 15-period EMA, we're not selecting a window of 15 data points as with an SMA. Instead, we are using that number to calculate a decay factor (α) that determines how quickly older data loses influence in EMA result. Every trader knows EMA calculation: α = 1 / (1+period) – or at least every trader claims to know this while secretly checking the formula when they need it.
Thinking in terms of "period" seriously restricts EMA. The α parameter can be - should be! - any value between 0.0 and 1.0, offering infinite tuning possibilities of the indicator. When we limit ourselves to whole-number periods that we use in FIR indicators, we can only access a small subset of possible IIR calculations – it's like having access to the entire RGB color spectrum with 16.7 million possible colors but stubbornly sticking to the 8 basic crayons in a child's first art set because the coloring book only mentioned those by name.
For example:
Period 10 → alpha = 0.1818
Period 11 → alpha = 0.1667
What about wanting an alpha of 0.17, which might yield superior returns in your strategy that uses EMA? No whole-number period can provide this! Direct α parameterization offers more precision, much like how an analog tuner lets you find the perfect radio frequency while digital presets force you to choose only from predetermined stations, potentially missing the clearest signal sitting right between channels.
Sidenote: the choice of α = 1 / (1+period) is just a convention from 1970s, probably started by J. Welles Wilder, who popularized the use of the 14-day EMA. It was designed to create an approximate equivalence between EMA and SMA over the same number of periods, even thought SMA needs a period window (as it is FIR filter) and EMA doesn't. In reality, the decay factor α in EMA should be allowed any valye between 0.0 and 1.0, not just some discrete values derived from an integer-based period! Algorithmic systems should find the best α decay for EMA directly, allowing the system to fine-tune at will and not through conversion of integer period to float α decay – though this might put a few traditionalist traders into early retirement. Well, to prevent that, most traditionalist implementations of EMA only use period and no alpha at all. Heaven forbid we disturb people who print their charts on paper, draw trendlines with rulers, and insist the market "feels different" since computers do algotrading!
▶️ Calculating EMAs Efficiently
The standard textbook formula for EMA is:
EMA = CurrentPrice × alpha + PreviousEMA × (1 - alpha)
But did you know that a more efficient version exists, once you apply a tiny bit of high school algebra:
EMA = alpha × (CurrentPrice - PreviousEMA) + PreviousEMA
The first one requires three operations: 2 multiplications + 1 addition. The second one also requires three ops: 1 multiplication + 1 addition + 1 subtraction.
That's pathetic, you say? Not worth implementing? In most computational models, multiplications cost much more than additions/subtractions – much like how ordering dessert costs more than asking for a water refill at restaurants.
Relative CPU cost of float operations :
Addition/Subtraction: ~1 cycle
Multiplication: ~5 cycles (depending on precision and architecture)
Now you see the difference? 2 * 5 + 1 = 11 against 5 + 1 + 1 = 7. That is ≈ 36.36% efficiency gain just by swapping formulas around! And making your high school math teacher proud enough to finally put your test on the refrigerator.
▶️ The Warmup Problem: how to start the EMA sequence right
How do we calculate the first EMA value when there's no previous EMA available? Let's see some possible options used throughout the history:
Start with zero : EMA(0) = 0. This creates stupidly large distortion until enough bars pass for the horrible effect to diminish – like starting a trading account with zero balance but backdating a year of missed trades, then watching your balance struggle to climb out of a phantom debt for months.
Start with first price : EMA(0) = first price. This is better than starting with zero, but still causes initial distortion that will be extra-bad if the first price is an outlier – like forming your entire opinion of a stock based solely on its IPO day price, then wondering why your model is tanking for weeks afterward.
Use SMA for warmup : This is the tradition from the pencil-and-paper era of technical analysis – when calculators were luxury items and "algorithmic trading" meant your broker had neat handwriting. We first calculate an SMA over the initial period, then kickstart the EMA with this average value. It's widely used due to tradition, not merit, creating a mathematical Frankenstein that uses an FIR filter (SMA) during the initial period before abruptly switching to an IIR filter (EMA). This methodology is so aesthetically offensive (abrupt kink on the transition from SMA to EMA) that charting platforms hide these early values entirely, pretending EMA simply doesn't exist until the warmup period passes – the technical analysis equivalent of sweeping dust under the rug.
Use WMA for warmup : This one was never popular because it is harder to calculate with a pencil - compared to using simple SMA for warmup. Weighted Moving Average provides a much better approximation of a starting value as its linear descending profile is much closer to the EMA's decay profile.
These methods all share one problem: they produce inaccurate initial values that traders often hide or discard, much like how hedge funds conveniently report awesome performance "since strategy inception" only after their disastrous first quarter has been surgically removed from the track record.
▶️ A Better Way to start EMA: Decaying compensation
Think of it this way: An ideal EMA uses an infinite history of prices, but we only have data starting from a specific point. This creates a problem - our EMA starts with an incorrect assumption that all previous prices were all zero, all close, or all average – like trying to write someone's biography but only having information about their life since last Tuesday.
But there is a better way. It requires more than high school math comprehension and is more computationally intensive, but is mathematically correct and numerically stable. This approach involves compensating calculated EMA values for the "phantom data" that would have existed before our first price point.
Here's how phantom data compensation works:
We start our normal EMA calculation:
EMA_today = EMA_yesterday + α × (Price_today - EMA_yesterday)
But we add a correction factor that adjusts for the missing history:
Correction = 1 at the start
Correction = Correction × (1-α) after each calculation
We then apply this correction:
True_EMA = Raw_EMA / (1-Correction)
This correction factor starts at 1 (full compensation effect) and gets exponentially smaller with each new price bar. After enough data points, the correction becomes so small (i.e., below 0.0000000001) that we can stop applying it as it is no longer relevant.
Let's see how this works in practice:
For the first price bar:
Raw_EMA = 0
Correction = 1
True_EMA = Price (since 0 ÷ (1-1) is undefined, we use the first price)
For the second price bar:
Raw_EMA = α × (Price_2 - 0) + 0 = α × Price_2
Correction = 1 × (1-α) = (1-α)
True_EMA = α × Price_2 ÷ (1-(1-α)) = Price_2
For the third price bar:
Raw_EMA updates using the standard formula
Correction = (1-α) × (1-α) = (1-α)²
True_EMA = Raw_EMA ÷ (1-(1-α)²)
With each new price, the correction factor shrinks exponentially. After about -log₁₀(1e-10)/log₁₀(1-α) bars, the correction becomes negligible, and our EMA calculation matches what we would get if we had infinite historical data.
This approach provides accurate EMA values from the very first calculation. There's no need to use SMA for warmup or discard early values before output converges - EMA is mathematically correct from first value, ready to party without the awkward warmup phase.
Here is Pine Script 6 implementation of EMA that can take alpha parameter directly (or period if desired), returns valid values from the start, is resilient to dirty input values, uses decaying compensator instead of SMA, and uses the least amount of computational cycles possible.
// Enhanced EMA function with proper initialization and efficient calculation
ema(series float source, simple int period=0, simple float alpha=0)=>
// Input validation - one of alpha or period must be provided
if alpha<=0 and period<=0
runtime.error("Alpha or period must be provided")
// Calculate alpha from period if alpha not directly specified
float a = alpha > 0 ? alpha : 2.0 / math.max(period, 1)
// Initialize variables for EMA calculation
var float ema = na // Stores raw EMA value
var float result = na // Stores final corrected EMA
var float e = 1.0 // Decay compensation factor
var bool warmup = true // Flag for warmup phase
if not na(source)
if na(ema)
// First value case - initialize EMA to zero
// (we'll correct this immediately with the compensation)
ema := 0
result := source
else
// Standard EMA calculation (optimized formula)
ema := a * (source - ema) + ema
if warmup
// During warmup phase, apply decay compensation
e *= (1-a) // Update decay factor
float c = 1.0 / (1.0 - e) // Calculate correction multiplier
result := c * ema // Apply correction
// Stop warmup phase when correction becomes negligible
if e <= 1e-10
warmup := false
else
// After warmup, EMA operates without correction
result := ema
result // Return the properly compensated EMA value
▶️ CONCLUSION
EMA isn't just a "better SMA"—it is a fundamentally different tool, like how a submarine differs from a sailboat – both float, but the similarities end there. EMA responds to inputs differently, weighs historical data differently, and requires different initialization techniques.
By understanding these differences, traders can make more informed decisions about when and how to use EMA in trading strategies. And as EMA is embedded in so many other complex and compound indicators and strategies, if system uses tainted and inferior EMA calculatiomn, it is doing a disservice to all derivative indicators too – like building a skyscraper on a foundation of Jell-O.
The next time you add an EMA to your chart, remember: you're not just looking at a "faster moving average." You're using an INFINITE IMPULSE RESPONSE filter that carries the echo of all previous price actions, properly weighted to help make better trading decisions.
EMA done right might significantly improve the quality of all signals, strategies, and trades that rely on EMA somewhere deep in its algorithmic bowels – proving once again that math skills are indeed useful after high school, no matter what your guidance counselor told you.
Precision LevelsThis open-source Support and Resistance Indicator helps traders plot key price levels where the market may reverse or consolidate. By plotting support and resistance zones based on historical price action, it provides clear visual cues for potential entry and exit points across various timeframes.
Customizable Settings: Adjust visual styles to suit your trading strategy.
Multi-Timeframe Support: View and plot levels from higher timeframes using the monthly and weekly levels.
User-Friendly: Lightweight design with clear plotting for easy integration into any setup.
How It Works:
The indicator plots simple Support and resistance. Zones are labeled monthly, weekly, and daily
Usage:
Apply the indicator to your chart.
Enter a value for each support and resistance level. Drag and Adjust on the chart to your liking.
Use the plotted levels to identify potential reversals, breakouts, or stop-loss placements.
Combine with other tools (e.g., trendlines or oscillators) for confirmation.
Note: This is the open-source version of my previously protected Support and Resistance Indicator. The protected version is flagged and hidden from community and no longer maintained. Feel free to explore and modify the code to fit your needs! For feedback or suggestions, leave a comment below or message me direct.
AQPRO Pattern Map
📝 INTRODUCTION
AQPRO Pattern Map is a comprehensive trading tool designed to automate the detection of 27 most popular candlestick patterns across any financial asset, making it a powerful tool for traders who use strategies, which are based on candlestick patterns.
This indicator not only identifies candlestick patterns but also incorporates multi-timeframe (MTF) analysis , risk management tools like Take-Profit (TP) and Stop-Loss (SL) , and labeled visual cues for effortless chart reading. Below is the complete list of patterns it supports:
📜 Patterns scanned by the indicator:
One-candle patterns:
Hammer;
Shooting Star;
Marubozu (Bullish/Bearish);
Doji.
Two-candle patterns:
Belt Hold (Bullish/Bearish);
Engulfing (Bullish/Bearish);
Harami (Bullish/Bearish);
Harami Cross (Bullish/Bearish);
Kicker (Bullish/Bearish);
Window (Rising/Falling Gap);
Piercing Line / Dark Cloud Cover.
Three-candle patterns:
Outside Up / Down Bar;
Inside Up / Down Bar;
Morning Star / Evening Star;
Three White Soldiers / Three Black Crows;
Advance Block / Descent Block;
Tasuki Gap (Upside/Downside);
Side-by-Side White Lines.
Multi-candle patterns:
Rising One / Falling One;
Rising Two / Falling Two;
Rising Three / Falling Three;
Rising Four / Falling Four;
Rising Five / Falling Five;
Breakaway Two / Three / Four / Five (Bullish/Bearish);
Fakey (Bullish/Bearish).
With this tool, traders can visually and systematically track key candlestick setups across multiple timeframes simultaneously, making it an all-in-one solution for identifying actionable patterns.
🎯 PURPOSE OF USAGE
The primary goal of the "AQPRO Pattern Map" is to equip traders with a highly efficient way of identifying significant candlestick patterns across different timeframes, making the decision-making process stronger in a sense of both quality and quantity of presented information.
Specifically, this indicator addresses the following needs:
Automation of pattern detection.
Nobody likes searching for patterns on the chart "by hand", because it takes too much time and mental energy. With this screener you can forget about this problem: automatic scanning for 27 of the most commonly used patterns will save your tens, if not hundreds of hours of time, so you can focus on what really matters;
Multi-timeframe (MTF) analysis.
This one is one of the most unique features of this indicator, because after conducting product research in library of open-source scripts alike this screener, almost none of reviewed indicators had MTF analysis feature embedded in them. This feature is important for the simplest of reasons: you see candlestick data from other timeframes without jumping from one timeframe to another . Needless to say how much time it will save for traders over the years of trading. See description below to learn more on exact functionality of our MTF analysis;
Risk management automation.
Humans tend to overestimate risk, when matters are about earning money from "financially-dangerous" activities and trading is no exception. To help traders better understand what they risk, we implemented a simple, yet effective way of displaying levels of risk for each pattern. For each new pattern on the chart you will be able see automatic creation of Take-Profit (TP) and Stop-Loss (SL) levels. It involves creation and displaying of lines and labels, representing each level at its exact coordinates. This elevates visual perception of risk for fellow traders and avoid excessive risk in many cases;
Simplicity in data visualization.
Charts, which are cluttered with pointless visual noise, presented as 'additional confirmation analysis', don't foster insights and are not worth a dime . We understand this issue very well and we designed our indicator with the solution to this problem in mind. Every bit of information, that you will see on your chart, will make sense both technically and visually — no more wasting time cleaning mess on your charts.
By addressing the needs, described above, this indicator will be a useful tool for any trader, who employs principles of candlestick pattern analysis, because most important pains of this kind of analysis are efficiently handled by our indicator.
⚙️ SETTINGS OVERVIEW
Customization options of our indicator are quite extensive, because flexibility in such indicator is in the top of most important qualities. Let's review each group of settings deeper:
📊 Patterns: One-Candle
This group allows you to enable or disable specific onep -candle candlestick patterns.
Toggle on/off switch for Hammer, Shooting Star, Marubozu, and Doji .
📊 Patterns: Two-Candle
This group allows you to enable or disable specific two -candle candlestick patterns.
Toggle on/off switch for Belt Hold, Engulfing, Harami & Harami Cross, Kicker, Window, Piercing Line & Dark Cloud Cover .
📊 Patterns: Three-Candle
This group allows you to enable or disable specific three -candle candlestick patterns.
Toggle on/off switch for Morning Star & Evening Star, Three White Soldiers, Three Black Crows, Advance Block & Descent Block, Tasuki Gap, Side-by-Side Gap (Bullish), Squeeze .
📊 Patterns: Multi-Candle
This group allows you to enable or disable specific multi -candle (3 or more candle) candlestick patterns.
Toggle on/off switch for Rising/Falling sequences, Breakaway patterns, and Fakey .
📊 MTF Settings
These settings allow you to use the Multi-Timeframe Screener to display patterns from additional timeframes.
"Use MTF Screener" — toggles the addition of MTF Screener to main dashboard ( described in 'Visual Settings' ). If enabled, adds section of MTF Screener below main dashboard
* List of four timeframes — your personal list to choose your timeframe, which will be used to get data about latest patterns. Default list of timeframes includes timeframes like 15min, 30min 1hr, 4hr .
* The detected patterns from these timeframes will be displayed in the MTF Dashboard on the chart.
🛡️ Risk Settings
As was described above, risk settings in our indicator will control appearance of TP and SL labels and lines, which appear for each new trade. Here you can customize the most essential parameters.
"Show TP/SL" — toggles the visibility of Take-Profit (TP) and Stop-Loss (SL) values for the most recent pattern.
"Risk-to-Reward Ratio (R:R)" — defines your desired risk/reward ratio for the TP and SL calculations. The more this parameter is, the further the TP from entry level will be.
🎨 Visual Settings
In this group of settings you can fine-tune the visual appearance of the indicator to fit your preferences.
IMPORTANT: colour parameters from this group of settings affect ONLY colours in the dashboard.
"Use info dashboard" — if enabled, shows dashboard in the top right corner of the chart, which displays latest pattern's TP and SL alongside with this pattern's trade status: '⏳' - TP or SL have not been reached yet, '✋' - TP or SL have already been reached already, refrain from taking the trade.
"Bullish Pattern" — defines the color for bullish patterns.
"Bearish Pattern" — defines the color for bearish patterns.
"Neutral Pattern" — specify the color for neutral patterns like Doji.
"Frame Width" — adjusts the thickness of frames highlighting detected patterns on the chart.
📈 APPLICATION GUIDE
The way of application of this indicator is pretty straightforward, because trading methodologies based on candlestick patterns were developed decades ago and haven't changed much since then. However, we find it necessary to explain the most essential ways of application in this section.
Let's start with the basics — how you will your chart look when you load the indicator for the first time:
By default we have 5 main visual data "blocks":
Bullish patterns;
Bearish patterns;
Risk visualization;
Main Dashboard;
MTF Screener.
Let's review each of these groups one by one.
BULLISH & BEARISH PATTERNS
Patterns are displayed as up/down labels, which are styled in corresponding to trend colours. Each patterns has its own unique emoji to help traders easily navigate between patterns.
Also by default each pattern has its custom frame, inside of which resides candle (or multiple candles) of the pattern iself. These frames are made with purpose to show each pattern in a very clear way on the chart, because huge number of public scripts usually only show simple label of such patterns and don't highlight the pattern itself on the chart. To remove frames you can set "Frame Width" parameter to 0 in 'Visual Settings' group in the settings.
You can see the examples of frame on the screenshot below:
RISK VISUALIZATION (TP & SL)
Displaying Take-Profits and Stop-Losses in our indicator on the chart works quite simple: for each new trade indicator creates new pairs of lines and labels for TP and SL, while lines & labels from previous trade are erased for aesthetics purposes. Each label shows price coordinates, so that each trader would be able to grap the numbers in seconds.
See the visual showcase of TP & SL visualization on the screenshot below:
Also, whenever TP or SL of the current trade is reached, drawing of both TP and SL stops . When the TP is reached, additional '✅' emoji on the TP price is shown as confirmation of Take-Profit.
However, while TP or SL has not been reached, TP&SL labels and lines will be prolonged until one of them will be reached or new signals will come.
See the visual showcase of TP & SL stopping being visualized & TP on the screenshot below:
MAIN DASHBOARD
Main dashboard is displayed in the top right corner of the chart and it shows the data of latest pattern, that occurred on the current asset and current timeframe: pattern's name, TP, SL and trade status. Depending on bullishness or bearishness of the pattern, dashboard is colour in respective colour.
Also on the right of side TP and SL data block there is a so called trade status. It is basically an indication of wether or not latest pattern's trade is still active or not:
If TP or SL of the pattern have not been reached yet, trade is considered active and is marked with '⏳' emoji;
If TP or SL of the pattern have already been reached, trade is considered inactive and is marked with '✋' emoji.
See the visual showcase of dashboard on the screenshot below:
MTF Screener
MTF Screener is displayed right below the main dashboard and its has distinctive 'MTF Patterns' header row on the top, painted in gray colour to make sure that every traders understand he is looking at.
This screener shows the timeframe and name of patterns from four other timeframes, which trader can customize in the settings to his liking. This will help trader get more insights on global sentiment of other timeframes, which improves trading results overall if applied correctly.
In the future MTF Screener will be expanded to have more data in it, like TP and SL, age of pattern and etc.
See the visual showcase of the MTF Screener on the screenshot below:
Features, explained above, make this indicator quite versatile and suitable for incorporation in any trading strategy, which uses candlestick patterns. They are simple, yet insightful, and traders, which use similar strategies everyday, will truly appreciate the benefits of this indicator when they will set up this indicator for the first time on their chart.
🔔 ALERTS
This indicator employs alerts for an event when new pattern occurs. While creating the alert below 'Condition' field choose 'any alert() function call' .
When this alert is triggered, it will generate this kind of message:
string msg_template = "EXCHANGE:ASSET, TIMEFRAME: BULLISH_OR_BEARISH pattern PATTERN_NAME was found."
string msg_example = "BINANCE:BTCUSDT, 15m: bullish pattern 'Hammer' was found."
📌 NOTES
This indicator is most effective when used in combination with other technical analysis tools such as trendlines, moving averages, support/resistance levels or any other indicator-type tool. We strongly recommend using this indicator as confirmation indicator for your main trading strategy, not as primary source of signals;
If you want to trade directly by these patterns, make sure to use proper risk management techniques of your own and use TP&SL visualization on the chart to always have a clue about your current position;
If you lost track of visual components on the chart, look at the main dashboard to see text summary of data from latest pattern. Also don't forget to look at MTF Screener to have more context about MTF sentiment, because it is increases your understandings of MTF price trend and improves your decision-making process.
🏁 AFTERWORD
AQPRO Pattern Map was built to help traders automate candlestick pattern searching routine, improve chart readability and enhance perception of current potential risks, which may come from trading from a specific pattern. Indicator's main dashboard and MTF screener eliminate the need for constantly checking other timeframe for global sentiment, helping traders save even more time and fostering improved decision making.
This indicator will work in great conjunction with any other trading strategy as confirmation tool for entry decision. Using this indicator as primary source of signals is not recommended due to unstable nature of trading patterns.
ℹ️ If you have questions about this or any other our indicator, please leave it in the comments.
SuperTrend: Silent Shadow 🕶️ SuperTrend: Silent Shadow — Operate in trend. Vanish in noise.
Overview
SuperTrend: Silent Shadow is an enhanced trend-following system designed for traders who demand clarity in volatile markets and silence during indecision.
It combines classic Supertrend logic with a proprietary ShadowTrail engine and an adaptive Silence Protocol to filter noise and highlight only the cleanest signals.
Key Features
✅ Core Supertrend Logic
Built on Average True Range (ATR), this trend engine identifies directional bias with visual clarity. Lines adjust dynamically with price action and flip when meaningful reversals occur.
✅ ShadowTrail: Stepped Counter-Barrier
ShadowTrail doesn’t predict reversals — it reinforces structure.
When price is trending, ShadowTrail forms a stepped ceiling in downtrends and a stepped floor in uptrends. This visual containment zone helps define the edges of price behavior and offers a clear visual anchor for stop-loss placement and trade containment.
✅ Silence Protocol: Adaptive Noise Filtering
During low-volatility zones, the system enters “stealth mode”:
• Trend lines turn white to indicate reduced signal quality
• Fill disappears to reduce distraction
This helps avoid choppy entries and keeps your focus sharp when the market isn’t.
✅ Visual Support & Stop-Loss Utility
When trendlines flatten or pause, they naturally highlight price memory zones. These flat sections often align with:
• Logical stop-loss levels
• Prior support/resistance areas
• Zones of reduced volatility where price recharges or rejects
✅ Custom Styling
Full control over line colors, width, transparency, fill visibility, and silence behavior. Tailor it to your strategy and visual preferences.
How to Use
• Use Supertrend color to determine bias — flips mark momentum shifts
• ShadowTrail mirrors the primary trend as a structural ceiling/floor
• Use flat segments of both lines to identify consolidation zones or place stops
• White lines = low-quality signal → stand by
• Combine with RSI, volume, divergence, or your favorite tools for confirmation
Recommended For:
• Traders seeking clearer trend signals
• Avoiding false entries in sideways or silent markets
• Identifying key support/resistance visually
• Structuring stops around real market containment levels
• Scalping, swing, or position trading with adaptive clarity
Built by Sherlock Macgyver
Forged for precision. Designed for silence.
When the market speaks, you listen.
When it doesn’t — you wait in the shadows.
BK AK-47 Divergence🚨 Introducing BK AK-47 Divergence — Multi-Timeframe Precision Firepower for True Traders 🚨
After months of development, I’m proud to release my fifth weapon in the arsenal — BK AK-47 Divergence.
💥 Why “AK-47”? The Meaning Behind the Name
The AK-47 isn’t just a rifle. It’s the symbol of reliability, versatility, and raw stopping power. It performs in every environment — from the mud to the mountains — just like this indicator cuts through noise on any timeframe, any asset, any condition.
🔸 “AK” honors the same legacy as before — my mentor, A.K., whose discipline and vision forged my trading edge.
🔸 “47” signifies layered precision: 4 = structure, 7 = spiritual completion. Together, it’s the weapon of divine order that adapts, reacts, and strikes with purpose.
🔍 What Is BK AK-47 Divergence?
It’s a next-generation divergence detector — a smart hybrid of MACD, Bollinger Bands, and multi-timeframe divergence logic wrapped in a custom volatility engine and real-time flash alerts.
Designed for snipers in the market — those who only take the highest-probability shots.
⚙️ Core Weapon Systems
✅ MACD + BB Precision Overlay → MACD plotted inside dynamic Bollinger Bands — reveals hidden pressure zones where most indicators fail.
✅ Smart Histogram Scaling → Adaptive amplification based on volatility. No more weak histograms in strong markets.
✅ Full Multi-Timeframe Divergence Detection:
🔻 Current TF Divergence
🕐 Higher TF Divergence
⏱️ Lower TF Divergence
Each plotted with clean visual alerts, color-coded by direction and timeframe. You get instant divergence recognition across dimensions.
✅ Background Flash Alerts → When MACD hits BB extremes, the background lights up in red or green. Eyes instantly lock in on key moments.
✅ Advanced Pivot Lookback Control → New lookback system compares multiple pivot layers, not just the last swing. This gives true structural divergence, not just noise.
✅ Dynamic Fill Zones:
🔴 Oversold
🟢 Overbought
🔵 Neutral
Built to filter false signals and highlight hidden edge.
🛡️ Why This Indicator Changes the Game
🔹 Built for divergence snipers — not lagging MACD watchers.
🔹 Perfect for traders who sync with:
• Elliott Waves
• Fibonacci Time/Price Clusters
• Harmonic Patterns
• Gann Angles or Squares
• Price Action & Trendlines
🔹 Lets you visually map:
• Converging divergences (multi-TF confirmation)
• High-volatility histograms in low-volatility price zones (entry sweet spots)
• Flash-momentum warnings at BB pressure zones
🎯 How to Use BK AK-47 Divergence
🔹 Breakout Confirmation → MACD breaches upper BB with bullish divergence = signal to ride momentum.
🔹 Mean Reversion Reversals → MACD breaks lower BB + bullish div = setup for sniper long.
🔹 Top/Bottom Detection → Bearish divergence + MACD failure at upper BB = early reversal signal.
🔹 TF Sync Strategy → Align current TF with higher or lower divergences for laser-confirmed entries.
🧠 Final Thoughts
This isn’t just a divergence tool. It’s a battlefield reconnaissance system — one that lets you see when, where, and why the next pivot is forming.
🔹 Built in honor of the AK-legacy — reliability, discipline, and firepower.
🔹 Designed to cut through noise, expose structure, and alert you to what really matters.
🔹 Crafted for those who trade with intent, vision, and respect for the craft.
🙏 And most importantly: All glory to Gd — the One who gives wisdom, clarity, and purpose.
Without Him, the markets are chaos. With Him, we move in structure, order, and divine timing.
—
⚡ Stay dangerous. Stay precise. Stay aligned.
🔥 BK AK-47 Divergence — Locked. Loaded. Laser-focused. 🔥
May the markets bend to your discipline.
Gd bless. 🙏
Rocky's Dynamic DikFat Supply & Demand ZonesDynamic Supply & Demand Zones
Overview
The Dynamic Supply & Demand Zones indicator identifies key supply and demand levels on your chart by detecting pivot highs and lows. It draws customizable boxes around these zones, helping traders visualize areas where price may react. With flexible display options and dynamic box behavior, this tool is designed to assist in identifying potential support and resistance levels for various trading strategies.
Key Features
Pivot-Based Zones: Automatically detects supply (resistance) and demand (support) zones using pivot highs and lows on the chart’s timeframe.
Dynamic Box Sizing: Boxes shrink when price enters them, reflecting reduced zone strength, and stop adjusting once price fully crosses through.
Customizable Display: Choose to show current-day boxes, historical boxes, or all boxes, with an option to update past box colors dynamically.
Session-Based Extension: Boxes can extend to the current bar or stop at 4:00 PM of the creation day’s 9:30 AM–4:00 PM trading session (ideal for stock markets).
Color Coding: Borders change color based on price position:
Green for demand zones (price above the box).
Red for supply zones (price below the box).
White for neutral zones (price inside the box).
User-Friendly Inputs: Adjust pivot lookback periods, box visibility, extension behavior, and colors via intuitive input settings.
How It Works
Zone Detection: The indicator uses pivot highs and lows to define supply and demand zones, plotting boxes between these levels.
Box Behavior:
Boxes are created when pivot highs and lows are confirmed, with no overlap with the previous box.
When price enters a box, it shrinks to reflect interaction, stopping once price exits completely.
Boxes can extend to the current bar or end at 4:00 PM of the creation day (or next trading day if created after 4:00 PM or on weekends).
Display Options:
Current Only: Shows boxes created on the current day.
Historical Only: Shows boxes from previous days, with optional color updates.
All Boxes: Shows all boxes, with an option to hide historical box color updates.
Performance: Limits the number of boxes to 200 to ensure smooth performance, removing older boxes as needed.
Inputs
Pivot Look Right/Left: Set the number of bars (default: 2) to confirm pivot highs and lows.
What Boxes to Show: Select Current Only, Historical Only, or All Boxes (default: Current Only).
Boxes On/Off: Toggle box visibility (default: on).
Extend Boxes to Current Bar: Choose whether boxes extend to the current bar or stop at 4:00 PM (default: off, stops at 4:00 PM).
Update Past Box Colors: Enable/disable color updates for historical boxes (default: on).
Demand/Supply/Neutral Box Color: Customize border colors (default: green, red, white).
How to Use
Add the indicator to your chart.
Adjust inputs to match your trading style (e.g., pivot lookback, box extension, colors).
Use the boxes to identify potential support (demand) and resistance (supply) zones:
Green-bordered boxes (price above) may act as support.
Red-bordered boxes (price below) may act as resistance.
White-bordered boxes (price inside) indicate active price interaction.
Combine with other analysis tools (e.g., trendlines, indicators) to confirm trade setups.
Monitor box shrinking to gauge zone strength and watch for breakouts when price fully crosses a box.
Understanding Supply and Demand in Stock Trading
In stock trading, supply and demand are fundamental forces driving price movements. Demand refers to the willingness of buyers to purchase a stock at a given price, often creating support levels where buying interest prevents further price declines. Supply represents the willingness of sellers to offload a stock, forming resistance levels where selling pressure halts price increases. These zones are critical because they highlight areas where significant buying or selling activity has occurred, influencing future price behavior.
The importance of supply and demand lies in their ability to reveal where institutional traders, with large orders, have entered or exited the market. Demand zones, often seen at pivot lows, indicate strong buying interest and potential areas for price reversals or bounces. Supply zones, typically at pivot highs, signal heavy selling and possible reversal points for downward moves. By identifying these zones, traders can anticipate where price is likely to stall, reverse, or break out, enabling better entry and exit decisions. This indicator visualizes these zones as dynamic boxes, making it easier to spot high-probability trading opportunities while emphasizing the core market dynamics of supply and demand.
Feedback
This indicator is designed to help traders visualize supply and demand zones effectively. If you have suggestions for improvements, please share your feedback in the comments!
