EMA-Based Squeeze Dynamics (Gap Momentum & EWMA Projection)EMA-Based Squeeze Dynamics (Gap Momentum & EWMA Projection)
🚨 Main Utility: Early Squeeze Warning
The primary function of this indicator is to warn traders early when the market is approaching a "squeeze"—a tightening condition that often precedes significant moves or regime shifts. By visually highlighting areas of increasing tension, it helps traders anticipate potential volatility and prepare accordingly. This is intended to be a statistically and psychologically grounded replacement of so-called "fib-time-zones," which are overly-deterministic and subjective.
📌 Overview
The EMA-Based Squeeze Dynamics indicator projects future regime shifts (such as golden and death crosses) using exponential moving averages (EMAs). It employs historical interval data and current market conditions to dynamically forecast when the critical EMAs (50-period and 200-period) will reconverge, marking likely trend-change points.
This indicator leverages two core ideas:
Behavioral finance theory: Traders often collectively anticipate popular EMA crossovers, creating a self-fulfilling prophecy (normative social influence), similar to findings from Solomon Asch’s conformity experiments.
Bayesian-like updates: It utilizes historical crossover intervals as a prior, dynamically updating expectations based on evolving market data, ensuring its signals remain objectively grounded in actual market behavior.
⚙️ Technical & Mathematical Explanation
1. EMA Calculations and Regime Definitions
The indicator uses three EMAs:
Fast (9-period): Represents short-term price movement.
Medial (50-period): Indicates medium-term trend direction.
Slow (200-period): Defines long-term market sentiment.
Regime States:
Bullish: 50 EMA is above the 200 EMA.
Bearish: 50 EMA is below the 200 EMA.
A shift between these states triggers visual markers (arrows and labels) directly on the chart.
2. Gap Dynamics and Historical Intervals
At each crossover:
The indicator records the gap (distance) between the 50 and 200 EMAs.
It tracks the historical intervals between past crossovers.
An Exponentially Weighted Moving Average (EWMA) of these intervals is calculated, weighting recent intervals more heavily, dynamically updating expectations.
Important note:
After every regime shift, the projected crossover line resets its calculation. This reset is visually evident as the projection line appears to move further away after each regime change, temporarily "repelled" until the EMAs begin converging again. This ensures projections remain realistic, grounded in actual EMA convergence, and prevents overly optimistic forecasts immediately after a regime shift.
3. Gap Momentum & Adaptive Scaling
The indicator measures how quickly or slowly the gap between EMAs is changing ("gap momentum") and adjusts its forecast accordingly:
If the gap narrows rapidly, a crossover becomes more imminent.
If the gap widens, the next crossover is pushed further into the future.
The "gap factor" dynamically scales the projection based on recent gap momentum, bounded between reasonable limits (0.7–1.3).
4. Squeeze Ratio & Background Color (Visual Cues)
A "squeeze ratio" is computed when market conditions indicate tightening:
In a bullish regime, if the fast EMA is below the medial EMA (price pulling back towards long-term support), the squeeze ratio increases.
In a bearish regime, if the fast EMA rises above the medial EMA (price rallying into long-term resistance), the squeeze ratio increases.
What the Background Colors Mean:
Red Background: Indicates a bullish squeeze—price is compressing downward, hinting a bullish reversal or continuation breakout may occur soon.
Green Background: Indicates a bearish squeeze—price is compressing upward, suggesting a bearish reversal or continuation breakout could soon follow.
Opacity Explanation:
The transparency (opacity) of the background indicates the intensity of the squeeze:
High Opacity (solid color): Strong squeeze, high likelihood of imminent volatility or regime shift.
Low Opacity (faint color): Mild squeeze, signaling early stages of tightening.
Thus, more vivid colors serve as urgent visual warnings that a squeeze is rapidly intensifying.
5. Projected Next Crossover and Pseudo Crossover Mechanism
The indicator calculates an estimated future bar when a crossover (and thus, regime shift) is expected to occur. This calculation incorporates:
Historical EWMA interval.
Current squeeze intensity.
Gap momentum.
A dynamic penalty based on divergence from baseline conditions.
The "Pseudo Crossover" Explained:
A key adaptive feature is the pseudo crossover mechanism. If price action significantly deviates from the projected crossover (for example, if price stays beyond the projected line longer than expected), the indicator acknowledges the projection was incorrect and triggers a "pseudo crossover" event. Essentially, this acts as a reset, updating historical intervals with a weighted adjustment to recalibrate future predictions. In other words, if the indicator’s initial forecast proves inaccurate, it recognizes this quickly, resets itself, and tries again—ensuring it remains responsive and adaptive to actual market conditions.
🧠 Behavioral Theory: Normative Social Influence
This indicator is rooted in behavioral finance theory, specifically leveraging normative social influence (conformity). Traders commonly watch EMA signals (especially the 50 and 200 EMA crossovers). When traders collectively anticipate these signals, they begin trading ahead of actual crossovers, effectively creating self-fulfilling prophecies—similar to Solomon Asch’s famous conformity experiments, where individuals adopted group behaviors even against direct evidence.
This behavior means genuine regime shifts (actual EMA crossovers) rarely occur until EMAs visibly reconverge due to widespread anticipatory trading activity. The indicator quantifies these dynamics by objectively measuring EMA convergence and updating projections accordingly.
📊 How to Use This Indicator
Monitor the background color and opacity as primary visual cues.
A strongly colored background (solid red/green) is an early alert that a squeeze is intensifying—prepare for potential volatility or a regime shift.
Projected crossover lines give a dynamic target bar to watch for trend reversals or confirmations.
After each regime shift, expect a reset of the projection line. The line may seem initially repelled from price action, but it will recalibrate as EMAs converge again.
Trust the pseudo crossover mechanism to automatically recalibrate the indicator if its original projection misses.
🎯 Why Choose This Indicator?
Early Warning: Visual squeeze intensity helps anticipate market breakouts.
Behaviorally Grounded: Leverages real trader psychology (conformity and anticipation).
Objective & Adaptive: Uses real-time, data-driven updates rather than static levels or subjective analysis.
Easy to Interpret: Clear visual signals (arrows, labels, colors) simplify trading decisions.
Self-correcting (Pseudo Crossovers): Quickly adjusts when initial predictions miss, maintaining accuracy over time.
Summary:
The EMA-Based Squeeze Dynamics Indicator combines behavioral insights, dynamic Bayesian-like updates, intuitive visual cues, and a self-correcting pseudo crossover feature to offer traders a reliable early warning system for market squeezes and impending regime shifts. It transparently recalibrates after each regime shift and automatically resets whenever projections prove inaccurate—ensuring you always have an adaptive, realistic forecast.
Whether you're a discretionary trader or algorithmic strategist, this indicator provides a powerful tool to navigate market volatility effectively.
Happy Trading! 📈✨
Hareketli Ortalamalar
Half Causal EstimatorOverview
The Half Causal Estimator is a specialized filtering method that provides responsive averages of market variables (volume, true range, or price change) with significantly reduced time delay compared to traditional moving averages. It employs a hybrid approach that leverages both historical data and time-of-day patterns to create a timely representation of market activity while maintaining smooth output.
Core Concept
Traditional moving averages suffer from time lag, which can delay signals and reduce their effectiveness for real-time decision making. The Half Causal Estimator addresses this limitation by using a non-causal filtering method that incorporates recent historical data (the causal component) alongside expected future behavior based on time-of-day patterns (the non-causal component).
This dual approach allows the filter to respond more quickly to changing market conditions while maintaining smoothness. The name "Half Causal" refers to this hybrid methodology—half of the data window comes from actual historical observations, while the other half is derived from time-of-day patterns observed over multiple days. By incorporating these "future" values from past patterns, the estimator can reduce the inherent lag present in traditional moving averages.
How It Works
The indicator operates through several coordinated steps. First, it stores and organizes market data by specific times of day (minutes/hours). Then it builds a profile of typical behavior for each time period. For calculations, it creates a filtering window where half consists of recent actual data and half consists of expected future values based on historical time-of-day patterns. Finally, it applies a kernel-based smoothing function to weight the values in this composite window.
This approach is particularly effective because market variables like volume, true range, and price changes tend to follow recognizable intraday patterns (they are positive values without DC components). By leveraging these patterns, the indicator doesn't try to predict future values in the traditional sense, but rather incorporates the average historical behavior at those future times into the current estimate.
The benefit of using this "average future data" approach is that it counteracts the lag inherent in traditional moving averages. In a standard moving average, recent price action is underweighted because older data points hold equal influence. By incorporating time-of-day averages for future periods, the Half Causal Estimator essentially shifts the center of the filter window closer to the current bar, resulting in more timely outputs while maintaining smoothing benefits.
Understanding Kernel Smoothing
At the heart of the Half Causal Estimator is kernel smoothing, a statistical technique that creates weighted averages where points closer to the center receive higher weights. This approach offers several advantages over simple moving averages. Unlike simple moving averages that weight all points equally, kernel smoothing applies a mathematically defined weight distribution. The weighting function helps minimize the impact of outliers and random fluctuations. Additionally, by adjusting the kernel width parameter, users can fine-tune the balance between responsiveness and smoothness.
The indicator supports three kernel types. The Gaussian kernel uses a bell-shaped distribution that weights central points heavily while still considering distant points. The Epanechnikov kernel employs a parabolic function that provides efficient noise reduction with a finite support range. The Triangular kernel applies a linear weighting that decreases uniformly from center to edges. These kernel functions provide the mathematical foundation for how the filter processes the combined window of past and "future" data points.
Applicable Data Sources
The indicator can be applied to three different data sources: volume (the trading volume of the security), true range (expressed as a percentage, measuring volatility), and change (the absolute percentage change from one closing price to the next).
Each of these variables shares the characteristic of being consistently positive and exhibiting cyclical intraday patterns, making them ideal candidates for this filtering approach.
Practical Applications
The Half Causal Estimator excels in scenarios where timely information is crucial. It helps in identifying volume climaxes or diminishing volume trends earlier than conventional indicators. It can detect changes in volatility patterns with reduced lag. The indicator is also useful for recognizing shifts in price momentum before they become obvious in price action, and providing smoother data for algorithmic trading systems that require reduced noise without sacrificing timeliness.
When volatility or volume spikes occur, conventional moving averages typically lag behind, potentially causing missed opportunities or delayed responses. The Half Causal Estimator produces signals that align more closely with actual market turns.
Technical Implementation
The implementation of the Half Causal Estimator involves several technical components working together. Data collection and organization is the first step—the indicator maintains a data structure that organizes market data by specific times of day. This creates a historical record of how volume, true range, or price change typically behaves at each minute/hour of the trading day.
For each calculation, the indicator constructs a composite window consisting of recent actual data points from the current session (the causal half) and historical averages for upcoming time periods from previous sessions (the non-causal half). The selected kernel function is then applied to this composite window, creating a weighted average where points closer to the center receive higher weights according to the mathematical properties of the chosen kernel. Finally, the kernel weights are normalized to ensure the output maintains proper scaling regardless of the kernel type or width parameter.
This framework enables the indicator to leverage the predictable time-of-day components in market data without trying to predict specific future values. Instead, it uses average historical patterns to reduce lag while maintaining the statistical benefits of smoothing techniques.
Configuration Options
The indicator provides several customization options. The data period setting determines the number of days of observations to store (0 uses all available data). Filter length controls the number of historical data points for the filter (total window size is length × 2 - 1). Filter width adjusts the width of the kernel function. Users can also select between Gaussian, Epanechnikov, and Triangular kernel functions, and customize visual settings such as colors and line width.
These parameters allow for fine-tuning the balance between responsiveness and smoothness based on individual trading preferences and the specific characteristics of the traded instrument.
Limitations
The indicator requires minute-based intraday timeframes, securities with volume data (when using volume as the source), and sufficient historical data to establish time-of-day patterns.
Conclusion
The Half Causal Estimator represents an innovative approach to technical analysis that addresses one of the fundamental limitations of traditional indicators: time lag. By incorporating time-of-day patterns into its calculations, it provides a more timely representation of market variables while maintaining the noise-reduction benefits of smoothing. This makes it a valuable tool for traders who need to make decisions based on real-time information about volume, volatility, or price changes.
ATLAS Reversion Bands v2 [EMA % Spread]🧠 About the ATLAS Reversion Bands v2
I created this indicator to answer a simple question:
"When is price extended too far from trend, and likely to revert?"
The ATLAS Reversion Bands measure the percentage spread between a fast and slow EMA (default 25/200) and track how far that spread moves from its historical average using z-score and standard deviation bands—essentially building a Bollinger Band system on top of EMA distance.
Instead of relying on traditional oscillators like RSI or MACD, this tool is purely math-driven and tailored for spotting overextensions across any asset.
🔍 What It Does
Tracks the normalized spread between EMA 25 and EMA 200
Highlights statistically rare zones using ±2 and ±3 standard deviation bands
Plots BUY/SELL triangle markers only on first entry into extreme zones
Helps identify mean reversion opportunities (deep pullbacks or FOMO tops)
📈 How to Use It
Wait for the spread to hit or exceed ±2.5 or ±3 standard deviations
Look for confirmation via price structure, candles, or volume
Best used on spot or perp markets with healthy liquidity
Ideal for swing trading or narrative-based rotational setups
🕐 Recommended Timeframes
1H, 4H, and 1D are optimal
Use MTF mode to apply daily logic on lower timeframes (e.g., see 1D exhaustion while trading 4H)
Works across:
✅ BTC, ETH, Majors
✅ Meme coins (better on 1H/4H)
✅ Market indexes (TOTAL2, BTC.D, etc.)
📌 Pro Tips
Raise the Z-score alert threshold for stricter signals (e.g., 3.0 for only the wildest extensions)
Use with other confluence tools (like S/R, candles, or RSI)
Not designed for chasing trends — this is a fade-the-hype, buy-the-blood kind of tool
Multi-Timeframe Trading SystemOverview
The Multi-Timeframe Trading System is an advanced technical analysis indicator designed to identify high-probability trading opportunities by combining signals from multiple timeframes and trading strategies. This system analyzes market context, identifies optimal setups, and confirms entries with lower timeframe precision, significantly increasing signal reliability.
Key Features
Triple Timeframe Analysis: Combines high, medium, and low timeframe data for comprehensive market analysis
Three Trading Strategies in One: Incorporates trend-following, mean-reversion, and breakout strategies
Adaptive to Market Conditions: Automatically identifies the current market context (trending or ranging) and applies the appropriate strategy
Signal Strength Evaluation: Rates buy/sell signals from weak to strong based on indicator confluence
Visual Alerts: Clear buy/sell signals with on-chart markers and signal labels
Customizable Parameters: Fully adjustable settings for all indicators and timeframes
Technical Indicators Included
-Moving Averages (EMA 50, EMA 200)
-Ichimoku Cloud components
-ADX for trend strength
-RSI for momentum and oversold/overbought conditions
-Stochastic oscillator for entry timing
-MACD for trend confirmation
-Bollinger Bands for volatility and price channels
-ATR for measuring market volatility
Trading Strategies
1. Trend-Following Strategy
Identifies the primary trend direction on higher timeframes
Locates optimal pullback entry points on medium timeframes
Confirms entries with precision using lower timeframe momentum signals
2. Mean-Reversion Strategy
Activates during ranging market conditions
Identifies oversold and overbought conditions using Bollinger Bands and RSI
Confirms reversals with Stochastic crossovers
3. Breakout Strategy
Detects price consolidation periods through Bollinger Band width
Identifies volatility expansion and price breakouts
Confirms breakout direction with momentum indicators
Ideal For
Swing traders looking for high-probability setups
Day traders seeking to align with the larger trend
Traders who want systematic confirmation across multiple timeframes
Those looking to adapt their trading approach to changing market conditions
How To Use
Apply the indicator to your chart and customize the timeframe settings to match your trading style
-Observe the market context information (uptrend, downtrend, or ranging)
-Wait for a setup to form on the medium timeframe
-Enter when the low timeframe confirms the signal
-Use the signal strength rating to prioritize the highest probability trades
The Multi-Timeframe Trading System eliminates the guesswork from your trading by providing clear, objective signals based on professional-grade multi-timeframe analysis techniques.
Multi-Timeframe Trend Analysis [BigBeluga]Multi-Timeframe Trend Analysis
A powerful trend-following dashboard designed to help traders monitor and compare trend direction across multiple higher timeframes. By analyzing EMA conditions from five customizable timeframes, this tool gives a clear visual breakdown of short- to long-term trend alignment.
🔵Key Features:
Multi-Timeframe EMA Dashboard:
➣ Displays a table in the top-right corner showing trend direction across 5 user-defined timeframes.
➣ Each row shows whether ema is rising or falling its corresponding EMA for that timeframe.
➣ Green arrows (🢁) indicate uptrends, purple arrows (🢃) signal downtrends.
Custom Timeframe Selection:
➣ Traders can input any 5 timeframes (e.g., 1h, 2h, 3h, etc.) with individual EMA lengths for flexible trend mapping.
➣ The tool auto-adjusts to match and align external timeframe EMAs to the current chart for seamless overlay.
Dynamic Chart Arrows:
➣ On-chart arrows mark when EMA rising or falling EMAs from the current chart timeframe.
➣ Each EMA arrows has a unique transparency level—shorter EMA arrows are more transparent, longer EMA arrows are more vivid. (Hover Mouse over the arrow to see which EMAs it is)
Gradient EMA Plotting:
➣ All five EMAs are plotted with gradually increasing opacity.
➣ Gradient fills between EMAs enhance visual structure, making it easier to track convergence/divergence.
🔵Usage:
Trend Confirmation: Use the dashboard to confirm multi-timeframe trend alignment before entering trades.
Entry Filtering: Avoid countertrend trades by spotting when higher timeframes disagree with the current one.
Momentum Insight: Track the transition of arrows from lighter to stronger opacity to visualize trend shifts over time.
Scalping or Swinging: Customize timeframes depending on your strategy—from intraday scalps to longer-term swings.
Multi-Timeframe Trend Analysis is the ultimate visual companion for traders who want clarity on how price behaves across multiple time horizons. With its smart EMA mapping and dashboard feedback, it keeps you aligned with dominant trend directions and transition zones at all times.
RSI + SMA Strategy (Second Touch Confirmation + Volume Filter)RSI + SMA Strategy (Second Touch Confirmation + Volume Filter)
👉 Optimized for the 3-minute timeframe
This indicator combines the power of the RSI (Relative Strength Index) and its SMA (Simple Moving Average) to generate highly reliable BUY and SELL signals. The strategy is designed to confirm signals only on the second consecutive touch of the overbought (70) and oversold (30) thresholds, reducing false signals caused by sudden market movements. Additionally, it includes a dynamic volume filter, ensuring that signals are generated only during periods of high liquidity.
Key Features
Second Touch RSI:
BUY and SELL signals are generated only after the RSI reaches the overbought/oversold threshold for the second consecutive time, improving accuracy.
Volume Filter:
Signals are confirmed only if the current volume exceeds the 20-period moving average multiplied by a configurable value (volume_multiplier), filtering out low-liquidity moments.
Optimized for Short Timeframes:
Perfect for the 3-minute timeframe, ideal for scalping and intraday trading strategies.
Customizable Parameters:
Adjustable settings for RSI, SMA, overbought/oversold thresholds, and volume filter, making it adaptable to various markets and conditions.
How to Use It
BUY Signal: When RSI touches the oversold threshold (30) for the second consecutive time and crosses above its SMA, with volume higher than average.
SELL Signal: When RSI touches the overbought threshold (70) for the second consecutive time and crosses below its SMA, with volume higher than average.
Upcoming Developments
📢 We will soon release our private strategy!
This strategy will be based on advanced logic and optimized to achieve even more consistent results in volatile markets like cryptocurrencies. Stay tuned for more details!
Disclaimer
This indicator is designed to support decision-making in trading. We recommend testing it on a demo account before using it in live trading. Remember that trading involves risks and does not guarantee profits.
Pullback Entry Zone FinderPullback Entry Zone Finder
Overview:
This indicator is designed to help traders identify potential buying opportunities during short-term pullbacks, particularly when faster-moving averages show signs of converging back towards slower ones. It visually flags potential zones where price might find support and resume its upward movement, based on moving average dynamics and price proximity.
How It Works:
The indicator utilizes four customizable moving averages (Trigger, Short-term, Intermediate, and Long-term) and Average True Range (ATR) to pinpoint specific conditions:
Pullback Detection: It identifies when the fast 'Trigger MA' is below the 'Short-term MA', indicating a potential short-term pullback or consolidation phase.
MA Convergence: Crucially, it looks for signs that the pullback might be weakening by detecting when the gap between the Short-term MA and the Trigger MA is narrowing (maConverging). This suggests the faster average is starting to catch up, potentially preceding a move back up.
Base Buy Zone (Orange Diamond): This signal appears when both the Pullback and Convergence conditions are met simultaneously. It indicates the general area where conditions are becoming favourable for a potential entry.
Refined Entry Zones:
Prime Entry Zone (Green Diamond): This appears within a Base Buy Zone if the bar's low comes within a specified percentage (Max Distance %) of the Short-term MA. It suggests price has pulled back close to the dynamic support of the Short MA.
ATR Entry Zone (Purple Diamond): This appears within a Base Buy Zone if the bar's low comes within the specified percentage (Max Distance %) of an ATR-based target level. This target level (Buy ATR Target Level, plotted as a purple line when active) is calculated by adding a multiple (ATR Multiplier %) of the ATR to the Short-term MA, providing a volatility-adjusted potential entry area.
Visual Elements:
Moving Averages: Four lines representing the Trigger, Short-term, Intermediate, and Long-term MAs (colors and opacity are customizable). Use the Intermediate and Long-term MAs to gauge the broader market trend.
Orange Diamond (Below Bar): Indicates a 'Base Buy Zone' where a pullback and MA convergence are detected.
Green Diamond (Below Bar): Indicates a 'Prime Entry Zone' where price is close to the Short-term MA during a Base Buy Zone.
Purple Diamond (Below Bar): Indicates an 'ATR Entry Zone' where price is close to the ATR-based target level during a Base Buy Zone.
Purple Line: Plots the calculated 'Buy ATR Target Level' only when the Base Buy Zone condition is active.
Input Parameters:
Moving Averages: Customize the Length and Type (EMA, SMA, WMA, VWMA) for all four moving averages.
ATR Settings: Adjust the ATR Length, the ATR Multiplier % (for calculating the target level), and the Max Distance % (for triggering the Prime and ATR Entry Zones).
Visualization: Set the colors for the four Moving Average lines.
How to Use:
Look for the Orange Diamond as the initial signal that pullback/convergence conditions are met.
The Green and Purple Diamonds suggest price has reached potentially more optimal entry levels within that zone, based on proximity to the Short MA or the ATR target, respectively.
Always consider the signals within the context of the broader trend, indicated by the Intermediate and Long-term MAs. This indicator is generally more effective when used to find entries during pullbacks within an established uptrend (e.g., Intermediate MA > Long MA).
Combine these signals with other forms of analysis, such as chart patterns, support/resistance levels, volume analysis, or other indicators for confirmation.
Disclaimer:
You should always use proper risk management techniques and conduct your own analysis before making any trading decisions. This indicator, or any other, will be of no use if you don't have good risk management.
RSI Price LadderFX:XAUUSD
Overview
RSI Price Ladder is an indicator that visualizes RSI levels mapped directly to price levels across multiple timeframes.
It helps traders see where the RSI will reach certain threshold values (like 30, 50, 70) in terms of price, without calculating manually.
It dynamically draws ladder lines (price levels) based on user-defined RSI targets, allowing clear visualization of RSI movements versus price action.
Purpose for Traders
Forecast Price Zones: Understand at which price levels RSI would hit oversold/overbought zones.
Multi-Timeframe Analysis: Monitor RSI-price relationships across multiple timeframes simultaneously (e.g., M5, M15, H1, H4).
Timing Entries and Exits: Plan precise entries or exits based on expected RSI behavior without switching between charts.
Visual Clarity: Simplifies multi-timeframe RSI tracking by ladder-style price mapping directly on the current chart.
Configuration
RSI length: The period for RSI calculation (default 14).
RSI Target Levels (1–7): Define up to 7 custom RSI levels (e.g., 20, 30, 40, 50, 60, 70, 80).
Spacing Between Ladders: Horizontal spacing between different timeframe ladders on the chart.
Pointer Colors: Customize colors for current RSI, EMA(9) of RSI, and WMA(45) of RSI.
Show TF1–TF4: Toggle visibility of up to four different timeframe ladders.
Interval TF1–TF4: Select timeframes to draw ladders (choices from 1m to 1W including 3D).
Ladder Colors: Customize the ladder color for each timeframe separately.
How to read data
See explaination:
How to use
The primary goal of this indicator is to help traders easily and accurately see price levels corresponding to specific RSI values .
Identifying Multi-Timeframe Support and Resistance
According to RSI behavior:
- In an uptrend, RSI tends to find support around 40, previous RSI bottoms, and the WMA45.
- In a downtrend, RSI tends to face resistance around 60, previous RSI tops, and the WMA45.
Using the RSI Price Ladder, you can accurately pinpoint the exact price levels corresponding to these RSI support and resistance zones.
Defining Entry Zones, Stop Loss, and Take-Profit Areas Based on RSI
For example:
By observing RSI behavior, I noticed a downward trend forming.
On both M15 and H1 timeframes, RSI resistance levels align with the price zone around 3043–3054.
Thus, I can plan a sell trade in this entry zone:
- Stop loss: If RSI breaks above the resistance level, which also corresponds to a price resistance.
- Take-profits at two areas:
RSI support on M5 at RSI 30, corresponding to price 3007.
RSI support on M15 at RSI 30, corresponding to price 2988.
You see, with the ladder, we can directly visualize the price levels corresponding to RSI points on the chart, making decision-making more intuitive.
Result:
The price successfully hit TP1 and TP2.
Visualizing Buying and Selling Strength Across Timeframes
The indicator helps track the correlation of buying and selling strength across different timeframes at the same time. For instance: when selling pressure increases, higher timeframe RSI will typically be higher than lower timeframe RSI. Visualizing this makes it easier to observe and connect price movements across multiple timeframes quickly and clearly.
Visualizing When Combining with Other Methods
In this example:
- RSI shows support around 27.
- Instantly, on the price chart, I notice that the RSI 27 level aligns with the EMA200, a major dynamic price support.
Thus, a long setup can be considered:
- Entry: Near this confluence zone.
- Stop loss: Below the EMA200 or if RSI drops to 20.
Summary
RSI Price Ladder gives traders a powerful visual tool to link RSI behavior to real price levels across multiple timeframes, enhancing strategic entry/exit planning without needing to flip charts.
- Save time spotting RSI targets.
- Stay organized across multiple timeframes.
- Customize the entire ladder experience from colors to intervals.
Deadzone Pro @DaviddTechDeadzone Pro by @DaviddTech – Adaptive Multi-Strategy NNFX Trading System
Deadzone Pro by @DaviddTech is a meticulously engineered trading indicator that strictly adheres to the No-Nonsense Forex (NNFX) methodology. It integrates adaptive trend detection, dual confirmation indicators, advanced volatility filtering, and dynamic risk management into one powerful, visually intuitive system. Ideal for traders seeking precision and clarity, this indicator consistently delivers high-probability trade setups across all market conditions.
🔥 Key Features:
The Setup:
Adaptive Hull Moving Average Baseline: Clearly identifies trend direction using an advanced, gradient-colored Hull MA that intensifies based on trend strength, providing immediate visual clarity.
Dual Confirmation Indicators: Combines Waddah Attar Explosion (momentum detector) and Bull/Bear Power (strength gauge) for robust validation, significantly reducing false entries.
Volatility Filter (ADX): Ensures entries are only made during strong trending markets, filtering out weak, range-bound scenarios for enhanced trade accuracy.
Dynamic Trailing Stop Loss: Implements a SuperTrend-based trailing stop using adaptive ATR calculations, managing risk effectively while optimizing exits.
Dashboard:
💎 Gradient Visualization & User Interface:
Dynamic gradient colors enhance readability, clearly indicating bullish/bearish strength.
Comprehensive dashboard summarizes component statuses, real-time market sentiment, and entry conditions at a glance.
Distinct and clear buy/sell entry and exit signals, with adaptive stop-loss levels visually plotted.
Candlestick coloring based on momentum signals (Waddah Attar) for intuitive market reading.
📈 How to Interpret Signals:
Bullish Signal: Enter when Hull MA baseline trends upward, both confirmation indicators align bullish, ADX indicates strong trend (>25), and price breaks above the previous trailing stop.
Bearish Signal: Enter short or exit long when Hull MA baseline trends downward, confirmations indicate bearish momentum, ADX confirms trend strength, and price breaks below previous trailing stop.
📊 Recommended Usage:
Timeframes: Ideal on 1H, 4H, and Daily charts for swing trading; effective on shorter (5M, 15M) charts for day trading.
Markets: Compatible with Forex, Crypto, Indices, Stocks, and Commodities.
The Entry & Exit:
🎯 Trading Styles:
Choose from three distinct trading modes:
Conservative: Requires full alignment of all indicators for maximum accuracy.
Balanced (Default): Optimized balance between signal frequency and reliability.
Aggressive: Fewer confirmations needed for more frequent trading signals.
📝 Credits & Originality:
Deadzone Pro incorporates advanced concepts inspired by:
Hull Moving Average by @Julien_Eche
Waddah Attar Explosion by @LazyBear
Bull Bear Power by @Pinecoders
ADX methodology by @BeikabuOyaji
This system has been significantly refactored and enhanced by @DaviddTech to maximize synergy, clarity, and usability, standing apart distinctly from its original components.
Deadzone Pro exemplifies precision and discipline, aligning fully with NNFX principles to provide traders with a comprehensive yet intuitive trading advantage.
Falcon SignalsThis script is a TradingView Pine Script for a trading strategy called "Falcon Signals." It combines multiple technical indicators and strategies to generate buy and sell signals. Here’s a breakdown of what the script does:
1. Supertrend Indicator:
The script calculates the Supertrend indicator using the Average True Range (ATR) and a specified multiplier (factor). The Supertrend is used to define the trend direction, with a green line for an uptrend and a red line for a downtrend.
2. EMA (Exponential Moving Average):
Two EMAs are used: a fast EMA (9-period) and a slow EMA (21-period). The script checks for crossovers of the fast EMA above or below the slow EMA as a basis for buying and selling signals.
3. RSI (Relative Strength Index):
The RSI (14-period) is used to measure the momentum of the price. A buy signal is generated when the RSI is less than 70, while a sell signal is generated when it’s greater than 30.
4. Take Profit (TP) and Stop Loss (SL):
The script allows users to set custom percentages for take profit and stop loss. The take profit is set at a certain percentage above the entry price for buy signals, and the stop loss is set at a percentage below the entry price, and vice versa for sell signals.
5. Trailing Stop:
A trailing stop can be enabled, which dynamically adjusts the stop loss level as the price moves in the favorable direction. If the price moves against the position by a certain trailing percentage, the position will be closed.
6. Engulfing Patterns:
The script checks for bullish and bearish engulfing candlestick patterns, indicating potential reversals. A bullish engulfing pattern is marked with a teal label ("🔄 Reversal Up"), and a bearish engulfing pattern is marked with a fuchsia label ("🔄 Reversal Down").
7. Plotting:
The script plots various indicators and signals:
Entry line: Shows where the buy or sell signal is triggered.
Take profit and stop loss levels are plotted as lines.
EMA and Supertrend lines are plotted on the chart.
Trailing stop line, if enabled, is also plotted.
8. Buy and Sell Labels:
The script places labels on the chart when buy or sell signals are triggered, indicating the price at which the order should be placed.
9. Exit Line:
The script plots an exit line when the trailing stop is hit, signaling when a position should be closed.
10. Alerts:
Alerts are set for both buy and sell signals, notifying the trader when to act based on the strategy's conditions.
This strategy combines trend-following (Supertrend), momentum (RSI), and price action patterns (EMA crossovers and engulfing candlestick patterns) to generate trade signals. It also offers the flexibility of take profit, stop loss, and trailing stop features.
Multi-Symbol EMA Status Table🔍 Multi-Symbol EMA Trend Scanner Table
This script displays a clean, customizable table showing whether the price of up to 16 different assets is above or below a user-defined EMA, on a per-symbol and per-timeframe basis.
✅ Supports up to 16 symbols, each with:
Custom exchange + ticker (e.g., BINANCE:BTCUSDT.P, PEPPERSTONE:EURUSD)
Custom timeframe (e.g., 15, 60, 240, D, W)
Custom EMA length (e.g., 50, 100, 200)
🧩 Fully customizable visuals:
Table position (top, middle, bottom + left, center, right)
Text size and text color
Background color for "above" and "below" EMA
Optional ✅❌ emojis
📊 The table updates live on your main chart — no switching required!
💡 Great for:
Monitoring trend direction across multiple markets
Spotting trend alignment (e.g., price above 200 EMA on 4H + 1D)
Multi-asset swing trading or scalping strategies
📘 How to Use:
Open a chart and add the indicator from your scripts.
In the settings panel:
Enter any symbol (with exchange prefix, like BINANCE:BTCUSDT.P or OANDA:EURUSD)
Set a timeframe (e.g., "15" for 15min, "60" for 1h, "D" for daily)
Choose your EMA length (e.g., 200)
Repeat for as many symbols as you need (up to 16).
Customize table visuals:
Position on the screen
Font size and color
Enable/disable emojis ✅❌
Watch the table update live!
🧠 Optional Tips:
Use different colors or groupings to track asset classes (crypto, forex, stocks).
Combine it with your favorite entry/exit signals for confirmation.
Try setting all symbols to the same EMA (e.g., 200) but with different timeframes to monitor multi-timeframe alignment.
Ultimate MA & PSAR [TARUN]Overview
This indicator combines a customizable Moving Average (MA) and Parabolic SAR (PSAR) to generate precise long and short trade signals. A dashboard displays real-time trade conditions, including signal direction, entry price, stop loss, and PnL tracking.
Key Features
✅ Customizable MA Type & Period – Choose between SMA or EMA with adjustable length.
✅ Adaptive PSAR Settings – Modify start, increment, and max step values to fine-tune stop levels.
✅ Trade Signal Logic – Identifies potential buy (long) and sell (short) opportunities based on:
Price action relative to MA
MA trend direction (rising or falling)
PSAR confirmation
✅ Dynamic Stop Loss Calculation – Uses lowest low/highest high over a specified period for stop loss placement.
✅ Trade State & Reversal Handling – Manages active trades, pending signals, and stop loss exits dynamically.
✅ PnL & Dashboard Table – Displays real-time signal status, entry price, stop loss, and profit/loss (PnL) in an easy-to-read format.
How It Works
1.Buy (Long) Condition:
MA is rising
Price is above the MA
PSAR is below price
2.Sell (Short) Condition:
MA is falling
Price is below the MA
PSAR is above price
3.Stop Loss Handling:
For long trades → stop loss is set at the lowest low of the last X candles
For short trades → stop loss is set at the highest high of the last X candles
4.Trade Execution & PnL Calculation:
If a valid long/short setup is detected, a pending signal is placed.
On the next bullish (for long) or bearish (for short) candle, the trade is confirmed.
Real-time PnL updates help track trade performance.
Customization Options
🔹 Moving Average: SMA or EMA, adjustable period
🔹 PSAR Settings: Start, Increment, Maximum step values
🔹 Stop Loss Lookback: Choose how many candles to consider for stop loss placement
🔹 Dashboard Positioning: Select preferred display location (top/bottom, left/right)
🔹 Trade Signal Selection: Enable/Disable Long and Short signals individually
How to Use
Add the indicator to your chart.
Customize the MA & PSAR settings according to your trading strategy.
Follow the dashboard signals for trade setups.
Use stop loss levels to manage risk effectively.
Disclaimer
⚠️ This indicator is for educational purposes only and does not constitute financial advice. Always perform proper risk management and backtesting before using it in live trading.
Blood IndicatorBlood Indicator
Weekly (FRED:TB3MS / FRED:BAMLH0A0HYM2) plotted against the 100 WK MA. If red be ready for a sell off. Use Confluence in price action to confirm trades.
SEMA JMA | QuantEdgeB
📈 Introducing SEMA JMA by QuantEdgeB
🛠️ Overview
SEMA JMA is a precision-engineered, dual-signal trend indicator that blends Jurik Moving Average (JMA) logic with Double Exponential Moving Average (DEMA) smoothing and normalized statistical filters.
This advanced indicator is built for high-quality trend detection, reducing false signals by confirming momentum through both price-based SD bands and normalized JMA logic. The result is a powerful, noise-filtered tool ideal for directional trading in volatile and ranging environments.
SEMA JMA offers adaptive volatility bands, backtest-ready analytics, and dynamic signal labeling, making it a favorite for traders demanding speed, precision, and strategic clarity.
✨ Key Features
🔹 Hybrid JMA + DEMA Core
Combines the ultra-smooth JMA with lag-reducing DEMA for exceptional trend clarity.
🔹 Volatility-Based SD Band Filtering
Uses rolling standard deviation on JMA for adaptive long/short bands that respond to market dynamics.
🔹 Normalized Price Filter Confirmation
A second JMA stream is normalized against price and filtered via SD for added trend confirmation and false signal suppression.
🔹 Backtest Integration & Equity Curve Plotting
Built-in compatibility with QuantEdgeB/BacktestingIndV2, delivering historical metrics, equity visualization, and strategic evaluation.
🔹 Fully Customizable UI
Includes label toggles, signal overlays, visual themes, and backtest table position selection.
📊 How It Works
1️⃣ JMA-DEMA Hybrid Trend Engine
The foundation of SEMA JMA lies in a custom-built JMA engine, enhanced by a DEMA smoothing layer to:
• Minimize lag without losing trend integrity.
• Maintain responsiveness in noisy or low-volume environments.
• Create a central trend structure used by both raw price and normalized filters.
2️⃣ Standard Deviation Band Filtering
SEMA JMA applies a rolling SD filter over the JMA signal. This creates adaptive upper and lower bands:
• Long Signal = Price > Upper Band
• Short Signal = Price < Lower Band
These bands adjust based on price volatility, offering a dynamic alternative to traditional fixed thresholds.
3️⃣ Normalized JMA for Momentum Confirmation
A second JMA-DEMA structure is normalized by dividing by price, then smoothed:
• If the normalized signal rises above -1, it suggests upside pressure.
• If it drops below -1, it signals momentum decay.
Only when both raw and normalized signals agree does the indicator issue a trade trigger.
✅ Signal Logic
📌 Long Signal →
🔹 Price breaks above volatility-adjusted upper SD band
🔹 AND Normalized JMA rises above -1
📌 Short Signal →
🔹 Price breaks below lower SD band
🔹 AND Normalized JMA falls below -1
⚙️ SEMA JMA stays in its active trend state until an opposing signal triggers, enabling tren riding while filtering short lived swings.
👥 Who Should Use It?
✅ Swing & Trend Traders → Ride strong directional moves with reduced whipsaws
✅ Volatility-Adaptive Systems → Filter trades using rolling SD-based thresholds
✅ Quantitative Strategy Builders → Deploy within algo-driven strategies using backtest-ready metrics
✅ Risk-Aware Traders → Use dual confirmation to minimize signal risk
⚙️ Customization & Default Settings
🔧 Core Settings:
• JMA Length (Default: 35) → Defines JMA sensitivity.
• DEMA Length (Default: 20) → Smoothing after JMA to refine structure.
• Normalized JMA Lengths → Control confirmation layer smoothness (default: 1 for short and long).
• Standard Deviation Length (Default: 30) → Determines the volatility lookback.
• SD Weight Factors → Separate values for long (default: 1.0) and short (default: 1.002) bands.
📊 Backtest Mode
SEMA JMA includes an optional backtest table, enabling traders to assess its historical effectiveness before applying it in live trading conditions.
🔹 Backtest Metrics Displayed:
• Equity Max Drawdown → Largest historical loss from peak equity.
• Profit Factor → Ratio of total profits to total losses, measuring system efficiency.
• Sharpe Ratio → Assesses risk-adjusted return performance.
• Sortino Ratio → Focuses on downside risk-adjusted returns.
• Omega Ratio → Evaluates return consistency & performance asymmetry.
• Half Kelly → Optimal position sizing based on risk/reward analysis.
• Total Trades & Win Rate → Assess historical success rate.
📌 Disclaimer:
Backtest results are based on past performance and do not guarantee future success. Always incorporate real-time validation and risk management in live trading.
🚀 Why This Matters?
✅ Strategy Validation → Gain insight into historical trend accuracy.
✅ Customization Insights → See how different settings impact performance.
✅ Risk Awareness → Understand potential drawdowns before deploying capital.
📌 How to Use SEMA JMA
🌀 Trend-Following Strategy
✔ Go Long: When price breaks above SD band and normalized momentum rises
✔ Go Short: When price breaks below SD band and normalized momentum falls
✔ Stay in position: Until signal reversal confirms
⚙️ Volatility-Adaptive Configuration
✔ Tune w1 (Long SD weight) and w2 (Short SD weight) for responsiveness
✔ Increase SD length in noisy markets for smoother bands
📌 Conclusion
SEMA JMA by QuantEdgeB delivers surgical precision trend signals using a dual-layer approach:
• JMA + DEMA core smoothing
• Statistical SD breakout filters
• Normalized confirmation logic
It’s a versatile indicator suited for trend-following, volatility tracking, and system-based signal generation—engineered for clarity, confidence, and adaptability.
🔹 Key Takeaways:
1️⃣ Multi-Filter Trend Logic – JMA + DEMA + Normalized filtering for high-confidence signals
2️⃣ SD-Based Volatility Control – Reduces noise, avoids ATR limitations
3️⃣ Quant-Ready System – Includes full backtesting
📌 Master your market edge with precision – SEMA JMA | QuantEdgeB
🔹 Disclaimer: Past performance is not indicative of future results.
🔹 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.
14 EMA & RSI Combo with First Buy/SellEMA14 & RSI stratergy - Used as a indication for BUY and Sell based on EMA 14 and RSI. Chk for higher timeframe trend and stick to the entries that are following the trend
Scalping all timeframe EMA & RSIEMA 50 and EMA 100 combined with RSI 14
Should also be accompanied by the RSI 14 chart.
With the following conditions:
IF the EMAs are close but not crossing:
* Be prepared to take a Sell position if the first Bearish Candlestick crosses the lowest EMA, and the RSI value is equal to or below 40.
* Be prepared to take a Buy position if the first Bullish Candlestick crosses the highest EMA, and the RSI value is equal to or above 60.
IF the EMAs are overlapping and crossing:
* Be prepared to take a Sell position if the first Bearish Candlestick crosses both EMAs, and the RSI value crosses below 50.
*Be prepared to take a Buy position if the first Bullish Candlestick crosses both EMAs, and the RSI value crosses above 50.
P-Motion Trend | QuantEdgeB⚡ Introducing P-Motion Trend (PMT) by QuantEdgeB
🧭 Overview
P-Motion Trend is a refined trend-following framework built for modern market dynamics. It combines DEMA filtering, percentile-based smoothing, and volatility-adjusted envelopes to create a clear, noise-filtered trend map directly on your chart.
This overlay indicator is engineered to detect breakout zones, trend continuation setups, and market regime shifts with maximum clarity and minimum lag.
Whether you're swing trading crypto, managing intraday FX moves, or positioning in equities — P-Motion Trend adapts, aligns, and simplifies.
🧠 Core Logic
1️⃣ DEMA Filtering Core
The input source is processed through a Double EMA to reduce lag while retaining trend sensitivity.
2️⃣ Percentile Median Smoothing
To eliminate short-lived spikes, the DEMA output is passed through a percentile median rank — effectively smoothing without distortion.
3️⃣ Volatility Envelope with EMA Basis
An exponential moving average (EMA) is applied to the smoothed median, and standard deviation bands are wrapped around it:
• ✅ Long Signal → Price closes above the upper band
• ❌ Short Signal → Price closes below the lower band
• ➖ Inside Band = Neutral
These bands expand/contract with market volatility — protecting against false breakouts in quiet regimes and adapting quickly to strong moves.
📊 Visual & Analytical Layers
• 🎯 Bar Coloring: Color-coded candles highlight trend state at a glance.
• 📈 EMA Ribbon Overlay: A dynamic ribbon of EMAs helps confirm internal momentum and detect transitions (trend decay or acceleration).
• 🔹Gradient Fill Zones: Visually communicates squeeze vs. expansion phases based on band width.
⚙️ Custom Settings
• EMA Length – Defines the core trend path (default: 21)
• SD Length – Controls volatility band smoothing (default: 30)
• SD Mult Up/Down – Sets thresholds for breakout confirmation (default: 1.5)
• DEMA Filter Source – Raw input used for trend processing
• DEMA Filter Length – Sets DEMA smoothing (default: 7)
• Median Length – Percentile-based smoothing window (default: 2)
📌 Use Cases
✅ Trend Confirmation
Use PMT to confirm whether the price action is structurally valid for trend continuation. A close above the upper band signals entry alignment.
🛡️ Reversal Guard
Avoid early reversion entries. PMT keeps you in-trend until price truly breaks structure.
🔍 Momentum Visualizer
With multiple EMA bands, the indicator also functions as a momentum envelope to spot divergence between price and smoothed trend flow.
🔚 Conclusion
P-Motion Trend is a hybrid volatility + trend system built with precision smoothing, dynamic filtering, and clean visual output. It balances agility with stability, helping you:
• Filter out price noise
• Enter with structure
• Stay in trades longer
• Exit with confidence
🧩 Summary of Benefits
• 🔹 Lag-minimized trend structure via DEMA core
• 🔹 Real-time volatility band adaptation
• 🔹 Gradient visual feedback on compression/expansion
• 🔹 EMA ribbon assists in phase detection
• 🔹 Suitable for all markets & timeframes
📌 Disclaimer: Past performance is not indicative of future results. No trading strategy can guarantee success in financial markets.
📌 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.
DEGA RMA | QuantEdgeB🧠 Introducing DEGA RMA (DGR ) by QuantEdgeB
🛠️ Overview
DEGA RMA (DGR) is a precision-engineered trend-following system that merges DEMA, Gaussian kernel smoothing, and ATR-based envelopes into a single, seamless overlay indicator. Its mission: to filter out market noise while accurately capturing directional bias using a layered volatility-sensitive trend core.
DGR excels at identifying valid breakouts, sustained momentum conditions, and trend-defining price behavior without falling into the trap of frequent signal reversals.
🔍 How It Works
1️⃣ Double Exponential Moving Average (DEMA)
The system begins by applying a DEMA to the selected price source. DEMA responds faster than a traditional EMA, making it ideal for capturing transitions in momentum.
2️⃣ Gaussian Filtering
A custom Gaussian kernel is used to smooth the DEMA signal. The Gaussian function applies symmetrical weights, centered around the most recent bar, effectively softening sharp price oscillations while preserving the underlying trend structure.
3️⃣ Recursive Moving Average (RMA) Core
The filtered Gaussian output is then processed through an RMA to generate a stable dynamic baseline. This baseline becomes the foundation for the final trend logic.
4️⃣ ATR-Scaled Breakout Zones
Upper and lower trend envelopes are calculated using a custom ATR filter built on DEMA-smoothed volatility.
• ✅ Long Signal when price closes above the upper envelope
• ❌ Short Signal when price closes below the lower envelope
• ➖ Neutral when inside the band (no signal noise)
✨ Key Features
🔹 Multi-Layer Trend Model
DEMA → Gaussian → RMA creates a signal structure that is both responsive and robust.
🔹 Volatility-Aware Entry System
Adaptive ATR bands adjust in real-time, expanding during high volatility and contracting during calm periods.
🔹 Noise-Reducing Gaussian Kernel
Sigma-adjustable kernel ensures signal smoothness without introducing excessive lag.
🔹 Clean Visual System
Candle coloring and band fills make trend state easy to read and act on at a glance.
⚙️ Custom Settings
• DEMA Source – Input source for trend core (default: close)
• DEMA Length – Length for initial smoothing (default: 30)
• Gaussian Filter Length – Determines smoothing depth (default: 4)
• Gaussian Sigma – Sharpness of Gaussian curve (default: 2.0)
• RMA Length – Core baseline smoothing (default: 12)
• ATR Length – Volatility detection period (default: 40)
• ATR Mult Up/Down – Controls the upper/lower threshold range for signals (default: 1.7)
📌 How to Use
1️⃣ Trend-Following Mode
• Go Long when price closes above the upper ATR band
• Go Short when price closes below the lower ATR band
• Remain neutral otherwise
2️⃣ Breakout Confirmation Tool
DGR’s ATR-based zone logic helps validate price breakouts and filter out false signals that occur inside compressed ranges.
3️⃣ Volatility Monitoring
Watch the ATR envelope width — a narrowing band often precedes expansion and potential directional shifts.
📌 Conclusion
DEGA RMA (DGR) is a thoughtfully constructed trend-following framework that goes beyond basic moving averages. Its Gaussian smoothing, adaptive ATR thresholds, and layered filtering logic provide a versatile solution for traders looking for cleaner signals, less noise, and real-time trend awareness.
Whether you're trading crypto, forex, or equities — DGR adapts to volatility while keeping your chart clean and actionable.
🔹 Summary
• ✅ Advanced Smoothing → DEMA + Gaussian + RMA = ultra-smooth trend core
• ✅ Volatility-Adjusted Zones → ATR envelope scaling removes whipsaws
• ✅ Fully Customizable → Tailor to any asset or timeframe
• ✅ Quant-Inspired Structure → Built for clarity, consistency, and confidence
📌 Disclaimer: Past performance is not indicative of future results. No trading strategy can guarantee success in financial markets.
📌 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.
Gaussian Smooth Trend | QuantEdgeB🧠 Introducing Gaussian Smooth Trend (GST) by QuantEdgeB
🛠️ Overview
Gaussian Smooth Trend (GST) is an advanced volatility-filtered trend-following system that blends multiple smoothing techniques into a single directional bias tool. It is purpose-built to reduce noise, isolate meaningful price shifts, and deliver early trend detection while dynamically adapting to market volatility.
GST leverages the Gaussian filter as its core engine, wrapped in a layered framework of DEMA smoothing, SMMA signal tracking, and standard deviation-based breakout thresholds, producing a powerful toolset for trend confirmation and momentum-based decision-making.
🔍 How It Works
1️⃣ DEMA Smoothing Engine
The indicator begins by calculating a Double Exponential Moving Average (DEMA), which provides a responsive and noise-resistant base input for subsequent filtering.
2️⃣ Gaussian Filter
A custom Gaussian kernel is applied to the DEMA signal, allowing the system to detect smooth momentum shifts while filtering out short-term volatility.
This is especially powerful during low-volume or sideways markets where traditional MAs struggle.
3️⃣ SMMA Layer with Z-Filtering
The filtered Gaussian signal is then passed through a custom Smoothed Moving Average (SMMA). A standard deviation envelope is constructed around this SMMA, dynamically expanding/contracting based on market volatility.
4️⃣ Signal Generation
• ✅ Long Signal: Price closes above Upper SD Band
• ❌ Short Signal: Price closes below Lower SD Band
• ➖ No trade: Price stays within the band → market indecision
✨ Key Features
🔹 Multi-Stage Trend Detection
Combines DEMA → Gaussian Kernel → SMMA → SD Bands for robust signal integrity across market conditions.
🔹 Gaussian Adaptive Filtering
Applies a tunable sigma parameter for the Gaussian kernel, enabling you to fine-tune smoothness vs. responsiveness.
🔹 Volatility-Aware Trend Zones
Price must close outside of dynamic SD envelopes to trigger signals — reducing whipsaws and increasing signal quality.
🔹 Dynamic Color-Coded Visualization
Candle coloring and band fills reflect live trend state, making the chart intuitive and fast to read.
⚙️ Custom Settings
• DEMA Source: Price stream used for smoothing (default: close)
• DEMA Length: Period for initial exponential smoothing (default: 7)
• Gaussian Length / Sigma: Controls smoothing strength of kernel filter
• SMMA Length: Final smoothing layer (default: 12)
• SD Length: Lookback period for standard deviation filtering (default: 30)
• SD Mult Up / Down: Adjusts distance of upper/lower breakout zones (default: 2.5 / 1.8)
• Color Modes: Six distinct color palettes (e.g., Strategy, Warm, Cool)
• Signal Labels: Toggle on/off entry markers ("𝓛𝓸𝓷𝓰", "𝓢𝓱𝓸𝓻𝓽")
📌 Trading Applications
✅ Trend-Following → Enter on confirmed breakouts from Gaussian-smoothed volatility zones
✅ Breakout Validation → Use SD bands to avoid false breakouts during chop
✅ Volatility Compression Monitoring → Narrowing bands often precede large directional moves
✅ Overlay-Based Confirmation → Can complement other QuantEdgeB indicators like K-DMI, BMD, or Z-SMMA
📌 Conclusion
Gaussian Smooth Trend (GST) delivers a precision-built trend model tailored for modern traders who demand both clarity and control. The layered signal architecture, combined with volatility awareness and Gaussian signal enhancement, ensures accurate entries, clean visualizations, and actionable trend structure — all in real-time.
🔹 Summary Highlights
1️⃣ Multi-stage Smoothing — DEMA → Gaussian → SMMA for deep signal integrity
2️⃣ Volatility-Aware Filtering — SD bands prevent false entries
3️⃣ Visual Trend Mapping — Gradient fills + candle coloring for clean charts
4️⃣ Highly Customizable — Adapt to your timeframe, style, and volatility
📌 Disclaimer: Past performance is not indicative of future results. No trading strategy can guarantee success in financial markets.
📌 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.
Z SMMA | QuantEdgeB📈 Introducing Z-Score SMMA (Z SMMA) by QuantEdgeB
🛠️ Overview
Z SMMA is a momentum-driven oscillator designed to track the standardized deviation of a Smoothed Moving Average (SMMA). By applying Z-score normalization, this tool dynamically adapts to price volatility, enabling traders to detect meaningful directional shifts and trend changes with enhanced clarity.
It serves both as a trend-following and mean-reversion system, identifying opportunities through standardized thresholds while remaining robust across volatile and calm market conditions.
✨ Key Features
🔹 Z-Score Normalization Engine
Applies Z-score to a custom SMMA baseline, allowing traders to compare price action relative to its recent volatility-adjusted mean.
🔹 Dynamic Trend Detection
Generates actionable long/short signals based on customizable Z-thresholds, making it adaptable across different asset classes and timeframes.
🔹 Overbought/Oversold Zones
Highlight reversion and profit-taking zones (default OB: +2 to +4, OS: -2 to -4), great for counter-trend or mean-reversion strategies.
🔹 Visual Reinforcement Tools
Includes candle coloring, gradient fills, and optional ALMA/EMA band overlays to visualize trend regime transitions.
🔍 How It Works
1️⃣ Z-Score SMMA Calculation
The core is a custom Smoothed Moving Average (SMMA) that is normalized by its standard deviation over a lookback period.
Final Formula:
Z = (SMMA - Mean) / StdDev
2️⃣ Signal Generation
• ✅ Long Bias: Z-Score > Long Threshold (default: 0)
• ❌ Short Bias: Z-Score < Short Threshold (default: 0)
3️⃣ Visual Aids
• Candle Color → Shows trend bias
• Band Fills → Highlight trend strength
• Overlays → Optional ALMA/EMA bands for structure analysis
⚙️ Custom Settings
• SMMA Length → Default: 12
• Z-Score Lookback → Default: 30
• Long Threshold → Default: 0
• Short Threshold → Default: 0
• Color Themes → Choose from 6 visual modes
• Extra Plots → Toggle advanced overlays (ALMA, EMA, bands)
• Label Display → Show/hide “𝓛𝓸𝓷𝓰” & “𝓢𝓱𝓸𝓻𝓽” markers
👥 Who Should Use It?
✅ Trend Traders → For early entries with confirmation from Z-score expansion
✅ Quantitative Analysts → Standardized deviation enables comparison across assets
✅ Mean-Reversion Traders → Use OB/OS zones to fade parabolic spikes
✅ Swing & Systematic Traders → Identify momentum shifts with optional ALMA/EMA overlays
📌 Conclusion
Z SMMA offers a smart, adaptive framework for tracking deviation from equilibrium in a quant-friendly format. Whether you're looking to follow trends or catch exhaustion points, Z SMMA provides a clear, standardized view of momentum and price extremes.
🔹 Key Takeaways:
1️⃣ Z-Score standardization ensures dynamic range awareness
2️⃣ SMMA base filters out noise, offering smoother signals
3️⃣ Color-coded visuals support faster reaction and cleaner charts
📌 Disclaimer: Past performance is not indicative of future results. No trading strategy can guarantee success in financial markets.
📌 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before
Quantile DEMA Trend | QuantEdgeB🚀 Introducing Quantile DEMA Trend (QDT) by QuantEdgeB
🛠️ Overview
Quantile DEMA Trend (QDT) is an advanced trend-following and momentum detection indicator designed to capture price trends with superior accuracy. Combining DEMA (Double Exponential Moving Average) with SuperTrend and Quantile Filtering, QDT identifies strong trends while maintaining the ability to adapt to various market conditions.
Unlike traditional trend indicators, QDT uses percentile filtering to adjust for volatility and provides dynamic thresholds, ensuring consistent signal performance across different assets and timeframes.
✨ Key Features
🔹 Trend Following with Adaptive Sensitivity
The DEMA component ensures quicker responses to price changes while reducing lag, offering a real-time reflection of market momentum.
🔹 Volatility-Adjusted Filtering
The SuperTrend logic incorporates quantile percentile filters and ATR (Average True Range) multipliers, allowing QDT to adapt to fluctuating market volatility.
🔹 Clear Signal Generation
QDT generates clear Long and Short signals using percentile thresholds, effectively identifying trend changes and market reversals.
🔹 Customizable Visual & Signal Settings
With multiple color modes and customizable settings, you can easily align the QDT indicator with your trading strategy, whether you're focused on trend-following or volatility adjustments.
📊 How It Works
1️⃣ DEMA Calculation
DEMA is used to reduce lag compared to traditional moving averages. It is calculated by applying a Double Exponential Moving Average to price data. This smoother trend-following mechanism ensures responsiveness to market movements without introducing excessive noise.
2️⃣ SuperTrend with Percentile Filtering
The SuperTrend component adapts the trend-following signal by incorporating quantile percentile filters. It identifies dynamic support and resistance levels based on historical price data:
• Upper Band: Calculated using the 75th percentile + ATR (adjusted with multiplier)
• Lower Band: Calculated using the 25th percentile - ATR (adjusted with multiplier)
These dynamic bands adjust to market conditions, filtering out noise while identifying the true direction.
3️⃣ Signal Generation
• Long Signal: Triggered when price crosses below the SuperTrend Lower Band
• Short Signal: Triggered when price crosses above the SuperTrend Upper Band
The indicator provides signals with corresponding trend direction based on these crossovers.
👁 Visual & Custom Features
• 🎨 Multiple Color Modes: Choose from "Strategy", "Solar", "Warm", "Cool", "Classic", and "Magic" color palettes to match your charting style.
• 🏷️ Long/Short Signal Labels: Optional labels for visual cueing when a long or short trend is triggered.
• 📉 Bar Color Customization: Bar colors dynamically adjust based on trend direction to visually distinguish the market bias.
👥 Who Should Use QDT?
✅ Trend Followers: Use QDT as a dynamic tool to confirm trends and capture profits in trending markets.
✅ Swing Traders: Use QDT to time entries based on confirmed breakouts or breakdowns.
✅ Volatility Traders: Identify market exhaustion or expansion points, especially during volatile periods.
✅ Systematic & Quant Traders: Integrate QDT into algorithmic strategies to enhance market detection with adaptive filtering.
⚙️ Customization & Default Settings
- DEMA Length(30): Controls the lookback period for DEMA calculation
- Percentile Length(10): Sets the lookback period for percentile filtering
- ATR Length(14): Defines the length for calculating ATR (used in SuperTrend)
- ATR Multiplier(1.2 ): Multiplier for ATR in SuperTrend calculation
- SuperTrend Length(30):Defines the length for SuperTrend calculations
📌 How to Use QDT in Trading
1️⃣ Trend-Following Strategy
✔ Enter Long positions when QDT signals a bullish breakout (price crosses below the SuperTrend lower band).
✔ Enter Short positions when QDT signals a bearish breakdown (price crosses above the SuperTrend upper band).
✔ Hold positions as long as QDT continues to provide the same direction.
2️⃣ Reversal Strategy
✔ Take profits when price reaches extreme levels (upper or lower percentile zones) that may indicate trend exhaustion or reversion.
3️⃣ Volatility-Driven Entries
✔ Use the percentile filtering to enter positions based on mean-reversion logic or breakout setups in volatile markets.
🧠 Why It Works
QDT combines the DEMA’s quick response to price changes with SuperTrend's volatility-adjusted thresholds, ensuring a responsive and adaptive indicator. The use of percentile filters and ATR multipliers helps adjust to varying market conditions, making QDT suitable for both trending and range-bound environments.
🔹 Conclusion
The Quantile DEMA Trend (QDT) by QuantEdgeB is a powerful, adaptive trend-following and momentum detection system. By integrating DEMA, SuperTrend, and quantile percentile filtering, it provides accurate and timely signals while adjusting to market volatility. Whether you are a trend follower or volatility trader, QDT offers a robust solution to identify high-probability entry and exit points.
🔹 Key Takeaways:
1️⃣ Trend Confirmation – Uses DEMA and SuperTrend for dynamic trend detection
2️⃣ Volatility Filtering – Adjusts to varying market conditions using percentile logic
3️⃣ Clear Signal Generation – Easy-to-read signals and visual cues for strategy implementation
📌 Disclaimer: Past performance is not indicative of future results. No trading strategy can guarantee success in financial markets.
📌 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.
TP/SL Percentage & RR Visual ToolThis tool is designed to help traders visually and statistically assess their trade setup by calculating Stop Loss (SL), Take Profit (TP), and Risk-to-Reward (RR) based on percentage inputs from the current price.
🔧 How It Works:
Uses the current candle’s close price as your entry.
Calculates TP and SL as percentage-based levels (e.g., 1% SL, 1.5% TP).
Displays horizontal lines and labels on the chart for TP and SL (only on the latest candle to reduce clutter).
Shows a compact table in the top-right corner with all key values:
Entry Price
Current Price
TP Price (+%)
SL Price (-%)
TP Distance from current price
RR Ratio (e.g., 1:1.5)
💡 Use Cases:
Quickly validate if a trade setup meets your desired RR profile (e.g., 1:2).
Perfect for scalpers, swing traders, and position traders who rely on structured risk management.
Combine with your entry signal strategy to visualize targets and stops without manual calculations.
⚙️ Inputs:
Stop Loss % – Sets how far your SL is from the entry.
Take Profit % – Sets how far your TP is from the entry.
Coppock Curve
The Coppock Curve is a long-term momentum indicator, also known as the "Coppock Guide," used to identify potential long-term market turning points, particularly major downturns and upturns, by smoothing the sum of 14-month and 11-month rates of change with a 10-month weighted moving average.
Here's a more detailed breakdown:
What it is:
The Coppock Curve is a technical indicator designed to identify long-term buy and sell signals in major stock market indices and related ETFs.
How it's calculated:
Rate of Change (ROC): The indicator starts by calculating the rate of change (ROC) for 14 and 11 periods (usually months).
Sum of ROCs: The ROC for the 14-period and 11-period are summed.
Weighted Moving Average (WMA): A 10-period weighted moving average (WMA) is then applied to the sum of the ROCs.
Interpreting the Curve:
Buy Signals: A buy signal is often generated when the Coppock Curve crosses above the zero line, suggesting a potential transition from a bearish to a bullish phase.
Sell Signals: While primarily designed to identify market bottoms, some traders may interpret a cross below the zero line as a sell signal or a bearish warning.
Origin and Purpose:
The Coppock Curve was introduced by economist Edwin Coppock in 1962.
It was originally designed to help investors identify opportune moments to enter the market.
Coppock's inspiration came from the Episcopal Church's concept of the average mourning period, which he believed mirrored the stock market's recovery period.
Limitations:
The Coppock Curve is primarily used for long-term analysis and may not be as effective for short-term or intraday trading.
It may lag in rapidly changing markets, and its signals may not always be reliable.
