Lorentzian Theory Classifier🧮 Lorentzian Theory Classifier: An Observatory for Market Spacetime
Transcend the flat plane of traditional charting. Enter the curved, dynamic reality of market spacetime. The Lorentzian Theory Classifier (LTC) is not an indicator; it is a computational observatory. It is an instrument engineered to decode the geometry of market behavior, revealing the hidden curvatures and resonant frequencies that precede significant turning points.
We discard the outdated tools of Euclidean simplicity and embrace a more profound truth: financial markets, much like the cosmos described by general relativity, are governed by a fabric that is warped by the mass of participation and the energy of volatility. The LTC is your lens to perceive this fabric, to move beyond predicting lines on a chart and begin reading the very architecture of probability.
The Resonance Manifold: Standard Euclidean models search for historical analogues within a rigid sphere, missing the crucial outliers that define market extremes. The LTC's Lorentzian Resonance engine operates in a curved, non-Euclidean space, allowing it to connect with these "fat-tail" events—the true genesis points of major reversals.
🌌 THE THEORETICAL FRAMEWORK: A new Grand Unified Theory of Market Analysis
The LTC is built upon a revolutionary synthesis of concepts from special relativity, quantum mechanics, and information theory. It reframes market analysis not as a problem of forecasting, but as a problem of state recognition in a non-Euclidean manifold.
1. The Lorentzian Kernel: The Mathematics of Reality
Financial markets are not Gaussian. Their reality is one of "fat tails"—sudden, high-impact events that standard models dismiss as anomalies. The LTC acknowledges this reality by using the mathematically pure and robust Lorentzian kernel as its core engine:
Similarity(x, y) = 1 / (1 + (||x − y||² / γ²))
||x − y||²: The squared distance between the current market state (x) and a historical state (y) in our 8-dimensional feature space.
γ (Gamma): A dynamic bandwidth parameter, our "Lorentz factor," which adapts to market entropy (chaos). In calm markets, gamma is small, demanding precise resonance. In chaotic markets, gamma expands, intelligently seeking broader patterns.
This heavy-tailed function is revolutionary. It correctly assigns profound significance to the rare, extreme events that truly define market structure, while gracefully tuning out the noise of mundane price action. It doesn't just calculate; it understands context.
2. The 8-Dimensional State Vector: The Market's Quantum Fingerprint
To achieve a holistic view, the LTC projects the market onto an 8-dimensional Hilbert space, where each dimension represents a critical "observable":
Momentum & Acceleration (f_rsi, f_roc): The market's velocity and its rate of change.
Cyclical Position (f_stoch, f_cci): The market's location within its recent oscillation cycles.
Energy & Participation (f_vol, f_cor): The force of capital flow and its harmony with price.
Chaos & Uncertainty (f_ent, f_mom): The degree of randomness and the standardized force of price changes.
These are not eight separate indicators. They are entangled properties of a single "market wavefunction." The LTC's genius lies in measuring the geometric distance between these complete quantum states.
3. The k-NN Oracle: A Council of Past Universes
The LTC employs a k-Nearest Neighbors algorithm, but in our curved Lorentzian spacetime. It poses a constant, profound question: " Which moments in history are most geometrically congruent to the present moment across all eight dimensions? "
It then summons a "council" of these historical neighbors. Each neighbor's future outcome (did price ascend or descend?) casts a vote, weighted by its resonant similarity. The result is a probabilistic forecast of stunning clarity:
Prognosis: The final weighted consensus on future direction.
Assurance: The degree of unanimity within the council—a direct measure of the prediction's confidence.
The Funnel of Conviction: The LTC's process is a rigorous distillation of information. Raw, chaotic market data is resolved into a clean 8-dimensional state vector. The Lorentzian Kernel filters these states for resonance, which are then passed to the k-NN Oracle for a vote. Noise is eliminated at each stage, resulting in a single, validated, high-conviction signal.
⚙️ THE COMMAND CONSOLE: A Guide to Calibrating Your Observatory
Mastering the LTC's inputs is to become an architect of your own analytical universe. Each parameter is a dial that tunes the observatory's focus, from galactic structures to subatomic fluctuations. The tooltips in-script—over 6,000 words of documentation—provide immediate reference; this guide provides the philosophy.
A summarized guide to the Core, Signal, Supreme, and Visual controls is included directly in the indicator's code and tooltips. We encourage all users to explore these settings to tune the LTC to their unique analytical style.
🏆 THE SUPREME DASHBOARD: Your Mission Control
The dashboard is not a data table; it is your command interface with market reality. It translates the intricate dance of probabilities and vectors into clear, actionable intelligence.
⚡ ORACLE STATUS
Prognosis: The primary directional vector. Its color, magnitude, and emoji (⚡) reveal the strength and conviction of the Oracle's forward guidance.
Assurance: A real-time gauge of prediction quality, from "LOW" (high uncertainty) to "ELITE" (overwhelming statistical consensus). Interpret this as your core risk metric: trade with conviction when Assurance is ELITE; trade with caution when it is LOW.
🔮 RESONANCE ANALYSIS
Chaos: A direct measurement of market entropy. "LOW CHAOS" signifies a predictable, orderly regime. "HIGH CHAOS" is a warning of randomness and unpredictability, where trend-following logic may fail.
Turbulence: A measure of raw volatility. When the market is "TURBULENT," expect wider price swings and increased risk. Use this metric to adjust stop-loss distances and profit targets dynamically.
🏆 PERFORMANCE & ⚔️ GUARD METRICS
These sections provide illustrative statistics on the script's recent historical behavior. Metrics like Yield Ratio and Guard Index offer a quick heuristic on the prevailing risk-reward environment. Crucially, these are for observational context only and are not a substitute for your own rigorous testing and analysis.
🎨 THE VISUAL MANIFESTATION: Charting the Unseen
The LTC's visuals are designed to transform your chart from a 2D price graph into a 4D informational battlespace.
The Dynamic Aura (Background Color): This is the ambient energy field of the market. A luminous green (Ascend) signifies a bullish resonance field; a deep red (Descend) indicates bearish pressure.
The Assurance Shroud (Blue Bands): A visualization of confidence. When the shroud is wide and expansive , the Oracle's vision is clear and its predictions are robust.
The Prognosis Arc (Curved Line): A geodesic projection of the market's most likely path, based on the current Prognosis.
The Turbulence Cloud (Orange Mist): A visual warning system for market chaos. When this entropic mist expands , it is a clear sign that you are navigating a nebula of high unpredictability.
Oracle Markers (▲▼): The final, validated signals. These are not merely pivot points. They are moments in spacetime where a structural pivot has been confirmed and then ratified by a high-conviction vote from the Lorentzian Oracle. They are the pinnacles of confluence.
The Analyst's Observatory: The LTC transforms your chart into a command center for market analysis, providing a complete, at-a-glance view of market state, risk, and probabilistic trajectory.
🔧 THE ARCHITECT'S VISION: From a Blank Slate to a New Cosmos
The LTC was not assembled; it was derived. It began not with code, but with first principles, asking: "If we were to build an instrument to measure the market today, unbound by the technical dogmas of the 20th century, what would it look like?" The answer was clear: it must be multi-dimensional, it must be adaptive, and it must be built on a mathematical framework that respects the "fat-tailed" nature of reality.
The decision to use a pure Lorentzian kernel was non-negotiable. It represented a commitment to intellectual honesty over computational ease. The development of the Supreme Dashboard was driven by the philosophy of the "glass cockpit"—a belief that a trader's greatest asset is not a black box signal, but a transparent and intuitive flow of high-quality information. This script is the result of that unwavering vision: to create not just another indicator, but a new lens through which to perceive the market.
⚠️ RISK DISCLOSURE & PHILOSOPHY OF USE
The Lorentzian Theory Classifier is an instrument of profound analytical power, intended for the serious, discerning trader. It does not generate infallible signals. It generates high-probability, data-driven hypotheses based on a rigorous and transparent methodology. All trading involves substantial risk, and the future is fundamentally unknowable. Past performance, whether real or simulated, is no guarantee of future results. Use this tool to augment your own skill, to confirm your own analysis, and to manage your own risk within a well-defined trading plan.
"The effort to understand the universe is one of the very few things that lifts human life a little above the level of farce, and gives it some of the grace of tragedy."
— Steven Weinberg, Nobel Laureate in Physics
Trade with rigor. Trade with perspective. Trade with enlightenment. Trade with insight. Trade with anticipation.
— Dskyz, for DAFE Trading Systems
Cerca negli script per "demand"
Reversal Point Dynamics⇋ Reversal Point Dynamics (RPD)
This is not an indicator; it is a complete system for deconstructing the mechanics of a market reversal. Reversal Point Dynamics (RPD) moves far beyond simplistic pattern recognition, venturing into a deep analysis of the underlying forces that cause trends to exhaust, pause, and turn. It is engineered from the ground up to identify high-probability reversal points by quantifying the confluence of market dynamics in real-time.
Where other tools provide a static signal, RPD delivers a dynamic probability. It understands that a true market turning point is not a single event, but a cascade of failing momentum, structural breakdown, and a shift in market order. RPD's core engine meticulously analyzes each of these dynamic components—the market's underlying state, its velocity and acceleration, its degree of chaos (entropy), and its structural framework. These forces are synthesized into a single, unified Probability Score, offering you an unprecedented, transparent view into the conviction behind every potential reversal.
This is not a "black box" system. It is an open-architecture engine designed to empower the discerning trader. Featuring real-time signal projection, an integrated Fibonacci R2R Target Engine, and a comprehensive dashboard that acts as your Dynamics Control Center , RPD gives you a complete, holistic view of the market's state.
The Theoretical Core: Deconstructing Market Dynamics
RPD's analytical power is born from the intelligent synthesis of multiple, distinct theoretical models. Each pillar of the engine analyzes a different facet of market behavior. The convergence of these analyses—the "Singularity" event referenced in the dashboard—is what generates the final, high-conviction probability score.
1. Pillar One: Quantum State Analysis (QSA)
This is the foundational analysis of the market's current state within its recent context. Instead of treating price as a random walk, QSA quantizes it into a finite number of discrete "states."
Formulaic Concept: The engine establishes a price range using the highest high and lowest low over the Adaptive Analysis Period. This range is then divided into a user-defined number of Analysis Levels. The current price is mapped to one of these states (e.g., in a 9-level system, State 0 is the absolute low, and State 8 is the absolute high).
Analytical Edge: This acts as a powerful foundational filter. The engine will only begin searching for reversal signals when the market has reached a statistically stretched, extreme state (e.g., State 0 or 8). The Edge Sensitivity input allows you to control exactly how close to this extreme edge the price must be, ensuring you are trading from points of maximum potential exhaustion.
2. Pillar Two: Price State Roc (PSR) - The Dynamics of Momentum
This pillar analyzes the kinetic forces of the market: its velocity and acceleration. It understands that it’s not just where the price is, but how it got there that matters.
Formulaic Concept: The psr function calculates two derivatives of price.
Velocity: (price - price ). This measures the speed and direction of the current move.
Acceleration: (velocity - velocity ). This measures the rate of change in that speed. A negative acceleration (deceleration) during a strong rally is a critical pre-reversal warning, indicating momentum is fading even as price may be pushing higher.
Analytical Edge: The engine specifically hunts for exhaustion patterns where momentum is clearly decelerating as price reaches an extreme state. This is the mechanical signature of a weakening trend.
3. Pillar Three: Market Entropy Analysis - The Dynamics of Order & Chaos
This is RPD's chaos filter, a concept borrowed from information theory. Entropy measures the degree of randomness or disorder in the market's price action.
Formulaic Concept: The calculateEntropy function analyzes recent price changes. A market moving directionally and smoothly has low entropy (high order). A market chopping back and forth without direction has high entropy (high chaos). The value is normalized between 0 and 1.
Analytical Edge: The most reliable trades occur in low-entropy, ordered environments. RPD uses the Entropy Threshold to disqualify signals that attempt to form in chaotic, unpredictable conditions, providing a powerful shield against whipsaw markets.
4. Pillar Four: The Synthesis Engine & Probability Calculation
This is where all the dynamic forces converge. The final probability score is a weighted calculation that heavily rewards confluence.
Formulaic Concept: The calculateProbability function intelligently assembles the final score:
A Base Score is established from trend strength and entropy.
An Entropy Score adds points for low entropy (order) and subtracts for high entropy (chaos).
A significant Divergence Bonus is awarded for a classic momentum divergence.
RSI & Volume Bonuses are added if momentum oscillators are in extreme territory or a volume spike confirms institutional interest.
MTF & Adaptive Bonuses add further weight for alignment with higher timeframe structure.
Analytical Edge: A signal backed by multiple dynamic forces (e.g., extreme state + decelerating momentum + low entropy + volume spike) will receive an exponentially higher probability score. This is the very essence of analyzing reversal point dynamics.
The Command Center: Mastering the Inputs
Every input is a precise lever of control, allowing you to fine-tune the RPD engine to your exact trading style, market, and timeframe.
🧠 Core Algorithm
Predictive Mode (Early Detection):
What It Is: Enables the engine to search for potential reversals on the current, unclosed bar.
How It Works: Analyzes intra-bar acceleration and state to identify developing exhaustion. These signals are marked with a ' ? ' and are tentative.
How To Use It: Enable for scalping or very aggressive day trading to get the earliest possible indication. Disable for swing trading or a more conservative approach that waits for full bar confirmation.
Live Signal Mode (Current Bar):
What It Is: A highly aggressive mode that plots tentative signals with a ' ! ' on the live bar based on projected price and momentum. These signals repaint intra-bar.
How It Works: Uses a linear regression projection of the close to anticipate a reversal.
How To Use It: For advanced users who use intra-bar dynamics for execution and understand the nature of repainting signals.
Adaptive Analysis Period:
What It Is: The main lookback period for the QSA, PSR, and Entropy calculations. This is the engine's "memory."
How It Works: A shorter period makes the engine highly sensitive to local price swings. A longer period makes it focus only on major, significant market structure.
How To Use It: Scalping (1-5m): 15-25. Day Trading (15m-1H): 25-40. Swing Trading (4H+): 40-60.
Fractal Strength (Bars):
What It Is: Defines the strength of the pivot detection used for confirming reversal events.
How It Works: A value of '2' requires a candle's high/low to be more extreme than the two bars to its left and right.
How To Use It: '2' is a robust standard. Increase to '3' for an even stricter definition of a structural pivot, which will result in fewer signals.
MTF Multiplier:
What It Is: Integrates pivot data from a higher timeframe for confluence.
How It Works: A multiplier of '4' on a 15-minute chart will pull pivot data from the 1-hour chart (15 * 4 = 60m).
How To Use It: Set to a multiple that corresponds to your preferred higher timeframe for contextual analysis.
🎯 Signal Settings
Min Probability %:
What It Is: Your master quality filter. A signal is only plotted if its score exceeds this threshold.
How It Works: Directly filters the output of the final probability calculation.
How To Use It: High-Quality (80-95): For A+ setups only. Balanced (65-75): For day trading. Aggressive (50-60): For scalping.
Min Signal Distance (Bars):
What It Is: A noise filter that prevents signals from clustering in choppy conditions.
How It Works: Enforces a "cooldown" period of N bars after a signal.
How To Use It: Increase in ranging markets to focus on major swings. Decrease on lower timeframes.
Entropy Threshold:
What It Is: Your "chaos shield." Sets the maximum allowable market randomness for a signal.
How It Works: If calculated entropy is above this value, the signal is invalidated.
How To Use It: Lower values (0.1-0.5): Extremely strict. Higher values (0.7-1.0): More lenient. 0.85 is a good balance.
Adaptive Entropy & Aggressive Mode:
What It Is: Toggles for dynamically adjusting the engine's core parameters.
How It Works: Adaptive Entropy can slightly lower the required probability in strong trends. Aggressive Mode uses more lenient settings across the board.
How To Use It: Keep Adaptive on. Use Aggressive Mode sparingly, primarily for scalping highly volatile assets.
📊 State Analysis
Analysis Levels:
What It Is: The number of discrete "states" for the QSA.
How It Works: More levels create a finer-grained analysis of price location.
How To Use It: 6-7 levels are ideal. Increasing to 9 can provide more precision on very volatile assets.
Edge Sensitivity:
What It Is: Defines how close to the absolute top/bottom of the range price must be.
How It Works: '0' means price must be in the absolute highest/lowest state. '3' allows a signal within the top/bottom 3 states.
How To Use It: '3' provides a good balance. Lower it to '1' or '0' if you only want to trade extreme exhaustion.
The Dashboard: Your Dynamics Control Center
The dashboard provides a transparent, real-time view into the engine's brain. Use it to understand the context behind every signal and to gauge the current market environment at a glance.
🎯 UNIFIED PROB SCORE
TOTAL SCORE: The highest probability score (either Peak or Valley) the engine is currently calculating. This is your main at-a-glance conviction metric. The "Singularity" header refers to the event where market dynamics align—the event RPD is built to detect.
Quality: A human-readable interpretation of the Total Score. "EXCEPTIONAL" (🌟) is a rare, A+ confluence event. "STRONG" (💪) is a high-quality, tradable setup.
📊 ORDER FLOW & COMPONENT ANALYSIS
Volume Spike: Shows if the current volume is significantly higher than average (YES/NO). A 'YES' adds major confirmation.
Peak/Valley Conf: This breaks down the probability score into its directional components, showing you the separate confidence levels for a potential top (Peak) versus a bottom (Valley).
🌌 MARKET STRUCTURE
HTF Trend: Shows the direction of the underlying trend based on a Supertrend calculation.
Entropy: The current market chaos reading. "🔥 LOW" is an ideal, ordered state for trading. "😴 HIGH" is a warning of choppy, unpredictable conditions.
🔮 FIB & R2R ZONE (Large Dashboard)
This section gives you the status of the Fibonacci Target Engine. It shows if an Active Channel (entry zone) or Stop Zone (invalidation zone) is active and displays the precise price levels for the static entry, target, and stop calculated at the time of the signal.
🛡️ FILTERS & PREDICTIVES (Large Dashboard)
This panel provides a status check on all the bonus filters. It shows the current RSI Status, whether a Divergence is present, and if a Live Pending signal is forming.
The Visual Interface: A Symphony of Data
Every visual element is designed for instant, intuitive interpretation of market dynamics.
Signal Markers: These are the primary outputs of the engine.
▼/▲ b: A fully confirmed signal that has passed all filters.
? b: A tentative signal generated in Predictive Mode, indicating developing dynamics.
◈ b: This diamond icon replaces the standard triangle when the signal is confirmed by a strong momentum divergence, highlighting it as a superior setup where dynamics are misaligned with price.
Harmonic Wave: The flowing, colored wave around the price.
What It Represents: The market's "flow dynamic" and volatility.
How to Interpret It: Expanding waves show increasing volatility. The color is tied to the "Quantum Color" in your theme, representing the underlying energy field of the market.
Entropy Particles: The small dots appearing above/below price.
What They Represent: A direct visualization of the "order dynamic."
How to Interpret Them: Their presence signifies a low-entropy, ordered state ideal for trading. Their color indicates the direction of momentum (PSR velocity). Their absence means the market is too chaotic (high entropy).
The Fibonacci Target Engine: The dynamic R2R system appearing post-signal.
Static Fib Levels: Colored horizontal lines representing the market's "structural dynamic."
The Green "Active Channel" Box: Your zone of consideration. An area to manage a potential entry.
Development Philosophy
Reversal Point Dynamics was engineered to answer a fundamental question: can we objectively measure the forces behind a market turn? It is a synthesis of concepts from market microstructure, statistics, and information theory. The objective was never to create a "perfect" system, but to build a robust decision-support tool that provides a measurable, statistical edge by focusing on the principle of confluence.
By demanding that multiple, independent market dynamics align simultaneously, RPD filters out the vast majority of market noise. It is designed for the trader who thinks in terms of probability and risk management, not in terms of certainties. It is a tool to help you discount the obvious and bet on the unexpected alignment of market forces.
"Markets are constantly in a state of uncertainty and flux and money is made by discounting the obvious and betting on the unexpected."
— George Soros
Trade with insight. Trade with anticipation.
— Dskyz, for DAFE Trading Systems
Inflection PointInflection Point - The Adaptive Confluence Reversal Engine
This is not just another peak and valley indicator; it is a complete and total reimagining of how market turning points are detected, qualified, and acted upon. Born from the foundational concepts explored in systems like my earlier creation, DAFE - Turning Point, Inflection Point is a ground-up engineering feat designed for the modern trader. It moves beyond static rules and simple pattern recognition into the realm of dynamic, multi-factor confluence analysis and adaptive machine learning.
Where other indicators provide a guess, Inflection Point provides a probability. It meticulously analyzes the market's deepest currents—momentum, exhaustion, and reversal velocity—and fuses them into a single, unified "Confluence Score." This is not a simple combination of indicators; it is an intelligent, weighted system where each component works in concert, creating an analytical engine that is orders of magnitude more sophisticated and reliable than any standard reversal tool.
Furthermore, Inflection Point learns. Through its advanced Adaptive Learning Engine, it constantly monitors its own performance, adjusting its confidence and selectivity in real-time based on its recent success rate. This allows it to adapt its behavior to any security, on any timeframe, with remarkable success.
Theoretical Foundation - Confluence Core
Inflection Point's predictive power does not come from a single, magical formula. It comes from the intelligent synthesis of three critical market phenomena, weighted and scored in real-time to generate a single, high-conviction probability rating.
1. Factor One: Pre-Reversal Momentum State (RSI Analysis)
Instead of reacting to a simple RSI cross, Inflection Point proactively scans for the build-up of momentum that precedes a reversal.
• Formulaic Concept: It measures the highest RSI value over a lookback period for peaks and the lowest RSI for valleys. A signal is only considered valid if significant momentum has been established before the turn, indicating a stretched market condition ripe for reversal.
• Asymmetric Sophistication: The engine uses different, optimized thresholds for bull and bear momentum, recognizing that markets often fall faster than they rise.
2. Factor Two: Volatility Exhaustion (Bollinger Band Analysis)
A true reversal often occurs when price makes a final, exhaustive push into unsustainable territory.
• Formulaic Concept: The engine detects when price has significantly pierced the outer Bollinger Bands. This is not just a touch, but a statistical deviation from the mean that signals volatility exhaustion, where the energy for the current move is likely depleted.
3. Factor Three: Reversal Strength (Rate of Change Analysis)
The character of a reversal matters. A sharp, decisive turn is more significant than a slow, meandering one.
• Formulaic Concept: Using a short-term Rate of Change (ROC), the engine measures the velocity of the reversal itself. A higher ROC score adds significant weight to the final probability, confirming that the new direction has conviction.
4. The Final Calculation: The Adaptive Learning Engine
This is the system's "brain." It maintains a history of its past signals and calculates its real-time win rate. This hitRate is then used to generate an adaptiveMultiplier.
• Self-Correction: In "Quality Control" mode, a high win rate makes the indicator more selective, demanding a higher probability score to issue a signal, thereby protecting streaks. A lower win rate makes it slightly less selective to ensure it continues learning from new market conditions.
• The result is a system that is not static, but a living, breathing tool that adapts its personality to the unique rhythm of any chart.
Why Inflection Point is a Paradigm Shift
Inflection Point is fundamentally different from other reversal indicators for three key reasons:
Confluence Over Isolation: Standard indicators look at one thing (e.g., RSI > 70). Inflection Point simultaneously analyzes momentum, volatility, and velocity, understanding that true reversals are a product of multiple converging factors. It answers not just "if," but "why" a reversal is likely.
Probabilistic Over Binary: Other tools give you a simple "yes" or "no." Inflection Point provides a probability score from 0-100, allowing you to gauge the conviction of every potential signal. This empowers you to differentiate between a weak setup and an A+ opportunity.
Adaptive Over Static: Every other indicator uses the same rules forever. Inflection Point's Adaptive Engine means it is constantly refining its own logic based on what is actually working in the current market, on the specific asset you are trading. It is tailored to the now.
The Inputs Menu - Your Command Center
Every setting is a lever of control, allowing you to tune the engine to your precise trading style and market focus.
🧠 Neural Core Engine
Analysis Depth: This is the primary lookback for the Bollinger Band and other core calculations. A shorter depth makes the indicator faster and more sensitive, ideal for scalping. A longer depth makes it slower and more stable, ideal for swing trading.
Minimum Probability %: This is your master signal filter. It sets the minimum Confluence Score required to plot a signal. Higher values (85-95) will give you only the highest-conviction A+ setups. Lower values (70-80) will show more potential opportunities.
🤖 Adaptive Neural Learning
Enable Adaptive Learning Engine: Toggles the entire learning system. Disabling it will make the indicator's logic static.
Peak/Valley Success Threshold (ATR): This defines what constitutes a "successful" trade for the learning engine. A value of 1.5 means price must move 1.5x the ATR in your favor for the signal to be marked as a win. Adjust this to match your personal take-profit strategy.
Adaptive Mode: This dictates how the engine uses its hitRate. "Quality Control" is recommended for its intelligent filtering. "Aggressive" will always boost signal scores, useful for finding more setups in a known, trending environment.
Asymmetric Balance: Allows you to apply a "boost" to either peak (short) or valley (long) signals. If you find the market you're trading has stronger long reversals, you can increase the "Valley Signal Boost" to catch them more effectively.
🛡️ Elite Filters
Market Noise Filter: An exceptional tool for avoiding choppy markets. It counts the number of directional changes in the last 5 bars. If the market is whipping back and forth too much, it will block the signal. Lower the "Max Direction Changes" to be extremely selective.
Volume Filter: Requires signal confirmation from a significant volume spike. The "Volume Multiplier" dictates how large this spike must be (e.g., 1.2 = 20% above average volume). This is invaluable for filtering out low-conviction moves in stocks and crypto.
The Dashboard - Your Analytical Co-Pilot
The dashboard is not just a set of numbers; it is a holistic overview of the market's health and the engine's current state.
Unified AI Score: This section provides the most critical, at-a-glance information. "Total Score" is the current probability reading, while "Quality" gives you a human-readable interpretation. "Win Rate" shows the real-time performance of the Adaptive Engine.
Order Flow (OFPI): This measures the "weight" of money behind recent price moves by analyzing price change relative to volume. A high positive OFPI suggests strong buying pressure, while a high negative value suggests strong selling pressure. It gives you a peek into the market's underlying flow.
Component Analysis: This allows you to see the individual "Peak" and "Valley" confidence scores before they are filtered, giving you insight into building momentum before a signal forms.
Market Structure: This panel assesses the broader environment. "HTF Trend" tells you the direction of the larger trend (based on EMAs), while "Vol Regime" tells you if the market is in a high, medium, or low volatility state. Use this to align your signals with the broader market context.
Filter & Engine Statistics: Available on the "Large" dashboard, this provides deep insight into how many signals are being blocked by your filters and the current status of the Adaptive Engine's multiplier.
The Visual Interface - A Symphony of Data
Every visual element on the chart is designed for instant interpretation and insight.
Signal Markers: Simple, clean triangles mark the exact bar of a valid signal. A box is drawn around the high/low of the signal bar to highlight the precise point of inflection.
Dynamic Support/Resistance Zones: These are the glowing lines on your chart. They are not static lines; they are dynamic levels that represent the current battlefield between buyers and sellers.
Cyber Cyan (Valley Blue): This is the current Support Zone. This is the price level the market is currently trying to defend.
Neural Pink (Peak Red): This is the current Resistance Zone. This is the price level the market is currently trying to break through.
Grey (Next Level): This line is a projection, based on the current momentum and the size of the S/R range, of where the next major level of conflict will likely be. It acts as a potential price target.
Development & Philosophy
Inflection Point was not assembled; it was engineered. It represents hundreds of hours of research into market dynamics, statistical analysis, and machine learning principles. The goal was to create a tool that moves beyond the limitations of traditional technical analysis, which often fails in modern, algorithm-driven markets. By building a system based on multi-factor confluence and self-adaptive logic, Inflection Point provides a quantifiable, statistical edge that is simply unattainable with simpler tools. This is the result of a relentless pursuit of a better, more intelligent way to trade.
Universal Applicability
The principles of momentum, exhaustion, and velocity are universal to all freely traded markets. Because of its adaptive core and robust filtering options, Inflection Point has proven to be exceptionally effective on any security (stocks, crypto, forex, indices, futures) and on any timeframe (from 1-minute scalping charts to daily swing trading charts).
" Markets are constantly in a state of uncertainty and flux and money is made by discounting the obvious and betting on the unexpected. "
— George Soros
Trade with insight. Trade with anticipation.
— Dskyz, for DAFE Trading Systems
[blackcat] L2 Multi-Level Price Condition TrackerOVERVIEW
The L2 Multi-Level Price Condition Tracker represents an innovative approach to analyzing financial markets by simultaneously monitoring multiple price levels, thus providing traders with a holistic view of market dynamics. By combining dynamic calculations based on moving averages and price deviations, this tool aims to deliver precise and actionable insights into potential entry and exit points. It leverages sophisticated statistical measures to identify key thresholds that signify shifts in market sentiment, thereby aiding traders in making well-informed decisions. 🎯
Key benefits encompass:
• Comprehensive calculation of midpoints and average prices indicating short-term trend directions.
• Interactive visualization elements enhancing interpretability effortlessly.
• Real-time generation of buy/sell signals driven by precise condition evaluations.
TECHNICAL ANALYSIS COMPONENTS
📉 Midpoint Calculations:
Computes central reference points derived from high-low ranges establishing baseline supports/resistances.
Utilizes Simple Moving Averages (SMAs) along with standardized deviation formulas smoothing out volatility while preserving long-term trends accurately.
Facilitates identification of directional biases reflecting underlying market forces dynamically.
🕵️♂️ Advanced Price Level Detection:
Derives upper/lower bounds adjusting sensitivities adaptively responding to changing conditions flexibly.
Employs proprietary logic distinguishing between bullish/bearish sentiments promptly signaling transitions effectively.
Ensures consistent adherence to predefined statistical protocols maintaining accuracy robustly.
🎥 Dynamic Signal Generation:
Detects crossovers indicating dominance shifts between buyers/sellers promptly triggering timely alerts.
Integrates conditional logic reinforcing signal validity minimizing erroneous activations systematically.
Supports adaptive thresholds tuning sensitivities based on evolving market conditions flexibly accommodating varying scenarios.
INDICATOR FUNCTIONALITY
🔢 Core Algorithms:
Utilizes moving averages alongside standardized deviation formulas generating precise net volume measurements.
Implements Arithmetic Mean Line Algorithm (AMLA) smoothing techniques improving interpretability.
Ensures consistent alignment with established statistical principles preserving fidelity.
🖱️ User Interface Elements:
Dedicated plots displaying real-time midpoint markers facilitating swift decision-making.
Context-sensitive color coding distinguishing positive/negative deviations intuitively highlighting key activations clearly.
Background shading emphasizing proximity to crucial threshold activations enhancing visibility focusing attention on vital signals promptly.
STRATEGY IMPLEMENTATION
✅ Entry Conditions:
Confirm bullish/bearish setups validated through multiple confirmatory signals assessing concurrent market sentiment factors.
Validate entry decisions considering alignment between calculated midpoints and broader trend directions ensuring coherence.
Monitor cumulative breaches signifying potential trend reversals executing partial/total closes contingent upon predetermined loss limits preserving capital efficiently.
🚫 Exit Mechanisms:
Trigger exits upon hitting predefined thresholds derived from historical analyses promptly executing closures.
Execute partial/total closes contingent upon cumulative loss limits preserving capital efficiently managing exposures prudently.
Conduct periodic reviews gauging strategy effectiveness rigorously identifying areas needing refinement implementing corrective actions iteratively enhancing performance metrics steadily.
PARAMETER CONFIGURATIONS
🎯 Optimization Guidelines:
Lookback Period: Governs responsiveness versus stability balancing sensitivity/stability governing moving averages aligning with preferred granularity.
Price Source: Dictates primary data series driving volume calculations selecting relevant inputs accurately tailoring strategies accordingly.
💬 Customization Recommendations:
Commence with baseline defaults; iteratively refine parameters isolating individual impacts evaluating adjustments independently prior to combined modifications minimizing disruptions.
Prioritize minimizing erroneous trigger occurrences first optimizing signal fidelity sustaining balanced risk-reward profiles irrespective of chosen settings upholding disciplined approaches preserving capital efficiently.
ADVANCED RISK MANAGEMENT
🛡️ Proactive Risk Mitigation Techniques:
Enforce strict compliance with pre-defined maximum leverage constraints adhering strictly to guidelines managing exposures prudently.
Mandatorily apply trailing stop-loss orders conforming to script outputs enforcing discipline rigorously preventing adverse consequences.
Allocate positions proportionately relative to available capital reserves conducting periodic reviews gauging effectiveness continuously identifying improvement opportunities steadily.
⚠️ Potential Pitfalls & Solutions:
Address frequent violations arising during heightened volatility phases necessitating manual interventions judiciously preparing contingency plans proactively mitigating risks effectively.
Manage false alerts warranting immediate attention avoiding adverse consequences systematically implementing corrective actions reliably.
Prepare proactive responses amid adverse movements ensuring seamless functionality amidst fluctuating conditions fortifying resilience against anomalies robustly.
PERFORMANCE MONITORING METRICS
🔍 Evaluation Criteria:
Assess win percentages consistently across diverse trading instruments gauging reliability measuring profitability efficiency accurately evaluating downside risks comprehensively uncovering systematic biases potentially skewing outcomes.
Calculate average profit ratios per successful execution benchmarking actual vs expected performances documenting results meticulously tracking progress dynamically addressing identified shortcomings proactively fostering continuous improvements.
📈 Historical Data Analysis Tools:
Maintain detailed logs capturing every triggered event recording realized profits/losses comparing simulated projections accurately identifying discrepancies warranting investigation implementing iterative refinements steadily enhancing performance metrics progressively.
Identify recurrent systematic errors demanding corrective actions implementing iterative refinements steadily addressing identified shortcomings proactively fostering continuous enhancements dynamically improving robustness resiliently.
PROBLEM SOLVING ADVICE
🔧 Frequent Encountered Challenges:
Unpredictable behaviors emerging within thinly traded markets requiring filtration processes enhancing signal integrity excluding low-liquidity assets prone to erratic movements effectively.
Latency issues manifesting during abrupt price fluctuations causing missed opportunities introducing buffer intervals safeguarding major news/event impacts mitigating distortions seamlessly verifying reliable connections ensuring uninterrupted data flows guaranteeing accurate interpretations dependably.
💡 Effective Resolution Pathways:
Limit ongoing optimization attempts preventing model degradation maintaining optimal performance levels consistently recalibrating parameters periodically adapting strategies flexibly responding appropriately amidst varying conditions dynamically improving robustness resiliently.
Verify reliable connections ensuring uninterrupted data flows guaranteeing accurate interpretations dependably bolstering overall efficacy systematically addressing identified shortcomings dynamically fostering continuous advancements.
THANKS
Heartfelt acknowledgment extends to all developers contributing invaluable insights regarding multi-level price condition-based trading methodologies! ✨
[blackcat] L3 Mean Reversion ATR Stop Loss OVERVIEW
The L3 Mean Reversion ATR Stop Loss indicator is meticulously crafted to empower traders by offering statistically-driven stop-loss levels that adapt seamlessly to evolving market dynamics. By harmoniously blending mean reversion concepts with Advanced True Range (ATR) metrics, it delivers a robust framework for managing risks more effectively. 🌐 The primary objective is to furnish traders with intelligent exit points grounded in both short-term volatility assessments and long-term trend evaluations.
Key highlights encompass:
• Dynamic calculation of Z-scores to evaluate deviations from established means
• Adaptive stop-loss pricing leveraging real-time ATR measurements
• Clear visual cues enabling swift decision-making processes
TECHNICAL ANALYSIS COMPONENTS
📉 Z-SCORE CALCULATION
Measures how many standard deviations an asset's current price lies away from its average
Facilitates identification of extreme conditions indicative of impending reversals
Utilizes simple moving averages and standard deviation computations
📊 STANDARD DEVIATION MEASUREMENT
Quantifies dispersion of closing prices around the mean
Provides insights into underlying price distribution characteristics
Crucial for assessing potential volatility levels accurately
🕵️♂️ ADAPTIVE STOP-LOSS DETECTION
Employs ATR as a proxy for prevailing market volatility
Modulates stop-loss placements dynamically responding to shifting trends
Ensures consistent adherence to predetermined risk management protocols
INDICATOR FUNCTIONALITY
🔢 Core Algorithms
Integrate Smooth Moving Averages (SMAs) alongside standardized deviation formulas
Generate precise Z-scores reflecting true price deviations
Leverage ATR-derived multipliers for fine-grained stop-loss adjustments
🖱️ User Interface Elements
Interactive plots displaying real-time stop-loss markers
Context-sensitive color coding enhancing readability
Background shading indicating proximity to stop-level activations
STRATEGY IMPLEMENTATION
✅ Entry Conditions
Confirm bullish/bearish setups validated through multiple confirmatory signals
Ensure alignment between Z-score readings and broader trend directions
Validate entry decisions considering concurrent market sentiment factors
🚫 Exit Mechanisms
Trigger exits upon hitting predefined ATR-based stop-loss thresholds
Monitor continuous breaches signifying potential trend reversals
Execute partial/total closes contingent upon cumulative loss limits
PARAMETER CONFIGURATIONS
🎯 Optimization Guidelines
Period Length: Governs responsiveness versus smoothing trade-offs
ATR Length: Dictates the temporal scope for volatility analysis
Stop Loss ATR Multiplier: Tunes sensitivity towards stop-trigger activations
💬 Customization Recommendations
Commence with baseline defaults; iteratively refine parameters
Evaluate impacts independently prior to combined adjustments
Prioritize minimizing erroneous trigger occurrences first
Sustain balanced risk-reward profiles irrespective of chosen settings
ADVANCED RISK MANAGEMENT
🛡️ Proactive Risk Mitigation Techniques
Enforce strict compliance with pre-defined maximum leverage constraints
Mandatorily apply trailing stop-loss orders conforming to script outputs
Allocate positions proportionately relative to available capital reserves
Conduct periodic reviews gauging strategy effectiveness rigorously
⚠️ Potential Pitfalls & Solutions
Address frequent violations arising during heightened volatility phases
Manage false alerts warranting manual interventions judiciously
Prepare contingency plans mitigating margin call possibilities
Continuously assess automated system reliability amidst fluctuating conditions
PERFORMANCE AUDITS & REFINEMENTS
🔍 Critical Evaluation Metrics
Assess win percentages consistently across diverse trading instruments
Calculate average profit ratios per successful execution
Measure peak drawdown durations alongside associated magnitudes
Analyze signal generation frequencies revealing hidden patterns
📈 Historical Data Analysis Tools
Maintain comprehensive records capturing every triggered event
Compare realized profits/losses against backtested simulations
Identify recurrent systematic errors demanding corrective actions
Implement iterative refinements bolstering overall efficacy steadily
PROBLEM SOLVING ADVICE
🔧 Frequent Encountered Challenges
Unpredictable behaviors emerging within thinly traded markets
Latency issues manifesting during abrupt price fluctuations
Overfitted models yielding suboptimal results post-extensive tuning
Inaccuracies stemming from incomplete or delayed data inputs
💡 Effective Resolution Pathways
Exclude low-liquidity assets prone to erratic movements
Introduce buffer intervals safeguarding major news/event impacts
Limit ongoing optimization attempts preventing model degradation
Verify seamless connectivity ensuring uninterrupted data flows
USER ENGAGEMENT SEGMENT
🤝 Community Contributions Welcome
Highly encourage active participation sharing experiences & recommendations!
THANKS
A heartfelt acknowledgment extends to all developers contributing invaluable insights about adaptive stop-loss strategies using statistical measures! ✨
Enhanced Volume Trend Indicator with BB SqueezeEnhanced Volume Trend Indicator with BB Squeeze: Comprehensive Explanation
The visualization system allows traders to quickly scan multiple securities to identify high-probability setups without detailed analysis of each chart. The progression from squeeze to breakout, supported by volume trend confirmation, offers a systematic approach to identifying trading opportunities.
The script combines multiple technical analysis approaches into a comprehensive dashboard that helps traders make informed decisions by identifying high-probability setups while filtering out noise through its sophisticated confirmation requirements. It combines multiple technical analysis approaches into an integrated visual system that helps traders identify potential trading opportunities while filtering out false signals.
Core Features
1. Volume Analysis Dashboard
The indicator displays various volume-related metrics in customizable tables:
AVOL (After Hours + Pre-Market Volume): Shows extended hours volume as a percentage of the 21-day average volume with color coding for buying/selling pressure. Green indicates buying pressure and red indicates selling pressure.
Volume Metrics: Includes regular volume (VOL), dollar volume ($VOL), relative volume compared to 21-day average (RVOL), and relative volume compared to 90-day average (RVOL90D).
Pre-Market Data: Optional display of pre-market volume (PVOL), pre-market dollar volume (P$VOL), pre-market relative volume (PRVOL), and pre-market price change percentage (PCHG%).
2. Enhanced Volume Trend (VTR) Analysis
The Volume Trend indicator uses adaptive analysis to evaluate buying and selling pressure, combining multiple factors:
MACD (Moving Average Convergence Divergence) components
Volume-to-SMA (Simple Moving Average) ratio
Price direction and market conditions
Volume change rates and momentum
EMA (Exponential Moving Average) alignment and crossovers
Volatility filtering
VTR Visual Indicators
The VTR score ranges from 0-100, with values above 50 indicating bullish conditions and below 50 indicating bearish conditions. This is visually represented by colored circles:
"●" (Filled Circle):
Green: Strong bullish trend (VTR ≥ 80)
Red: Strong bearish trend (VTR ≤ 20)
"◯" (Hollow Circle):
Green: Moderate bullish trend (VTR 65-79)
Red: Moderate bearish trend (VTR 21-35)
"·" (Small Dot):
Green: Weak bullish trend (VTR 55-64)
Red: Weak bearish trend (VTR 36-45)
"○" (Medium Hollow Circle): Neutral conditions (VTR 46-54), shown in gray
In "Both" display mode, the VTR shows both the numerical score (0-100) alongside the appropriate circle symbol.
Enhanced VTR Settings
The Enhanced Volume Trend component offers several advanced customization options:
Adaptive Volume Analysis (volTrendAdaptive):
When enabled, dynamically adjusts volume thresholds based on recent market volatility
Higher volatility periods require proportionally higher volume to generate significant signals
Helps prevent false signals during highly volatile markets
Keep enabled for most trading conditions, especially in volatile markets
Speed of Change Weight (volTrendSpeedWeight, range 0-1):
Controls emphasis on volume acceleration/deceleration rather than absolute levels
Higher values (0.7-1.0): More responsive to new volume trends, better for momentum trading
Lower values (0.2-0.5): Less responsive, better for trend following
Helps identify early volume trends before they fully develop
Momentum Period (volTrendMomentumPeriod, range 2-10):
Defines lookback period for volume change rate calculations
Lower values (2-3): More responsive to recent changes, better for short timeframes
Higher values (7-10): Smoother, better for daily/weekly charts
Directly affects how quickly the indicator responds to new volume patterns
Volatility Filter (volTrendVolatilityFilter):
Adjusts significance of volume by factoring in current price volatility
High volume during high volatility receives less weight
High volume during low volatility receives more weight
Helps distinguish between genuine volume-driven moves and volatility-driven moves
EMA Alignment Weight (volTrendEmaWeight, range 0-1):
Controls importance of EMA alignments in final VTR calculation
Analyzes multiple EMA relationships (5, 10, 21 period)
Higher values (0.7-1.0): Greater emphasis on trend structure
Lower values (0.2-0.5): More focus on pure volume patterns
Display Mode (volTrendDisplayMode):
"Value": Shows only numerical score (0-100)
"Strength": Shows only symbolic representation
"Both": Shows numerical score and symbol together
3. Bollinger Band Squeeze Detection (SQZ)
The BB Squeeze indicator identifies periods of low volatility when Bollinger Bands contract inside Keltner Channels, often preceding significant price movements.
SQZ Visual Indicators
"●" (Filled Circle): Strong squeeze - high probability setup for an impending breakout
Green: Strong squeeze with bullish bias (likely upward breakout)
Red: Strong squeeze with bearish bias (likely downward breakout)
Orange: Strong squeeze with unclear direction
"◯" (Hollow Circle): Moderate squeeze - medium probability setup
Green: With bullish EMA alignment
Red: With bearish EMA alignment
Orange: Without clear directional bias
"-" (Dash): Gray dash indicates no squeeze condition (normal volatility)
The script identifies squeeze conditions through multiple methods:
Bollinger Bands contracting inside Keltner Channels
BB width falling to bottom 20% of recent range (BB width percentile)
Very narrow Keltner Channel (less than 5% of basis price)
Tracking squeeze duration in consecutive bars
Different squeeze strengths are detected:
Strong Squeeze: BB inside KC with tight BB width and narrow KC
Moderate Squeeze: BB inside KC with either tight BB width or narrow KC
No Squeeze: Normal market conditions
4. Breakout Detection System
The script includes two breakout indicators working in sequence:
4.1 Pre-Breakout (PBK) Indicator
Detects potential upcoming breakouts by analyzing multiple factors:
Squeeze conditions lasting 2-3 bars or more
Significant price ranges
Strong volume confirmation
EMA/MACD crossovers
Consistent price direction
PBK Visual Indicators
"●" (Filled Circle): Detected pre-breakout condition
Green: Likely upward breakout (bullish)
Red: Likely downward breakout (bearish)
Orange: Direction not yet clear, but breakout likely
"-" (Dash): Gray dash indicates no pre-breakout condition
The PBK uses sophisticated conditions to reduce false signals including minimum squeeze length, significant price movement, and technical confirmations.
4.2 Breakout (BK) Indicator
Confirms actual breakouts in progress by identifying:
End of squeeze or strong expansion of Bollinger Bands
Volume expansion
Price moving outside Bollinger Bands
EMA crossovers with volume confirmation
MACD crossovers with significant price range
BK Visual Indicators
"●" (Filled Circle): Confirmed breakout in progress
Green: Upward breakout (bullish)
Red: Downward breakout (bearish)
Orange: Unusual breakout pattern without clear direction
"◆" (Diamond): Special breakout conditions (meets some but not all criteria)
"-" (Dash): Gray dash indicates no breakout detected
The BK indicator uses advanced filters for confirmation:
Requires consecutive breakout signals to reduce false positives
Strong volume confirmation requirements (40% above average)
Significant price movement thresholds
Consistency checks between price action and indicators
5. Market Metrics and Analysis
Price Change Percentage (CHG%)
Displays the current percentage change relative to the previous day's close, color-coded green for positive changes and red for negative changes.
Average Daily Range (ADR%)
Calculates the average daily percentage range over a specified period (default 20 days), helping traders gauge volatility and set appropriate price targets.
Average True Range (ATR)
Shows the Average True Range value, a volatility indicator developed by J. Welles Wilder that measures market volatility by decomposing the entire range of an asset price for that period.
Relative Strength Index (RSI)
Displays the standard 14-period RSI, a momentum oscillator that measures the speed and change of price movements on a scale from 0 to 100.
6. External Market Indicators
QQQ Change
Shows the percentage change in the Invesco QQQ Trust (tracking the Nasdaq-100 Index), useful for understanding broader tech market trends.
UVIX Change
Displays the percentage change in UVIX, a volatility index, providing insight into market fear and potential hedging activity.
BTC-USD
Shows the current Bitcoin price from Coinbase, useful for traders monitoring crypto correlation with equities.
Market Breadth (BRD)
Calculates the percentage difference between ATHI.US and ATLO.US (high vs. low securities), indicating overall market direction and strength.
7. Session Analysis and Volume Direction
Session Detection
The script accurately identifies different market sessions:
Pre-market: 4:00 AM to 9:30 AM
Regular market: 9:30 AM to 4:00 PM
After-hours: 4:00 PM to 8:00 PM
Closed: Outside trading hours
This detection works on any timeframe through careful calculation of current time in seconds.
Buy/Sell Volume Direction
The script analyzes buying and selling pressure by:
Counting up volume when close > open
Counting down volume when close < open
Tracking accumulated volume within the day
Calculating intraday pressure (up volume minus down volume)
Enhanced AVOL Calculation
The improved AVOL calculation works in all timeframes by:
Estimating typical pre-market and after-hours volume percentages
Combining yesterday's after-hours with today's pre-market volume
Calculating this as a percentage of the 21-day average volume
Determining buying/selling pressure by analyzing after-hours and pre-market price changes
Color-coding results: green for buying pressure, red for selling pressure
This calculation is particularly valuable because it works consistently across any timeframe.
Customization Options
Display Settings
The dashboard has two customizable tables: Volume Table and Metrics Table, with positions selectable as bottom_left or bottom_right.
All metrics can be individually toggled on/off:
Pre-market data (PVOL, P$VOL, PRVOL, PCHG%)
Volume data (AVOL, RVOL Day, RVOL 90D, Volume, SEED_YASHALGO_NSE_BREADTH:VOLUME )
Price metrics (ADR%, ATR, RSI, Price Change%)
Market indicators (QQQ, UVIX, Breadth, BTC-USD)
Analysis indicators (Volume Trend, BB Squeeze, Pre-Breakout, Breakout)
These toggle options allow traders to customize the dashboard to show only the metrics they find most valuable for their trading style.
Table and Text Customization
The dashboard's appearance can be customized:
Table background color via tableBgColor
Text color (White or Black) via textColorOption
The indicator uses smart formatting for volume and price values, automatically adding appropriate suffixes (K, M, B) for readability.
MACD Configuration for VTR
The Volume Trend calculation incorporates MACD with customizable parameters:
Fast Length: Controls the period for the fast EMA (default 3)
Slow Length: Controls the period for the slow EMA (default 9)
Signal Length: Controls the period for the signal line EMA (default 5)
MACD Weight: Controls how much influence MACD has on the volume trend score (default 0.3)
These settings allow traders to fine-tune how momentum is factored into the volume trend analysis.
Bollinger Bands and Keltner Channel Settings
The Bollinger Bands and Keltner Channels used for squeeze detection have preset (hidden) parameters:
BB Length: 20 periods
BB Multiplier: 2.0 standard deviations
Keltner Length: 20 periods
Keltner Multiplier: 1.5 ATR
These settings follow standard practice for squeeze detection while maintaining simplicity in the user interface.
Practical Trading Applications
Complete Trading Strategies
1. Squeeze Breakout Strategy
This strategy combines multiple components of the indicator:
Wait for a strong squeeze (SQZ showing ●)
Look for pre-breakout confirmation (PBK showing ● in green or red)
Enter when breakout is confirmed (BK showing ● in same direction)
Use VTR to confirm volume supports the move (VTR ≥ 65 for bullish or ≤ 35 for bearish)
Set profit targets based on ADR (Average Daily Range)
Exit when VTR begins to weaken or changes direction
2. Volume Divergence Strategy
This strategy focuses on the volume trend relative to price:
Identify when price makes a new high but VTR fails to confirm (divergence)
Look for VTR to show weakening trend (● changing to ◯ or ·)
Prepare for potential reversal when SQZ begins to form
Enter counter-trend position when PBK confirms reversal direction
Use external indicators (QQQ, BTC, Breadth) to confirm broader market support
3. Pre-Market Edge Strategy
This strategy leverages pre-market data:
Monitor AVOL for unusual pre-market activity (significantly above 100%)
Check pre-market price change direction (PCHG%)
Enter position at market open if VTR confirms direction
Use SQZ to determine if volatility is likely to expand
Exit based on RVOL declining or price reaching +/- ADR for the day
Market Context Integration
The indicator provides valuable context for trading decisions:
QQQ change shows tech market direction
BTC price shows crypto market correlation
UVIX change indicates volatility expectations
Breadth measurement shows market internals
This context helps traders avoid fighting the broader market and align trades with overall market direction.
Timeframe Optimization
The indicator is designed to work across different timeframes:
For day trading: Focus on AVOL, VTR, PBK/BK, and use shorter momentum periods
For swing trading: Focus on SQZ duration, VTR strength, and broader market indicators
For position trading: Focus on larger VTR trends and use EMA alignment weight
Advanced Analytical Components
Enhanced Volume Trend Score Calculation
The VTR score calculation is sophisticated, with the base score starting at 50 and adjusting for:
Price direction (up/down)
Volume relative to average (high/normal/low)
Volume acceleration/deceleration
Market conditions (bull/bear)
Additional factors are then applied, including:
MACD influence weighted by strength and direction
Volume change rate influence (speed)
Price/volume divergence effects
EMA alignment scores
Volatility adjustments
Breakout strength factors
Price action confirmations
The final score is clamped between 0-100, with values above 50 indicating bullish conditions and below 50 indicating bearish conditions.
Anti-False Signal Filters
The indicator employs multiple techniques to reduce false signals:
Requiring significant price range (minimum percentage movement)
Demanding strong volume confirmation (significantly above average)
Checking for consistent direction across multiple indicators
Requiring prior bar consistency (consecutive bars moving in same direction)
Counting consecutive signals to filter out noise
These filters help eliminate noise and focus on high-probability setups.
MACD Enhancement and Integration
The indicator enhances standard MACD analysis:
Calculating MACD relative strength compared to recent history
Normalizing MACD slope relative to volatility
Detecting MACD acceleration for stronger signals
Integrating MACD crossovers with other confirmation factors
EMA Analysis System
The indicator uses a comprehensive EMA analysis system:
Calculating multiple EMAs (5, 10, 21 periods)
Detecting golden cross (10 EMA crosses above 21 EMA)
Detecting death cross (10 EMA crosses below 21 EMA)
Assessing price position relative to EMAs
Measuring EMA separation percentage
Recent Enhancements and Evolution
Version 5.2 includes several improvements:
Enhanced AVOL to show buying/selling direction through color coding
Improved VTR with adaptive analysis based on market conditions
AVOL display now works in all timeframes through sophisticated estimation
Removed animal symbols and streamlined code with bright colors for better visibility
Improved anti-false signal filters throughout the system
Optimizing Indicator Settings
For Different Market Types
Range-Bound Markets:
Lower EMA Alignment Weight (0.2-0.4)
Higher Speed of Change Weight (0.8-1.0)
Focus on SQZ and PBK signals for breakout potential
Trending Markets:
Higher EMA Alignment Weight (0.7-1.0)
Moderate Speed of Change Weight (0.4-0.6)
Focus on VTR strength and BK confirmations
Volatile Markets:
Enable Volatility Filter
Enable Adaptive Volume Analysis
Lower Momentum Period (2-3)
Focus on strong volume confirmation (VTR ≥ 80 or ≤ 20)
For Different Asset Classes
Equities:
Standard settings work well
Pay attention to AVOL for gap potential
Monitor QQQ correlation
Futures:
Consider higher Volume/RVOL weight
Reduce MACD weight slightly
Pay close attention to SQZ duration
Crypto:
Higher volatility thresholds may be needed
Monitor BTC price for correlation
Focus on stronger confirmation signals
Integrated Visual System for Trading Decisions
The colored circle indicators create an intuitive visual system for quick market assessment:
Progression Sequence: SQZ (Squeeze) → PBK (Pre-Breakout) → BK (Breakout)
This sequence often occurs in order, with the squeeze leading to pre-breakout conditions, followed by an actual breakout.
VTR (Volume Trend): Provides context about the volume supporting these movements.
Color Coding: Green for bullish conditions, red for bearish conditions, and orange/gray for neutral or undefined conditions.
Strong Trend Bars (ATR-based)This is a ChatGPT pinescript meant as an indicator for detecting strength in the market. The primary function I use it for is to decide which bars to trail a stop loss beneath.
💥 Explanation of adjustable inputs:
Bull Close Threshold (default 0.6):
If set to 0.6, bull bars must close above 60% of bar height → low + 0.6 * barHeight
Bear Close Threshold (default 0.6):
If set to 0.6, bear bars must close below 40% of bar height → high - 0.6 * barHeight
This lets you experiment with tighter or looser filters. For example:
0.7 → only bars closing near the extremes will light up
0.5 → about midpoint
0.8 → very demanding, “almost full body” bars
[blackcat] L2 Enhanced MACD Trend█ OVERVIEW
The Enhanced MACD Trend script combines traditional Moving Average Convergence Divergence (MACD) analysis with On-Balance Volume (OBV) insights to provide traders with a comprehensive understanding of market trends. By examining both price momentum and volume fluctuations, this tool aids in identifying potential upward or downward market transitions.
█ LOGICAL FRAMEWORK
Initially, the script prompts users to configure fundamental parameters such as the speed of moving averages. It subsequently utilizes a specialized auxiliary function named calculate_macd_obv_signals to perform intricate computations. This function calculates the discrepancy between two distinct types of moving averages (captured via MACD analysis), evaluates the direction of capital inflows and outflows within securities (using OBV), and applies smoothing techniques to mitigate undue influence from minor fluctuations. Ultimately, visual representations of these calculations are rendered on an additional chart pane for enhanced interpretability.
█ CUSTOM FUNCTIONS
Function: calculate_macd_obv_signals
• Purpose: Determines critical aspects associated with MACD and OBV.
• Parameters:
• fastLength (int): Dictates the responsiveness of the shorter Exponential Moving Average (EMA) to price variations.
• slowLength (int): Specifies the reactivity of the longer EMA.
• signalSmoothing (int): Defines the degree of smoothness applied to the divergence between EMAs.
• Functionality:
• macd_diff: Illustrates whether price increases have accelerated relative to previous levels or decelerated, providing insight into existing momentum.
• macd_signal_line: Smoothens macd_diff values, serving akin to a trailing indicator for macd_diff.
• macd_histogram: Visually accentuates disparities between macd_diff and macd_signal_line employing color-coded bars, facilitating identification of significant divergences.
• obv_signal: Represents a refined variant of short-term OBV concentrating solely on periods characterized by elevated buying interest, aiding in reduction of extraneous signals.
• moving_average_short: Analyzes recent closing prices across several sessions to corroborate burgeoning bullish or bearish tendencies.
• Returns: An array encompassing .
█ KEY POINTS AND TECHNIQUES
Advanced Features: Employs sophisticated functions including ta.ema() and ta.sma(), enabling accurate calculation of EMAs and SMAs respectively, thus enhancing precision in trend detection.
Optimization Techniques: Incorporates customizable inputs (input.int) permitting strategic adjustments alongside scrutiny of escalating or declining volumes to accurately gauge genuine sentiment shifts while discounting insignificant anomalies.
Best Practices: Maintains separation between algorithmic processes and graphical outputs, preserving organizational clarity; hence simplifying debugging efforts and future enhancements.
Unique Approaches: Integrates multifaceted assessments simultaneously – amalgamating candlestick formations and volumetric activities – offering a holistic perspective instead of reliance on singular indicators. Consequently, delivers astute recommendations grounded in diverse analytical underpinnings rather than speculative forecasts.
█ EXTENDED KNOWLEDGE AND APPLICATIONS
Potential Modifications:
1 — Implement automated alert mechanisms signaling crossover events pinpointing optimal buy/sell junctures to fine-tune timing preemptively minimizing losses proactively.
2 — Enable user customization of sensitivity criteria governing trigger intensity thereby eliminating trivial aberrations and emphasizing substantial patterns exclusively.
Application Scenarios:
Beneficial for high-frequency trading aiming to capitalize on fleeting price movements swiftly. Suitable for dynamic environments necessitating rapid responses due to frequent market volatility demanding prompt reactions. Perfect for individuals engaging in regular transactions seeking unparalleled accuracy navigating fluctuating circumstances ensuring consistent profitability amidst disturbances maintaining steady yields irrespective of upheavals.
Related Concepts:
Contemplate interactions among oscillators (such as MACD) and volume metrics detecting instances wherein they oppose each other (indicative of divergences) or concur (signaling crossovers). Profound comprehension of these interrelationships substantially refines trading strategies integrating broader economic factors, seasonal influences guiding overarching plans resulting in heightened predictive capabilities elevating trading effectiveness leveraging cumulative information transforming unprocessed statistics into actionable intelligence empowering informed decisions advancing confidently toward objectives effortlessly scaling achievements seamlessly realizing aspirations effortlessly.
Market Stats Panel [Daveatt]█ Introduction
I've created a script that brings TradingView's watchlist stats panel functionality directly to your charts. This isn't just another performance indicator - it's a pixel-perfect (kidding) recreation of TradingView's native stats panel.
Important Notes
You might need to adjust manually the scaling the firs time you're using this script to display nicely all the elements.
█ Core Features
Performance Metrics
The panel displays key performance metrics (1W, 1M, 3M, 6M, YTD, 1Y) in real-time, with color-coded boxes (green for positive, red for negative) for instant performance assessment.
Display Modes
Switch seamlessly between absolute prices and percentage returns, making it easy to compare assets across different price scales.
Absolute mode
Percent mode
Historical Comparison
View year-over-year performance with color-coded lines, allowing for quick historical pattern recognition and analysis.
Data Structure Innovation
Let's talk about one of the most interesting challenges I faced. PineScript has this quirky limitation where request.security() can only return 127 tuples at most. £To work around this, I implemented a dual-request system. The first request handles indices 0-63, while the second one takes care of indices 64-127.
This approach lets us maintain extensive historical data without compromising script stability.
And here's the cool part: if you need to handle even more years of historical data, you can simply extend this pattern by adding more request.security() calls.
Each additional call can fetch another batch of monthly open prices and timestamps, following the same structure I've used.
Think of it as building with LEGO blocks - you can keep adding more pieces to extend your historical reach.
Flexible Date Range
Unlike many scripts that box you into specific timeframes, I've designed this one to be completely flexible with your date selection. You can set any start year, any end year, and the script will dynamically scale everything to match. The visual presentation automatically adjusts to whatever range you choose, ensuring your data is always displayed optimally.
█ Customization Options
Visual Settings
The panel's visual elements are highly customizable. You can adjust the panel width to perfectly fit your workspace, fine-tune the line thickness to match your preferences, and enjoy the pre-defined year color scheme that makes tracking historical performance intuitive and visually appealing.
Box Dimensions
Every aspect of the performance boxes can be tailored to your needs. Adjust their height and width, fine-tune the spacing between them, and position the entire panel exactly where you want it on your chart. The goal is to make this tool feel like it's truly yours.
█ Technical Challenges Solved
Polyline Precision
Creating precise polylines was perhaps the most demanding aspect of this project.
The challenge was ensuring accurate positioning across both time and price axes, while handling percentage mode scaling with precision.
The script constantly updates the current year's data in real-time, seamlessly integrating new information as it comes in.
Axis Management
Getting the axes right was like solving a complex puzzle. The Y-axis needed to scale dynamically whether you're viewing absolute prices or percentages.
The X-axis required careful month labeling that stays clean and readable regardless of your selected timeframe.
Everything needed to align perfectly while maintaining proper spacing in all conditions.
█ Final Notes
This tool transforms complex market data into clear, actionable insights. Whether you're day trading or analyzing long-term trends, it provides the information you need to make informed decisions. And remember, while we can't predict the future, we can certainly be better prepared for it with the right tools at hand.
A word of warning though - seeing those red numbers in a beautifully formatted panel doesn't make them any less painful! 😉
---
Happy Trading! May your charts be green and your stops be far away!
Daveatt
EMD Oscillator (Zeiierman)█ Overview
The Empirical Mode Decomposition (EMD) Oscillator is an advanced indicator designed to analyze market trends and cycles with high precision. It breaks down complex price data into simpler parts called Intrinsic Mode Functions (IMFs), allowing traders to see underlying patterns and trends that aren’t visible with traditional indicators. The result is a dynamic oscillator that provides insights into overbought and oversold conditions, as well as trend direction and strength. This indicator is suitable for all types of traders, from beginners to advanced, looking to gain deeper insights into market behavior.
█ How It Works
The core of this indicator is the Empirical Mode Decomposition (EMD) process, a method typically used in signal processing and advanced scientific fields. It works by breaking down price data into various “layers,” each representing different frequencies in the market’s movement. Imagine peeling layers off an onion: each layer (or IMF) reveals a different aspect of the price action.
⚪ Data Decomposition (Sifting): The indicator “sifts” through historical price data to detect natural oscillations within it. Each oscillation (or IMF) highlights a unique rhythm in price behavior, from rapid fluctuations to broader, slower trends.
⚪ Adaptive Signal Reconstruction: The EMD Oscillator allows traders to select specific IMFs for a custom signal reconstruction. This reconstructed signal provides a composite view of market behavior, showing both short-term cycles and long-term trends based on which IMFs are included.
⚪ Normalization: To make the oscillator easy to interpret, the reconstructed signal is scaled between -1 and 1. This normalization lets traders quickly spot overbought and oversold conditions, as well as trend direction, without worrying about the raw magnitude of price changes.
The indicator adapts to changing market conditions, making it effective for identifying real-time market cycles and potential turning points.
█ Key Calculations: The Math Behind the EMD Oscillator
The EMD Oscillator’s advanced nature lies in its high-level mathematical operations:
⚪ Intrinsic Mode Functions (IMFs)
IMFs are extracted from the data and act as the building blocks of this indicator. Each IMF is a unique oscillation within the price data, similar to how a band might be divided into treble, mid, and bass frequencies. In the EMD Oscillator:
Higher-Frequency IMFs: Represent short-term market “noise” and quick fluctuations.
Lower-Frequency IMFs: Capture broader market trends, showing more stable and long-term patterns.
⚪ Sifting Process: The Heart of EMD
The sifting process isolates each IMF by repeatedly separating and refining the data. Think of this as filtering water through finer and finer mesh sieves until only the clearest parts remain. Mathematically, it involves:
Extrema Detection: Finding all peaks and troughs (local maxima and minima) in the data.
Envelope Calculation: Smoothing these peaks and troughs into upper and lower envelopes using cubic spline interpolation (a method for creating smooth curves between data points).
Mean Removal: Calculating the average between these envelopes and subtracting it from the data to isolate one IMF. This process repeats until the IMF criteria are met, resulting in a clean oscillation without trend influences.
⚪ Spline Interpolation
The cubic spline interpolation is an advanced mathematical technique that allows smooth curves between points, which is essential for creating the upper and lower envelopes around each IMF. This interpolation solves a tridiagonal matrix (a specialized mathematical problem) to ensure that the envelopes align smoothly with the data’s natural oscillations.
To give a relatable example: imagine drawing a smooth line that passes through each peak and trough of a mountain range on a map. Spline interpolation ensures that line is as smooth and close to reality as possible. Achieving this in Pine Script is technically demanding and demonstrates a high level of mathematical coding.
⚪ Amplitude Normalization
To make the oscillator more readable, the final signal is scaled by its maximum amplitude. This amplitude normalization brings the oscillator into a range of -1 to 1, creating consistent signals regardless of price level or volatility.
█ Comparison with Other Signal Processing Methods
Unlike standard technical indicators that often rely on fixed parameters or pre-defined mathematical functions, the EMD adapts to the data itself, capturing natural cycles and irregularities in real-time. For example, if the market becomes more volatile, EMD adjusts automatically to reflect this without requiring parameter changes from the trader. In this way, it behaves more like a “smart” indicator, intuitively adapting to the market, unlike most traditional methods. EMD’s adaptive approach is akin to AI’s ability to learn from data, making it both resilient and robust in non-linear markets. This makes it a great alternative to methods that struggle in volatile environments, such as fixed-parameter oscillators or moving averages.
█ How to Use
Identify Market Cycles and Trends: Use the EMD Oscillator to spot market cycles that represent phases of buying or selling pressure. The smoothed version of the oscillator can help highlight broader trends, while the main oscillator reveals immediate cycles.
Spot Overbought and Oversold Levels: When the oscillator approaches +1 or -1, it may indicate that the market is overbought or oversold, signaling potential entry or exit points.
Confirm Divergences: If the price movement diverges from the oscillator's direction, it may indicate a potential reversal. For example, if prices make higher highs while the oscillator makes lower highs, it could be a sign of weakening trend strength.
█ Settings
Window Length (N): Defines the number of historical bars used for EMD analysis. A larger window captures more data but may slow down performance.
Number of IMFs (M): Sets how many IMFs to extract. Higher values allow for a more detailed decomposition, isolating smaller cycles within the data.
Amplitude Window (L): Controls the length of the window used for amplitude calculation, affecting the smoothness of the normalized oscillator.
Extraction Range (IMF Start and End): Allows you to select which IMFs to include in the reconstructed signal. Starting with lower IMFs captures faster cycles, while ending with higher IMFs includes slower, trend-based components.
Sifting Stopping Criterion (S-number): Sets how precisely each IMF should be refined. Higher values yield more accurate IMFs but take longer to compute.
Max Sifting Iterations (num_siftings): Limits the number of sifting iterations for each IMF extraction, balancing between performance and accuracy.
Source: The price data used for the analysis, such as close or open prices. This determines which price movements are decomposed by the indicator.
-----------------
Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
FVG Instantaneous Mitigation Signals [LuxAlgo]The FVG Instantaneous Mitigation Signals indicator detects and highlights "instantaneously" mitigated fair value gaps (FVG), that is FVGs that get mitigated one bar after their creation, returning signals upon mitigation.
Take profit/stop loss areas, as well as a trailing stop loss are also included to complement the signals.
🔶 USAGE
Instantaneous Fair Value Gap mitigation is a new concept introduced in this script and refers to the event of price mitigating a fair value gap one bar after its creation.
The resulting signal sentiment is opposite to the bias of the mitigated fair value gap. As such an instantaneously mitigated bearish FGV results in a bullish signal, while an instantaneously mitigated bullish FGV results in a bearish signal.
Fair value gap areas subject to instantaneous mitigation are highlighted alongside their average level, this level is extended until reached in a direction opposite to the FVG bias and can be used as a potential support/resistance level.
Users can filter out less volatile fair value gaps using the "FVG Width Filter" setting, with higher values highlighting more volatile fair value gaps subject to instantaneous mitigation.
🔹 TP/SL Areas
Users can enable take-profit/stop-loss areas. These are displayed upon a new signal formation, with an area starting from the mitigated FVG area average to this average plus/minus N ATRs, where N is determined by their respective multiplier settings.
Using a higher multiplier will return more distant areas from the price, requiring longer-term variations to be reached.
🔹 Trailing Stop Loss
A trailing-stop loss is included, increasing when the price makes a new higher high or lower low since the trailing has been set. Using a higher trailing stop multiplier will allow its initial position to be further away from the price, reducing its chances of being hit.
The trailing stop can be reset on "Every Signal", whether they are bullish or bearish, or only on an "Inverse Signal", which will reset the trailing when a signal of opposite bias is detected, this will preserve an existing trailing stop when a new signal of the same bias to the present one is detected.
🔶 DETAILS
Fair Value Gaps are ubiquitous to price action traders. These patterns arise when there exists a disparity between supply and demand. The action of price coming back and filling these imbalance areas is referred to as "mitigation" or "rebalancing".
"Instantaneous mitigation" refers to the event of price quickly mitigating a prior fair value gap, which in the case of this script is one bar after their creation. These events are indicative of a market more attentive to imbalances, and more willing to correct disparities in supply and demand.
If the market is particularly sensitive to imbalances correction then these can be excessively corrected, leading to further imbalances, highlighting a potential feedback process.
🔶 SETTINGS
FVG Width Filter: Filter out FVGs with thinner areas from returning a potential signal.
🔹 TP/SL
TP Area: Enable take-profit areas for new signals.
Multiplier: Control the distance from the take profit and the price, with higher values returning more distant TP's.
SL Area: Enable stop-loss areas for new signals.
Multiplier: Control the distance from the stop loss and the price, with higher values returning more distant SL's.
🔹 Trailing Stop
Reset Trailing Stop: Determines when the trailing stop is reset.
Multiplier: Controls the initial position of the trailing stop, with higher values returning more distant trailing stops.
Adaptive Trend Finder (log)In the dynamic landscape of financial markets, the Adaptive Trend Finder (log) stands out as an example of precision and professionalism. This advanced tool, equipped with a unique feature, offers traders a sophisticated approach to market trend analysis: the choice between automatic detection of the long-term or short-term trend channel.
Key Features:
1. Choice Between Long-Term or Short-Term Trend Channel Detection: Positioned first, this distinctive feature of the Adaptive Trend Finder (log) allows traders to customize their analysis by choosing between the automatic detection of the long-term or short-term trend channel. This increased flexibility adapts to individual trading preferences and changing market conditions.
2. Autonomous Trend Channel Detection: Leveraging the robust statistical measure of the Pearson coefficient, the Adaptive Trend Finder (log) excels in autonomously locating the optimal trend channel. This data-driven approach ensures objective trend analysis, reducing subjective biases, and enhancing overall precision.
3. Precision of Logarithmic Scale: A distinctive characteristic of our indicator is its strategic use of the logarithmic scale for regression channels. This approach enables nuanced analysis of linear regression channels, capturing the subtleties of trends while accommodating variations in the amplitude of price movements.
4. Length and Strength Visualization: Traders gain a comprehensive view of the selected trend channel, with the revelation of its length and quantification of trend strength. These dual pieces of information empower traders to make informed decisions, providing insights into both the direction and intensity of the prevailing trend.
In the demanding universe of financial markets, the Adaptive Trend Finder (log) asserts itself as an essential tool for traders, offering an unparalleled combination of precision, professionalism, and customization. Highlighting the choice between automatic detection of the long-term or short-term trend channel in the first position, this indicator uniquely caters to the specific needs of each trader, ensuring informed decision-making in an ever-evolving financial environment.
2Rsi buy & sell & candlesticks patterns in rsi[Trader's Journal]An Ingenious Trading Indicator: RSI, Japanese Candlesticks, and Buy/Sell Signals
The world of trading is a subtle game of analysis, where the smallest piece of information can make the difference between success and failure. In this perpetual quest to anticipate market movements, one indicator stands out: the Relative Strength Index (RSI), a powerful tool that measures the strength of price movements. However, RSI alone may not always suffice for informed trading decisions.
This is where our indicator comes into play, adding a new dimension to your analysis. The indicator skillfully combines RSI with Japanese candlesticks, those small candles rich in market movement information. The goal is clear: to generate buy and sell signals during trend reversals while keeping a keen eye on overbought and oversold zones.
RSI: Guardian of Extremes
The RSI is a basic tool that measures buying and selling pressure on an asset. It oscillates between 0 and 100, signaling overbought levels when the RSI exceeds 70 and oversold levels below 30. These extreme zones are often the stage for trend reversals, but timing is crucial.
Japanese Candlesticks: Messengers of the Market
Japanese candlesticks are more than just candles on a chart. They depict market emotions, reflecting the ongoing struggle between buyers and sellers. Trend reversals are typically heralded by specific candlestick patterns such as the Bearish Engulfing, Evening Star, or Inverted Hammer. These candlesticks act as powerful visual signals.
The Indicator in Action: Timing and Confirmation
When the RSI reaches the overbought zone (above 70) or oversold zone (below 30), our indicator is on alert. This is when vigilance is at its peak. However, buy and sell signals don't occur automatically. They await confirmation from Japanese candlesticks.
For a sell signal, the indicator awaits an exit from the overbought zone, followed by a bearish reversal candlestick. When these conditions are met, the sell signal is triggered. For a buy signal, the process is similar, but upon exiting the oversold zone and in the presence of a bullish candlestick.
The Elegance of the Combination
The beauty of this indicator lies in its ability to combine RSI analysis with the power of Japanese candlesticks. It doesn't just predict trend reversals, it does so elegantly, demanding visual confirmation, thus avoiding false signals.
As the market moves relentlessly, this indicator is your ally for making informed decisions. It reminds you that the wisdom of trading lies in combining different analytical tools to decipher the mysteries of the financial market. Envelop your trading strategies with this indicator, and witness how it can illuminate your path to success.
Open Interest Chart [LuxAlgo]The Open Interest Chart displays Commitments of Traders %change of futures open interest , with a unique circular plotting technique, inspired from this publication Periodic Ellipses .
🔶 USAGE
Open interest represents the total number of contracts that have been entered by market participants but have not yet been offset or delivered. This can be a direct indicator of market activity/liquidity, with higher open interest indicating a more active market.
Increasing open interest is highlighted in green on the circular plot, indicating money coming into the market, while decreasing open interests highlighted in red indicates money coming out of the market.
You can set up to 6 different Futures Open interest tickers for a quick follow up:
🔶 DETAILS
Circles are drawn, using plot() , with the functions createOuterCircle() (for the largest circle) and createInnerCircle() (for inner circles).
Following snippet will reload the chart, so the circles will remain at the right side of the chart:
if ta.change(chart.left_visible_bar_time ) or
ta.change(chart.right_visible_bar_time)
n := bar_index
Here is a snippet which will draw a 39-bars wide circle that will keep updating its position to the right.
//@version=5
indicator("")
n = bar_index
barsTillEnd = last_bar_index - n
if ta.change(chart.left_visible_bar_time ) or
ta.change(chart.right_visible_bar_time)
n := bar_index
createOuterCircle(radius) =>
var int end = na
var int start = na
var basis = 0.
barsFromNearestEdgeCircle = 0.
barsTillEndFromCircleStart = radius
startCylce = barsTillEnd % barsTillEndFromCircleStart == 0 // start circle
bars = ta.barssince(startCylce)
barsFromNearestEdgeCircle := barsTillEndFromCircleStart -1
basis := math.min(startCylce ? -1 : basis + 1 / barsFromNearestEdgeCircle * 2, 1) // 0 -> 1
shape = math.sqrt(1 - basis * basis)
rad = radius / 2
isOK = barsTillEnd <= barsTillEndFromCircleStart and barsTillEnd > 0
hi = isOK ? (rad + shape * radius) - rad : na
lo = isOK ? (rad - shape * radius) - rad : na
start := barsTillEnd == barsTillEndFromCircleStart ? n -1 : start
end := barsTillEnd == 0 ? start + radius : end
= createOuterCircle(40)
plot(h), plot(l)
🔶 LIMITATIONS
Due to the inability to draw between bars, from time to time, drawings can be slightly off.
Bar-replay can be demanding, since it has to reload on every bar progression. We don't recommend using this script on bar-replay. If you do, please choose the lowest speed and from time to time pause bar-replay for a second. You'll see the script gets reloaded.
🔶 SETTINGS
🔹 TICKERS
Toggle :
• Enabled -> uses the first column with a pre-filled list of Futures Open Interest tickers/symbols
• Disabled -> uses the empty field where you can enter your own ticker/symbol
Pre-filled list : the first column is filled with a list, so you can choose your open interest easily, otherwise you would see COT:088691_F_OI aka Gold Futures Open Interest for example.
If applicable, you will see 3 different COT data:
• COT: Legacy Commitments of Traders report data
• COT2: Disaggregated Commitments of Traders report data
• COT3: Traders in Financial Futures report data
Empty field : When needed, you can pick another ticker/symbol in the empty field at the right and disable the toggle.
Timeframe : Commitments of Traders (COT) data is tallied by the Commodity Futures Trading Commission (CFTC) and is published weekly. Therefore data won't change every day.
Default set TF is Daily
🔹 STYLE
From middle:
• Enabled (default): Drawings start from the middle circle -> towards outer circle is + %change , towards middle of the circle is - %change
• Disabled: Drawings start from the middle POINT of the circle, towards outer circle is + OR -
-> in both options, + %change will be coloured green , - %change will be coloured red .
-> 0 %change will be coloured blue , and when no data is available, this will be coloured gray .
Size circle : options tiny, small, normal, large, huge.
Angle : Only applicable if "From middle" is disabled!
-> sets the angle of the spike:
Show Ticker : Name of ticker, as seen in table, will be added to labels.
Text - fill
• Sets colour for +/- %change
Table
• Sets 2 text colours, size and position
Circles
• Sets the colour of circles, style can be changed in the Style section.
You can make it as crazy as you want:
Magic levelsIt is by far the simplest on chart presentation of Gann square of 9. It calculates the levels based on previous day closing. These levels usually acts as support and resistance.
Webhook Starter Kit [HullBuster]
Introduction
This is an open source strategy which provides a framework for webhook enabled projects. It is designed to work out-of-the-box on any instrument triggering on an intraday bar interval. This is a full featured script with an emphasis on actual trading at a brokerage through the TradingView alert mechanism and without requiring browser plugins.
The source code is written in a self documenting style with clearly defined sections. The sections “communicate” with each other through state variables making it easy for the strategy to evolve and improve. This is an excellent place for Pine Language beginners to start their strategy building journey. The script exhibits many Pine Language features which will certainly ad power to your script building abilities.
This script employs a basic trend follow strategy utilizing a forward pyramiding technique. Trend detection is implemented through the use of two higher time frame series. The market entry setup is a Simple Moving Average crossover. Positions exit by passing through conditional take profit logic. The script creates ten indicators including a Zscore oscillator to measure support and resistance levels. The indicator parameters are exposed through 47 strategy inputs segregated into seven sections. All of the inputs are equipped with detailed tool tips to help you get started.
To improve the transition from simulation to execution, strategy.entry and strategy.exit calls show enhanced message text with embedded keywords that are combined with the TradingView placeholders at alert time. Thereby, enabling a single JSON message to generate multiple execution events. This is genius stuff from the Pine Language development team. Really excellent work!
This document provides a sample alert message that can be applied to this script with relatively little modification. Without altering the code, the strategy inputs can alter the behavior to generate thousands of orders or simply a few dozen. It can be applied to crypto, stocks or forex instruments. A good way to look at this script is as a webhook lab that can aid in the development of your own endpoint processor, impress your co-workers and have hours of fun.
By no means is a webhook required or even necessary to benefit from this script. The setups, exits, trend detection, pyramids and DCA algorithms can be easily replaced with more sophisticated versions. The modular design of the script logic allows you to incrementally learn and advance this script into a functional trading system that you can be proud of.
Design
This is a trend following strategy that enters long above the trend line and short below. There are five trend lines that are visible by default but can be turned off in Section 7. Identified, in frequency order, as follows:
1. - EMA in the chart time frame. Intended to track price pressure. Configured in Section 3.
2. - ALMA in the higher time frame specified in Section 2 Signal Line Period.
3. - Linear Regression in the higher time frame specified in Section 2 Signal Line Period.
4. - Linear Regression in the higher time frame specified in Section 2 Signal Line Period.
5. - DEMA in the higher time frame specified in Section 2 Trend Line Period.
The Blue, Green and Orange lines are signal lines are on the same time frame. The time frame selected should be at least five times greater than the chart time frame. The Purple line represents the trend line for which prices above the line suggest a rising market and prices below a falling market. The time frame selected for the trend should be at least five times greater than the signal lines.
Three oscillators are created as follows:
1. Stochastic - In the chart time frame. Used to enter forward pyramids.
2. Stochastic - In the Trend period. Used to detect exit conditions.
3. Zscore - In the Signal period. Used to detect exit conditions.
The Stochastics are configured identically other than the time frame. The period is set in Section 2.
Two Simple Moving Averages provide the trade entry conditions in the form of a crossover. Crossing up is a long entry and down is a short. This is in fact the same setup you get when you select a basic strategy from the Pine editor. The crossovers are configured in Section 3. You can see where the crosses are occurring by enabling Show Entry Regions in Section 7.
The script has the capacity for pyramids and DCA. Forward pyramids are enabled by setting the Pyramid properties tab with a non zero value. In this case add on trades will enter the market on dips above the position open price. This process will continue until the trade exits. Downward pyramids are available in Crypto and Range mode only. In this case add on trades are placed below the entry price in the drawdown space until the stop is hit. To enable downward pyramids set the Pyramid Minimum Span In Section 1 to a non zero value.
This implementation of Dollar Cost Averaging (DCA) triggers off consecutive losses. Each loss in a run increments a sequence number. The position size is increased as a multiple of this sequence. When the position eventually closes at a profit the sequence is reset. DCA is enabled by setting the Maximum DCA Increments In Section 1 to a non zero value.
It should be noted that the pyramid and DCA features are implemented using a rudimentary design and as such do not perform with the precision of my invite only scripts. They are intended as a feature to stress test your webhook endpoint. As is, you will need to buttress the logic for it to be part of an automated trading system. It is for this reason that I did not apply a Martingale algorithm to this pyramid implementation. But, hey, it’s an open source script so there is plenty of room for learning and your own experimentation.
How does it work
The overall behavior of the script is governed by the Trading Mode selection in Section 1. It is the very first input so you should think about what behavior you intend for this strategy at the onset of the configuration. As previously discussed, this script is designed to be a trend follower. The trend being defined as where the purple line is predominately heading. In BiDir mode, SMA crossovers above the purple line will open long positions and crosses below the line will open short. If pyramiding is enabled add on trades will accumulate on dips above the entry price. The value applied to the Minimum Profit input in Section 1 establishes the threshold for a profitable exit. This is not a hard number exit. The conditional exit logic must be satisfied in order to permit the trade to close. This is where the effort put into the indicator calibration is realized. There are four ways the trade can exit at a profit:
1. Natural exit. When the blue line crosses the green line the trade will close. For a long position the blue line must cross under the green line (downward). For a short the blue must cross over the green (upward).
2. Alma / Linear Regression event. The distance the blue line is from the green and the relative speed the cross is experiencing determines this event. The activation thresholds are set in Section 6 and relies on the period and length set in Section 2. A long position will exit on an upward thrust which exceeds the activation threshold. A short will exit on a downward thrust.
3. Exponential event. The distance the yellow line is from the blue and the relative speed the cross is experiencing determines this event. The activation thresholds are set in Section 3 and relies on the period and length set in the same section.
4. Stochastic event. The purple line stochastic is used to measure overbought and over sold levels with regard to position exits. Signal line positions combined with a reading over 80 signals a long profit exit. Similarly, readings below 20 signal a short profit exit.
Another, optional, way to exit a position is by Bale Out. You can enable this feature in Section 1. This is a handy way to reduce the risk when carrying a large pyramid stack. Instead of waiting for the entire position to recover we exit early (bale out) as soon as the profit value has doubled.
There are lots of ways to implement a bale out but the method I used here provides a succinct example. Feel free to improve on it if you like. To see where the Bale Outs occur, enable Show Bale Outs in Section 7. Red labels are rendered below each exit point on the chart.
There are seven selectable Trading Modes available from the drop down in Section 1:
1. Long - Uses the strategy.risk.allow_entry_in to execute long only trades. You will still see shorts on the chart.
2. Short - Uses the strategy.risk.allow_entry_in to execute short only trades. You will still see long trades on the chart.
3. BiDir - This mode is for margin trading with a stop. If a long position was initiated above the trend line and the price has now fallen below the trend, the position will be reversed after the stop is hit. Forward pyramiding is available in this mode if you set the Pyramiding value in the Properties tab. DCA can also be activated.
4. Flip Flop - This is a bidirectional trading mode that automatically reverses on a trend line crossover. This is distinctively different from BiDir since you will get a reversal even without a stop which is advantageous in non-margin trading.
5. Crypto - This mode is for crypto trading where you are buying the coins outright. In this case you likely want to accumulate coins on a crash. Especially, when all the news outlets are talking about the end of Bitcoin and you see nice deep valleys on the chart. Certainly, under these conditions, the market will be well below the purple line. No margin so you can’t go short. Downward pyramids are enabled for Crypto mode when two conditions are met. First the Pyramiding value in the Properties tab must be non zero. Second the Pyramid Minimum Span in Section 1 must be non zero.
6. Range - This is a counter trend trading mode. Longs are entered below the purple trend line and shorts above. Useful when you want to test your webhook in a market where the trend line is bisecting the signal line series. Remember that this strategy is a trend follower. It’s going to get chopped out in a range bound market. By turning on the Range mode you will at least see profitable trades while stuck in the range. However, when the market eventually picks a direction, this mode will sustain losses. This range trading mode is a rudimentary implementation that will need a lot of improvement if you want to create a reliable switch hitter (trend/range combo).
7. No Trade. Useful when setting up the trend lines and the entry and exit is not important.
Once in the trade, long or short, the script tests the exit condition on every bar. If not a profitable exit then it checks if a pyramid is required. As mentioned earlier, the entry setups are quite primitive. Although they can easily be replaced by more sophisticated algorithms, what I really wanted to show is the diminished role of the position entry in the overall life of the trade. Professional traders spend much more time on the management of the trade beyond the market entry. While your trade entry is important, you can get in almost anywhere and still land a profitable exit.
If DCA is enabled, the size of the position will increase in response to consecutive losses. The number of times the position can increase is limited by the number set in Maximum DCA Increments of Section 1. Once the position breaks the losing streak the trade size will return the default quantity set in the Properties tab. It should be noted that the Initial Capital amount set in the Properties tab does not affect the simulation in the same way as a real account. In reality, running out of money will certainly halt trading. In fact, your account would be frozen long before the last penny was committed to a trade. On the other hand, TradingView will keep running the simulation until the current bar even if your funds have been technically depleted.
Entry and exit use the strategy.entry and strategy.exit calls respectfully. The alert_message parameter has special keywords that the endpoint expects to properly calculate position size and message sequence. The alert message will embed these keywords in the JSON object through the {{strategy.order.alert_message}} placeholder. You should use whatever keywords are expected from the endpoint you intend to webhook in to.
Webhook Integration
The TradingView alerts dialog provides a way to connect your script to an external system which could actually execute your trade. This is a fantastic feature that enables you to separate the data feed and technical analysis from the execution and reporting systems. Using this feature it is possible to create a fully automated trading system entirely on the cloud. Of course, there is some work to get it all going in a reliable fashion. Being a strategy type script place holders such as {{strategy.position_size}} can be embedded in the alert message text. There are more than 10 variables which can write internal script values into the message for delivery to the specified endpoint.
Entry and exit use the strategy.entry and strategy.exit calls respectfully. The alert_message parameter has special keywords that my endpoint expects to properly calculate position size and message sequence. The alert message will embed these keywords in the JSON object through the {{strategy.order.alert_message}} placeholder. You should use whatever keywords are expected from the endpoint you intend to webhook in to.
Here is an excerpt of the fields I use in my webhook signal:
"broker_id": "kraken",
"account_id": "XXX XXXX XXXX XXXX",
"symbol_id": "XMRUSD",
"action": "{{strategy.order.action}}",
"strategy": "{{strategy.order.id}}",
"lots": "{{strategy.order.contracts}}",
"price": "{{strategy.order.price}}",
"comment": "{{strategy.order.alert_message}}",
"timestamp": "{{time}}"
Though TradingView does a great job in dispatching your alert this feature does come with a few idiosyncrasies. Namely, a single transaction call in your script may cause multiple transmissions to the endpoint. If you are using placeholders each message describes part of the transaction sequence. A good example is closing a pyramid stack. Although the script makes a single strategy.close() call, the endpoint actually receives a close message for each pyramid trade. The broker, on the other hand, only requires a single close. The incongruity of this situation is exacerbated by the possibility of messages being received out of sequence. Depending on the type of order designated in the message, a close or a reversal. This could have a disastrous effect on your live account. This broker simulator has no idea what is actually going on at your real account. Its just doing the job of running the simulation and sending out the computed results. If your TradingView simulation falls out of alignment with the actual trading account lots of really bad things could happen. Like your script thinks your are currently long but the account is actually short. Reversals from this point forward will always be wrong with no one the wiser. Human intervention will be required to restore congruence. But how does anyone find out this is occurring? In closed systems engineering this is known as entropy. In practice your webhook logic should be robust enough to detect these conditions. Be generous with the placeholder usage and give the webhook code plenty of information to compare states. Both issuer and receiver. Don’t blindly commit incoming signals without verifying system integrity.
Setup
The following steps provide a very brief set of instructions that will get you started on your first configuration. After you’ve gone through the process a couple of times, you won’t need these anymore. It’s really a simple script after all. I have several example configurations that I used to create the performance charts shown. I can share them with you if you like. Of course, if you’ve modified the code then these steps are probably obsolete.
There are 47 inputs divided into seven sections. For the most part, the configuration process is designed to flow from top to bottom. Handy, tool tips are available on every field to help get you through the initial setup.
Step 1. Input the Base Currency and Order Size in the Properties tab. Set the Pyramiding value to zero.
Step 2. Select the Trading Mode you intend to test with from the drop down in Section 1. I usually select No Trade until I’ve setup all of the trend lines, profit and stop levels.
Step 3. Put in your Minimum Profit and Stop Loss in the first section. This is in pips or currency basis points (chart right side scale). Remember that the profit is taken as a conditional exit not a fixed limit. The actual profit taken will almost always be greater than the amount specified. The stop loss, on the other hand, is indeed a hard number which is executed by the TradingView broker simulator when the threshold is breached.
Step 4. Apply the appropriate value to the Tick Scalar field in Section 1. This value is used to remove the pipette from the price. You can enable the Summary Report in Section 7 to see the TradingView minimum tick size of the current chart.
Step 5. Apply the appropriate Price Normalizer value in Section 1. This value is used to normalize the instrument price for differential calculations. Basically, we want to increase the magnitude to significant digits to make the numbers more meaningful in comparisons. Though I have used many normalization techniques, I have always found this method to provide a simple and lightweight solution for less demanding applications. Most of the time the default value will be sufficient. The Tick Scalar and Price Normalizer value work together within a single calculation so changing either will affect all delta result values.
Step 6. Turn on the trend line plots in Section 7. Then configure Section 2. Try to get the plots to show you what’s really happening not what you want to happen. The most important is the purple trend line. Select an interval and length that seem to identify where prices tend to go during non-consolidation periods. Remember that a natural exit is when the blue crosses the green line.
Step 7. Enable Show Event Regions in Section 7. Then adjust Section 6. Blue background fills are spikes and red fills are plunging prices. These measurements should be hard to come by so you should see relatively few fills on the chart if you’ve set this up as intended. Section 6 includes the Zscore oscillator the state of which combines with the signal lines to detect statistically significant price movement. The Zscore is a zero based calculation with positive and negative magnitude readings. You want to input a reasonably large number slightly below the maximum amplitude seen on the chart. Both rise and fall inputs are entered as a positive real number. You can easily use my code to create a separate indicator if you want to see it in action. The default value is sufficient for most configurations.
Step 8. Turn off Show Event Regions and enable Show Entry Regions in Section 7. Then adjust Section 3. This section contains two parts. The entry setup crossovers and EMA events. Adjust the crossovers first. That is the Fast Cross Length and Slow Cross Length. The frequency of your trades will be shown as blue and red fills. There should be a lot. Then turn off Show Event Regions and enable Display EMA Peaks. Adjust all the fields that have the word EMA. This is actually the yellow line on the chart. The blue and red fills should show much less than the crossovers but more than event fills shown in Step 7.
Step 9. Change the Trading Mode to BiDir if you selected No Trades previously. Look on the chart and see where the trades are occurring. Make adjustments to the Minimum Profit and Stop Offset in Section 1 if necessary. Wider profits and stops reduce the trade frequency.
Step 10. Go to Section 4 and 5 and make fine tuning adjustments to the long and short side.
Example Settings
To reproduce the performance shown on the chart please use the following configuration: (Bitcoin on the Kraken exchange)
1. Select XBTUSD Kraken as the chart symbol.
2. On the properties tab set the Order Size to: 0.01 Bitcoin
3. On the properties tab set the Pyramiding to: 12
4. In Section 1: Select “Crypto” for the Trading Model
5. In Section 1: Input 2000 for the Minimum Profit
6. In Section 1: Input 0 for the Stop Offset (No Stop)
7. In Section 1: Input 10 for the Tick Scalar
8. In Section 1: Input 1000 for the Price Normalizer
9. In Section 1: Input 2000 for the Pyramid Minimum Span
10. In Section 1: Check mark the Position Bale Out
11. In Section 2: Input 60 for the Signal Line Period
12. In Section 2: Input 1440 for the Trend Line Period
13. In Section 2: Input 5 for the Fast Alma Length
14. In Section 2: Input 22 for the Fast LinReg Length
15. In Section 2: Input 100 for the Slow LinReg Length
16. In Section 2: Input 90 for the Trend Line Length
17. In Section 2: Input 14 Stochastic Length
18. In Section 3: Input 9 Fast Cross Length
19. In Section 3: Input 24 Slow Cross Length
20. In Section 3: Input 8 Fast EMA Length
21. In Section 3: Input 10 Fast EMA Rise NetChg
22. In Section 3: Input 1 Fast EMA Rise ROC
23. In Section 3: Input 10 Fast EMA Fall NetChg
24. In Section 3: Input 1 Fast EMA Fall ROC
25. In Section 4: Check mark the Long Natural Exit
26. In Section 4: Check mark the Long Signal Exit
27. In Section 4: Check mark the Long Price Event Exit
28. In Section 4: Check mark the Long Stochastic Exit
29. In Section 5: Check mark the Short Natural Exit
30. In Section 5: Check mark the Short Signal Exit
31. In Section 5: Check mark the Short Price Event Exit
32. In Section 5: Check mark the Short Stochastic Exit
33. In Section 6: Input 120 Rise Event NetChg
34. In Section 6: Input 1 Rise Event ROC
35. In Section 6: Input 5 Min Above Zero ZScore
36. In Section 6: Input 120 Fall Event NetChg
37. In Section 6: Input 1 Fall Event ROC
38. In Section 6: Input 5 Min Below Zero ZScore
In this configuration we are trading in long only mode and have enabled downward pyramiding. The purple trend line is based on the day (1440) period. The length is set at 90 days so it’s going to take a while for the trend line to alter course should this symbol decide to node dive for a prolonged amount of time. Your trades will still go long under those circumstances. Since downward accumulation is enabled, your position size will grow on the way down.
The performance example is Bitcoin so we assume the trader is buying coins outright. That being the case we don’t need a stop since we will never receive a margin call. New buy signals will be generated when the price exceeds the magnitude and speed defined by the Event Net Change and Rate of Change.
Feel free to PM me with any questions related to this script. Thank you and happy trading!
CFTC RULE 4.41
These results are based on simulated or hypothetical performance results that have certain inherent limitations. Unlike the results shown in an actual performance record, these results do not represent actual trading. Also, because these trades have not actually been executed, these results may have under-or over-compensated for the impact, if any, of certain market factors, such as lack of liquidity. Simulated or hypothetical trading programs in general are also subject to the fact that they are designed with the benefit of hindsight. No representation is being made that any account will or is likely to achieve profits or losses similar to these being shown.
Realtime Delta Volume Action [LucF]█ OVERVIEW
This indicator displays on-chart, realtime, delta volume and delta ticks information for each bar. It aims to provide traders who trade price action on small timeframes with volume and tick information gathered as updates come in the chart's feed. It builds its own candles, which are optimized to display volume delta information. It only works in realtime.
█ WARNING
This script is intended for traders who can already profitably trade discretionary on small timeframes. The high cost in fees and the excitement of trading at small timeframes have ruined many newcomers to trading. While trading at small timeframes can work magic for adrenaline junkies in search of thrills rather than profits, I DO NOT recommend it to most traders. Only seasoned discretionary traders able to factor in the relatively high cost of such a trading practice can ever hope to take money out of markets in that type of environment, and I would venture they account for an infinitesimal percentage of traders. If you are a newcomer to trading, AVOID THIS TOOL AT ALL COSTS — unless you are interested in experimenting with the interpretation of volume delta combined with price action. No tool currently available on TradingView provides this type of close monitoring of volume delta information, but if you are not already trading small timeframes profitably, please do not let yourself become convinced that it is the missing piece you needed. Avoid becoming a sucker who only contributes by providing liquidity to markets.
The information calculated by the indicator cannot be saved on charts, nor can it be recalculated from historical bars.
If you refresh the chart or restart the script, the accumulated information will be lost.
█ FEATURES
Key values
The script displays the following key values:
• Above the bar: ticks delta (DT), the total ticks for the bar, the percentage of total ticks that DT represents (DT%)
• Below the bar: volume delta (DV), the total volume for the bar, the percentage of total volume that DV represents (DV%).
Candles
Candles are composed of four components:
1. A top shaped like this: ┴, and a bottom shaped like this: ┬ (picture a normal Japanese candle without a body outline; the values used are the same).
2. The candle bodies are filled with the bull/bear color representing the polarity of DV. The intensity of the body's color is determined by the DV% value.
When DV% is 100, the intensity of the fill is brightest. This plays well in interpreting the body colors, as the smaller, less significant DV% values will produce less vivid colors.
3. The bright-colored borders of the candle bodies occur on "strong bars", i.e., bars meeting the criteria selected in the script's inputs, which you can configure.
4. The POC line is a small horizontal line that appears to the left of the candle. It is the volume-weighted average of all price updates during the bar.
Calculations
This script monitors each realtime update of the chart's feed. It first determines if price has moved up or down since the last update. The polarity of the price change, in turn, determines the polarity of the volume and tick for that specific update. If price does not move between consecutive updates, then the last known polarity is used. Using this method, we can calculate a running volume delta and ticks delta for the bar, which becomes the bar's final delta values when the bar closes (you can inspect values of elapsed realtime bars in the Data Window or the indicator's values). Note that these values will all reset if the script re-executes because of a change in inputs or a chart refresh.
While this method of calculating is not perfect, it is by far the most precise way of calculating volume delta available on TradingView at the moment. Calculating more precise results would require scripts to have access to tick data from any chart timeframe. Charts at seconds timeframes do use exchange/broker ticks when the feeds you are using allow for it, and this indicator will run on them, but tick data is not yet available from higher timeframes. Also, note that the method used in this script is far superior to the intrabar inspection technique used on historical bars in my other "Delta Volume" indicators. This is because volume and ticks delta here are calculated from many more realtime updates than the available intrabars in history. Unfortunately, the calculation method used here cannot be used on historical bars, where intrabar inspection remains, in my opinion, the optimal method.
Inputs
The script's inputs provide many ways to personalize all the components: what is displayed, the colors used to display the information, and the marker conditions. Tooltips provide details for many of the inputs; I leave their exploration to you.
Markers
Markers provide a way for you to identify the points of interest of your choice on the chart. You control the set of conditions that trigger each of the five available markers.
You select conditions by entering, in the field for each marker, the number of each condition you want to include, separated by a comma. The conditions are:
1 — The bar's polarity is up/dn.
2 — `close` rises/falls ("rises" means it is higher than its value on the previous bar).
3 — DV's polarity is +/–.
4 — DV% rises (↕).
5 — POC rises/falls.
6 — The quantity of realtime updates rises (↕).
7 — DV > limit (You specify the limit in the inputs. Since DV can be +/–, DV– must be less than `–limit` for a short marker).
8 — DV% > limit (↕).
9 — DV+ rises for a long marker, DV– falls for a short.
10 — Consecutive DV+/DV– on two bars.
11 — Total volume rises (↕).
12 — DT's polarity is +/–.
13 — DT% rises (↕).
14 — DT+ rises for a long marker, DT– falls for a short.
Conditions showing the (↕) symbol do not have symmetrical states; they act more like filters. If you only include condition 4 in a marker's setup, for example, both long and short markers will trigger on bars where DV% rises. To trigger only long or short markers, you must add a condition providing directional differentiation, such as conditions 1 or 2. Accordingly, you would enter "1,4" or "2,4".
For a marker to trigger, ALL the conditions you specified for it must be met. Long markers appear on the chart as "Mx▲" signs under the values displayed below candles. Short markers display "Mx▼" over the number of updates displayed above candles. The marker's number will replace the "x" in "Mx▲". The script loads with five markers that will not trigger because no conditions are associated with them. To activate markers, you will need to select and enter the set of conditions you require for each one.
Alerts
You can configure alerts on this script. They will trigger whenever one of the configured markers triggers. Alerts do not repaint, so they trigger at the bar's close—which is also when the markers will appear.
█ HOW TO USE IT
As a rule, I do not prescribe expected use of my indicators, as traders have proved to be much more creative than me in using them. Additionally, I tend to think that if you expect detailed recommendations from me to be able to use my indicators, it's a sign you are in a precarious situation and should go back to the drawing board and master the necessary basics that will allow you to explore and decide for yourself if my indicators can be useful to you, and how you will use them. I will make an exception for this thing, as it presents fairly novel information. I will use simple logic to surmise potential uses, as contrary to most of my other indicators, I have NOT used this one to actually trade. Markets have a way of throwing wrenches in our seemingly bullet-proof rationalizing, so drive cautiously and please forgive me if the pointers I share here don't pan out.
The first thing to do is to disable your normal bars. You can do this by clicking on the eye icon that appears when you hover over the symbol's name in the upper-left corner of your chart.
The absolute value and polarity of DV mean little without perspective; that's why I include both total volume for the bar and the percentage that DV represents of that total volume. I interpret a low DV% value as indecision. If you share that opinion, you could, let's say, configure one of the markers on "DV% > 80%", for example (to do so you would enter "8" in the condition field of any marker, and "80" in the limit field for condition 8, below the marker conditions).
I also like to analyze price action on the bar with DV%. Small DV% values should often produce small candle bodies. If a small DV% value occurs on a bar with much movement and high volume, I'm thinking "tough battle with potential explosive power when one side wins". Conversely, large bodies with high DV% mean that large volume is breaching through multiple levels, or that nobody is suddenly willing to take the other side of a normal volume of trades.
I find the POC lines really interesting. First, they tell us the price point where the most significant action (taking into account both price occurrences AND volume) during the bar occurred. Second, they can be useful when compared against past values. Third, their color helps us in figuring out which ones are the most significant. Unsurprisingly, bunches of orange POCs tend to appear in consolidation zones, in pauses, and before reversals. It may be useful to often focus more on POC progression than on `close` values. This is not to say that OHLC values are not useful; looking, as is customary, for higher highs or lower lows, or for repeated tests of precise levels can of course still be useful. I do like how POCs add another dimension to chart readings.
What should you do with the ticks delta above bars? Old-time ticker tape readers paid attention to the sounds coming from it (the "ticker" moniker actually comes from the sound they made). They knew activity was picking up when the frequency of the "ticks" increased. My thinking is that the total number of ticks will help you in the same way, since increasing updates usually mean growing interest—and thus perhaps price movement, as increasing volatility or volume would lead us to surmise. Ticks delta can help you figure out when proportionally large, random orders come in from traders with other perspectives than the short-term price action you are typically working with when you use this tool. Just as volume delta, ticks delta are one more informational component that can help you confirm convergence when building your opinions on price action.
What are strong bars? They are an attempt to identify significance. They are like a default marker, except that instead of displaying "Mx▲/▼" below/above the bar, the candle's body is outlined in bright bull/bear color when one is detected. Strong bars require a respectable amount of conditions to be met (you can see and re-configure them in the inputs). Think of them as pushes rather than indications of an upcoming, strong and multi-bar move. Pushes do, for sure, often occur at the beginning of strong trends. You will often see a few strong bars occur at 2-3 bar intervals at the beginning or middle of trends. But they also tend to occur at tops/bottoms, which makes their interpretation problematic. Another pattern that you will see quite frequently is a final strong bar in the direction of the trend, followed a few bars later by another strong bar in the reverse direction. My summary analyses seemed to indicate these were perhaps good points where one could make a bet on an early, risky reversal entry.
The last piece of information displayed by the indicator is the color of the candle bodies. Three possible colors are used. Bull/bear is determined by the polarity of DV, but only when the bar's polarity matches that of DV. When it doesn't, the color is the divergence color (orange, by default). Whichever color is used for the body, its intensity is determined by the DV% value. Maximum intensity occurs when DV%=100, so the more significant DV% values generate more noticeable colors. Body colors can be useful when looking to confirm the convergence of other components. The visual effect this creates hopefully makes it easier to detect patterns on the chart.
One obvious methodology that comes to mind to trade with this tool would be to use another indicator like Technical Ratings at a higher timeframe to identify the larger context's trend, and then use this tool to identify entries for short-term trades in that direction.
█ NOTES AND RAMBLINGS
Instant Calculations
This indicator uses instant values calculated on the bar only. No moving averages or calculations involving historical periods are used. The only exception to this rule is in some of the marker conditions like "Two consecutive DV+ values", where information from the previous bar is used.
Trading Small vs Long Timeframes
I never trade discretionary at the 5sec–5min timeframes this indicator was designed to be used with; I trade discretionary at 1D, 1W and 1M timeframes, and let systems trade at smaller timeframes. The higher the timeframe you trade at, the fewer fees you will pay because you trade less and are not churning trading volume, as is inevitable at smaller timeframes. Trading at higher timeframes is also a good way to gain an instant edge on most of the trading crowd that has its nose to the ground and often tends to forget the big picture. It also makes for a much less demanding trading practice, where you have lots of time to research and build your long-term opinions on potential future outcomes. While the future is always uncertain, I believe trades riding on long-term trends have stronger underlying support from the reality outside markets.
To traders who will ask why I publish an indicator designed for small timeframes, let me say that my main purpose here is to showcase what can be done with Pine. I often see comments by coders who are obviously not aware of what Pine is capable of in 2021. Since its humble beginnings seven years ago, Pine has grown and become a serious programming language. TradingView's growing popularity and its ongoing commitment to keep Pine accessible to newcomers to programming is gradually making Pine more and more of a standard in indicator and strategy programming. The technical barriers to entry for traders interested in owning their trading practice by developing their personal tools to trade have never been so low. I am also publishing this script because I value volume delta information, and I present here what I think is an original way of analyzing it.
Performance
The script puts a heavy load on the Pine runtime and the charting engine. After running the script for a while, you will often notice your chart becoming less responsive, and your chart tab can take longer to activate when you go back to it after using other tabs. That is the reason I encourage you to set the number of historical values displayed on bars to the minimum that meets your needs. When your chart becomes less responsive because the script has been running on it for many hours, refreshing the browser tab will restart everything and bring the chart's speed back up. You will then lose the information displayed on elapsed bars.
Neutral Volume
This script represents a departure from the way I have previously calculated volume delta in my scripts. I used the notion of "neutral volume" when inspecting intrabar timeframes, for bars where price did not move. No longer. While this had little impact when using intrabar inspection because the minimum usable timeframe was 1min (where bars with zero movement are relatively infrequent), a more precise way was required to handle realtime updates, where multiple consecutive prices often have the same value. This will usually happen whenever orders are unable to move across the bid/ask levels, either because of slow action or because a large-volume bid/ask level is taking time to breach. In either case, the proper way to calculate the polarity of volume delta for those updates is to use the last known polarity, which is how I calculate now.
The Order Book
Without access to the order book's levels (the depth of market), we are limited to analyzing transactions that come in the TradingView feed for the chart. That does not mean the volume delta information calculated this way is irrelevant; on the contrary, much of the information calculated here is not available in trading consoles supplied by exchanges/brokers. Yet it's important to realize that without access to the order book, you are forfeiting the valuable information that can be gleaned from it. The order book's levels are always in movement, of course, and some of the information they contain is mere posturing, i.e., attempts to influence the behavior of other players in the market by traders/systems who will often remove their orders when price comes near their order levels. Nonetheless, the order book is an essential tool for serious traders operating at intraday timeframes. It can be used to time entries/exits, to explain the causes of particular price movements, to determine optimal stop levels, to get to know the traders/systems you are betting against (they tend to exhibit behavioral patterns only recognizable through the order book), etc. This tool in no way makes the order book less useful; I encourage all intraday traders to become familiar with it and avoid trading without one.
Theil–Sen EstimatorThe Theil-Sen estimator is a nonparametric statistics method for robustly fitting a regression line to sample points (1,2).
As stated in the Wikipedia article (3), the method is " the most popular nonparametric technique for estimating a linear trend " in the applied sciences due to its robustness to outliers and limited assumptions regarding measurement errors.
Relation with other Methods
The Theil-Sen estimator can be significantly more accurate than simple linear regression (least squares) for skewed and heteroskedastic data.
Method Description
The script computes all the slopes between pairs of points and takes the median as the estimate of the regression slope, m . Subsequently, the intercept, b , is determined from the sample points as the median of y(i) − m x(i) values. The regression line in the slope–intercept form, y = m x + b , is then plotted along with the calculated prediction interval (estimated by means of the root-mean-square error).
I have added two options for how to handle pairs of points:
Method == "All" to use the slopes of all pairs of points;
Method == "Random" to use the slopes of randomly generated pairs of points.
The random choice of the pairs of points is based on the Wichmann–Hill is a pseudorandom number generator.
The reason for introducing the "Random" method is that the calculation of the median involves sorting the array of slopes (the size of N*(N-1)/2, where N is the number of sample points). This is a computationally demanding procedure, which runs into the limit on the cycle computation time (200 ms) set in TradingView. Therefore, the "All" method works only with Length < 50.
Also note that the number of lookback points is limited by by the maximum array size allowed in TradingView.
Literature
1. Sen, P. K. (1968) "Estimates of the regression coefficient based on Kendall's tau." JASA, 1379-1389.
2. Theil, H. (1950) "A rank-invariant method of linear and polynomial regression analysis." Reprinted in 1992 in Henri Theil’s contributions to economics and econometrics, Springer, 345-381.
3. en.wikipedia.org
Waindrops [Makit0]█ OVERALL
Plot waindrops (custom volume profiles) on user defined periods, for each period you get high and low, it slices each period in half to get independent vwap, volume profile and the volume traded per price at each half.
It works on intraday charts only, up to 720m (12H). It can plot balanced or unbalanced waindrops, and volume profiles up to 24H sessions.
As example you can setup unbalanced periods to get independent volume profiles for the overnight and cash sessions on the futures market, or 24H periods to get the full session volume profile of EURUSD
The purpose of this indicator is twofold:
1 — from a Chartist point of view, to have an indicator which displays the volume in a more readable way
2 — from a Pine Coder point of view, to have an example of use for two very powerful tools on Pine Script:
• the recently updated drawing limit to 500 (from 50)
• the recently ability to use drawings arrays (lines and labels)
If you are new to Pine Script and you are learning how to code, I hope you read all the code and comments on this indicator, all is designed for you,
the variables and functions names, the sometimes too big explanations, the overall structure of the code, all is intended as an example on how to code
in Pine Script a specific indicator from a very good specification in form of white paper
If you wanna learn Pine Script form scratch just start HERE
In case you have any kind of problem with Pine Script please use some of the awesome resources at our disposal: USRMAN , REFMAN , AWESOMENESS , MAGIC
█ FEATURES
Waindrops are a different way of seeing the volume and price plotted in a chart, its a volume profile indicator where you can see the volume of each price level
plotted as a vertical histogram for each half of a custom period. By default the period is 60 so it plots an independent volume profile each 30m
You can think of each waindrop as an user defined candlestick or bar with four key values:
• high of the period
• low of the period
• left vwap (volume weighted average price of the first half period)
• right vwap (volume weighted average price of the second half period)
The waindrop can have 3 different colors (configurable by the user):
• GREEN: when the right vwap is higher than the left vwap (bullish sentiment )
• RED: when the right vwap is lower than the left vwap (bearish sentiment )
• BLUE: when the right vwap is equal than the left vwap ( neutral sentiment )
KEY FEATURES
• Help menu
• Custom periods
• Central bars
• Left/Right VWAPs
• Custom central bars and vwaps: color and pixels
• Highly configurable volume histogram: execution window, ticks, pixels, color, update frequency and fine tuning the neutral meaning
• Volume labels with custom size and color
• Tracking price dot to be able to see the current price when you hide your default candlesticks or bars
█ SETTINGS
Click here or set any impar period to see the HELP INFO : show the HELP INFO, if it is activated the indicator will not plot
PERIOD SIZE (max 2880 min) : waindrop size in minutes, default 60, max 2880 to allow the first half of a 48H period as a full session volume profile
BARS : show the central and vwap bars, default true
Central bars : show the central bars, default true
VWAP bars : show the left and right vwap bars, default true
Bars pixels : width of the bars in pixels, default 2
Bars color mode : bars color behavior
• BARS : gets the color from the 'Bars color' option on the settings panel
• HISTOGRAM : gets the color from the Bearish/Bullish/Neutral Histogram color options from the settings panel
Bars color : color for the central and vwap bars, default white
HISTOGRAM show the volume histogram, default true
Execution window (x24H) : last 24H periods where the volume funcionality will be plotted, default 5
Ticks per bar (max 50) : width in ticks of each histogram bar, default 2
Updates per period : number of times the histogram will update
• ONE : update at the last bar of the period
• TWO : update at the last bar of each half period
• FOUR : slice the period in 4 quarters and updates at the last bar of each of them
• EACH BAR : updates at the close of each bar
Pixels per bar : width in pixels of each histogram bar, default 4
Neutral Treshold (ticks) : delta in ticks between left and right vwaps to identify a waindrop as neutral, default 0
Bearish Histogram color : histogram color when right vwap is lower than left vwap, default red
Bullish Histogram color : histogram color when right vwap is higher than left vwap, default green
Neutral Histogram color : histogram color when the delta between right and left vwaps is equal or lower than the Neutral treshold, default blue
VOLUME LABELS : show volume labels
Volume labels color : color for the volume labels, default white
Volume Labels size : text size for the volume labels, choose between AUTO, TINY, SMALL, NORMAL or LARGE, default TINY
TRACK PRICE : show a yellow ball tracking the last price, default true
█ LIMITS
This indicator only works on intraday charts (minutes only) up to 12H (720m), the lower chart timeframe you can use is 1m
This indicator needs price, time and volume to work, it will not work on an index (there is no volume), the execution will not be allowed
The histogram (volume profile) can be plotted on 24H sessions as limit but you can plot several 24H sessions
█ ERRORS AND PERFORMANCE
Depending on the choosed settings, the script performance will be highly affected and it will experience errors
Two of the more common errors it can throw are:
• Calculation takes too long to execute
• Loop takes too long
The indicator performance is highly related to the underlying volatility (tick wise), the script takes each candlestick or bar and for each tick in it stores the price and volume, if the ticker in your chart has thousands and thousands of ticks per bar the indicator will throw an error for sure, it can not calculate in time such amount of ticks.
What all of that means? Simply put, this will throw error on the BITCOIN pair BTCUSD (high volatility with tick size 0.01) because it has too many ticks per bar, but lucky you it will work just fine on the futures contract BTC1! (tick size 5) because it has a lot less ticks per bar
There are some options you can fine tune to boost the script performance, the more demanding option in terms of resources consumption is Updates per period , by default is maxed out so lowering this setting will improve the performance in a high way.
If you wanna know more about how to improve the script performance, read the HELP INFO accessible from the settings panel
█ HOW-TO SETUP
The basic parameters to adjust are Period size , Ticks per bar and Pixels per bar
• Period size is the main setting, defines the waindrop size, to get a better looking histogram set bigger period and smaller chart timeframe
• Ticks per bar is the tricky one, adjust it differently for each underlying (ticker) volatility wise, for some you will need a low value, for others a high one.
To get a more accurate histogram set it as lower as you can (min value is 1)
• Pixels per bar allows you to adjust the width of each histogram bar, with it you can adjust the blank space between them or allow overlaping
You must play with these three parameters until you obtain the desired histogram: smoother, sharper, etc...
These are some of the different kind of charts you can setup thru the settings:
• Balanced Waindrops (default): charts with waindrops where the two halfs are of same size.
This is the default chart, just select a period (30m, 60m, 120m, 240m, pick your poison), adjust the histogram ticks and pixels and watch
• Unbalanced Waindrops: chart with waindrops where the two halfs are of different sizes.
Do you trade futures and want to plot a waindrop with the first half for the overnight session and the second half for the cash session? you got it;
just adjust the period to 1860 for any CME ticker (like ES1! for example) adjust the histogram ticks and pixels and watch
• Full Session Volume Profile: chart with waindrops where only the first half plots.
Do you use Volume profile to analize the market? Lucky you, now you can trick this one to plot it, just try a period of 780 on SPY, 2760 on ES1!, or 2880 on EURUSD
remember to adjust the histogram ticks and pixels for each underlying
• Only Bars: charts with only central and vwap bars plotted, simply deactivate the histogram and volume labels
• Only Histogram: charts with only the histogram plotted (volume profile charts), simply deactivate the bars and volume labels
• Only Volume: charts with only the raw volume numbers plotted, simply deactivate the bars and histogram
If you wanna know more about custom full session periods for different asset classes, read the HELP INFO accessible from the settings panel
EXAMPLES
Full Session Volume Profile on MES 5m chart:
Full Session Unbalanced Waindrop on MNQ 2m chart (left side Overnight session, right side Cash Session):
The following examples will have the exact same charts but on four different tickers representing a futures contract, a forex pair, an etf and a stock.
We are doing this to be able to see the different parameters we need for plotting the same kind of chart on different assets
The chart composition is as follows:
• Left side: Volume Labels chart (period 10)
• Upper Right side: Waindrops (period 60)
• Lower Right side: Full Session Volume Profile
The first example will specify the main parameters, the rest of the charts will have only the differences
MES :
• Left: Period size: 10, Bars: uncheck, Histogram: uncheck, Execution window: 1, Ticks per bar: 2, Updates per period: EACH BAR,
Pixels per bar: 4, Volume labels: check, Track price: check
• Upper Right: Period size: 60, Bars: check, Bars color mode: HISTOGRAM, Histogram: check, Execution window: 2, Ticks per bar: 2,
Updates per period: EACH BAR, Pixels per bar: 4, Volume labels: uncheck, Track price: check
• Lower Right: Period size: 2760, Bars: uncheck, Histogram: check, Execution window: 1, Ticks per bar: 1, Updates per period: EACH BAR,
Pixels per bar: 2, Volume labels: uncheck, Track price: check
EURUSD :
• Upper Right: Ticks per bar: 10
• Lower Right: Period size: 2880, Ticks per bar: 1, Pixels per bar: 1
SPY :
• Left: Ticks per bar: 3
• Upper Right: Ticks per bar: 5, Pixels per bar: 3
• Lower Right: Period size: 780, Ticks per bar: 2, Pixels per bar: 2
AAPL :
• Left: Ticks per bar: 2
• Upper Right: Ticks per bar: 6, Pixels per bar: 3
• Lower Right: Period size: 780, Ticks per bar: 1, Pixels per bar: 2
█ THANKS TO
PineCoders for all they do, all the tools and help they provide and their involvement in making a better community
scarf for the idea of coding a waindrops like indicator, I did not know something like that existed at all
All the Pine Coders, Pine Pros and Pine Wizards, people who share their work and knowledge for the sake of it and helping others, I'm very grateful indeed
I'm learning at each step of the way from you all, thanks for this awesome community;
Opensource and shared knowledge: this is the way! (said with canned voice from inside my helmet :D)
█ NOTE
This description was formatted following THIS guidelines
═════════════════════════════════════════════════════════════════════════
I sincerely hope you enjoy reading and using this work as much as I enjoyed developing it :D
GOOD LUCK AND HAPPY TRADING!
Voss Predictor (A Peek Into the Future) - Dr. John EhlersI have been sitting on this for over a year, but I now present this "Voss Predictive Filter" multicator employing PSv4.0 upon initial release, originally formulated by the great and empowering Dr. John Ehlers for TASC - August 2019 Traders Tips. This is a slightly modified version of the original indicator John Ehlers designed. My improved implementation is an all-in-one combination of three indicators, consisting of Ehlers' 2-pole bandpass filter, fed into the Voss predictor, and my Correlation Color. I also purposefully attempted to make this indicator work on both "Light" and "Dark" charts equally well.
You can search for this indicator's white paper, entitled "A PEEK INTO THE FUTURE By John Ehlers", on his site in the educational reference section. It's VERY important that you fully grasp how this indicator works and when it doesn't during trending price movements. According to "TV House Rules", I can't link directly to his white paper on his web site. Technically he's a vendor, even though it has been divulged to me, that he is intending to retire after his last and final wØℾk$#Øp, where he is publicly disseminating the bulk of his unpublished proprietary code that drives his other website VERY SOON.
I love John Ehlers in a respectfully appreciative manner and he is my hero in life! I simply don't revel about pretended celebrities and supposed rock stars. I will never be able to adequately explain to you how much he has influenced me AND this website as it currently exists AND what is in store for the future of the ever evolving "Power of Pine". His inspiring legacy of code poetry shall forever be immortally enshrined here on TV and influence it.
Back to the topic of interest, this script originating from John Ehlers' mind... This indicator helps to anticipate cyclic turning points via negative group delay. It is NOT a predictive crystal ball. Do not become cluelessly disillusioned by it's title. I need to explain.
For example, this indicator could not have anticipated that the bold faced lie of "15 Days to Slow the Spread" of the CHImeravirus "plandemic" in the USA, would turn into our factual reality of multi state mandated orders demanding months of unconstitutional prison cell styled lockdowns with closures and the absurd criminalization of not wearing a mouth mask made from underwear while not being evidently ill, additionally combined with 24/7 black magick mass hypnosis spoon feeding non-scientific fear based psychological propaganda from the world's "finest" epidemiological data analysts and misleaders, eventually decimating the world's markets into zombie economies with abhorrent results of long term massive unemployment and financial hardship on a chart scale never before witnessed. Yep, it's NOT capable of predetermining any of that. I just wanted to make that very clear by example in a metaphorical manner many people can relate to concerning Voss' ability to anticipate.
The indicator consists of a bandpass filter coupled to the Voss predictor. Also, one thing about the Voss predictor, it can catch minute turning points or even false ones as explained in the white paper. So... I included my Correlation Color as a fitting companion to aid you in filtering out false signals during trending price movements. The Voss Predictive Filter should never be used alone, be forewarned!
Features List Includes:
Dark Background - Easily disabled in indicator Settings->Style for "Light" charts or with Pine commenting
AND a few more... Why list them, when you have the source code to explore!
When available time provides itself, I will consider your inquiries, thoughts, and concepts presented below in the comments section, should you have any questions or comments regarding this indicator. When my indicators achieve more prevalent use by TV members , I may implement more ideas when they present themselves as worthy additions. Have a profitable future everyone!
Example: Monte Carlo SimulationExperimental:
Example execution of Monte Carlo Simulation applied to the markets(this is my interpretation of the algo so inconsistencys may appear).
note:
the algorithm is very demanding so performance is limited.
[PX] Exhaustion LevelHello guys,
I love to play around with different methods for detecting support and resistance level. So today here is a new approach, which could be interesting to a few of you. I call it exhaustion level.
I'll give a brief introduction on how the indicator works and leave the testing/applying to you.
How does it work?
The method is basically very simple. The indicator constantly keeps track of the difference between the current close and the VWAP. The detected value will then be normalized and therefore put into comparison to it's previous "n" candles. (You decide yourself which value will be used for "n" by setting the "Length" -parameter in the settings tab.)
Once the normalized value equals "1", the price movement is considered to be somewhat overheated and the indicator starts plotting a level at the current high. The level will continually change until the movement goes the opposite way. Then it will settle and change its color.
The same approach takes place when the normalized value reaches "0", this time plotting a level at the low.
I hope some of you will find it useful and if so, please leave a " like " :)
Have fun, happy trading and merry Christmas :)))
AlgoWay GRSIM🧭 What this strategy tries to do
This strategy detects when a market move is losing strength and prepares for a potential reversal, but it waits for fresh momentum confirmation before acting.
It combines:
• RSI-based divergence (to spot exhaustion and potential turning points),
• Impulse MACD (to verify that the new direction actually has force behind it).
________________________________________
⚙️ When it takes trades
Long (Buy):
• A bullish RSI divergence appears (a clue that selling pressure is fading);
• Within a short time window, the Impulse MACD turns strongly positive;
• Optionally, the impulse line itself must be rising (if the Impulse Direction Filter is
enabled).
Short (Sell):
• A bearish RSI divergence appears (buying pressure fading);
• Within a short time window, the Impulse MACD turns strongly negative;
• Optionally, the impulse line must be falling (if the Impulse Direction Filter is enabled).
If momentum confirmation happens too late, the divergence “expires” and the signal is ignored.
________________________________________
🧩 How entries work
1. Reversal clue:
The strategy detects disagreement between price and RSI (price makes a new high/low, RSI doesn’t).
That suggests a shift in underlying strength.
2. Momentum confirmation:
Before entering, the Impulse MACD must agree — showing real push in the same direction.
3. Impulse direction filter (optional):
When enabled, the impulse itself must accelerate (rise for longs, fall for shorts), avoiding fake signals where price diverges but momentum is still fading.
4. No stacking:
It opens only one position at a time.
________________________________________
🚪 How exits work
Two main exit styles:
Conservative (default):
Longs close when impulse crosses below its signal line.
Shorts close when impulse crosses above its signal line.
✅ Keeps trades as long as momentum agrees.
Color-change (fast):
Longs close immediately when impulse flips bearish.
Shorts close immediately when impulse flips bullish.
⚡ Faster and more defensive.
Plus:
Stop Loss (%) and Take Profit (%) act as fixed-distance protective exits (set to 0 to disable either one).
________________________________________
📊 What you’ll see on the chart
A thick Impulse MACD line and thin signal line (oscillator view).
Diamonds — detected bullish/bearish divergence points.
Circles — where impulse crosses its signal (momentum change).
A performance panel (top-right) showing Net Profit, Trades, Win Rate, Profit Factor, Pessimistic PF, and Max Drawdown.
________________________________________
🔧 What you can tune
Signal Lifetime (bars): how long a divergence remains valid.
Impulse Direction Filter: ensure the impulse itself is moving in the trade’s direction.
Stop Loss / Take Profit (%): risk and target in percent.
Exit Style: conservative cross or faster color-change.
RSI / MA / Signal Lengths: adjust responsiveness (defaults are balanced).
________________________________________
💪 Strengths
Confirms reversals using momentum direction, not just divergence.
Avoids “early” signals where momentum is still fading.
Works symmetrically for longs and shorts.
Built-in stop/target protection.
Clear, visual confirmation of all logic components.
________________________________________
⚠️ Things to keep in mind
In sideways markets, the impulse can flip often — prefer conservative exits.
Too small SL/TP → constant stop-outs.
Too wide SL/TP → deep drawdowns.
Always test with different timeframes and markets.
________________________________________
💡 Practical tips
Start with default settings.
Enable “Use Impulse Direction Filter” in trending markets, disable it in very choppy ones.
Focus on Profit Factor, Win Rate, and Max Drawdown after several dozen trades.
Keep SL/TP roughly aligned with typical swing size.
“AlgoWay GRSIM” is a reversal-with-confirmation strategy: it spots likely turns, demands real momentum alignment (optionally verified by impulse direction), and manages exits with clear momentum cues plus built-in protective limits.
