Mercury Venus Conjunction Sextiles 2019-2026How to Use It and What It Means Astrologically
How to Use the Script in TradingView
This Pine Script, called "Mercury Venus Aspects 2019–2026," is made to highlight the dates of Mercury-Venus conjunctions (0°) and sextiles (60°) from 2019 to 2026 on TradingView charts. Here's how to use it:
click “Add to Chart.” It will apply to any chart you have open—stocks, forex, crypto, etc.
Customize the Display
You can turn on/off the visibility of conjunctions and sextiles using checkboxes under "Inputs" in the settings.
You can also adjust the label size (small, normal, large, or huge) for better readability on your chart.
What You’ll See on the Chart
Conjunctions appear as blue shaded zones with labels like “C1,” “C2,” etc. These mark dates when Mercury and Venus are at the same degree.
Sextiles show up in orange with labels like “S1,” “S2,” marking when they’re about 60° apart.
Each event spans a 2-day window (one day before and after the exact aspect).
How to Use It Practically
You can overlay the script on market charts to look for any patterns between these planetary aspects and price movements.
You can also use it to plan personal or financial activities, since these aspects often affect communication, money, and relationships.
What to Keep in Mind
Dates are approximate and based on average planetary cycles (Mercury: ~88 days, Venus: ~225 days). For exact timing, use an ephemeris.
Only conjunctions and sextiles are shown. Oppositions, squares, and trines aren’t included because Mercury and Venus never get far enough apart (more than 75°).
This script is great for astrologers, traders, and enthusiasts who want to see Mercury-Venus aspects directly on their charts and explore their possible effects.
Astrological Meaning of Mercury-Venus Aspects
What Mercury and Venus Represent
Mercury rules communication, thinking, technology, travel, and trade. In global events (mundane astrology), it affects media, markets, and movement of information.
Venus is about love, beauty, money, and pleasure. It influences relationships, aesthetics, and finance. In the world stage, it’s linked to luxury, art, fashion, and economic balance.
When Mercury and Venus form aspects (like conjunctions or sextiles), their energies mix in helpful ways that can affect people and events.
Conjunction (0°) – Mercury and Venus Together
These two planets are in the same sign and degree, so their qualities merge.
For people:
Positive: Smooth communication, charm, creativity, and better relationships. Great for romance, art, and social interaction.
Negative: Too much focus on appearances, sweet talk, or pleasure can cloud judgment. Decisions may lack depth.
For the economy:
Positive: Boosts in media, entertainment, fashion, and tech. Good for trade, deals, and optimism in financial markets.
Negative: Risk of overspending or unrealistic expectations. May cause small market bubbles or misleading hype.
Sextile (60°) – Mercury and Venus in Harmony
These two planets are two signs apart, creating a smooth, supportive energy.
For people:
Positive: Easy conversations, creative teamwork, small financial wins, and pleasant social experiences.
Negative: Energy is mild, so opportunities might be missed if not acted on. People may avoid hard decisions.
For the economy:
Positive: Gradual improvements in areas like marketing, social media, hospitality, and design. Good for diplomacy.
Negative: Lack of strong initiative could limit bigger gains. Minor missteps are possible due to a laid-back attitude.
General Effects
These aspects are mostly beneficial. They support creativity, financial thinking, and social harmony.
Downsides: Conjunctions may lead to overindulgence or shallow choices, while sextiles may cause missed chances due to low energy.
These aspects rarely cause major economic shifts on their own but can amplify trends depending on other planetary influences (like Saturn or Uranus).
Zodiac Sign Influence
Fire signs (Aries, Leo, Sagittarius): Bold communication, energetic spending, gains in media or entertainment.
Earth signs (Taurus, Virgo, Capricorn): Practical results, stable finances, growth in real-world assets like property or food.
Air signs (Gemini, Libra, Aquarius): Intellectual growth, tech innovation, and social ideas flourish.
Water signs (Cancer, Scorpio, Pisces): Emotional depth in conversations, artistic growth, and financial sensitivity.
Mercury-Venus aspects are gentle but helpful. They combine logic (Mercury) with emotion and value (Venus). They’re good times for love, communication, and money—but their benefits depend on how we use the energy. This script lets you easily track these moments on a chart and explore how they might align with real-life trends or decisions.
Disclaimer: This script and its interpretations are for informational and educational purposes only. They do not constitute financial, trading, or professional astrological advice. Always conduct your own research and consult qualified professionals before making any financial or personal decisions. Use at your own discretion.
Forecasting
Probability Grid [LuxAlgo]The Probability Grid tool allows traders to see the probability of where and when the next reversal would occur, it displays a 10x10 grid and/or dashboard with the probability of the next reversal occurring beyond each cell or within each cell.
🔶 USAGE
By default, the tool displays deciles (percentiles from 0 to 90), users can enable, disable and modify each percentile, but two of them must always be enabled or the tool will display an error message alerting of it.
The use of the tool is quite simple, as shown in the chart above, the further the price moves on the grid, the higher the probability of a reversal.
In this case, the reversal took place on the cell with a probability of 9%, which means that there is a probability of 91% within the square defined by the last reversal and this cell.
🔹 Grid vs Dashboard
The tool can display a grid starting from the last reversal and/or a dashboard at three predefined locations, as shown in the chart above.
🔶 DETAILS
🔹 Raw Data vs Normalized Data
By default the tool displays the normalized data, this means that instead of using the raw data (price delta between reversals) it uses the returns between each reversal, this is useful to make an apples to apples comparison of all the data in the dataset.
This can be seen in the left side of the chart above (BTCUSD Daily chart) where normalize data is disabled, the percentiles from 0 to 40 overlap and are indistinguishable from each other because the tool uses the raw price delta over the entire bitcoin history, with normalize data enabled as we can see in the right side of the chart we can have a fair comparison of the data over the entire history.
🔹 Probability Beyond or Within Each Cell
Two different probability modes are available, the default mode is Probability Beyond Each Cell, the number displayed in each cell is the probability of the next reversal to be located in the area beyond the cell, for example, if the cell displays 20%, it means that in the area formed by the square starting from the last reversal and ending at the cell, there is an 80% probability and outside that square there is a 20% probability for the location of the next reversal.
The second probability mode is the probability within each cell, this outlines the chance that the next reversal will be within the cell, as we can see on the right chart above, when using deciles as percentiles (default settings), each cell has the same 1% probability for the 10x10 grid.
🔶 SETTINGS
Swing Length: The maximum length in bars used to identify a swing
Maximum Reversals: Maximum number of reversals included in calculations
Normalize Data: Use returns between swings instead of raw price
Probability: Choose between two different probability modes: beyond and inside each cell
Percentiles: Enable/disable each of the ten percentiles and select the percentile number and line style
🔹 Dashboard
Show Dashboard: Enable or disable the dashboard
Position: Choose dashboard location
Size: Choose dashboard size
🔹 Style
Show Grid: Enable or disable the grid
Size: Choose grid text size
Colors: Choose grid background colors
Show Marks: Enable/disable reversal markers
SMT Divergence ICT 02 [TradingFinder] Smart Money Technique SMC🔵 Introduction
SMT Divergence (Smart Money Technique Divergence) is a price action-based trading concept that detects discrepancies in market behavior between two assets that are generally expected to move in the same direction. Rooted in ICT (Inner Circle Trader) methodology, this approach helps traders recognize subtle signs of market manipulation or imbalance, often ahead of traditional indicators.
The core idea behind SMT divergence is simple: when two correlated instruments—such as currency pairs, indices, or assets from the same sector—start forming different swing points (highs or lows), this can reveal a lack of confirmation in the trend. Such divergence is often a precursor to a price reversal or pause in momentum.
This technique works effectively across various markets including Forex, stocks, and cryptocurrencies. It’s particularly valuable when used alongside concepts like liquidity sweeps, market structure breaks (MSBs), or order block identification.
In advanced use cases, Sequential SMT helps uncover patterns of alternating divergences across sessions, often signaling engineered liquidity traps before price reacts.
When combined with the Quarterly Theory—which segments market behavior into Accumulation, Manipulation, Distribution, and Continuation/Reversal phases—traders gain insight not only into where divergence happens, but when it's most likely to be significant within the market cycle.
Bullish SMT :
Bullish SMT Divergence occurs when one asset prints a higher low while the correlated asset forms a lower low. This asymmetry often suggests that the downside move is losing strength, hinting at a potential bullish shift.
Bearish SMT :
Bearish SMT Divergence is formed when one asset creates a higher high, while the second asset fails to confirm by printing a lower high. This typically signals weakening bullish pressure and the possibility of a reversal to the downside.
🔵 How to Use
The SMT Divergence indicator is designed to detect imbalances between two positively correlated assets—such as major currency pairs, indices, or commodities. These divergences often indicate early signs of market inefficiency or smart money manipulation and can help traders anticipate trend shifts with higher precision.
Unlike traditional divergence indicators or earlier versions of this script, this upgraded version does not rely solely on consecutive pivot comparisons. Instead, it dynamically scans all available pivots within the chart to identify divergences at any structural level—major or minor—across the price action. This broader detection method increases the reliability and frequency of meaningful SMT signals.
Moreover, when integrated with Sequential SMT logic, the indicator is capable of identifying multiple divergence sequences across sessions. These sequences often signal engineered liquidity traps and can be mapped within the Quarterly Theory framework, allowing traders to pinpoint not just the presence of divergence but also the phase of the market cycle it appears in (Accumulation, Manipulation, Distribution, or Continuation).
🟣 Bullish SMT Divergence
This signal occurs when the primary asset forms a higher low, while the correlated asset forms a lower low. This pattern implies weakening bearish momentum and a potential shift to the upside.
If the correlated asset breaks its previous low but the primary asset does not, this divergence suggests absorption of selling pressure and possible accumulation by smart money—making it a strong bullish signal, especially when aligned with a favorable market phase (e.g., the end of a manipulation phase in Q2).
🟣 Bearish SMT Divergence
This signal occurs when the primary asset creates a higher high, while the correlated asset forms a lower high. This mismatch indicates fading bullish momentum and a potential reversal to the downside.
If the correlated asset fails to confirm a breakout made by the main asset, the divergence may point to distribution or exhaustion. When seen within Q3 or Q4 phases of the Quarterly Theory, this pattern often precedes sharp declines or fake-outs engineered by smart money
🔵 Settings
⚙️ Logical Settings
Symbol : Choose the secondary asset to compare with the main chart asset (e.g., XAUUSD, US100, GBPUSD).
Pivot Period : Sets the sensitivity of the pivot detection algorithm. A smaller value increases responsiveness to price swings.
Activate Max Pivot Back : When enabled, limits the maximum number of past pivots to be considered for divergence detection.
Max Pivot Back Length : Defines how many past pivots can be used (if the above toggle is active).
Pivot Sync Threshold : The maximum allowed difference (in bars) between pivots of the two assets for them to be compared.
Validity Pivot Length : Defines the time window (in bars) during which a divergence remains valid before it's considered outdated.
🎨 Display Settings
Show Bullish SMT Line : Draws a line connecting the bullish divergence points.
Show Bullish SMT Label : Displays a label on the chart when a bullish divergence is detected.
Bullish Color : Sets the color for bullish SMT markers (label, shape, and line).
Show Bearish SMT Line : Draws a line for bearish divergence.
Show Bearish SMT Label : Displays a label when a bearish SMT divergence is found.
Bearish Color : Sets the color for bearish SMT visual elements.
🔔 Alert Settings
Alert Name : Custom name for the alert messages (used in TradingView’s alert system).
Message Frequency :
All : Every signal triggers an alert.
Once Per Bar : Alerts once per bar regardless of how many signals occur.
Per Bar Close : Only triggers when the bar closes and the signal still exists.
Time Zone Display : Choose the time zone in which alert timestamps are displayed (e.g., UTC).
Bullish SMT Divergence Alert : Enable/disable alerts specifically for bullish signals.
Bearish SMT Divergence Alert : Enable/disable alerts specifically for bearish signals
🔵Conclusion
The SMT Plus indicator offers a refined and powerful approach to detecting smart money behavior through divergence analysis between correlated assets. By removing the limitations of consecutive pivot comparisons and allowing for broader structural detection, it captures more accurate and timely signals that often precede major market moves.
When paired with frameworks like Sequential SMT and the Quarterly Theory, the indicator not only highlights where divergence occurs, but also when in the market cycle it's most likely to matter. Its flexible settings, customizable visuals, and integrated alert system make it suitable for intraday scalpers, swing traders, and even long-term macro analysts.
Whether you're using it as a standalone decision-making tool or combining it with other ICT concepts, SMT Plus gives you an edge in recognizing manipulation, timing reversals, and staying in sync with the real market narrative—not just the chart.
Sessions with Mausa session high/low tracker that draws flat, horizontal lines for Asia, London, and New York trading sessions. It updates those levels in real time during each session, locks them in once the session ends, and keeps them on the chart for context.
At a glance, you always know:
Where each session’s highs and lows were set
Which session produced them (ASIA, LDN, NY labels float cleanly above the highs)
When price is approaching or reacting to prior session levels
🔹 Use Cases:
• Key Levels – See where Asia, London, or NY set boundaries, and watch how price respects or rejects them
• Breakout Zones – Monitor when price breaks above/below session highs/lows
• Session Structure – Know instantly if a move happened during London or NY without squinting at the clock
• Backtesting – Keep historic session levels on the chart for reference — nothing gets deleted
• Confluence – Align these levels with support/resistance, fibs, or liquidity zones
Simple, visual, no distractions — just session structure at a glance.
EMA-Based Squeeze Dynamics (Gap Momentum & EWMA Projection)EMA-Based Squeeze Dynamics (Gap Momentum & EWMA Projection)
🚨 Main Utility: Early Squeeze Warning
The primary function of this indicator is to warn traders early when the market is approaching a "squeeze"—a tightening condition that often precedes significant moves or regime shifts. By visually highlighting areas of increasing tension, it helps traders anticipate potential volatility and prepare accordingly. This is intended to be a statistically and psychologically grounded replacement of so-called "fib-time-zones," which are overly-deterministic and subjective.
📌 Overview
The EMA-Based Squeeze Dynamics indicator projects future regime shifts (such as golden and death crosses) using exponential moving averages (EMAs). It employs historical interval data and current market conditions to dynamically forecast when the critical EMAs (50-period and 200-period) will reconverge, marking likely trend-change points.
This indicator leverages two core ideas:
Behavioral finance theory: Traders often collectively anticipate popular EMA crossovers, creating a self-fulfilling prophecy (normative social influence), similar to findings from Solomon Asch’s conformity experiments.
Bayesian-like updates: It utilizes historical crossover intervals as a prior, dynamically updating expectations based on evolving market data, ensuring its signals remain objectively grounded in actual market behavior.
⚙️ Technical & Mathematical Explanation
1. EMA Calculations and Regime Definitions
The indicator uses three EMAs:
Fast (9-period): Represents short-term price movement.
Medial (50-period): Indicates medium-term trend direction.
Slow (200-period): Defines long-term market sentiment.
Regime States:
Bullish: 50 EMA is above the 200 EMA.
Bearish: 50 EMA is below the 200 EMA.
A shift between these states triggers visual markers (arrows and labels) directly on the chart.
2. Gap Dynamics and Historical Intervals
At each crossover:
The indicator records the gap (distance) between the 50 and 200 EMAs.
It tracks the historical intervals between past crossovers.
An Exponentially Weighted Moving Average (EWMA) of these intervals is calculated, weighting recent intervals more heavily, dynamically updating expectations.
Important note:
After every regime shift, the projected crossover line resets its calculation. This reset is visually evident as the projection line appears to move further away after each regime change, temporarily "repelled" until the EMAs begin converging again. This ensures projections remain realistic, grounded in actual EMA convergence, and prevents overly optimistic forecasts immediately after a regime shift.
3. Gap Momentum & Adaptive Scaling
The indicator measures how quickly or slowly the gap between EMAs is changing ("gap momentum") and adjusts its forecast accordingly:
If the gap narrows rapidly, a crossover becomes more imminent.
If the gap widens, the next crossover is pushed further into the future.
The "gap factor" dynamically scales the projection based on recent gap momentum, bounded between reasonable limits (0.7–1.3).
4. Squeeze Ratio & Background Color (Visual Cues)
A "squeeze ratio" is computed when market conditions indicate tightening:
In a bullish regime, if the fast EMA is below the medial EMA (price pulling back towards long-term support), the squeeze ratio increases.
In a bearish regime, if the fast EMA rises above the medial EMA (price rallying into long-term resistance), the squeeze ratio increases.
What the Background Colors Mean:
Red Background: Indicates a bullish squeeze—price is compressing downward, hinting a bullish reversal or continuation breakout may occur soon.
Green Background: Indicates a bearish squeeze—price is compressing upward, suggesting a bearish reversal or continuation breakout could soon follow.
Opacity Explanation:
The transparency (opacity) of the background indicates the intensity of the squeeze:
High Opacity (solid color): Strong squeeze, high likelihood of imminent volatility or regime shift.
Low Opacity (faint color): Mild squeeze, signaling early stages of tightening.
Thus, more vivid colors serve as urgent visual warnings that a squeeze is rapidly intensifying.
5. Projected Next Crossover and Pseudo Crossover Mechanism
The indicator calculates an estimated future bar when a crossover (and thus, regime shift) is expected to occur. This calculation incorporates:
Historical EWMA interval.
Current squeeze intensity.
Gap momentum.
A dynamic penalty based on divergence from baseline conditions.
The "Pseudo Crossover" Explained:
A key adaptive feature is the pseudo crossover mechanism. If price action significantly deviates from the projected crossover (for example, if price stays beyond the projected line longer than expected), the indicator acknowledges the projection was incorrect and triggers a "pseudo crossover" event. Essentially, this acts as a reset, updating historical intervals with a weighted adjustment to recalibrate future predictions. In other words, if the indicator’s initial forecast proves inaccurate, it recognizes this quickly, resets itself, and tries again—ensuring it remains responsive and adaptive to actual market conditions.
🧠 Behavioral Theory: Normative Social Influence
This indicator is rooted in behavioral finance theory, specifically leveraging normative social influence (conformity). Traders commonly watch EMA signals (especially the 50 and 200 EMA crossovers). When traders collectively anticipate these signals, they begin trading ahead of actual crossovers, effectively creating self-fulfilling prophecies—similar to Solomon Asch’s famous conformity experiments, where individuals adopted group behaviors even against direct evidence.
This behavior means genuine regime shifts (actual EMA crossovers) rarely occur until EMAs visibly reconverge due to widespread anticipatory trading activity. The indicator quantifies these dynamics by objectively measuring EMA convergence and updating projections accordingly.
📊 How to Use This Indicator
Monitor the background color and opacity as primary visual cues.
A strongly colored background (solid red/green) is an early alert that a squeeze is intensifying—prepare for potential volatility or a regime shift.
Projected crossover lines give a dynamic target bar to watch for trend reversals or confirmations.
After each regime shift, expect a reset of the projection line. The line may seem initially repelled from price action, but it will recalibrate as EMAs converge again.
Trust the pseudo crossover mechanism to automatically recalibrate the indicator if its original projection misses.
🎯 Why Choose This Indicator?
Early Warning: Visual squeeze intensity helps anticipate market breakouts.
Behaviorally Grounded: Leverages real trader psychology (conformity and anticipation).
Objective & Adaptive: Uses real-time, data-driven updates rather than static levels or subjective analysis.
Easy to Interpret: Clear visual signals (arrows, labels, colors) simplify trading decisions.
Self-correcting (Pseudo Crossovers): Quickly adjusts when initial predictions miss, maintaining accuracy over time.
Summary:
The EMA-Based Squeeze Dynamics Indicator combines behavioral insights, dynamic Bayesian-like updates, intuitive visual cues, and a self-correcting pseudo crossover feature to offer traders a reliable early warning system for market squeezes and impending regime shifts. It transparently recalibrates after each regime shift and automatically resets whenever projections prove inaccurate—ensuring you always have an adaptive, realistic forecast.
Whether you're a discretionary trader or algorithmic strategist, this indicator provides a powerful tool to navigate market volatility effectively.
Happy Trading! 📈✨
Half Causal EstimatorOverview
The Half Causal Estimator is a specialized filtering method that provides responsive averages of market variables (volume, true range, or price change) with significantly reduced time delay compared to traditional moving averages. It employs a hybrid approach that leverages both historical data and time-of-day patterns to create a timely representation of market activity while maintaining smooth output.
Core Concept
Traditional moving averages suffer from time lag, which can delay signals and reduce their effectiveness for real-time decision making. The Half Causal Estimator addresses this limitation by using a non-causal filtering method that incorporates recent historical data (the causal component) alongside expected future behavior based on time-of-day patterns (the non-causal component).
This dual approach allows the filter to respond more quickly to changing market conditions while maintaining smoothness. The name "Half Causal" refers to this hybrid methodology—half of the data window comes from actual historical observations, while the other half is derived from time-of-day patterns observed over multiple days. By incorporating these "future" values from past patterns, the estimator can reduce the inherent lag present in traditional moving averages.
How It Works
The indicator operates through several coordinated steps. First, it stores and organizes market data by specific times of day (minutes/hours). Then it builds a profile of typical behavior for each time period. For calculations, it creates a filtering window where half consists of recent actual data and half consists of expected future values based on historical time-of-day patterns. Finally, it applies a kernel-based smoothing function to weight the values in this composite window.
This approach is particularly effective because market variables like volume, true range, and price changes tend to follow recognizable intraday patterns (they are positive values without DC components). By leveraging these patterns, the indicator doesn't try to predict future values in the traditional sense, but rather incorporates the average historical behavior at those future times into the current estimate.
The benefit of using this "average future data" approach is that it counteracts the lag inherent in traditional moving averages. In a standard moving average, recent price action is underweighted because older data points hold equal influence. By incorporating time-of-day averages for future periods, the Half Causal Estimator essentially shifts the center of the filter window closer to the current bar, resulting in more timely outputs while maintaining smoothing benefits.
Understanding Kernel Smoothing
At the heart of the Half Causal Estimator is kernel smoothing, a statistical technique that creates weighted averages where points closer to the center receive higher weights. This approach offers several advantages over simple moving averages. Unlike simple moving averages that weight all points equally, kernel smoothing applies a mathematically defined weight distribution. The weighting function helps minimize the impact of outliers and random fluctuations. Additionally, by adjusting the kernel width parameter, users can fine-tune the balance between responsiveness and smoothness.
The indicator supports three kernel types. The Gaussian kernel uses a bell-shaped distribution that weights central points heavily while still considering distant points. The Epanechnikov kernel employs a parabolic function that provides efficient noise reduction with a finite support range. The Triangular kernel applies a linear weighting that decreases uniformly from center to edges. These kernel functions provide the mathematical foundation for how the filter processes the combined window of past and "future" data points.
Applicable Data Sources
The indicator can be applied to three different data sources: volume (the trading volume of the security), true range (expressed as a percentage, measuring volatility), and change (the absolute percentage change from one closing price to the next).
Each of these variables shares the characteristic of being consistently positive and exhibiting cyclical intraday patterns, making them ideal candidates for this filtering approach.
Practical Applications
The Half Causal Estimator excels in scenarios where timely information is crucial. It helps in identifying volume climaxes or diminishing volume trends earlier than conventional indicators. It can detect changes in volatility patterns with reduced lag. The indicator is also useful for recognizing shifts in price momentum before they become obvious in price action, and providing smoother data for algorithmic trading systems that require reduced noise without sacrificing timeliness.
When volatility or volume spikes occur, conventional moving averages typically lag behind, potentially causing missed opportunities or delayed responses. The Half Causal Estimator produces signals that align more closely with actual market turns.
Technical Implementation
The implementation of the Half Causal Estimator involves several technical components working together. Data collection and organization is the first step—the indicator maintains a data structure that organizes market data by specific times of day. This creates a historical record of how volume, true range, or price change typically behaves at each minute/hour of the trading day.
For each calculation, the indicator constructs a composite window consisting of recent actual data points from the current session (the causal half) and historical averages for upcoming time periods from previous sessions (the non-causal half). The selected kernel function is then applied to this composite window, creating a weighted average where points closer to the center receive higher weights according to the mathematical properties of the chosen kernel. Finally, the kernel weights are normalized to ensure the output maintains proper scaling regardless of the kernel type or width parameter.
This framework enables the indicator to leverage the predictable time-of-day components in market data without trying to predict specific future values. Instead, it uses average historical patterns to reduce lag while maintaining the statistical benefits of smoothing techniques.
Configuration Options
The indicator provides several customization options. The data period setting determines the number of days of observations to store (0 uses all available data). Filter length controls the number of historical data points for the filter (total window size is length × 2 - 1). Filter width adjusts the width of the kernel function. Users can also select between Gaussian, Epanechnikov, and Triangular kernel functions, and customize visual settings such as colors and line width.
These parameters allow for fine-tuning the balance between responsiveness and smoothness based on individual trading preferences and the specific characteristics of the traded instrument.
Limitations
The indicator requires minute-based intraday timeframes, securities with volume data (when using volume as the source), and sufficient historical data to establish time-of-day patterns.
Conclusion
The Half Causal Estimator represents an innovative approach to technical analysis that addresses one of the fundamental limitations of traditional indicators: time lag. By incorporating time-of-day patterns into its calculations, it provides a more timely representation of market variables while maintaining the noise-reduction benefits of smoothing. This makes it a valuable tool for traders who need to make decisions based on real-time information about volume, volatility, or price changes.
Sun Moon Conjunctions Trine Oppositions 2025this script is an astrological tool designed to overlay significant Sun-Moon aspect events for 2025 on a Bitcoin chart. It highlights key lunar phases and aspects—Conjunctions (New Moon) in blue, Squares in red, Oppositions (Full Moon) in purple, and Trines in green—using background colors and labeled markers. Users can toggle visibility for each aspect type and adjust label sizes via customizable inputs. The script accurately marks events from January through December 2025, with labels appearing once per event, making it a valuable resource for exploring potential correlations between lunar cycles and Bitcoin price movements.
Kondratieff Wave & Benner Business CyclesKondratieff Wave Theory
Description: The Kondratieff Wave, also known as K-Waves or Long Waves, is an economic theory that posits long-term cycles of approximately 40-60 years in capitalist economies. These cycles consist of four phases: Spring (expansion and recovery), Summer (prosperity and peak), Autumn (stagnation and recession), and Winter (depression and restructuring). The theory suggests that technological innovations and major economic shifts drive these waves, influencing periods of growth and decline over decades.
Creator Bio: Nikolai Dmitriyevich Kondratieff (1892–1938) was a Russian economist born in the Kostroma Governorate. He studied at the University of St. Petersburg and became a prominent figure in Soviet economics. Kondratieff developed his long-wave theory in the 1920s while analyzing historical economic data, publishing works like The Major Economic Cycles (1925). His ideas clashed with Soviet ideology, leading to his arrest in 1930 during Stalin’s purges. He was executed in 1938, but his work gained recognition posthumously, influencing modern economic cycle analysis.
Benner Cycle Theory
Description: The Benner Cycle, proposed by Samuel Benner, is a predictive model for business and commodity price cycles, focusing on shorter-term economic fluctuations. Benner identified recurring patterns in market peaks (highs), panics (crashes), and buying opportunities (lows), with cycles averaging 8-10 years for highs, 7-8 years for panics, and 8-9 years for buys. His theory, based on historical observations of U.S. markets, aimed to guide farmers and investors by forecasting periods of prosperity and distress.
Creator Bio: Samuel T. Benner (1830s–unknown) was an American farmer and businessman from Ohio, not a formally trained economist. After losing his fortune in the Panic of 1873, Benner turned to studying economic patterns. In 1875, he self-published Benner’s Prophecies of Future Ups and Downs in Prices, a book that charted cycles in pig iron prices and other commodities. His work gained a cult following among traders and remains studied for its empirical approach, despite Benner’s lack of academic credentials and limited biographical records.
RVOL Effort Matrix💪🏻 RVOL Effort Matrix is a tiered volume framework that translates crowd participation into structure-aware visual zones. Rather than simply flagging spikes, it measures each bar’s volume as a ratio of its historical average and assigns to that effort dynamic tiers, creating a real-time map of conviction , exhaustion , and imbalance —before price even confirms.
⚖️ At its core, the tool builds a histogram of relative volume (RVOL). When enabled, a second layer overlays directional effort by estimating buy vs sell volume using candle body logic. If the candle closes higher, green (buy) volume dominates. If it closes lower, red (sell) volume leads. These components are stacked proportionally and inset beneath a colored cap line—a small but powerful layer that maintains visibility of the true effort tier even when split bars are active. The cap matches the original zone color, preserving context at all times.
Coloration communicates rhythm, tempo, and potential turning points:
• 🔴 = structurally weak effort, i.e. failed moves, fake-outs or trend exhaustion
• 🟡 = neutral volume, as seen in consolidations or pullbacks
• 🟢 = genuine commitment, good for continuation, breakout filters, or early rotation signals
• 🟣 = explosive volume signaling either climax or institutional entry—beware!
Background shading (optional) mirrors these zones across the pane for structural scanning at a glance. Volume bars can be toggled between full-stack mode or clean column view. Every layer is modular—built for composability with tools like ZVOL or OBVX Conviction Bias.
🧐 Ideal Use-Cases:
• 🕰 HTF bias anchoring → LTF execution
• 🧭 Identifying when structure is being driven by real crowd pressure
• 🚫 Fading green/fuchsia bars that fail to break structure
• ✅ Riding green/fuchsia follow-through in directional moves
🍷 Recommended Pairings:
• ZVOL for statistically significant volume anomaly detection
• OBVX Conviction Bias ↔️ for directional confirmation of effort zones
• SUPeR TReND 2.718 for structure-congruent entry filtering
• ATR Turbulence Ribbon to distinguish expansion pressure from churn
🥁 RVOL Effort Matrix is all about seeing—how much pressure is behind a move, whether that pressure is sustainable, and whether the crowd is aligned with price. It's volume, but readable. It’s structure, but dynamic. It’s the difference between obeying noise and trading to the beat of the market.
OBVX Conviction Bias🧮 The OBVX Conviction Bias overlay tracks the flow of directional volume using the classic On-Balance Volume calculation, then filters it through a layered moving average system to expose crowd commitment , pressure transitions , and momentum fatigue . The tool applies two smoothed averages to the OBV line—a fast curve and a longer-term baseline scaled using Euler’s constant (2.718)—and visualizes their relationship using a color-coded crossover ribbon and pressure fills. When used correctly, it reveals whether a move is being supported by meaningful volume, or whether the crowd is starting to disengage.
🚦 The core signal compares OBV to its fast moving average. When OBV climbs above the short average, it fills green—suggesting real directional effort. When OBV sinks below, the fill turns maroon—flagging fading conviction or pullback potential. A second fill between the short and long OBV moving averages captures the broader trend of volume intention. If the short is above the long, this space fills greenish, showing constructive pressure. If it flips, the fill fades red, signaling crowd hesitation, rotation, or early exhaustion.
⚖️ All smoothing is user-selectable, defaulting to VWMA for effort-sensitive structure. The long-term average is auto-scaled using the natural exponential multiplier (2.718), offering rhythm that reflects the curve of participation. OBVX Conviction Bias isn’t trying to predict—it’s trying to show you where the crowd is leaning , and whether that lean is gaining traction or losing strength.
🧐 Ideal Use-Cases:
• Detect divergence between volume flow and price action
• Confirm breakout validity with volume alignment
• Fade breakouts where OBV fails to follow through
• Time pullback entries when OBV pressure resumes in trend direction
🍷 Recommended Pairings:
• ZVOL to measure whether volume is statistically significant or just noise (as shown)
• RVOL Effort Matrix to validate crowd effort by tier and structure zone
• SUPeR TReND 2.718 and/or MA Ribbons for directional confluence
• ATR Turbulence to track volatility-phase alignment with volume intention
DB - Global M2 Money Index (Pro Version)This professional-grade TradingView indicator plots a composite Global M2 Money Supply Index by aggregating the money supply (M2) of 21+ global economies—adjusted to USD via currency conversion. It helps traders and investors assess the global liquidity cycle and its potential leading relationship with asset classes like Bitcoin, equities, and gold.
This Pro version includes an optional 5-color dynamic heatmap gradient, manual color override, correlation table, and preset time offsets for popular assets to easily visualize delayed macro correlations.
✅ Key Features:
1. 💰 Global M2 Aggregation
Sources daily M2 data from:
US, EU, UK, China, Japan, Canada, Brazil, India, Russia, and more (21 total).
Adjusts all foreign M2 values to USD via FX pairs.
Normalizes total M2 data to trillions (divided by 1e12).
2. 🔀 Time Offset Options
Easily offset the M2 curve to match lagging or leading macro behavior.
Preset Offsets for key assets like:
Bitcoin (108 days), SOL (82), SUI (84), ETH (78), TSLA (77), QQQ (50), Gold (7), etc.
Or use Manual Offset (custom range: ±1000 days).
3. 🌈 Visual Heatmap (Optional)
Enable 5-Color Heatmap Gradient for dynamic insight:
Blue to Green to Yellow to Orange to Red.
Indicates relative M2 supply pressure over a 90-day range.
Or use a Manual Line Color for static visualizations.
4. 📈 Overlay Plotting
Plots the M2 curve directly on the chart (right-scale overlay).
Adjustable offset aligns the plot visually with price action trends.
5. 📋 Built-In Correlation Table
Auto-calculates and displays correlations between the asset’s price (HLC3) and the M2 index (with offset applied) across:
30, 60, 90, 180, 360, 540, and 720-day lookbacks.
Dynamic table includes:
Correlation % (color-coded: red for negative, green for strong positive).
Adjustable position (top/bottom/left/right).
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🔧 Customization Inputs:
Manual Time Offset (days)
Asset Offset: dropdown with preset lags
Enable 5-Color Heatmap
Manual Line Color
Table Position: full placement control
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📊 Use Case:
Perfect for macro-focused traders who want to:
Track global liquidity trends.
Time lagged macro correlations (e.g., M2 expansion → crypto rallies).
Confirm or dismiss liquidity-driven market regimes.
Quantify [Trading Model] | FractalystNote: In this description, "TM" refers to Trading Model (not trademark) and "EM" refers to Entry Model
What’s the indicator’s purpose and functionality?
You know how to identify market bias but always struggle with figuring out the best exit method, or even hesitating to take your trades?
I've been there. That's why I built this solution—once and for all—to help traders who know the market bias but need a systematic and quantitative approach for their entries and trade management.
A model that shows you real-time market probabilities and insights, so you can focus on execution with confidence—not doubt or FOMO.
How does this Quantify differentiate from Quantify ?
Have you managed to code or even found an indicator that identifies the market bias for you, so you don’t have to manually spend time analyzing the market and trend?
Then that’s exactly why you might need the Quantify Trading Model.
With the Trading Model (TM) version, the script automatically uses your given bias identification method to determine the trend (bull vs bear and neutral), detect the bias, and provide instant insight into the trades you could’ve taken.
To avoid complications from consecutive signals, it uses a kNN machine learning algorithm that processes market structure and probabilities to predict the best future patterns.
(You don’t have to deal with any complexity—it’s all taken care of for you.)
Quantify TM uses the k-Nearest Neighbors (kNN) machine learning algorithm to learn from historical market patterns and adapt to changing market structures. This means it can recognize similar market conditions from the past and apply those lessons to current trading decisions.
On the other hand, Quantify EM requires you to manually select your directional bias. It then focuses solely on generating entry signals based on that pre-determined bias.
While the entry model version (EM) uses your manual bias selection to determine the trend, it then provides insights into trades you could’ve taken and should be taking.
Trading Model (TM)
- Uses `input.source()` to incorporate your personal methodology for identifying market bias
- Automates everything—from bias detection to entry and exit decisions
- Adapts to market bias changes through kNN machine learning optimization
- Reduces human intervention in trading decisions, limiting emotional interference
Entry Model (EM)
- Focuses specifically on optimizing entry points within your pre-selected directional bias
- Requires manual input for determining market bias
- Provides entry signals without automating alerts or bias rules
Can the indicator be applied to any market approach/trading strategy?
Yes, if you have clear rules for identifying the market bias, then you can code your bias detection and then use the input.source() user input to retrieve the direction from your own indicator, then the Quantify uses machine-learning identify the best setups for you.
Here's an example:
//@version=6
indicator('Moving Averages Bias', overlay = true)
// Input lengths for moving averages
ma10_length = input.int(10, title = 'MA 10 Length')
ma20_length = input.int(20, title = 'MA 20 Length')
ma50_length = input.int(50, title = 'MA 50 Length')
// Calculate moving averages
ma10 = ta.sma(close, ma10_length)
ma20 = ta.sma(close, ma20_length)
ma50 = ta.sma(close, ma50_length)
// Identify bias
var bias = 0
if close > ma10 and close > ma20 and close > ma50 and ma10 > ma20 and ma20 > ma50
bias := 1 // Bullish
bias
else if close < ma10 and close < ma20 and close < ma50 and ma10 < ma20 and ma20 < ma50
bias := -1 // Bearish
bias
else
bias := 0 // Neutral
bias
// Plot the bias
plot(bias, title = 'Identified Bias', color = color.blue,display = display.none)
Once you've created your custom bias indicator, you can integrate it with Quantify :
- Add your bias indicator to your chart
- Open the Quantify settings
- Set the Bias option to "Auto"
- Select your custom indicator as the bias source
The machine learning algorithms will then analyze historical price action and identify optimal setups based on your defined bias parameters. Performance statistics are displayed in summary tables, allowing you to evaluate effectiveness across different timeframes.
Can the indicator be used for different timeframes or trading styles?
Yes, regardless of the timeframe you’d like to take your entries, the indicator adapts to your trading style.
Whether you’re a swing trader, scalper, or even a position trader, the algorithm dynamically evaluates market conditions across your chosen timeframe.
How Quantify Helps You Trade Profitably?
The Quantify Trading Model offers several powerful features that can significantly improve your trading profitability when used correctly:
Real-Time Edge Assessment
It displays real-time probability of price moving in your favor versus hitting your stoploss
This gives you immediate insight into risk/reward dynamics before entering trades
You can make more informed decisions by knowing the statistical likelihood of success
Historical Edge Validation
Instantly shows whether your trading approach has demonstrated an edge in historical data
Prevents you from trading setups that historically haven't performed well
Gives confidence when entering trades that have proven statistical advantages
Optimized Position Sizing
Analyzes each setup's success rate to determine the adjusted Kelly criterion formula
Customizes position sizing based on your selected maximum drawdown tolerance
Helps prevent account-destroying losses while maximizing growth potential
Advanced Exit Management
Utilizes market structure-based trailing stop-loss mechanisms
Maximizes the average risk-reward ratio profit per winning trade
Helps capture larger moves while protecting gains during market reversals
Emotional Discipline Enforcement
Eliminates emotional bias by adhering to your pre-defined rules for market direction
Prevents impulsive decisions by providing objective entry and exit signals
Creates psychological distance between your emotions and trading decisions
Overtrading Prevention
Highlights only setups that demonstrate positive expectancy
Reduces frequency of low-probability trades
Conserves capital for higher-quality opportunities
Systematic Approach Benefits
By combining machine learning algorithms with your personal bias identification methods, Quantify helps transform discretionary trading approaches into more systematic, probability-based strategies.
What Entry Models are used in Quantify Trading Model version?
The Quantify Trading Model utilizes two primary entry models to identify high-probability trade setups:
Breakout Entry Model
- Identifies potential trade entries when price breaks through significant swing highs and swing lows
- Captures momentum as price moves beyond established trading ranges
- Particularly effective in trending markets when combined with the appropriate bias detection
- Optimized by machine learning to filter false breakouts based on historical performance
Fractals Entry Model
- Utilizes fractal patterns to identify potential reversal or continuation points
- Also uses swing levels to determine optimal entry locations
- Based on the concept that market structure repeats across different timeframes
- Identifies local highs and lows that form natural entry points
- Enhanced by machine learning to recognize the most profitable fractal formations
- These entry models work in conjunction with your custom bias indicator to ensure trades are taken in the direction of the overall market trend. The machine learning component analyzes historical performance of these entry types across different market conditions to optimize entry timing and signal quality.
How Does This Indicator Identify Market Structure?
1. Swing Detection
• The indicator identifies key swing points on the chart. These are local highs or lows where the price reverses direction, forming the foundation of market structure.
2. Structural Break Validation
• A structural break is flagged when a candle closes above a previous swing high (bullish) or below a previous swing low (bearish).
• Break Confirmation Process:
To confirm the break, the indicator applies the following rules:
• Valid Swing Preceding the Break: There must be at least one valid swing point before the break.
3. Numeric Labeling
• Each confirmed structural break is assigned a unique numeric ID starting from 1.
• This helps traders track breaks sequentially and analyze how the market structure evolves over time.
4. Liquidity and Invalidation Zones
• For every confirmed structural break, the indicator highlights two critical zones:
1. Liquidity Zone (LIQ): Represents the structural liquidity level.
2. Invalidation Zone (INV): Acts as Invalidation point if the structure fails to hold.
How does the trailing stop-loss work? what are the underlying calculations?
A trailing stoploss is a dynamic risk management tool that moves with the price as the market trend continues in the trader’s favor. Unlike a fixed take profit, which stays at a set level, the trailing stoploss automatically adjusts itself as the market moves, locking in profits as the price advances.
In Quantify, the trailing stoploss is enhanced by incorporating market structure liquidity levels (explain above). This ensures that the stoploss adjusts intelligently based on key price levels, allowing the trader to stay in the trade as long as the trend remains intact, while also protecting profits if the market reverses.
What is the Kelly Criterion, and how does it work in Quantify?
The Kelly Criterion is a mathematical formula used to determine the optimal position size for each trade, maximizing long-term growth while minimizing the risk of large drawdowns. It calculates the percentage of your portfolio to risk on a trade based on the probability of winning and the expected payoff.
Quantify integrates this with user-defined inputs to dynamically calculate the most effective position size in percentage, aligning with the trader’s risk tolerance and desired exposure.
How does Quantify use the Kelly Criterion in practice?
Quantify uses the Kelly Criterion to optimize position sizing based on the following factors:
1. Confidence Level: The model assesses the confidence level in the trade setup based on historical data and sample size. A higher confidence level increases the suggested position size because the trade has a higher probability of success.
2. Max Allowed Drawdown (User-Defined): Traders can set their preferred maximum allowed drawdown, which dictates how much loss is acceptable before reducing position size or stopping trading. Quantify uses this input to ensure that risk exposure aligns with the trader’s risk tolerance.
3. Probabilities: Quantify calculates the probabilities of success for each trade setup. The higher the probability of a successful trade (based on historical price action and liquidity levels), the larger the position size suggested by the Kelly Criterion.
How can I get started to use the indicator?
1. Set Your Market Bias
• Choose Auto.
• Select the source you want Quantify to use as for bias identification method (explained above)
2. Choose Your Entry Timeframes
• Specify the timeframes you want to focus on for trade entries.
• The indicator will dynamically analyze these timeframes to provide optimal setups.
3. Choose Your Entry Model and BE/TP Levels
• Choose a model that suits your personality
• Choose a level where you'd like the script to take profit or move stop-loss to BE
4. Set and activate the alerts
What tables are used in the Quantify?
• Quarterly
• Monthly
• Weekly
Terms and Conditions | Disclaimer
Our charting tools are provided for informational and educational purposes only and should not be construed as financial, investment, or trading advice. They are not intended to forecast market movements or offer specific recommendations. Users should understand that past performance does not guarantee future results and should not base financial decisions solely on historical data.
Built-in components, features, and functionalities of our charting tools are the intellectual property of @Fractalyst Unauthorized use, reproduction, or distribution of these proprietary elements is prohibited.
- By continuing to use our charting tools, the user acknowledges and accepts the Terms and Conditions outlined in this legal disclaimer and agrees to respect our intellectual property rights and comply with all applicable laws and regulations.
DB - CME Gap [Multi Asset Auto Detection: BTC,SOL, etc]DB - CME Gap is a pro-grade, zero-maintenance CME gap tracker designed for serious traders.
This script automatically detects unfilled CME futures gaps across a wide range of assets—crypto, equities, bonds, commodities, FX, and agriculture—by pulling the official Friday close from CME’s daily futures data. It visually highlights unfilled weekend gaps and keeps them active on the chart until the price fully crosses through the gap level, offering a reliable view of market inefficiencies that often attract future liquidity.
Whether you're trading BTC, ES, CL, ZN, 6E, or ZC... this tool auto-detects and adjusts to the asset you're charting, so you don’t need to change any settings.
🧠 Key Benefits
Fully Automated – No symbol selection required; works instantly across asset classes
Professional Grade – Clean, minimal visuals with dynamic gap tracking
Always Accurate – Uses CME official daily closes to identify true weekend gaps
Cross-Market Versatility – Supports a broad range of assets without editing code
✅ Features
🔍 Auto Symbol Detection
Automatically identifies whether you're viewing BTC, ETH, SOL, ES, NQ, CL, ZN, 6E, GC, ZC, and more—no input required.
📅 CME Friday Close Logic
Pulls the actual Friday close from CME's daily data to detect accurate gap reference points.
🚨 Weekend Gap Detection
Monitors Friday after-hours, Saturday, and Sunday to detect gaps between CME close and weekend price action.
🧠 Persistent Gap Tracking
Gaps remain active until price fully crosses the gap level—no false closures.
📈 Dynamic Line Drawing
Draws a horizontal line at the gap price and extends it to the point of fill.
🌈 Custom Gradient Shading
Fills the area between the current price and the CME gap with directional color gradients based on price movement.
🎨 User-Configurable Colors
Adjust bull and bear fill color themes to suit your personal style.
🧩 Compatible with All Major Asset Classes
Works with:
Crypto: BTC, ETH, SOL
Equities: ES, NQ, YM, MES, MNQ
Bonds & Rates: ZN, ZB, ZF, ZT, GE
Commodities: CL, GC, NG, BZ, SI
FX: 6E, 6J, 6B
Ags: ZC (Corn), ZS (Soybeans)
BB Sidecar CalculatorBB Sidecar Calculator
Visual trade planner and dynamic risk-to-reward tool
Overview
The BB Sidecar Calculator is a precision planning tool designed to help traders visualize risk, reward, and position sizing directly on their charts. By inputting basic trade parameters, the indicator calculates stop-loss distance, potential profit targets in R multiples, and total dollar risk or gain based on the instrument type and lot size. It supports a wide range of assets including futures, forex, and equities.
Features
• Manually input or click-to-place entry and stop levels directly on the chart
• Drag and adjust levels dynamically with real-time updates to targets and risk values
• Automatic detection of long or short direction based on entry vs. stop placement
• Supports optional Max Dollar Risk setting to cap trade risk based on your account limits
• Configurable number of R-multiple targets (1R to 10R)
• Instrument-aware calculations with pip support for forex and point-based logic for stocks and futures
• Adjustable label display with configurable text size, color, and price precision
• Customizable currency symbol to match your account denomination
How to Use
1. When you first add the indicator, click on the chart to place your Entry and Stop levels.
2. The indicator will automatically determine whether the trade is Long or Short.
3. Drag either level up or down to adjust your setup visually.
4. Set your Lot Size and optionally define a Max $ Risk value.
5. The indicator will display:
• Entry line with lot size label
• Stop line with dollar risk and distance
• Up to 10 risk-multiple profit targets (1R, 2R, etc.)
Max Risk Logic
When a value is entered for Max $ Risk, the indicator calculates the maximum price difference you can afford based on your lot size and instrument type. It will then:
• Calculate a stop-loss price that aligns with your risk cap
• Compare this with the user-defined stop price
• Select the more conservative stop (the one with less dollar risk)
• Display updated profit targets based on the selected stop level
For forex pairs, pip value and pip size are accounted for in risk calculations. For stocks and futures, point value is used.
If Max $ Risk is set to 0, the indicator uses your manually defined stop price exclusively.
Notes
• Labels and visuals are rendered only on the latest bar for clarity
• Supports various decimal precision levels for accurate price formatting
• Designed for use in planning, not live trade execution
• Works across multiple timeframes and instrument types
BeSight Mega SpotBeSight Mega Spot – Zone Based Price Grid Indicator
สคริปต์นี้ถูกออกแบบมาเพื่อช่วยเทรดเดอร์มองเห็นโซนราคาสำคัญที่ราคาอาจเกิดปฏิกิริยา โดยอ้างอิงจากระดับราคาที่ลงท้ายด้วย 0 และ 5 (เช่น 1350, 1355, 1360 เป็นต้น) ซึ่งมักเป็นระดับที่มีการตั้งคำสั่งซื้อขายจำนวนมากในตลาด
BeSight Mega Spot – Zone-Based Price Grid Indicator
This indicator is designed to help traders visualize key price zones where the market often reacts, based on price levels ending with 0 or 5 (e.g., 1350, 1355, 1360). These levels are commonly used for pending orders, liquidity, or price clustering zones.
It displays horizontal grid lines at fixed step intervals (default: every 5 points), covering the entire visible price range of the chart. Each price level is labeled for better clarity and planning.
🟦 Blue lines: Price levels ending in 0
⬜ Gray lines: Price levels ending in 5
This tool is useful for identifying potential institutional behavior zones, price consolidation, accumulation/distribution areas, or psychological support/resistance levels.
🧠 Notes:
- This indicator is not a buy/sell signal tool or predictive system.
- It works best when used in conjunction with other technical tools such as Supply/Demand zones or Smart Money Concepts (SMC) analysis.
- Compatible with all instruments: stocks, futures, forex, crypto, etc.
✅ How to use:
1. Add the indicator to your chart
2. Observe how price interacts with the 0/5 grid zones
3. Use the lines to assist with breakout, retest, or reversal planning
4. Combine with price action or other indicators for higher precision
✨ Developed by BeSight – A Community Of Traders
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อินดิเคเตอร์นี้จะแสดงเส้นแนวนอนแบบตาราง (Grid) ที่แบ่งช่วงราคาออกเป็นระยะ ๆ ตามค่าที่ผู้ใช้กำหนด เช่น ทุก ๆ 5 จุด และครอบคลุมช่วงราคาทั้งหมดของกราฟ โดยแสดงเป็นเส้นแบบ dotted พร้อมป้ายราคาเพื่อให้มองเห็นได้ชัดเจน
🟦 เส้นสีน้ำเงิน: แสดงระดับราคาที่ลงท้ายด้วย 0
⬜ เส้นสีเทา: แสดงระดับราคาที่ลงท้ายด้วย 5
เหมาะสำหรับผู้ที่ต้องการดูโซนราคา "หยุดพัก / เก็บของ / เปิดโพซิชัน" ซึ่งอาจสะท้อนพฤติกรรมของผู้เล่นรายใหญ่หรือสถาบันในตลาด
🧠 ข้อควรรู้:
- อินดิเคเตอร์นี้ไม่ได้บอกจุดเข้าเทรดหรือการคาดการณ์ แต่ช่วยในการวางแผนแนวรับ-แนวต้านร่วมกับเครื่องมือวิเคราะห์อื่น ๆ
- รองรับทุกสินทรัพย์ที่มีหน่วยราคาคงที่ (หุ้น, ฟิวเจอร์ส, ฟอเร็กซ์, คริปโต ฯลฯ)
✅ วิธีใช้งาน:
1. เพิ่มอินดิเคเตอร์นี้ลงบนกราฟ
2. ใช้เส้น Grid เป็นแนวประกอบในการดูพฤติกรรมราคา เช่น การหยุดลง, การเบรกแนว, การกลับตัว
3. ผสมผสานกับโซน Demand/Supply หรือโซน SMC เพื่อความแม่นยำ
✨ พัฒนาโดย BeSight – คอมมูนิตี้ของเทรดเดอร์ตัวจริง
Breakoutprop Daily Reset# Breakoutprop Daily Reset
This indicator helps Breakoutprop prop firm traders visualize daily reset times on their charts with precision. The indicator draws a vertical line at the exact reset time, making it easy to track when your daily profit/loss calculations will reset.
## What is this indicator for?
Breakoutprop and many other prop firms use a daily reset system where your trading metrics (like maximum drawdown) reset at a specific time each day. This indicator:
- Shows the exact daily reset time with a vertical line on your chart
- Helps you plan your trades around reset times
- Provides clear visual reference for when your daily trading metrics will reset
## Main Features
- **Daily Reset Visualization**: Clear vertical line showing when your daily metrics will reset
- **UTC Time Display**: Time label showing the exact reset time in UTC
- **Customizable Appearance**: Adjust colors, line styles, and transparency to match your chart setup
- **Advanced Customization**: Fully adjustable label positioning, sizes, and color settings
- **Additional Price Line**: Optional feature to mark significant price levels if needed (disabled by default)
## How to Use
### Basic Setup
1. Add the indicator to your chart
2. Set the reset hour and minute to match your Breakoutprop account's daily reset time (default is 00:30 UTC)
3. The indicator will automatically show a vertical line at the next reset time
### Appearance Customization
- Modify colors, line width, and style in the "Appearance Settings" group
- Adjust label settings in the "Label Settings" group
- Use "Compact Mode" to show only the time without additional text
### Additional Features (Optional)
- The indicator includes an optional price line feature that can be enabled if needed
- This is disabled by default but can be activated in the "Price Line Settings" section
## Tips for Breakoutprop Traders
- Set this indicator to match your account's specific reset time (check your Breakoutprop dashboard)
- Use the "Extend Lines" option to see the reset time projected across your entire chart
- Customize the label appearance and position to avoid overlapping with price action
- For night traders, the indicator automatically calculates the next reset time
This indicator is specifically designed for Breakoutprop traders but works with any prop firm that uses daily reset times for tracking trading performance.
H1 Candle Reference + n Pips TargetThis indicator uses the H1 candle at a specified time (default 8:00) to set daily reference levels. It captures the high and low of the 8:00 H1 candle and displays them as blue horizontal lines across all timeframes for the rest of the day. Additionally, it plots two red target lines, set a fixed number of ticks above and below these reference levels.
3SMA +30 Stan Weinstein +200WMA +alert-crossingIndicator Description: Stan Weinstein Strategy + Key Moving Averages
🔹 Introduction
This indicator combines the Classic Stan Weinstein Strategy with a modern update based on the author’s latest recommendations. It includes key moving averages that help identify trends and potential entry or exit points in the market.
📊 Included Moving Averages (Fully Customizable)
All moving averages in this indicator have modifiable parameters, allowing users to adjust values in the input settings.
1️⃣ 30-Week SMA (Stan Weinstein): A long-term trend indicator defining the asset’s main trend.
2️⃣ 40-Week SMA (Weinstein Update): An adjusted version recommended by the author in his recent updates.
3️⃣ 10-Day SMA: Displays short-term price action and helps confirm trend changes.
4️⃣ 100-Day SMA: A medium-term trend measure used by traders to assess trend strength.
5️⃣ 200-Day WMA (Weighted Moving Average): A very long-term indicator that filters market noise and confirms solid trends.
🔍 How to Interpret It
✔️ 30/40-Week SMA in an uptrend → Confirms an accumulation phase or an upward price trend.
✔️ Price above the 200-WMA → Indicates a strong and healthy long-term trend.
✔️ 10-SMA crossing other moving averages → Can signal an early entry or exit opportunity.
✔️ 100-SMA vs. 200-WMA → A breakout of the 100-SMA above the 200-WMA may signal a new bullish phase.
🚨 Built-in Alerts (Key Crossovers)
The indicator includes automatic alerts to notify traders when key moving averages cross, allowing timely reactions:
🔔 10-SMA crossing the 40-SMA → Possible medium-term trend shift.
🔔 10-SMA crossing the 200-WMA → Confirmation of a stronger trend.
🔔 40-SMA crossing the 200-WMA → Long-term trend reversal signal.
💡 Customization: All moving average periods can be adjusted in the input settings, making the indicator flexible for different trading strategies.
Open Vertical Lines [TradeWithRon]This indicator allows traders to draw vertical lines manually or automatically based on the current or specified higher timeframes. It is a versatile tool designed to help users identify and mark significant changes in the market, such as new candle formations, based on a selected or auto-adjusted timeframe.
Open Source
Features:
Timeframe Customization: Users can either manually specify a desired timeframe (e.g., 1-hour, 1-day, etc.) or enable the "Auto" feature, which automatically adjusts the timeframe based on the current chart's timeframe for better alignment with different trading strategies.
Customizable Line Style: The vertical line can be drawn in three different styles: Solid, Dashed, or Dotted, giving users the flexibility to choose their preferred appearance for better chart readability.
Line Color: Users can select the color of the vertical line with transparency options to match their chart's visual preferences.
Auto Timeframe Adjustments: The "Auto Align" option dynamically adjusts the timeframe used for vertical lines depending on the chart's current timeframe. For example, if you’re using a lower timeframe (e.g., 5 minutes), the indicator will automatically switch to a higher timeframe (e.g., 1 hour or daily) to mark vertical lines, ensuring the lines correspond to higher timeframe price action.
Vertical Line Placement:
A vertical line is placed each time a new candle appears on the chart, marking key moments for the user to analyze market movements. This can be helpful for marking the start of new trading sessions or significant events in the market.
How to Use:
1. Apply the indicator to your chart.
2. Configure the preferred timeframe settings (either fixed or auto-align).
3. Customize the line style and color according to your visual preference.
4. The indicator will automatically place vertical lines on the chart when a new candle is formed, based on your selected timeframe.
AltSeasonality - MTFAltSeason is more than a brief macro market cycle — it's a condition. This indicator helps traders identify when altcoins are gaining strength relative to Bitcoin dominance, allowing for more precise entries, exits, and trade selection across any timeframe.
The key for altcoin traders is that the lower the timeframe, the higher the alpha.
By tracking the TOTAL3/BTC.D ratio — a real-time measure of altcoin strength versus Bitcoin — this tool highlights when capital is rotating into or out of altcoins. It works as a bias filter, helping traders avoid low-conviction setups, especially in chop or during BTC-led conditions.
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It works well on the 1D chart to validate swing entries during strong altcoin expansion phases — especially when TOTAL3/BTC.D breaks out while BTCUSD consolidates.
On the 4H or 1D chart, rising TOTAL3/BTC.D + a breakout on your altcoin = high-conviction setup. If BTC is leading, fade the move or reduce size. Consider pairing with the Accumulation - Distribution Candles, optimized for the 1D (not shown).
🔍 Where this indicator really excels, however, is on the 1H and 15M charts, where short-term traders need fast bias confirmation before committing to a move. Designed for scalpers, intraday momentum traders, and tactical swing setups.
Use this indicator to confirm whether an altcoin breakout is supported by broad market flow — or likely to fail due to hidden BTC dominance pressure.
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🧠 How it works:
- TOTAL3 = market cap of altcoins (excl. BTC + ETH)
- BTC.D = Bitcoin dominance as % of total market cap
- TOTAL3 / BTC.D = a normalized measure of altcoin capital strength vs Bitcoin
- BTCUSD = trend baseline and comparison anchor
The indicator compares these forces side-by-side, using a normalized dual-line ribbon. There is intentionally no "smoothing".
When TOTAL3/BTC.D is leading, the ribbon shifts to an “altseason active” phase. When BTCUSD regains control, the ribbon flips back into BTC dominance — signaling defensive posture.
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💡 Strategy Example:
On the 1H chart, a crossover into altseason → check the 15M chart for confirmation. Consider adding the SUPeR TReND 2.718 for confirmation (not shown). If both align, you have trend + flow confluence. If BTCUSD is leading or ribbon is mixed, reduce exposure or wait for confirmation. Further confirmation via Volume breakouts in your specific coin.
⚙️ Features:
• MTF source selection (D, 1H, 15M)
• Normalized ribbon (TOTAL3/BTC.D vs BTCUSD)
• Cross-aware fill shading
• Custom color and transparency controls
• Optional crossover markers
• Midline + zone guides (0.2 / 0.5 / 0.8)
Cz ASR indicatorAverage session range indicator built by me. Great tool to gauge volatility and intraday reversal zones. Great for FX as there is an included table that shows range in pips; however, this can be applied across all assets as a volatility measure.
How it works:
The script measures the range of sessions, including Asia, London, and New York. The lookback period could be adjusted so you can find what length works best and is most accurate. This is then averaged out to provide the ASR. This provides us with an upper and lower bound of which the price could potentially fluctuate in based on the past session ranges. I have also added the 50% ASR, which is also a super useful metric for reversals or continuations.
There is also a configurable UTC so that you can adjust the indicator so it can accurately measure the range within certain sessions.
Note - different session start and stop times vary from market to market. I have set the code to the standard forex market opens however, if you wish to change the time ,you are able to do so by editing the variables in the script
Enjoy :)
Vertical Line at Specified HoursThis script helps you easily separate time.
This indicator can be used for many different purposes. For example, I use it to separate different days and sessions.
Features :
1- Ability to use 10 vertical lines simultaneously
2- The Possibility to change the color of lines
3- The Possibility to change the line type
Tip : The times you enter in the input section must be in the New York time zone.
ATR - Asymmetric Turbulence Ribbon🧭 Asymmetric Turbulence Ribbon (ATR)
The Asymmetric Turbulence Ribbon (ATR) is an enhanced and reimagined version of the standard Average True Range (ATR) indicator. It visualizes not just raw volatility, but the structure, momentum, and efficiency of volatility through a multi-layered visual approach.
It contains two distinct visual systems:
1. A zero-centered histogram that expresses how current volatility compares to its historical average, with intensity and color showing speed and conviction
2. A braided ribbon made of dual ATR-based moving averages that highlight transitions in volatility behavior—whether volatility is expanding or contracting
The name reflects its purpose: to capture asymmetric, evolving turbulence in market behavior, through structure-aware volatility tracking.
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🔧 Inputs (Fibonacci defaults)
ATR Length
Lookback period for ATR calculation (default: 13)
ATR Base Avg. Length
Moving average period used as the zero baseline for histogram (default: 55)
ATR ROC Lookback
Number of bars to measure rate of change for histogram color mapping (default: 8)
Timeframe Override
Optionally calculate ATR values from a higher or fixed timeframe (e.g., 1D) for macro-volatility overlay
Show Ribbon Fill
Toggles colored fill between ATR EMA and HMA lines
Show ATR MAs
Toggles visibility of ATR EMA and HMA lines
Show Crossover Markers
Shows directional triangle markers where ATR EMA and HMA cross
Show Histogram
Toggles the entire histogram display
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📊 Histogram Component: Volatility Energy Profile
The histogram shows how far the current ATR is from its moving average baseline, centered around zero. This lets you interpret volatility pressure—whether it's expanding, contracting, or preparing to reverse.
To complement this, the indicator also plots the raw ATR line in aqua. This is the actual average true range value—used internally in both the histogram and ribbon calculations. By default, it appears as a slightly thicker line, providing a clear reference point for comparing historical volatility trends and absolute levels.
Use the baseline ATR to:
- Compare real-time volatility to previous peaks or troughs
- Monitor how ATR behaves near histogram flips or ribbon crossovers
- Evaluate volatility phases in absolute terms alongside relative momentum
The ATR line is particularly helpful for users who want to keep tabs on raw volatility values while still benefiting from the enhanced visual storytelling of the histogram and ribbon systems.
Each histogram bar is colored based on the rate of change (ROC) in ATR: The faster ATR rises or falls, the more intense the color. Meanwhile, the opacity of each bar is adjusted by the effort/result ratio of the price candle (body vs. range), showing how much price movement was achieved with conviction.
Color Interpretation:
🔴 Red
Strong volatility expansion
Market entering or deepening into a volatility burst
Seen during breakouts, panic moves, or macro shock events
Often accompanied by large real candle bodies
🟠 Orange
Moderate volatility expansion
Heating up phase, often precedes breakouts
Common in strong trending environments
Signals tightening before acceleration
🟡 Yellow
Mild volatility increase
Transitional state—energy building, not yet exploding
Appears in early trend development or pullbacks
🟢 Green
Mild volatility contraction
ATR cooling off
Seen during consolidation, reversion, or range balance
Good time to assess upcoming directional setups
🔵 Aqua
Moderate compression
Volatility is clearly declining
Signals consolidation within larger structure
Pre-breakout zones often form here
🔵 Deep Blue
Strong volatility compression
Market is coiling or dormant
Can signal upcoming squeeze or fade environment
Often followed by sharp expansion
Opacity scaling:
Brighter bars = efficient, directional price action (strong bodies)
Faded bars = indecision, chop, absorption, or wick-heavy structure
Together, color and opacity give a 2D view of market volatility: Hue = the type and direction of volatility
Opacity = the quality and structure behind it
Use this to gauge whether volatility is rising with conviction, fading into neutrality, or compressing toward breakout potential.
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🪡 Ribbon Component: Volatility Rhythm Structure
The ribbon overlays two moving averages of ATR:
EMA (yellow) – faster, more reactive
HMA (orange) – smoother, more rhythmic
Their relationship creates the ribbon logic:
Yellow fill (EMA > HMA)
Short-term volatility is increasing faster than the longer-term rhythm
Signals active expansion and engagement
Orange fill (HMA > EMA)
Volatility is decaying or leveling off
Suggests possible exhaustion, pullback, or range
Crossover triangle markers (optional, off by default to avoid clutter) identify the moment of shift in volatility phase.
The ribbon reflects the shape of volatility over time—ideal for mapping cyclical energy shifts, transitional states, and alignment between current and average volatility.
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📐 Strategy Application
Use the Asymmetric Turbulence Ribbon to:
- Detect volatility expansions before breakouts or directional runs
- Spot compression zones that precede structural ruptures
- Visually separate efficient moves from noisy market activity
- Confirm or fade trade setups based on underlying energy state
- Track the volatility environment across multiple timeframes using the override
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🎯 Ideal Timeframes
Designed to function across all timeframes, but particularly powerful on intraday to daily ranges (1H to 1D)
Use the timeframe override to anchor your chart in higher-timeframe volatility context, like daily ATR behavior influencing a 1H setup.
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🧬 Customization Tips
- Increase ATR ROC Lookback for smoother color transitions
- Extend ATR Base Avg Length for more macro-driven histogram centering
- Disable the histogram for ribbon-only rhythm view
- Use opacity and color shifts in the histogram to detect stealth energy builds
- Align ATR phases with structure or order flow tools for high-quality setups
