Delta Pulse Oscillator — GSK-VIZAG-AP-INDIA“Delta Pulse Oscillator visualizes buy vs. sell pressure using smoothed delta %, baselines, and crossover markers.”
📌 Delta Pulse Oscillator — GSK-VIZAG-AP-INDIA
The Delta Pulse Oscillator is a custom-built momentum tool that measures the balance between buying and selling activity and smooths it with moving averages. It provides a visual representation of percentage delta strength with dynamic coloring, baseline levels, and crossover markers.
🔎 Key Features
Delta EMA (%) Line → Shows the smoothed percentage difference between simulated buy and sell volumes.
Signal EMA Line → A shorter EMA applied on Delta EMA to highlight momentum shifts.
Baseline Levels
0 line (neutral balance of buy/sell activity).
+5 baseline (stronger positive pressure).
-5 baseline (stronger negative pressure).
Dynamic Coloring → Green when Delta EMA is above zero, red when below.
Cross Dots
Yellow dots mark when Delta EMA or Signal EMA crosses the zero line.
Orange dots appear when Delta EMA crosses the +5 or –5 baselines.
Green/Red dots highlight when both EMAs stay above +5 or below –5.
Background Fills → Visual zones for positive and negative regions.
🧩 How It Can Be Used
Helps to visualize buying vs. selling pressure in real time.
Highlights when momentum is strengthening or weakening around defined baseline levels.
Useful as a confirmation tool when combined with other forms of analysis.
⚠️ Note: This script is for educational and analytical purposes only. It is not a trading strategy and does not provide buy/sell signals. Always use with additional tools, price action, and proper risk management.
Indicadores y estrategias
Pasrsifal.RegressionTrendStateSummary
The Parsifal.Regression.Trend.State Indicator analyzes the leading coefficients of linear and quadratic regressions of price (against time). It also considers their first- and second-order changes. These features are aggregated into a Trend-State background, shown as a gradient color. In addition, the indicator generates fast and slow signals that can be used as potential entry- or exit triggers.
This tool is designed for advanced trend-following strategies, leveraging information from multiple trendline features.
Background
Trendlines provide insight into the state of a trend or the “trendiness” of a price process. While moving averages or pivot-based lines can serve as envelopes and breakout levels, they are often too lagging for swing traders, who need tools that adapt more closely to price swings, ideally using trendlines, around which the price process swings continuously.
Regression lines address this by cutting directly through the data, making them a natural anchor for observing how price winds around a central trendline within a chosen lookback period.
Regression Trendlines
• Linear Regression:
o Minimizes distance to all closing values over the lookback period.
o The slope represents the short-term linear trend.
o The change of slope indicates trend acceleration or deceleration.
o Linear regression lags during phases of rapid market shifts.
• Quadratic Regression:
o Fits a second-degree polynomial to minimize deviation from closing prices.
o The convexity term (leading coefficient) reflects curvature:
Positive convexity → accelerating uptrend or fading downtrend.
Negative convexity → accelerating downtrend or fading uptrend.
o The change of convexity detects early shifts in momentum and often reacts faster than slope features.
Features Extracted
The indicator evaluates six features:
• Linear features: slope, first derivative of slope, second derivative of slope.
• Quadratic features: convexity term, first derivative of the convexity term, second derivative of the convexity term.
• Linear features: capture broad, background trend behavior.
• Quadratic features: detect deviations, accelerations, and smaller-scale dynamics.
Quadratic terms generally react first to market changes, while linear terms provide stability and context.
Dynamics of Market Moves as seen by linear and quadratic regressions
• At the start of a rapid move:
The change of convexity reacts first, capturing the shift in dynamics before other features. The convexity term then follows, while linear slope features lag further behind. Because convexity measures deviation from linearity, it reflects accelerating momentum more effectively than slope.
• At the end of a rapid move:
Again, the change of convexity responds first to fading momentum, signaling the transition from above-linear to below-linear dynamics. Even while a strong trend persists, the change of convexity may flip sign early, offering a warning of weakening strength. The convexity term itself adjusts more slowly but may still turn before the price process does. Linear features lag the most, typically only flipping after price has already reversed, thereby smoothing out the rapid, more sensitive reactions of quadratic terms.
________________________________________
Parsifal Regression.Trend.State Method
1. Feature Mapping:
Each feature is mapped to a range between -1 and 1, preserving zero-crossings (critical for sign interpretation).
2. Aggregation:
A heuristic linear combination*) produces a background information value, visualized as a gradient color scale:
o Deep green → strong positive trend.
o Deep red → strong negative trend.
o Yellow → neutral or transitional states.
3. Signals:
o Fast signal (oscillator): ranges from -1 to 1, reflecting short-term trend state.
o Slow signal (smoothed): moving average of the fast signal.
o Their interactions (crossovers, zero-crossings) provide actionable trading triggers.
How to Use
The Trend-State background gradient provides intuitive visual feedback on the aggregated regression features (slope, convexity, and their changes). Because these features reflect not only current trend strength but also their acceleration or deceleration, the color transitions help anticipate evolving market states:
• Solid Green: All features near their highs. Indicates a strong, accelerating uptrend. May also reflect explosive or hyperbolic upside moves (including gaps).
• Fading Solid Green: A recently strong uptrend is losing momentum. Price may shift into a slower uptrend, consolidation, or even a reversal.
• Fading Green → Yellow: Often appears as a dirty yellow or a rapidly mixing pattern of green and red. Signals that the uptrend is weakening toward neutrality or beginning to turn negative.
• Yellow → Deepening Red: Two possible scenarios:
o Coming from a strong uptrend → suggests a sharp fade, though the trend may still technically be up.
o Coming from a weaker uptrend or sideways market → suggests the start of an accelerating downtrend.
• Solid Red: All features near their lows. Indicates a strong, accelerating downtrend. May also reflect crash-type conditions or downside gaps.
• Fading Solid Red: A recently strong downtrend is losing strength. Market may move into a slower decline, consolidation, or early reversal upward.
• Fading Red → Yellow : The downtrend is weakening toward neutral, with potential for a bullish shift.
• Yellow → Increasing Green: Two possible scenarios:
o Coming from a strong downtrend, it reflects a sharp fade of bearish momentum, though the market may still technically be trending down.
o Coming from a weaker downtrend or sideways movement, it suggests the start of an accelerating uptrend.
Note: Market evolution does not always follow this neat “color cycle.” It may jump between states, skip stages, or reverse abruptly depending on market conditions. This makes the background coloring particularly valuable as a contextual map of current and evolving price dynamics.
Signal Crossovers:
Although the fast signal is very similar (but not identical) to the background coloring, it provides a numerical representation indicating a bullish interpretation for rising values and bearish for falling.
o High-confidence entries:
Fast signal rising from < -0.7 and crossing above the slow signal → potential long entry.
Fast signal falling from > +0.7 and crossing below the slow signal → potential short entry.
o Low-confidence entries:
Crossovers near zero may still provide a valid trigger but may be noisy and should be confirmed with other signals.
o Zero-crossings:
Indicate broader state changes, useful for conservative positioning or option strategies. For confirmation of a Fast signal 0-crossing, wait for the Slow signal to cross as well.
________________________________________
*) Note on Aggregation
While the indicator currently uses a heuristic linear combination of features, alternatives such as Principal Component Analysis (PCA) could provide a more formal aggregation. However, while in the absence of matrix algebra, the required eigenvalue decomposition can be approximated, its computational expense does not justify the marginal higher insight in this case. The current heuristic approach offers a practical balance of clarity, speed, and accuracy.
Combined RSI EnsembleRip from TrendSipider so all cred to them for the idea:
A combined RSI Ensemble indicator that colors candles based on both overbought (≥80) and oversold (≤30) conditions using three RSI lengths (14, 9, 5). It assigns distinct colors for varying levels of overbought (gray, yellow, orange, red) and oversold (gray, light green, dark green, neon green) signals. The script also registers "Surely Overbought/Oversold" and "Probably Overbought/Oversold" signals for use in scanning, backtesting, and alerts.
OHLC Horizontal Compact + Volume + Buy/SellA compact, single-row horizontal table for TradingView displaying Open, High, Low, Close (OHLC), net change, percentage change, volume, and buy/sell pressure percentages. The table is fully color-coded for easy interpretation: green for positive values, red for negative, and yellow for neutral. Table position is fully customizable (top, middle, bottom / left, center, right). Ideal for traders who want a concise, real-time snapshot of price action and market sentiment in a single row.
Features:
OHLC values in one horizontal row
Net change (Δ) and % change with directional arrows
Real-time volume display
Buy/Sell pressure % with dynamic coloring
Fully customizable table placement
Works on all timeframes
Altcoins % Above Weekly EMA21 Top50-550The indicator shows the percentage of altcoins trading above the weekly EMA21 within a selected group (Top50, Top150, Top550, or Personal).
It helps assess overall altcoin market strength, identify overbought/oversold zones, and spot potential entry or exit points.
Signal Validator - Signal Validator with Volume and IV ProxySignal Validator - Signal Validator with Volume and IV Proxy
Advanced Ghost Volume DetectorAdvanced Ghost Volume DetectorAdvanced Ghost Volume DetectorAdvanced Ghost Volume DetectorAdvanced Ghost Volume Detector
Polynomial Regression HeatmapPolynomial Regression Heatmap – Advanced Trend & Volatility Visualizer
Overview
The Polynomial Regression Heatmap is a sophisticated trading tool designed for traders who require a clear and precise understanding of market trends and volatility. By applying a second-degree polynomial regression to price data, the indicator generates a smooth trend curve, augmented with adaptive volatility bands and a dynamic heatmap. This framework allows users to instantly recognize trend direction, potential reversals, and areas of market strength or weakness, translating complex price action into a visually intuitive map.
Unlike static trend indicators, the Polynomial Regression Heatmap adapts to changing market conditions. Its visual design—including color-coded candles, regression bands, optional polynomial channels, and breakout markers—ensures that price behavior is easy to interpret. This makes it suitable for scalping, swing trading, and longer-term strategies across multiple asset classes.
How It Works
The core of the indicator relies on fitting a second-degree polynomial to a defined lookback period of price data. This regression curve captures the non-linear nature of market movements, revealing the true trajectory of price beyond the distortions of noise or short-term volatility.
Adaptive upper and lower bands are constructed using ATR-based scaling, surrounding the regression line to reflect periods of high and low volatility. When price moves toward or beyond these bands, it signals areas of potential overextension or support/resistance.
The heatmap colors each candle based on its relative position within the bands. Green shades indicate proximity to the upper band, red shades indicate proximity to the lower band, and neutral tones represent mid-range positioning. This continuous gradient visualization provides immediate feedback on trend strength, market balance, and potential turning points.
Optional polynomial channels can be overlaid around the regression curve. These three-line channels are based on regression residuals and a fixed width multiplier, offering additional reference points for analyzing price deviations, trend continuation, and reversion zones.
Signals and Breakouts
The Polynomial Regression Heatmap includes statistical pivot-based signals to highlight actionable price movements:
Buy Signals – A triangular marker appears below the candle when a pivot low occurs below the lower regression band.
Sell Signals – A triangular marker appears above the candle when a pivot high occurs above the upper regression band.
These markers identify significant deviations from the regression curve while accounting for volatility, providing high-quality visual cues for potential entry points.
The indicator ensures clarity by spacing markers vertically using ATR-based calculations, preventing overlap during periods of high volatility. Users can rely on these signals in combination with heatmap intensity and regression slope for contextual confirmation.
Interpretation
Trend Analysis :
The slope of the polynomial regression line represents trend direction. A rising curve indicates bullish bias, a falling curve indicates bearish bias, and a flat curve indicates consolidation.
Steeper slopes suggest stronger momentum, while gradual slopes indicate more moderate trend conditions.
Volatility Assessment :
Band width provides an instant visual measure of market volatility. Narrow bands correspond to low volatility and potential consolidation, whereas wide bands indicate higher volatility and significant price swings.
Heatmap Coloring :
Candle colors visually represent price position within the bands. This allows traders to quickly identify zones of bullish or bearish pressure without performing complex calculations.
Channel Analysis (Optional) :
The polynomial channel defines zones for evaluating potential overextensions or retracements. Price interacting with these lines may suggest areas where mean-reversion or trend continuation is likely.
Breakout Signals :
Buy and Sell markers highlight pivot points relative to the regression and volatility bands. These are statistical signals, not arbitrary triggers, and should be interpreted in context with trend slope, band width, and heatmap intensity.
Strategy Integration
The Polynomial Regression Heatmap supports multiple trading approaches:
Trend Following – Enter trades in the direction of the regression slope while using the heatmap for momentum confirmation.
Pullback Entries – Use breakouts or deviations from the regression bands as low-risk entry points during trend continuation.
Mean Reversion – Price reaching outer channel boundaries can indicate potential reversal or retracement opportunities.
Multi-Timeframe Alignment – Overlay on higher and lower timeframes to filter noise and improve entry timing.
Stop-loss levels can be set just beyond the opposing regression band, while take-profit targets can be informed by the distance between the bands or the curvature of the polynomial line.
Advanced Techniques
For traders seeking greater precision:
Combine the Polynomial Regression Heatmap with volume, momentum, or volatility indicators to validate signals.
Observe the width and slope of the regression bands over time to anticipate expanding or contracting volatility.
Track sequences of breakout signals in conjunction with heatmap intensity for systematic trade management.
Adjusting regression length allows customization for different assets or timeframes, balancing responsiveness and smoothing. The combination of polynomial curve, adaptive bands, heatmap, and optional channels provides a comprehensive statistical framework for informed decision-making.
Inputs and Customization
Regression Length – Determines the number of bars used for polynomial fitting. Shorter lengths increase responsiveness; longer lengths improve smoothing.
Show Bands – Toggle visibility of the ATR-based regression bands.
Show Channel – Enable or disable the polynomial channel overlay.
Color Settings – Customize bullish, bearish, neutral, and accent colors for clarity and visual preference.
All other internal parameters are fixed to ensure consistent statistical behavior and minimize potential misconfiguration.
Why Use Polynomial Regression Heatmap
The Polynomial Regression Heatmap transforms complex price action into a clear, actionable visual framework. By combining non-linear trend mapping, adaptive volatility bands, heatmap visualization, and breakout signals, it provides a multi-dimensional perspective that is both quantitative and intuitive.
This indicator allows traders to focus on execution, interpret market structure at a glance, and evaluate trend strength, overextensions, and potential reversals in real time. Its design is compatible with scalping, swing trading, and long-term strategies, providing a robust tool for disciplined, data-driven trading.
JessieOBS with MACD - The Evil MACD
中文版说明在后面
JessieOBS takes the classic MACD to the next level by clearly highlighting overbought and oversold zones.
While the traditional MACD works well for spotting uptrends and downtrends, it often struggles in sideways markets—producing false signals and useless crossovers that can trigger unnecessary stop losses. JessieOBS solves this problem, giving you cleaner, more reliable signals even when the market is moving sideways.
The thick white line signals an oversold area, hinting that a price reversal to an uptrend may happen soon.
The thick blue line signals an overbought area, hinting that a price reversal to a downtrend may happen soon.
JessieOBS helps you filter sideways trends, improving your win rate.
WARNING: JessieOBS is only an early WARNING, NOT A TRADE ENTRY SIGNAL.
When a warning appears, stay alert and wait for confirmation—through price action, divergences (HIGHLY RECOMMENDED with a win rate over 85%!), or the theory of entanglement (HIGHLY RECOMMENDED with a even higher win rate!).
With the right approach, JessieOBS can take your win rate to the next level!
中文版说明:
传统的MACD可以很明确识别出趋势,但有两个最大的缺点:第一是滞后性,第二是假信号。所以MACD在趋势行情里比较好用(不管是上升趋势还是下降趋势),但在横盘期间,就会产生很多的假信号。
JessieOBS就解决了MACD不准的问题,在MACD的信号线上,添加了白色和蓝色的粗线,白色粗线代表价格超卖,接下来很可能会反转上涨,蓝色粗线代表价格超买,接下来很可能会反转下跌。市场横盘期间,JessieOBS很少会给出超买或者超卖信号,从而有效过滤了MACD的假信号。
注意!JessieOBS只能作为一个提前的预警,一定不能把JessieOBS当做入场信号看待。因为JessieOBS只预警价格可能会反转,但并不能预测出价格发生反转的准确时间。
正确的做法是,一旦看见JessieOBS的预警信号,就应该重点关注,再用其他的方式找到准确的入场点。裸k交易法是有用的,找到反转的趋势k线作为入场点。
强烈推荐:出现预警信号之后根据背离点入场,这种方法的胜率可以超过85%。
强烈推荐:出现预警信号之后根据缠论分析入场,利用缠论分析出的入场点胜率可以更高。
Low Volatility Breakout in Trend
█ OVERVIEW
"Low Volatility Breakout in Trend" is a technical analysis tool that identifies periods of low-volatility consolidation within an ongoing trend and signals potential breakouts aligned with the trend's direction. The indicator detects trends using a simple moving average (SMA) of price, identifies consolidation zones based on the size of candle bodies, and displays the percentage change in volume (volume delta) at the breakout moment.
█ CONCEPTS
The core idea of the indicator is to pinpoint moments where traders can join an ongoing trend by capitalizing on breakouts from consolidation zones, supported by additional information such as volume delta. It provides clear visualizations of trends, consolidation zones, and breakout signals to facilitate trading decisions.
Why Use It?
* Breakout Identification: The indicator locates low-volatility consolidation zones (measured by the size of individual candle bodies, not the price range of the consolidation) and signals breakouts, enabling traders to join the trend at key moments.
* Volume Analysis: Displays the percentage change in volume (delta) relative to its simple moving average, providing insight into market activity rather than acting as a signal filter.
* Visual Clarity: Colored trend lines, consolidation boxes (drawn only after the breakout candle closes, not on subsequent candles), and volume delta labels enable quick chart analysis.
* Flexibility: Adjustable parameters, such as the volatility window length or SMA period, allow customization for various trading strategies and markets.
How It Works
* Trend Detection: The indicator calculates a simple moving average (SMA) of price (default: based on the midpoint of high/low) and creates dynamic trend bands, offset by a percentage of the average candle height (band scaling). A price above the upper band signals an uptrend, while a price below the lower band indicates a downtrend. Trend changes occur not when the price crosses the SMA but when it crosses above the upper band or below the lower band (offset by the average candle height multiplied by the scaling factor).
* Consolidation Identification: Identifies low-volatility zones when the candle body size is smaller than the average body size over a specified period (default: 20 candles) multiplied by a volatility threshold — the maximum allowable body size as a percentage of the average body (e.g., 2 means the candle body must be less than twice the average body to be considered low-volatility).
* Breakout Signals: A breakout occurs when the candle body exceeds the volatility threshold, is larger than the maximum body in the consolidation, and aligns with the trend direction (bullish in an uptrend, bearish in a downtrend).
* Visualization: Draws a trend line with a gradient, consolidation boxes (appearing only after the breakout candle closes, marking the consolidation zone), and volume delta labels. Optionally displays breakout signal arrows.
* Signals and Alerts: The indicator generates signals for bullish and bearish breakouts, including the volume delta percentage. Alerts are an additional feature that can be enabled for notifications.
Settings and Customization
* Volatility Window: Length of the period for calculating the average candle body size (default: 20).
* Volatility Threshold: Maximum candle body size as a percentage of the average body (default: 2).
* Minimum Consolidation Bars: Number of candles required for a consolidation (default: 10).
* SMA Length for Trend: Period of the SMA for trend detection (default: 100).
* Band Scaling: Offset of trend bands as a percentage of the average candle height (default: 250%), determining the distance from the SMA.
* Visualization Options: Enable/disable consolidation boxes (Show Consolidation Boxes, drawn after the breakout candle closes), volume delta labels (Show Volume Delta Labels), and breakout signals (Show Breakout Signals, e.g., triangles).
* Colors: Customize colors for the trend line, consolidation boxes, and volume delta labels.
█ OTHER SECTIONS
Usage Examples
* Joining an Uptrend: When the price breaks out of a consolidation in an uptrend with a volume delta of +50%, open a long position; the signal is stronger if the breakout candle surpasses a local high.
* Avoiding False Breakouts: Ignore breakout signals with low volume delta (e.g., below 0%) and combine the indicator with other tools (e.g., support/resistance levels or oscillators) to confirm moves in low-activity zones.
Notes for Users
* On markets that do not provide volume data, the indicator will not display volume delta — disable volume labels and enable breakout signals (e.g., triangles) instead.
* Adjust parameters to suit the market's characteristics to minimize noise.
* Combine with other tools, such as Fibonacci levels or oscillators, for greater precision.
Zones + Trendlines (raphii7)Here you go — in English, simple and clear:
Designed for a clear read of worked zones and trend paths on any timeframe.
-Zones: rectangles where price has touched multiple times = support/resistance zones.
-Trendlines: lines that connect two highs (H–H) or two lows (B–B), with a dotted extension.
Settings
Zones
-Minimum candles between highs/lows (minSepBars): minimum spacing between pivots. Larger = cleaner pivots.
-Show highs/lows (showHBZones): shows small H/B labels on the chart.
-Max highs/lows used (maxPivotsUsed): cap on stored pivots.
-Minimum contacts in the zone (minContacts): minimum touches required to draw a zone.
-Zone size unit (sizeMode):
-Pips = fixed thickness.
-ATR = thickness adapts to volatility.
-Zone size (zoneSize): zone thickness (in Pips or ATR).
-Max candles back (lookbackBars): how far back to scan.
-Max zones to draw (maxZonesDraw): prevents too many rectangles.
-Border / fill color (borderCol / fillCol): zone styling.
Trendlines
-Pivot Length (pivotLen): “size” of the pivot. Higher = more reliable lines, fewer of them.
-Pivot Type (pivotType):
Normal = cleaner, slower.
Fast = very reactive, can move more.
India Nifty Index Performances DashboardSelf explanatory tabular view of Nifty sector performance ranked top & bottom across calendar year vs. financial year — a clear view of market leaders and laggards.
Options available: Day, Week, Month, Quarter, Calendar Year, (India) Financial Year p
performances. Included Gold (from Mcx), Sme (from Bse), 10Y Gsec for comparison.
Fibonacci Sequence Circles [BigBeluga]🔵 Overview
The Fibonacci Sequence Circles is a unique and visually intuitive indicator designed for the TradingView platform. It combines the principles of the Fibonacci sequence with geometric circles to help traders identify potential support and resistance levels, as well as price expansion zones. The indicator dynamically anchors to key price points, such as pivot highs, pivot lows, or timeframe changes (daily, weekly, monthly), and generates Fibonacci-based circles around these anchor points.
⚠️For proper indicators visualization use simple not logarithmic chart
🔵 Key Features
Customizable Anchor Points : The indicator can be anchored to Pivot Highs , Pivot Lows , or timeframe changes ( Daily, Weekly, Monthly ), making it adaptable to various trading strategies.
Fibonacci Sequence Logic : The circles are generated using the Fibonacci sequence, where the diameter of each circle is the sum of the diameters of the two preceding circles.
first = start_val
secon = start_val + int(start_val/2)
three = first + secon
four = secon + three
five = three + four
six = four + five
seven = five + six
eight = six + seven
nine = seven + eight
ten = eight + nine
Adjustable Start Value : Traders can modify the starting value of the sequence to scale the circles larger or smaller, ensuring they fit the current price action.
Color Customization : Each circle can be individually enabled or disabled, and its color can be customized for better visual clarity.
Visual Labels : The diameter of each circle (in bars) is displayed next to the circle, providing additional context for analysis.
🔵 Usage
Step 1: Set the Anchor Point - Choose the anchor type ( Pivot High, Pivot Low, Daily, Weekly, Monthly ) to define the center of the Fibonacci circles.
Step 2: Adjust the Start Value - Modify the starting value of the Fibonacci sequence to scale the circles according to the price action.
Step 3: Customize Circle Colors - Enable or disable specific circles and adjust their colors for better visualization.
Step 4: Analyze Price Action - Use the circles to identify potential support/resistance levels, price expansion zones, or trend continuation areas.
Step 5: Combine with Other Tools - Enhance your analysis by combining the indicator with other technical tools like trendlines, moving averages, or volume indicators.
The Fibonacci Sequence Circles is a powerful and flexible tool for traders who rely on Fibonacci principles and geometric patterns. Its ability to anchor to key price points and dynamically scale based on market conditions makes it suitable for various trading styles and timeframes. Whether you're a day trader or a long-term investor, this indicator can help you visualize and anticipate price movements with greater precision.
Brandon MAA configurable moving-average tool (SMA/EMA/… including exotic types) that colors trend by “price vs MA” or “rising MA,” and marks MA touches (support/resistance) plus rejection breakouts with labels. It also offers tolerance bands, optional smoothing, bar coloring, and glow styling for rapid trend read-through.
Hamza Price action ConceptsPrice Action Hamza Concepts is a powerful all-in-one tool combining SMC, ICT concepts, and classic price action structure. It automatically detects market structure shifts, order blocks, FVGs, CHoCH, BOS, and premium-discount zones. Ideal for scalping, intraday, swing, and position trading.
Brandon MAA configurable moving-average tool (SMA/EMA/… including exotic types) that colors trend by “price vs MA” or “rising MA,” and marks MA touches (support/resistance) plus rejection breakouts with labels. It also offers tolerance bands, optional smoothing, bar coloring, and glow styling for rapid trend read-through.
VSTBrandonBuilds a volume-adjusted MA baseline, then runs an ATR Supertrend with asymmetric multipliers to determine bullish/bearish state. The line, glow band, gradient area, candles, and Long/Short labels all follow the active trend, with alert hooks for automation.
Brandon MA OscPlots the percent deviation of price from a chosen volume-weighted MA and envelopes it with smoothed standard-deviation bands. It supports Trend, Reversion, and Valuation modes with OB/OS markers and background shading, generating simple buy/sell cues when bands are crossed.
CyberFlow [Probabilities] | FractalystWhat's the indicator's purpose and functionality?
CyberFlow quantifies, per chosen higher-timeframe “Period 1/2/3”, what happens after price first taps the midpoint (Mid) of the previous period’s range. Specifically, it estimates P(High first | Mid tap) versus P(Low first | Mid tap): which side (previous High “PH” or previous Low “PL”) is typically reached first after that mid activation.
It extends a previously shared OrderFlow concept that used market structure; here it conditions on higher‑timeframe previous‑period PH/PL with the Mid as the explicit trigger.
Note: It's specifically designed to exports raw probabilistic series for algorithmic/system developers to integrate a probabilistic layer into strategies and to build/backtest ideas directly from those series.
What is “Mid activation”?
The Mid is the average of the previous period’s PH and PL. Activation occurs on the first bar in the current period whose high–low range includes the Mid. The first bar of a new period cannot activate Mid; activation can only start from the second bar of the period onward.
What counts as “first hit” after activation?
After a Mid activation, the script waits for a subsequent bar that touches either the previous High (PH) or previous Low (PL). The first side touched after the activation bar is recorded as that period’s first hit. Once decided, the other side is ignored for first‑hit statistics.
Which periods does it use?
You can select three custom reference timeframes (Period 1/2/3) in the UI (defaults: D/W/M). All logic—PH/PL/Mid, activation, first‑hit stats—runs independently per selected period.
Do the display controls change the calculation?
No. The “Show” selector only controls visuals:
Period 1/2/3: show only that period’s plots/barcolors.
OFF: shows all periods. Statistics and exported series are unaffected by this selector.
What do the bar/line colors mean?
Activation (first Mid tap): yellow bar.
Delivered to previous High after activation: blue
Delivered to previous Low after activation: red
Plots stop showing PH/PL once delivery happens (for that side) within the period.
What do the status symbols in the table mean?
■ Inactive — Mid not tapped this period.
▶ Activated — Mid tapped; awaiting delivery to PH or PL.
● Delivered — PH or PL was hit first after the Mid tap.
How are probabilities computed?
For each period, the script counts samples where the Mid was tapped and one side was hit first. It reports:
P(High first | Mid tap) and P(Low first | Mid tap).
Two‑sided p‑value vs 50% (H0: p = 0.5). These appear in the stats table with detailed tooltips.
What is “Bias” in exports?
Bias is a ternary signal derived from P(High first | Mid tap):
Bias = 1 if > 0.5
Bias = -1 if < 0.5
Bias = 0 if exactly 0.5 or no sample Source can be per period or “Merged” (simple average of available period probabilities).
Note: the UI uses a simple average; no weighted option is exposed.
What is “Entry” in exports?
Entry = 1 on bars where the selected period’s Mid activates (first tap), else 0. “Merged” emits 1 if any of the three periods activates on the bar.
What is “Exit” in exports?
Exit is the previous period’s Mid price (PH/PL average) for the selected period. “Merged” is the average of the three previous‑period Mid prices.
How do I integrate this into strategies? How to use the indicator?
CyberFlow is designed for algorithmic/system developers to add a probabilistic layer for entries and market‑regime detection.
What CyberFlow exports
- Bias (−1, 0, 1): from P(High first | Mid tap) vs 50% per your chosen source (Period 1/2/3 or Merged simple average).
- Entry (0/1): 1 only on the bar where the selected period’s Mid first activates (the “mid tap” bar).
- Exit (price): the previous period’s Mid price (average of previous High/Low) for the selected source.
- These appear in the Data Window as series named Bias, Entry, and Exit.
Connecting from your strategy (input.source)
- Add inputs in your strategy so users can select CyberFlow’s outputs:
- Bias source input: pick the indicator’s Bias.
- Entry source input: pick the indicator’s Entry.
- Exit source input: pick the indicator’s Exit.
In TradingView’s UI, users link these inputs to CyberFlow’s plots via the source picker.
Does this use request.security?
No. CyberFlow reconstructs your selected higher timeframes (Period 1/2/3) directly on the chart without request.security().
It detects new period boundaries via timeframe.change(tf), rolls the last period’s extremes into Previous High/Low (PH/PL), computes their Mid, then waits for a “Mid activation” (a bar after the first bar of the period whose range crosses the Mid).
From activation onward, it records which side (PH or PL) is reached first to build conditional probabilities per period.
Because levels and events are derived locally from the live bar stream, there are no cross-timeframe fetch artifacts or repaint nuances from request.security().
The exported series (Bias −1/0/1, Entry 0/1, Exit price) are produced natively and can be wired into strategies via TradingView’s input.source() for robust, low-latency integration.
What markets and assets does the indicator Extension work best on?
CyberFlow is market- and timeframe‑agnostic: it computes conditional probabilities (which side of the prior range is reached first after a mid tap) directly from price, so it can be applied to crypto, FX, indices, equities, futures, and commodities across intraday to higher timeframes. In practice, robustness depends on liquidity and sample size: higher timeframes usually yield more stable estimates (fewer activations, lower noise), while lower timeframes give more activations but can be noisier (spreads/fees matter more).
Because the study itself provides probabilities—not PnL—assess profitability in your context by integrating the exported series (Bias −1/0/1, Entry 0/1, Exit price) into your strategy via TradingView’s input.source(), then backtest with your fills, costs, and risk model to measure performance efficiency on your specific markets and settings.
What makes this script unique?
Custom higher-timeframes (beyond D/W/M)
You can pick any three reference periods (Period 1/2/3), not just Daily/Weekly/Monthly. The script rebuilds these periods directly on the chart and analyzes each independently.
True conditional probability (why it matters)
It measures P(High first | Mid tap) vs P(Low first | Mid tap) — i.e., “after the previous period’s midpoint is first tapped, which side is typically reached first?”
Conditioning on the mid‑tap event isolates the path that follows a specific trigger. Unconditioned counts (e.g., “how often PH/PL is hit”) mix pre‑ and post‑activation behavior and can be misleading. This conditional framing turns vague hit‑rates into decision‑grade odds tied to a clear setup.
Statistical confidence in‑context (p‑value in tooltips)
Tooltips show a Wilson 95% confidence interval and a two‑sided p‑value versus 50/50. This helps you judge whether an observed edge is likely signal or noise at your chosen periods.
Exports built for algorithmic integration
Three clean outputs in the Data Window for strategies:
Bias (−1/0/1) from the conditional probability versus 50%.
Entry (0/1) on the activation bar (first mid tap).
Exit (price) as the previous period’s Mid.
Hook these into your backtests via TradingView’s input.source(), then evaluate profitability with your own fills, costs, and risk model. This turns the probabilities into measurable performance you can optimize.
Disclaimer
This tool provides statistical estimates only and is not financial advice. Historical probabilities are not guarantees of future results. Always backtest with your own costs, fills, and risk model before using in live trading.
NYSE Advancing Issues & Volume RatiosOverview
This comprehensive market breadth indicator tracks two essential NYSE ratios that provide deep insights into market sentiment and internal strength:
NYSE Advancing Issues Ratio
NYSE Advancing Volume Ratio
Dual Ratio Analysis
Issues Ratio: Measures the percentage of NYSE stocks advancing vs. total issues
Volume Ratio: Measures the percentage of NYSE volume flowing into advancing stocks
Both ratios displayed as easy-to-read percentages (0-100%)
Customizable Display Options
Toggle each ratio on/off independently
Choose from multiple moving average types (SMA, EMA, WMA)
Adjustable moving average periods
Custom color schemes for better visualization
Reference Levels
50% Line: Market neutral point (gray dashed)
10% Line: Extremely bearish breadth (red dotted)
90% Line: Extremely bullish breadth (green dotted)
Optional background highlighting for extreme readings
Smart Alerts
Cross above/below 50% (neutral) for both ratios
Extreme readings: Above 90% (strong bullish) and below 10% (strong bearish)
Real-time notifications for key market breadth shifts
📈 How to Interpret
Bullish Signals
Above 50%: More stocks/volume advancing than declining
Above 90%: Extremely strong market breadth (rare occurrence)
Divergence: Price making new highs while breadth weakens (potential warning)
Market Timing
Extreme readings (10%/90%) often coincide with market turning points
Breadth thrusts from extreme levels can signal powerful moves
Use with other technical indicators for enhanced timing
Trendlines, SMC, SR, This is a Comprehensive Indicator - It includes Trendlines and shows break outs, SMC, FV gaps, Order Blocks, Support and Resistance, Moving Averages, and Kernel Switch. "All in One"
Economic Cycle ScoreCalculation
-Combine Business Cycle with Liquidity Cycle by applying Z-Score
-Rescale Z-Score to 0-100
-Smooth it with ema
-0-15 is oversold
-85-100 is overbought
Use Case
-Identify when risk asset (Bitcoin) is overbought/oversold
-Use this indicator together with other confluences
***USE ON MONTHLY CHART ONLY (due to the economic date release frequency)