Multiple Asset note_table Sections### Features
- **Expanded to 10 independent Sections**: Each Section has a title, content, and associated asset
- **Asset-based filtering**: Section only displays when the Section's asset name is empty or matches the current chart asset
- **Empty asset setting retained**: If Section asset name is left blank, that Section will display across all assets
- **Automatic display of current asset**: Current asset name is automatically shown in the header and footer
### Usage Instructions
1. Each Section can be assigned a specific asset name, such as "BTCUSDT", "ETHUSDT", etc.
2. A Section will only display when the current chart asset matches the asset specified for that Section
3. If you want a Section to display across all assets, simply leave the asset name blank for that Section
4. Each Section has independent title and content that can be customized as needed
5. When switching to different trading instruments, the indicator automatically displays notes relevant to the current instrument
在腳本中搜尋"ha溢价率"
Retail Sentiment Indicator - Multi-Asset CFD & Fear/Greed IndexRetail Sentiment Indicator - Multi-Asset CFD & Fear/Greed Index
Overview
The Retail Sentiment Indicator provides real-time sentiment data for major financial instruments including stocks, forex, commodities, and cryptocurrencies. This indicator displays retail trader positioning and market sentiment using CFD data and fear/greed indices.
Methodology and Scale Calculation
This indicator operates on a **-50 to +50 scale** with zero representing perfect market equilibrium.
Scale Interpretation:
- **Zero (0)**: Market balance - exactly 50% of investors buying, 50% selling
- **Positive values**: Majority buying pressure
- Example: If 63% of investors are buying, the indicator shows +13 (63 - 50 = +13)
- **Negative values**: Majority selling pressure
- Example: If 92% of investors are selling, the indicator shows -42 (50 - 92 = -42)
BTC Fear & Greed Index Scaling:
The original `BTC FEAR&GREED` index is natively scaled from 0-100 by its creator. In our indicator, this data has been rescaled to also fit the -50 to +50 range for consistency with other sentiment data sources.
This unified scaling approach allows for direct comparison across all instruments and data sources within the indicator.
-Important Data Source Selection-
Bitcoin (BTC) Data Sources
When viewing Bitcoin charts, the indicator offers **two different data sources**:
1. **Default Auto-Mode**: `BTCUSD Retail CFD` - Retail CFD traders sentiment data (automatically loaded).
2. **Manual Selection**: `BTC FEAR&GREED` - Fear & Greed Index from website: alternative dot me
**To access BTC Fear & Greed Index**: Input settings -> disable checkbox "Auto-load Sentiment Data" -> manually select "BTC FEAR&GREED" from the dropdown menu.
US Stock Market Data Sources
For US stocks and indices (S&P 500, NASDAQ, Dow Jones), there are **two data source options**:
1. **Default Auto-Mode**: Individual retail CFD sentiment data for each instrument
2. **Manual Selection**: `SNN FEAR&GREED` - SNN's Fear & Greed Index covering the overall US market sentiment. SNN was used as the name to avoid any potential trademark infringement.
**To access SNN Fear & Greed Index**: When viewing US market charts, disable in input settings checkbox "Auto-load Sentiment Data" and manually select "SNN FEAR&GREED" from the dropdown menu.
This distinction allows traders to choose between **instrument-specific retail sentiment** (auto-mode) or **broader market sentiment indices** (manual selection).
Features
- **Auto-Detection**: Automatically loads sentiment data based on the current chart symbol
- **Manual Selection**: Choose from 40+ supported instruments when auto-detection is unavailable
- **Multiple Data Sources**: Combines retail CFD sentiment with Fear & Greed indices
- **Visual Zones**: Clear greed/fear zones with color-coded backgrounds
- **Real-time Updates**: Live sentiment data from merged data sources
Supported Instruments
Major Indices
- S&P 500, NASDAQ, Dow Jones 30, DAX
Forex Pairs
- Major pairs: EURUSD, GBPUSD, USDJPY, USDCHF, USDCAD
- Cross pairs: EURJPY, GBPJPY, AUDUSD, NZDUSD, and 20+ others
Commodities
- Precious metals: Gold (XAUUSD), Silver (XAGUSD)
- Energy: WTI Oil
- Agricultural: Wheat, Coffee
- Industrial: Copper
Cryptocurrencies
- Bitcoin (BTC) sentiment data
- BTC & SNN Fear & Greed indices
How to Use
1. **Auto Mode** (Default): Enable "Auto-load Sentiment Data" to automatically display sentiment for the current chart symbol
2. **Manual Mode**: Disable auto-load and select from the dropdown menu for specific instruments
3. **Interpretation**:
- Values above 0 (green) indicate retail greed/bullish sentiment
- Values below 0 (red) indicate retail fear/bearish sentiment
- Fear & Greed indices use 0-100 scale (50 is neutral)
Data Sources
This indicator uses curated sentiment data from retail CFD providers and established fear/greed indices. Data is updated regularly and sourced from reputable financial data providers.
Trading Strategy & Market Philosophy
Contrarian Trading Approach
The primary purpose of this indicator is based on the fundamental market principle that **the majority of retail investors are often wrong**, and markets typically move opposite to the positions held by the majority of market participants.
Key Strategy Guidelines:
- **Contrarian Signal**: When the majority of users are positioned on one side of the market, there is statistically greater market advantage in taking positions in the opposite direction
- **Trend Exhaustion Signal**: An interesting observed phenomenon occurs when, during a long-lasting trend where the majority of investors have consistently been on the wrong side, the Sentiment indicator suddenly shows that the majority has flipped and opened positions in the direction of that long-running trend. This is often a signal of fuel exhaustion for further movement in that direction
Interpretation Examples
- High greed readings (majority bullish) → Consider bearish opportunities
- High fear readings (majority bearish) → Consider bullish opportunities
- Sudden sentiment flip during established trends → Potential trend reversal signal
Technical Notes
- Built with PineScript v6
- Dynamic symbol detection with fallback options
- Optimized for performance with minimal resource usage
- Color-coded visualization with customizable zones
Data Sources & Expansion
Acknowledgments
We extend our gratitude to **TradingView** for enabling the use of custom data feeds based on GitHub repositories, making this comprehensive sentiment analysis possible.
Data Expansion Opportunities
As the operator of this indicator, I am **open to suggestions for new data sources** that could be integrated and published. If you have ideas for additional instruments or sentiment data:
How to Submit Suggestions:
1. Send a **private message** with your proposal
2. Include: **instrument/data type**, **source**, and **brief description**
3. If technically feasible, we will work to import and publish the data
Data Infrastructure Status
Current Data Upload Process:
Please note that sentiment data uploads may occasionally experience minor interruptions. However, this should not pose significant issues as sentiment data typically changes gradually rather than rapidly.
Infrastructure Development:
We are actively working on establishing permanent cloud-based infrastructure to ensure continuous, automated data collection and upload processes. This will provide more reliable and consistent data availability in the future.
Disclaimer
This indicator is for educational and informational purposes only. Sentiment data should be used as part of a comprehensive trading strategy and not as the sole basis for trading decisions. Past performance does not guarantee future results. The contrarian approach described is a market theory and may not always produce profitable results.
Martingale Strategy Simulator [BackQuant]Martingale Strategy Simulator
Purpose
This indicator lets you study how a martingale-style position sizing rule interacts with a simple long or short trading signal. It computes an equity curve from bar-to-bar returns, adapts position size after losing streaks, caps exposure at a user limit, and summarizes risk with portfolio metrics. An optional Monte Carlo module projects possible future equity paths from your realized daily returns.
What a martingale is
A martingale sizing rule increases stake after losses and resets after a win. In its classical form from gambling, you double the bet after each loss so that a single win recovers all prior losses plus one unit of profit. In markets there is no fixed “even-money” payout and returns are multiplicative, so an exact recovery guarantee does not exist. The core idea is unchanged:
Lose one leg → increase next position size
Lose again → increase again
Win → reset to the base size
The expectation of your strategy still depends on the signal’s edge. Sizing does not create positive expectancy on its own. A martingale raises variance and tail risk by concentrating more capital as a losing streak develops.
What it plots
Equity – simulated portfolio equity including compounding
Buy & Hold – equity from holding the chart symbol for context
Optional helpers – last trade outcome, current streak length, current allocation fraction
Optional diagnostics – daily portfolio return, rolling drawdown, metrics table
Optional Monte Carlo probability cone – p5, p16, p50, p84, p95 aggregate bands
Model assumptions
Bar-close execution with no slippage or commissions
Shorting allowed and frictionless
No margin interest, borrow fees, or position limits
No intrabar moves or gaps within a bar (returns are close-to-close)
Sizing applies to equity fraction only and is capped by your setting
All results are hypothetical and for education only.
How the simulator applies it
1) Directional signal
You pick a simple directional rule that produces +1 for long or −1 for short each bar. Options include 100 HMA slope, RSI above or below 50, EMA or SMA crosses, CCI and other oscillators, ATR move, BB basis, and more. The stance is evaluated bar by bar. When the stance flips, the current trade ends and the next one starts.
2) Sizing after losses and wins
Position size is a fraction of equity:
Initial allocation – the starting fraction, for example 0.15 means 15 percent of equity
Increase after loss – multiply the next allocation by your factor after a losing leg, for example 2.00 to double
Reset after win – return to the initial allocation
Max allocation cap – hard ceiling to prevent runaway growth
At a high level the size after k consecutive losses is
alloc(k) = min( cap , base × factor^k ) .
In practice the simulator changes size only when a leg ends and its PnL is known.
3) Equity update
Let r_t = close_t / close_{t-1} − 1 be the symbol’s bar return, d_{t−1} ∈ {+1, −1} the prior bar stance, and a_{t−1} the prior bar allocation fraction. The simulator compounds:
eq_t = eq_{t−1} × (1 + a_{t−1} × d_{t−1} × r_t) .
This is bar-based and avoids intrabar lookahead. Costs, slippage, and borrowing costs are not modeled.
Why traders experiment with martingale sizing
Mean-reversion contexts – if the signal often snaps back after a string of losses, adding size near the tail of a move can pull the average entry closer to the turn
Behavioral or microstructure edges – some rules have modest edge but frequent small whipsaws; size escalation may shorten time-to-recovery when the edge manifests
Exploration and stress testing – studying the relationship between streaks, caps, and drawdowns is instructive even if you do not deploy martingale sizing live
Why martingale is dangerous
Martingale concentrates capital when the strategy is performing worst. The main risks are structural, not cosmetic:
Loss streaks are inevitable – even with a 55 percent win rate you should expect multi-loss runs. The probability of at least one k-loss streak in N trades rises quickly with N.
Size explodes geometrically – with factor 2.0 and base 10 percent, the sequence is 10, 20, 40, 80, 100 (capped) after five losses. Without a strict cap, required size becomes infeasible.
No fixed payout – in gambling, one win at even odds resets PnL. In markets, there is no guaranteed bounce nor fixed profit multiple. Trends can extend and gaps can skip levels.
Correlation of losses – losses cluster in trends and in volatility bursts. A martingale tends to be largest just when volatility is highest.
Margin and liquidity constraints – leverage limits, margin calls, position limits, and widening spreads can force liquidation before a mean reversion occurs.
Fat tails and regime shifts – assumptions of independent, Gaussian returns can understate tail risk. Structural breaks can keep the signal wrong for much longer than expected.
The simulator exposes these dynamics in the equity curve, Max Drawdown, VaR and CVaR, and via Monte Carlo sketches of forward uncertainty.
Interpreting losing streaks with numbers
A rough intuition: if your per-trade win probability is p and loss probability is q=1−p , the chance of a specific run of k consecutive losses is q^k . Over many trades, the chance that at least one k-loss run occurs grows with the number of opportunities. As a sanity check:
If p=0.55 , then q=0.45 . A 6-loss run has probability q^6 ≈ 0.008 on any six-trade window. Across hundreds of trades, a 6 to 8-loss run is not rare.
If your size factor is 1.5 and your base is 10 percent, after 8 losses the requested size is 10% × 1.5^8 ≈ 25.6% . With factor 2.0 it would try to be 10% × 2^8 = 256% but your cap will stop it. The equity curve will still wear the compounded drawdown from the sequence that led to the cap.
This is why the cap setting is central. It does not remove tail risk, but it prevents the sizing rule from demanding impossible positions
Note: The p and q math is illustrative. In live data the win rate and distribution can drift over time, so real streaks can be longer or shorter than the simple q^k intuition suggests..
Using the simulator productively
Parameter studies
Start with conservative settings. Increase one element at a time and watch how the equity, Max Drawdown, and CVaR respond.
Initial allocation – lower base reduces volatility and drawdowns across the board
Increase factor – set modestly above 1.0 if you want the effect at all; doubling is aggressive
Max cap – the most important brake; many users keep it between 20 and 50 percent
Signal selection
Keep sizing fixed and rotate signals to see how streak patterns differ. Trend-following signals tend to produce long wrong-way streaks in choppy ranges. Mean-reversion signals do the opposite. Martingale sizing interacts very differently with each.
Diagnostics to watch
Use the built-in metrics to quantify risk:
Max Drawdown – worst peak-to-trough equity loss
Sharpe and Sortino – volatility and downside-adjusted return
VaR 95 percent and CVaR – tail risk measures from the realized distribution
Alpha and Beta – relationship to your chosen benchmark
If you would like to check out the original performance metrics script with multiple assets with a better explanation on all metrics please see
Monte Carlo exploration
When enabled, the forecast draws many synthetic paths from your realized daily returns:
Choose a horizon and a number of runs
Review the bands: p5 to p95 for a wide risk envelope; p16 to p84 for a narrower range; p50 as the median path
Use the table to read the expected return over the horizon and the tail outcomes
Remember it is a sketch based on your recent distribution, not a predictor
Concrete examples
Example A: Modest martingale
Base 10 percent, factor 1.25, cap 40 percent, RSI>50 signal. You will see small escalations on 2 to 4 loss runs and frequent resets. The equity curve usually remains smooth unless the signal enters a prolonged wrong-way regime. Max DD may rise moderately versus fixed sizing.
Example B: Aggressive martingale
Base 15 percent, factor 2.0, cap 60 percent, EMA cross signal. The curve can look stellar during favorable regimes, then a single extended streak pushes allocation to the cap, and a few more losses drive deep drawdown. CVaR and Max DD jump sharply. This is a textbook case of high tail risk.
Strengths
Bar-by-bar, transparent computation of equity from stance and size
Explicit handling of wins, losses, streaks, and caps
Portable signal inputs so you can A–B test ideas quickly
Risk diagnostics and forward uncertainty visualization in one place
Example, Rolling Max Drawdown
Limitations and important notes
Martingale sizing can escalate drawdowns rapidly. The cap limits position size but not the possibility of extended adverse runs.
No commissions, slippage, margin interest, borrow costs, or liquidity limits are modeled.
Signals are evaluated on closes. Real execution and fills will differ.
Monte Carlo assumes independent draws from your recent return distribution. Markets often have serial correlation, fat tails, and regime changes.
All results are hypothetical. Use this as an educational tool, not a production risk engine.
Practical tips
Prefer gentle factors such as 1.1 to 1.3. Doubling is usually excessive outside of toy examples.
Keep a strict cap. Many users cap between 20 and 40 percent of equity per leg.
Stress test with different start dates and subperiods. Long flat or trending regimes are where martingale weaknesses appear.
Compare to an anti-martingale (increase after wins, cut after losses) to understand the other side of the trade-off.
If you deploy sizing live, add external guardrails such as a daily loss cut, volatility filters, and a global max drawdown stop.
Settings recap
Backtest start date and initial capital
Initial allocation, increase-after-loss factor, max allocation cap
Signal source selector
Trading days per year and risk-free rate
Benchmark symbol for Alpha and Beta
UI toggles for equity, buy and hold, labels, metrics, PnL, and drawdown
Monte Carlo controls for enable, runs, horizon, and result table
Final thoughts
A martingale is not a free lunch. It is a way to tilt capital allocation toward losing streaks. If the signal has a real edge and mean reversion is common, careful and capped escalation can reduce time-to-recovery. If the signal lacks edge or regimes shift, the same rule can magnify losses at the worst possible moment. This simulator makes those trade-offs visible so you can calibrate parameters, understand tail risk, and decide whether the approach belongs anywhere in your research workflow.
FibADX MTF Dashboard — DMI/ADX with Fibonacci DominanceFibADX MTF Dashboard — DMI/ADX with Fibonacci Dominance (φ)
This indicator fuses classic DMI/ADX with the Fibonacci Golden Ratio to score directional dominance and trend tradability across multiple timeframes in one clean panel.
What’s unique
• Fibonacci dominance tiers:
• BULL / BEAR → one side slightly stronger
• STRONG when one DI ≥ 1.618× the other (φ)
• EXTREME when one DI ≥ 2.618× (φ²)
• Rounded dominance % in the +DI/−DI columns (e.g., STRONG BULL 72%).
• ADX column modes: show the value (with strength bar ▂▃▅… and slope ↗/↘) or a tier (Weak / Tradable / Strong / Extreme).
• Configurable intraday row (30m/1H/2H/4H) + D/W/M toggles.
• Threshold line: color & width; Extended (infinite both ways) or Not extended (historical plot).
• Theme presets (Dark / Light / High Contrast) or full custom colors.
• Optional panel shading when all selected TFs are strong (and optionally directionally aligned).
How to use
1. Choose an intraday TF (30/60/120/240). Enable D/W/M as needed.
2. Use ADX ≥ threshold (e.g., 21 / 34 / 55) to find tradable trends.
3. Read the +DI/−DI labels to confirm bias (BULL/BEAR) and conviction (STRONG/EXTREME).
4. Prefer multi-TF alignment (e.g., 4H & D & W all strong bull).
5. Treat EXTREME as a momentum regime—trail tighter and scale out into spikes.
Alerts
• All selected TFs: Strong BULL alignment
• All selected TFs: Strong BEAR alignment
Notes
• Smoothing selectable: RMA (Wilder) / EMA / SMA.
• Percentages are whole numbers (72%, not 72.18%).
• Shorttitle is FibADX to comply with TV’s 10-char limit.
Why We Use Fibonacci in FibADX
Traditional DMI/ADX indicators rely on fixed numeric thresholds (e.g., ADX > 20 = “tradable”), but they ignore the relationship between +DI and −DI, which is what really determines trend conviction.
FibADX improves on this by introducing the Fibonacci Golden Ratio (φ ≈ 1.618) to measure directional dominance and classify trend strength more intelligently.
⸻
1. Fibonacci as a Natural Strength Threshold
The golden ratio φ appears everywhere in nature, growth cycles, and fractals.
Since financial markets also behave fractally, Fibonacci levels reflect natural crowd behavior and trend acceleration points.
In FibADX:
• When one DI is slightly larger than the other → BULL or BEAR (mild advantage).
• When one DI is at least 1.618× the other → STRONG BULL or STRONG BEAR (trend conviction).
• When one DI is 2.618× or more → EXTREME BULL or EXTREME BEAR (high momentum regime).
This approach adds structure and consistency to trend classification.
⸻
2. Why 1.618 and 2.618 Instead of Random Numbers
Other traders might pick thresholds like 1.5 or 2.0, but φ has special mathematical properties:
• φ is the most irrational ratio, meaning proportions based on φ retain structure even when scaled.
• Using φ makes FibADX naturally adaptive to all timeframes and asset classes — stocks, crypto, forex, commodities.
⸻
3 . Trading Advantages
Using the Fibonacci Golden Ratio inside DMI/ADX has several benefits:
• Better trend filtering → Avoid false DI crossovers without conviction.
• Catch early momentum shifts → Spot when dominance ratios approach φ before ADX reacts.
• Consistency across markets → Because φ is scalable and fractal, it works everywhere.
⸻
4. How FibADX Uses This
FibADX combines:
• +DI vs −DI ratio → Measures directional dominance.
• φ thresholds (1.618, 2.618) → Classifies strength into BULL, STRONG, EXTREME.
• ADX threshold → Confirms whether the move is tradable or just noise.
• Multi-timeframe dashboard → Aligns bias across 4H, D, W, M.
⸻
Quick Blurb for TradingView
FibADX uses the Fibonacci Golden Ratio (φ ≈ 1.618) to classify trend strength.
Unlike classic DMI/ADX, FibADX measures how much one side dominates:
• φ (1.618) = STRONG trend conviction
• φ² (2.618) = EXTREME momentum regime
This creates an adaptive, fractal-aware framework that works across stocks, crypto, forex, and commodities.
⚠️ Disclaimer : This script is provided for educational purposes only.
It does not constitute financial advice.
Use at your own risk. Always do your own research before making trading decisions.
Created by @nomadhedge
Machine Learning Z-Score Buy and Sell [SS]Hey everyone,
Releasing this Z-Score based buy and sell indicator.
What it does
This indicator:
Uses Z-score and trend to identify potential buy and sell areas.
Signals those buy and sell areas and provides a target price based on the mean.
Plots the target price for buy and sell signals as a red line (for sell signals) or green line (for buy signals).
Has some "machine learning" aspects, namely, it is able to auto select its lookback length based on its analysis of the trend using Pienscript's trend correlation function iterated over multiple lengths, in order for the indicator to identify:
a) The strongest trend; and
b) The correct target price
What is Z-Score
Z-Score is a measure of the mean. Thus, this is a mean reverting type strategy, as it uses z-score to determine price's distance from the mean (or a Z-Score of 0) and then it looks at historic deviations from the mean to signal the buy and sell signals (i.e. how far has price traditionally drifted from the mean before reverting).
Z-Score is a powerful tool in this sense, and if you folow my other indicators, you will know how much I love Z-score!
How to use the indicator
If you want to use the full Machine Learning capabilities of the indicator, its best to just leave all default settings. These default settings will automatically adjust the mean target price and buy and sell signals to align with the current price action.
If you want to be more aggressive in your
Target Price; and
Signals
Then you can opt to manually input a lookback length and mean reversion standard deviation. However, I generally suggest to avoid this as you are then making your own determination of trend by qualitative assessment. It can work, but its just not suggested.
In the input menu, you will see the option to "Manually select lookback" thus over-riding the auto-determination of trend and targets.
You will also see "manual pullback" enabler and "Pullback Standard Deviation". You can set your pullback standard deviation if you want to be more aggressive. The indicator will naturally shift to conservative target prices based on a neutral mean. However, if you want to increase the aggressiveness of the target price, you can increase or decrease the pullback standard deviation.
General Tips about Manually Adjusting Pullback Target
Here are some tips if you want to manually adjust the pullback targets:
The pullback target needs to be in a standard deviation value, this can be anywhere from 0 to 4 or 0 to -4 (you can theoretically go higher but its not really realistic). You can also do decimals, so 1.5 or 1.25 etc.
To determine whether you should be doing negative or positive standard deviation, you should determine the trend. If it is a downtrend and you are looking to short the rips, you will want to select a negative number, like -1.
If it is an uptrend and you want to buy the dips, you should be selecting a positive number, like 1 or 1.5.
Again, I do suggest leaving the indicator to decide for itself, but the options are there for those who wish.
Overall strategy
This is a mean reverting strategy. So if you are a mean reversion trader, this may be of particular interest to you.
Optional
Optionally, you can have the indicator plot the target prices or not, simply toggle this functionality off or on in the settings menu.
Concluding remarks
That is the indicator in a nutshell!
I hope you enjoy it and find it helpful.
Feel free to check out my other Z-Score based indicators if you find this interesting or want to learn more about the power of Z-Score in trading!
Thanks all and safe trades!
Market Spiralyst [Hapharmonic]Hello, traders and creators! 👋
Market Spiralyst: Let's change the way we look at analysis, shall we? I've got to admit, I scratched my head on this for weeks, Haha :). What you're seeing is an exploration of what's possible when code meets art on financial charts. I wanted to try blending art with trading, to do something new and break away from the same old boring perspectives. The goal was to create a visual experience that's not just analytical, but also relaxing and aesthetically pleasing.
This work is intended as a guide and a design example for all developers, born from the spirit of learning and a deep love for understanding the Pine Script™ language. I hope it inspires you as much as it challenged me!
🧐 Core Concept: How It Works
Spiralyst is built on two distinct but interconnected engines:
The Generative Art Engine: At its core, this indicator uses a wide range of mathematical formulas—from simple polygons to exotic curves like Torus Knots and Spirographs—to draw beautiful, intricate shapes directly onto your chart. This provides a unique and dynamic visual backdrop for your analysis.
The Market Pulse Engine: This is where analysis meets art. The engine takes real-time data from standard technical indicators (RSI and MACD in this version) and translates their states into a simple, powerful "Pulse Score." This score directly influences the appearance of the "Scatter Points" orbiting the main shape, turning the entire artwork into a living, breathing representation of market momentum.
🎨 Unleash Your Creativity! This Is Your Playground
We've included 25 preset shapes for you... but that's just the starting point !
The real magic happens when you start tweaking the settings yourself. A tiny adjustment can make a familiar shape come alive and transform in ways you never expected.
I'm genuinely excited to see what your imagination can conjure up! If you create a shape you're particularly proud of or one that looks completely unique, I would love to see it. Please feel free to share a screenshot in the comments below. I can't wait to see what you discover! :)
Here's the default shape to get you started:
The Dynamic Scatter Points: Reading the Pulse
This is where the magic happens! The small points scattered around the main shape are not just decorative; they are the visual representation of the Market Pulse Score.
The points have two forms:
A small asterisk (`*`): Represents a low or neutral market pulse.
A larger, more prominent circle (`o`): Represents a high, strong market pulse.
Here’s how to read them:
The indicator calculates the Pulse Strength as a percentage (from 0% to 100%) based on the total score from the active indicators (RSI and MACD). This percentage determines the ratio of circles to asterisks.
High Pulse Strength (e.g., 80-100%): Most of the scatter points will transform into large circles (`o`). This indicates that the underlying momentum is strong and It could be an uptrend. It's a visual cue that the market is gaining strength and might be worth paying closer attention to.
Low Pulse Strength (e.g., 0-20%): Most or all of the scatter points will remain as small asterisks (`*`). This suggests weak, neutral, or bearish momentum.
The key takeaway: The more circles you see, the stronger the bullish momentum is according to the active indicators. Watch the artwork "breathe" as the circles appear and disappear with the market's rhythm!
And don't worry about the shape you choose; the scatter points will intelligently adapt and always follow the outer boundary of whatever beautiful form you've selected.
How to Use
Getting started with Spiralyst is simple:
Choose Your Canvas: Start by going into the settings and picking a `Shape` and `Palette` from the "Shape Selection & Palette" group that you find visually appealing. This is your canvas.
Tune Your Engine: Go to the "Market Pulse Engine" settings. Here, you can enable or disable the RSI and MACD scoring engines. Want to see the pulse based only on RSI? Just uncheck the MACD box. You can also fine-tune the parameters for each indicator to match your trading style.
Read the Vibe: Observe the scatter points. Are they mostly small asterisks or are they transforming into large, vibrant circles? Use this visual feedback as a high-level gauge of market momentum.
Check the Dashboard: For a precise breakdown, look at the "Market Pulse Analysis" table on the top-right. It gives you the exact values, scores, and total strength percentage.
Explore & Experiment: Play with the different shapes and color palettes! The core analysis remains the same, but the visual experience can be completely different.
⚙️ Settings & Customization
Spiralyst is designed to be highly customizable.
Shape Selection & Palette: This is your main control panel. Choose from over 25 unique shapes, select a color palette, and adjust the line extension style ( `extend` ) or horizontal position ( `offsetXInput` ).
scatterLabelsInput: This setting controls the total number of points (both asterisks and circles) that orbit the main shape. Think of it as adjusting the density or visual granularity of the market pulse feedback.
The Market Pulse engine will always calculate its strength as a percentage (e.g., 75%). This percentage is then applied to the `scatterLabelsInput` number you've set to determine how many points transform into large circles.
Example: If the Pulse Strength is 75% and you set this to `100` , approximately 75 points will become circles. If you increase it to `200` , approximately 150 points will transform.
A higher number provides a more detailed, high-resolution view of the market pulse, while a lower number offers a cleaner, more minimalist look. Feel free to adjust this to your personal visual preference; the underlying analytical percentage remains the same.
Market Pulse Engine:
`⚙️ RSI Settings` & `⚙️ MACD Settings`: Each indicator has its own group.
Enable Scoring: Use the checkbox at the top of each group to include or exclude that indicator from the Pulse Score calculation. If you only want to use RSI, simply uncheck "Enable MACD Scoring."
Parameters: All standard parameters (Length, Source, Fast/Slow/Signal) are fully adjustable.
Individual Shape Parameters (01-25): Each of the 25+ shapes has its own dedicated group of settings, allowing you to fine-tune every aspect of its geometry, from the number of petals on a flower to the windings of a knot. Feel free to experiment!
For Developers & Pine Script™ Enthusiasts
If you are a developer and wish to add more indicators (e.g., Stochastic, CCI, ADX), you can easily do so by following the modular structure of the code. You would primarily need to:
Add a new `PulseIndicator` object for your new indicator in the `f_getMarketPulse()` function.
Add the logic for its scoring inside the `calculateScore()` method.
The `calculateTotals()` method and the dashboard table are designed to be dynamic and will automatically adapt to include your new indicator!
One of the core design philosophies behind Spiralyst is modularity and scalability . The Market Pulse engine was intentionally built using User-Defined Types (UDTs) and an array-based structure so that adding new indicators is incredibly simple and doesn't require rewriting the main logic.
If you want to add a new indicator to the scoring engine—let's use the Stochastic Oscillator as a detailed example—you only need to modify three small sections of the code. The rest of the script, including the adaptive dashboard, will update automatically.
Here’s your step-by-step guide:
#### Step 1: Add the User Inputs
First, you need to give users control over your new indicator. Find the `USER INTERFACE: INPUTS` section and add a new group for the Stochastic settings, right after the MACD group.
Create a new group name: `string GRP_STOCH = "⚙️ Stochastic Settings"`
Add the inputs: Create a boolean to enable/disable it, and then add the necessary parameters (`%K`, `%D`, `Smooth`). Use the `active` parameter to link them to the enable/disable checkbox.
// Add this code block right after the GRP_MACD and MACD inputs
string GRP_STOCH = "⚙️ Stochastic Settings"
bool stochEnabledInput = input.bool(true, "Enable Stochastic Scoring", group = GRP_STOCH)
int stochKInput = input.int(14, "%K Length", minval=1, group = GRP_STOCH, active = stochEnabledInput)
int stochDInput = input.int(3, "%D Smoothing", minval=1, group = GRP_STOCH, active = stochEnabledInput)
int stochSmoothInput = input.int(3, "Smooth", minval=1, group = GRP_STOCH, active = stochEnabledInput)
#### Step 2: Integrate into the Pulse Engine (The "Factory")
Next, go to the `f_getMarketPulse()` function. This function acts as a "factory" that builds and configures the entire market pulse object. You need to teach it how to build your new Stochastic indicator.
Update the function signature: Add the new `stochEnabledInput` boolean as a parameter.
Calculate the indicator: Add the `ta.stoch()` calculation.
Create a `PulseIndicator` object: Create a new object for the Stochastic, populating it with its name, parameters, calculated value, and whether it's enabled.
Add it to the array: Simply add your new `stochPulse` object to the `array.from()` list.
Here is the complete, updated `f_getMarketPulse()` function :
// Factory function to create and calculate the entire MarketPulse object.
f_getMarketPulse(bool rsiEnabled, bool macdEnabled, bool stochEnabled) =>
// 1. Calculate indicator values
float rsiVal = ta.rsi(rsiSourceInput, rsiLengthInput)
= ta.macd(close, macdFastInput, macdSlowInput, macdSignalInput)
float stochVal = ta.sma(ta.stoch(close, high, low, stochKInput), stochDInput) // We'll use the main line for scoring
// 2. Create individual PulseIndicator objects
PulseIndicator rsiPulse = PulseIndicator.new("RSI", str.tostring(rsiLengthInput), rsiVal, na, 0, rsiEnabled)
PulseIndicator macdPulse = PulseIndicator.new("MACD", str.format("{0},{1},{2}", macdFastInput, macdSlowInput, macdSignalInput), macdVal, signalVal, 0, macdEnabled)
PulseIndicator stochPulse = PulseIndicator.new("Stoch", str.format("{0},{1},{2}", stochKInput, stochDInput, stochSmoothInput), stochVal, na, 0, stochEnabled)
// 3. Calculate score for each
rsiPulse.calculateScore()
macdPulse.calculateScore()
stochPulse.calculateScore()
// 4. Add the new indicator to the array
array indicatorArray = array.from(rsiPulse, macdPulse, stochPulse)
MarketPulse pulse = MarketPulse.new(indicatorArray, 0, 0.0)
// 5. Calculate final totals
pulse.calculateTotals()
pulse
// Finally, update the function call in the main orchestration section:
MarketPulse marketPulse = f_getMarketPulse(rsiEnabledInput, macdEnabledInput, stochEnabledInput)
#### Step 3: Define the Scoring Logic
Now, you need to define how the Stochastic contributes to the score. Go to the `calculateScore()` method and add a new case to the `switch` statement for your indicator.
Here's a sample scoring logic for the Stochastic, which gives a strong bullish score in oversold conditions and a strong bearish score in overbought conditions.
Here is the complete, updated `calculateScore()` method :
// Method to calculate the score for this specific indicator.
method calculateScore(PulseIndicator this) =>
if not this.isEnabled
this.score := 0
else
this.score := switch this.name
"RSI" => this.value > 65 ? 2 : this.value > 50 ? 1 : this.value < 35 ? -2 : this.value < 50 ? -1 : 0
"MACD" => this.value > this.signalValue and this.value > 0 ? 2 : this.value > this.signalValue ? 1 : this.value < this.signalValue and this.value < 0 ? -2 : this.value < this.signalValue ? -1 : 0
"Stoch" => this.value > 80 ? -2 : this.value > 50 ? 1 : this.value < 20 ? 2 : this.value < 50 ? -1 : 0
=> 0
this
#### That's It!
You're done. You do not need to modify the dashboard table or the total score calculation.
Because the `MarketPulse` object holds its indicators in an array , the rest of the script is designed to be adaptive:
The `calculateTotals()` method automatically loops through every indicator in the array to sum the scores and calculate the final percentage.
The dashboard code loops through the `enabledIndicators` array to draw the table. Since your new Stochastic indicator is now part of that array, it will appear automatically when enabled!
---
Remember, this is your playground! I'm genuinely excited to see the unique shapes you discover. If you create something you're proud of, feel free to share it in the comments below.
Happy analyzing, and may your charts be both insightful and beautiful! 💛
Smart Money Footprint & Cost Basis Engine [AlgoPoint]Smart Money Footprint & Cost Basis Engine
This indicator is a comprehensive market analysis tool designed to identify the "footprints" of Smart Money (institutions, whales) and pinpoint high-probability reaction zones. Instead of relying on lagging averages, this engine analyzes the very structure of the market to find where large players have shown their hand.
How It Works: The Core Logic
The indicator operates on a multi-stage confirmation process to identify and validate Smart Money zones:
Smart Money Detection (The Trigger): The engine first scans the chart for signs of intense, urgent buying or selling. It does this by identifying Fair Value Gaps (FVGs) created by large, high-volume Displacement Candles. This is our initial Point of Interest (POI).
Cost Basis Calculation (The Average Price): Once a potential Smart Money move is detected, the indicator calculates the Volume-Weighted Average Price (VWAP) for that specific move. This gives us a highly accurate estimate of the average price at which the large players entered their positions.
Historical Confirmation (The "Memory"): This is the indicator's most unique feature. It checks its historical database to see if a similar Smart Money move (in the same direction) has occurred in the same price area in the past. If a match is found, the zone's significance is confirmed.
Verified Cost Basis Zone (The Final Output): A zone that passes all the above checks is drawn on the chart as a high-probability Verified Cost Basis Zone. These are the "memory zones" where the market is likely to react upon a re-visit.
How to Use This Indicator
Cost Basis Zones (The Boxes):
Green Boxes: Bullish zones where Smart Money likely accumulated positions. When the price returns here, a BUY reaction is expected.
Red Boxes: Bearish zones where Smart Money likely distributed positions. When the price returns here, a SELL reaction is expected.
Zone Strength (★★★): Each zone is created with a star rating. More stars indicate a higher-confidence zone (based on factors like volume intensity and historical confirmation).
BUY/SELL Signals: A signal is only generated when the price enters a zone AND the confirmation filters (if enabled in the settings) are passed.
Zone Statuses:
Green/Red: Active and waiting to be tested.
Gray: The zone has been tested, and a signal was produced.
Dark Gray (Invalidated): The zone was broken decisively and is no longer considered valid support/resistance.
Key Settings
Signal Accuracy Filters: You can enable/disable three powerful filters to balance signal quantity and quality:
Momentum Confirmation (Stoch): Waits for momentum to align with the zone's direction.
Candlestick Confirmation (Engulfing): Waits for a strong reversal candle inside the zone.
Lower Timeframe MSS Confirmation: The most advanced filter; waits for a trend shift on a lower timeframe before giving a signal.
Historical Confirmation:
Require Historical Confirmation: Toggle the "Memory" feature on/off. Turn it off to see all potential SM zones.
Tolerance Calculation Method: Choose between a dynamic ATR Multiplier (recommended for all-around use) or a fixed Percentage to define the zone size.
MEMA X-OL9+A. 5, 10, 20, 50 ema's
B. When the 10 goes below the 20 it has shades of red between the 10 and 20.
C. When there is a downward crossover, There will be a Red arrow pointing down.
D. When the 10 is moving closer (upward) towards the 20 it has orange shading. I use this to catch 10 over 20 crossovers.
E. When there is a crossover 10 over 20 it will shade green and have a gold arrow pointing upward. A little redundant, because you'll see the crossover from the shading.
F. Finally there will be smaller blue arrows that represent when there is a close of a candle, if it is lower than the prior candle.
All customizable and defaults should work.
EMA Percentile Rank [SS]Hello!
Excited to release my EMA percentile Rank indicator!
What this indicator does
Plots an EMA and colors it by short-term trend.
When price crosses the EMA (up or down) and remains on that side for three subsequent bars, the cross is “confirmed.”
At the moment of the most recent cross, it anchors a reference price to the crossover point to ensure static price targets.
It measures the historical distance between price and the EMA over a lookback window, separately for bars above and below the EMA.
It computes percentile distances (25%, 50%, 85%, 95%, 99%) and draws target bands above/below the anchor.
Essentially what this indicator does, is it converts the raw “distance from EMA” behavior into probabilistic bands and historical hit rates you can use for targets, stop placement, or mean-reversion/continuation decisions.
Indicator Inputs
EMA length: Default is 21 but you can use any EMA you prefer.
Lookback: Default window is 500, this is length that the percentiles are calculated. You can increase or decrease it according to your preference and performance.
Show Accumulation Table: This allows you to see the table that shows the hits/price accumulation of each of the percentile ranges. UCL means upper confidence and LCL means lower confidence (so upper and lower targets).
About Percentiles
A percentile is a way of expressing the position of a value within a dataset relative to all the other values.
It tells you what percentage of the data points fall at or below that value.
For example:
The 25th percentile means 25% of the values are less than or equal to it.
The 50th percentile (also called the median) means half the values are below it and half are above.
The 99th percentile means only 1% of the values are higher.
Percentiles are useful because they turn raw measurements into context — showing how “extreme” or “typical” a value is compared to historical behavior.
In the EMA Percentile Rank indicator, this concept is applied to the distance between price and the EMA. By calculating percentile distances, the script can mark levels that have historically been reached often (low percentiles) or rarely (high percentiles), helping traders gauge whether current price action is stretched or within normal bounds.
Use Cases
The EMA Percentile Rank indicator is best suited for traders who want to quantify how far price has historically moved away from its EMA and use that context to guide decision-making.
One strong use case is target setting after trend shifts: when a confirmed crossover occurs, the percentile bands (25%, 50%, 85%, 95%, 99%) provide statistically grounded levels for scaling out profits or placing stops, based on how often price has historically reached those distances. This makes it valuable for traders who prefer data-driven risk/reward planning instead of arbitrary point targets. Another use case is identifying stretched conditions — if price rapidly tags the 95% or 99% band after a cross, that’s an unusually large move relative to history, which could signal exhaustion and prompt mean-reversion trades or protective actions.
Conversely, if the accumulation table shows price frequently resides in upper bands after bullish crosses, traders may anticipate continuation and hold positions longer . The indicator is also effective as a trend filter when combined with its EMA color-coding : only taking trades in the trend’s direction and using the bands as dynamic profit zones.
Additionally, it can support multi-timeframe confluence (if you align your chart to the timeframes of interest), where higher-timeframe trend direction aligns with lower-timeframe percentile behavior for higher-probability setups. Swing traders can use it to frame pullbacks — entering near lower percentile bands during an uptrend — while intraday traders might use it to fade extremes or ride breakouts past the median band. Because the anchor price resets only on EMA crosses, the indicator preserves a consistent reference for ongoing trades, which is especially helpful for managing swing positions through noise .
Overall, its strength lies in transforming raw EMA distance data into actionable, probability-weighted levels that adapt to the instrument’s own volatility and tendencies .
Summary
This indicator transforms a simple EMA into a distribution-aware framework: it learns how far price tends to travel relative to the EMA on either side, and turns those excursions into percentile bands and historical hit rates anchored to the most recent cross. That makes it a flexible tool for targets, stops, and regime filtering, and a transparent way to reason about “how stretched is stretched?”—with context from your chosen market and timeframe.
I hope you all enjoy!
And as always, safe trades!
Liquidity Swing Points [BackQuant]Liquidity Swing Points
This tool marks recent swing highs and swing lows and turns them into persistent horizontal “liquidity” levels. These are places where resting orders often accumulate, such as stop losses above prior highs and below prior lows. The script detects confirmed pivots, records their prices, draws lines and labels, and manages their lifecycle on the chart so you can monitor potential sweep or breakout zones without manual redrawing.
What it plots
LQ-H at confirmed swing highs
LQ-L at confirmed swing lows
Horizontal levels that can optionally extend into the future
Timed removal of old levels to keep the chart clean
Each level stores its price, the bar where it was created, its type (high or low), plus a label and a line reference for efficient updates.
How it works
Pivot detection
A swing high is confirmed when the highest high has swing_length bars on both sides that are lower.
A swing low is confirmed when the lowest low has swing_length bars on both sides that are higher.
Pivots are only marked after they are confirmed, so they do not repaint.
Level creation
When a pivot confirms, the script records the price and the creation bar (offset by the right lookback).
A new line is plotted at that price, labeled LQ-H or LQ-L.
Rendering and extension
Levels can be drawn to the most recent bar only or extended to the right for forward reference.
Label size and line color/transparency are configurable.
Lifecycle management
On each confirmed bar, the script checks level age.
Levels older than a chosen bar count are removed automatically to reduce clutter.
How it can be used
Liquidity sweeps: Watch for price to probe beyond a level then close back inside. That behavior often signals a potential fade back into the prior range.
Breakout validation: If price pushes through a level and holds on closes, traders may treat that as continuation. Retests of the level from the other side can serve as structure checks.
Context for entries and exits: Use nearby LQ-H or LQ-L as reference for stop placement or partial-take zones, especially when other tools agree.
Multi-timeframe mapping: Plot swing points on higher timeframes, then drill down to time entries on lower timeframes as price interacts with those levels.
Why liquidity levels matter
Prior swing points are focal areas where many strategies set stops or pending orders. Price often revisits these zones, either to “sweep” resting liquidity before reversing, or to absorb it and trend. Marking these areas objectively helps frame scenarios like failed breaks, successful breakouts, and retests, and it reduces the subjectivity of eyeballing structure.
Settings to know
Swing Detection Length (swing_length), Controls sensitivity. Lower values find more local swings. Higher values find more significant ones.
Bars until removal (removeafter), Deletes levels after a fixed number of bars to prevent buildup.
Extend Levels Right (extend_levels), Keeps levels projected into the future for easier planning.
Label Size (label_size), Choose tiny to large for chart readability.
One color input controls both high and low levels with transparency for context.
Strengths
Objective marking of recent structure without hand drawing
No repaint after confirmation since pivots are locked once the right lookback completes
Lightweight and fast with simple lifecycle management
Clear visuals that integrate well with any price-action workflow
Practical tips
For scalping: use smaller swing_length to capture more granular liquidity. Keep removeafter short to avoid clutter.
For swing trading: increase swing_length so only more meaningful levels remain. Consider extending levels to the right for planning.
Combine with time-of-day filters, ATR for stop sizing, or a separate trend filter to bias trades taken at the levels.
Keep screenshots focused: one image showing a sweep and reversal, another showing a clean breakout and retest.
Limitations and notes
Levels appear after confirmation, so they are delayed by swing_length bars. This is by design to avoid repainting.
On very noisy or illiquid symbols, you may see many nearby levels. Increasing swing_length and shortening removeafter helps.
The script does not assess volume or session context. Consider pairing with volume or session tools if that is part of your process.
TAPDA Vision by TSINCHRONISE ft Grok This is the newly created TAPDA vision indictor 🔮
This time I used Grok to make the entire thing, It currently is working but I am refining and will be upgrading some features.
For now it can carry out a number of important tasks for TAPDA traders :
-Highlights FVGs that haven't been tapped within customizable size an time parameters
-Highlights OBs that haven't been tapped within customizable size an time parameters
-Has Option to Highlight PD Arrays in for 3 different specific times of day (optional)
-Has a Dynamic Highlight function which will highlight untapped PD arrays which were formed in the current hour you are using the indicator and adjusts every hour automatically
This is a work in progress but is useable - Updates to come.
Average Daily Range TrackerAverage Daily Range Tracker
This indicator helps you measure volatility in real time by tracking the Average Daily Range (ADR) and comparing it to the current day’s price action.
🔑 Features
Calculates the ADR over a user-defined lookback period (default = 14 days).
Displays today’s developing range (High–Low) as the session unfolds.
Shows what % of the ADR has already been consumed intraday.
Visual progress bar makes it easy to see how close today is to its historical average range.
Optional ADR plot available in a separate pane.
📈 How traders use it
Spot when a market has already made its “typical” daily move.
Adjust intraday trade expectations: avoid chasing after the bulk of the move is done.
Use % of ADR consumed as a volatility filter for setups.
Combine with support/resistance to identify exhaustion zones.
⚙️ Customization
Lookback length for ADR calculation.
Progress bar size and color.
Optional toggle to plot ADR in its own panel.
Follow-up Buy / Sell Volume Pressure at Supply / Demand Zones█ Overview:
BE-Volume Footprint & Pressure Candles, is an indicator which is preliminarily designed to analyze the supply and demand patterns based on Rally Base Rally (RBR), Drop Base Drop (DBD), Drop Base Rally (DBR) & Rally Base Drop (RBD) concepts in conjunction to volume pressure. Understanding these concepts are crucial. Let's break down why the "Base" is you Best friend in this context.
Commonness in RBR, DBD, DBR, RBD patterns ?
There is an impulse price movement at first, be it rally (price moving up) or the Drop (price moving down), followed by a period of consolidation which is referred as "BASE" and later with another impulse move of price (Rally or Drop).
Why is the Base Important
1. Market Balance: Base represents a balance between buyers and sellers. This is where decisions are made.
2. Confirmation: It confirms the strength of previous impulse move which has happened.
Base & the Liquidity Play:
Supply & Demand Zone predict the presence of all large orders within the limits of the Base Zone. Price is expected to return to the zone to fill the unfilled orders placed by large players.
For the price to move in the intended direction Liquidity plays the major role. hence indicator aims to help traders in identifying those zones where liquidity exists and the volume pressure helps in confirming that liquidity is making its play.
Bottom pane in the below snapshots is a visual representation of Buyers volume pressure (Green Line & the Green filled area) making the price move upwards vs Sellers volume pressure (Red Line & the Red filled area) making the price move downwards.
Top pane in the below snapshots is a visual representation on the pattern identification (Blue marked zone & the Blue line referred as Liquidity level)
Bullish Pressure On Buy Liquidity:
Bearish Pressure On Sell Liquidity:
█ How It Works:
1. Indicator computes technical & mathematical operations such as ATR, delta of Highs & Lows of the candle and Candle ranges to identify the patterns and marks the liquidity lines accordingly.
2. Indicator then waits for price to return to the liquidity levels and checks if Directional volume pressure to flow-in while the prices hover near the Liquidity zones.
3. Once the Volume pressure is evident, loop in to the ride.
█ When It wont Work:
When there no sufficient Liquidity or sustained Opposite volume pressure, trades are expected to fail.
█ Limitations:
Works only on the scripts which has volume info. Relays on LTF candles to determine intra-bar volumes. Hence, Use on TF greater than 1 min and lesser than 15 min.
█ Indicator Features:
1. StrictEntries: employs' tighter rules (rather most significant setups) on the directional volume pressure applied for the price to move. If unchecked, liberal rules applied on the directional volume pressure leading to more setups being identified.
2. Setup Confirmation period: Indicates Waiting period to analyze the directional volume pressure. Early (lesser wait period) is Risky and Late (longer wait period) is too late for the
ride. Find the quant based on the accuracy of the setup provided in the bottom right table.
3. Algo Enabled with Place Holders:
Indicator is equipped with algo alerts, supported with necessary placeholders to trade any instrument like stock, options etc.
Accepted PlaceHolders (Case Sensitive!!)
1. {{ticker}}-->InstrumentName
2. {{datetime}}-->Date & Time Of Order Placement
3. {{close}}-->LTP Price of Script
4. {{TD}}-->Current Level:
Note: Negative Numbers for Short Setup
5. {{EN}} {{SL}} {{TGT}} {{T1}} {{T2}} --> Trade Levels
6. {{Qty}} {{Qty*x}} --> Qty -> Trade Qty mapped in Settings. Replace x with actual number of your choice for the multiplier
7. {{BS}}-->Based on the Direction of Trade Output shall be with B or S (B == Long Trade & S == Short Trade)
8. {{BUYSELL}}-->Based on the Direction of Trade Output shall be with BUY or SELL (BUY == Long Trade & SELL == Short Trade)
9. {{IBUYSELL}}-->Based on the Direction of Trade Output shall be with BUY or SELL (BUY == SHORT Trade & SELL == LONG Trade)
Dynamic Alerts:
10. { {100R0} }-->Dynamic Place Holder 100 Refers to Strike Difference and Zero refers to ATM
11. { {100R-1} }-->Dynamic Place Holder 100 Refers to Strike Difference and -1 refers to
ATM - 100 strike
12. { {50R2} }-->Dynamic Place Holder 50 Refers to Strike Difference and 2 refers to
ATM + (2 * 50 = 100) strike
13. { {"ddMMyy", 0} }-->Dynamically Picks today date in the specified format.
14. { {"ddMMyy", n} }-->replace n with actual number of your choice to Pick date post today date in the specified format.
15. { {"ddMMyy", "MON"} }-->dynamically pick Monday date (coming Monday, if today is not Monday)
Note. for the 2nd Param-->you can choose to specify either Number OR any letter from =>
16. {{CEPE}} {{ICEPE}} {{CP}} {{ICP}} -> Dynamic Option Side CE or C refers to Calls and PE or P refers to Puts. If "I" is used in PlaceHolder text, On long entries PUTs shall be used
Indicator is equipped with customizable Trade & Risk management settings like multiple Take profit levels, Trailing SL.
Anchored Grids ft. VolumeINTRO
The 'Volume Profile' is a great tool, isn’t it? It shows us where volume has accumulated on the chart and helps guide trading decisions. The only catch is that we can’t really choose the levels—it’s all based on where volume happens to cluster. But what if we reversed the logic and measured the volume at the levels we define? That’s exactly what this script does, giving you a fresh way to spot support and resistance :)
OVERVIEW
'Anchored Grids ft. Volume' is a sophisticated technical analysis tool that combines price grid analysis with volume accumulation metrics. This indicator dynamically calculates and displays custom support and resistance levels based on a user-defined timeframe, while simultaneously tracking and visualizing volume accumulation at each specific price level. Unlike traditional volume profile indicators that use complex statistical clustering, this tool provides straightforward volume measurement at predetermined technical levels. It answers a critical question: "How much trading activity occurred near the key price levels I care about?".
HOW DOES THIS INDICATOR WORK?
This indicator builds a customizable grid system anchored to the opening price of any user-selected timeframe (hourly, daily, weekly, etc.). From that anchor point, it continuously tracks the highest high and lowest low, then calculates equidistant grid levels within that range. Two calculation modes are available—Arithmetic and Geometric—allowing flexibility in how the levels are distributed.
Once the grid is established, a volume accumulation engine comes into play. For each price bar, the script checks whether the bar’s range intersects with any level’s tolerance zone (default 0.01%). If a touch is detected, that bar’s volume is added to the corresponding level. Over time, this process builds a clear picture of where significant trading activity has clustered.
The visualization system highlights these dynamics by applying a color gradient based on volume intensity and adjusting line thickness proportional to accumulated volume. Each level is also labeled with four key data points:
The grid number (in square brackets)
The price of the level
The percentage distance between the level and the opening price of the selected timeframe
The total volume accumulated within the level’s tolerance range
PARAMETERS
Timeframe: Defines the anchor period for grid calculation. Then, the indicator automatically determines the open, high, and low prices.
Mode: This option determines how the distance between levels is calculated: Arithmetic (linear) means equal price spacing between levels, while Geometric (logarithmic) means equal percentage spacing between levels.
Grids: It's the number of levels between high and low.
Color: Base color for grid lines and labels. When volume data is displayed, lower values are darkened by 50%.
Show Volume Accumulation: When this parameter is activated, the volume calculation is enabled.
Tolerance : The Tolerance parameter (default range: 0.01%) defines the price range around each grid level where volume accumulation is registered. It acts as a sensitivity control that determines how close price must be to a level to count trading volume toward that level's accumulation.
ORIGINALITY
It’s possible to find comprehensive grid-drawing tools among community indicators, but I haven’t come across an example that combines this concept with volume data. More importantly, I wanted to demonstrate how volume accumulation can be generated for any data modeled as an array on the chart by developers.
SUMMARY
In conclusion, the selected timeframe and the number of grids are only used as a reference to determine where the levels are drawn. The true value of this indicator lies in its ability to calculate volume accumulation directly from the chart’s own candles, showing how much trading activity occurred around each level. The result is a hybrid framework that merges structural price analysis with volume distribution, offering traders deeper insights into where markets are likely to react.
NOTE
While powerful, this tool should be used as part of a comprehensive trading strategy rather than as a standalone system. Always combine with risk management principles and market context awareness. I hope it helps everyone. Trade as safely as possible. Best of luck!
Trading Stats BarSimple statistics bar designed to give important values for swing trading
Most of the values are self explanatory
Float Grade
Combines float and float % designed to give a sense if the stock has the potential to move quickly. If the float is less than 20 million and float % less than 50, this has a high potential to make fast moves.
Volume Run Rate
Concept is to focus on the opening x minutes and average this value over the previous y days
SExI - Super Exhaustion Indicator [Da_Prof]As we know, the RSI can remain at "overbought" or "oversold" levels for long periods of time while the price continues in that direction. The SExI (Super Exhaustion Indicator) is an indicator designed to help detect exhaustion of strong moves.
The SExI is a combination of the RSI and "upper" Aroon. For the indicator to trigger, the RSI has to be above or below a top/bottom trigger line when the Aroon has had a set number of drives up or down correspondingly. An Aroon top drive is defined as the Aroon hitting 100% on the current candle when the previous candle was below 100%. An Aroon bottom drive is defined as the Aroon hitting 0% on the current candle when the previous candle was above 0%. Consecutive top or bottom drives are counted and exhaustion triggers when these drives hit a setpoint (default is 5 drives = the Aroon exhaustion trigger). When Aroon exhaustion is triggered and the RSI is correspondingly above/below a trigger line, the overall indicator signals exhaustion. There are two lines for bottoms and tops, one each for a "normal" trigger and and an "extreme" trigger.
The Aroon drives are visualized at the top and bottom of the indicator. The RSI is plotted as a line that crosses top and bottom trigger lines. There are extreme trigger values for both the bottom and top exhaustion triggers.
--Da_Prof
Weekly pecentage tracker by PRIVATE
Settings Picture below this link: 👇
i.ibb.co
What it is
A lightweight “Weekly % Tracker” overlay that lets you manually enter weekly performance (in percent) for XAUUSD + up to 10 FX pairs, then shows:
a small table panel with each enabled symbol and its % result
one TOTAL row (Sum / Average / Compounded across all enabled symbols)
an optional mini badge showing the % for a single selected symbol
Nothing is auto-calculated from price—you type the % yourself.
Key settings
Panel: show/hide, position, number of decimals, colors (background, text, green/red).
Total mode:
Sum – adds percentages
Average – mean of enabled rows
Compounded –
(
∏
(
1
+
𝑝
/
100
)
−
1
)
×
100
(∏(1+p/100)−1)×100
Symbols:
XAUUSD (toggle + label + % input)
10 FX pairs (each has On/Off, label text, % input). You can rename labels to any symbol text you want.
Mini badge: show/hide, position, and symbol to display.
How it works
Overlay indicator: overlay=true; just draws UI on the chart (no plots).
Arrays (syms, vals, ons) collect the row data in order: XAU first, then FX1…FX10.
Helpers:
posFrom() converts a position string (e.g., “Top Right”) into a position.* constant.
wp_col() picks green/red/neutral based on the sign of the %.
wp_round() rounds values to the selected decimals.
calc_total() computes the TOTAL with the chosen mode over enabled rows only.
Table creation logic:
Counts how many rows are enabled.
If none enabled or panel is off: the panel table is deleted, so no box/background is visible.
If enabled and on: the panel is (re)created at the chosen position.
On each last bar (barstate.islast), it clears the table to transparent (bgcolor=na) and then fills one row per enabled symbol, followed by a single TOTAL row.
Mini badge:
Always (re)created on position change.
Shows selected symbol’s % (or “-” if that symbol isn’t enabled or has no value).
Colors text green/red by sign.
Notes & limits
It’s manual input—the script doesn’t read trades or P/L from price.
You can rename each row’s label to match any symbol name you want.
When no rows are enabled, the panel disappears entirely (no empty background).
Designed to be light: only draws tables; no heavy plotting.
If you want the TOTAL row to be optional, or different color thresholds, or CSV-style export/import of the values, say the word and I’ll add it.
DYNAMIC TRADING DASHBOARDStudy Material for the "Dynamic Trading Dashboard"
This Dynamic Trading Dashboard is designed as an educational tool within the TradingView environment. It compiles commonly used market indicators and analytical methods into one visual interface so that traders and learners can see relationships between indicators and price action. Understanding these indicators, step by step, can help traders develop discipline, improve technical analysis skills, and build strategies. Below is a detailed explanation of each module.
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1. Price and Daily Reference Points
The dashboard displays the current price, along with percentage change compared to the day’s opening price. It also highlights whether the price is moving upward or downward using directional symbols. Alongside, it tracks daily high, low, open, and daily range.
For traders, daily levels provide valuable reference points. The daily high and low are considered intraday support and resistance, while the median price of the day often acts as a pivot level for mean reversion traders. Monitoring these helps learners see how price oscillates within daily ranges.
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2. VWAP (Volume Weighted Average Price)
VWAP is calculated as a cumulative average price weighted by volume. The dashboard compares the current price with VWAP, showing whether the market is trading above or below it.
For traders, VWAP is often a guide for institutional order flow. Price trading above VWAP suggests bullish sentiment, while trading below VWAP indicates bearish sentiment. Learners can use VWAP as a training tool to recognize trend-following vs. mean reversion setups.
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3. Volume Analysis
The system distinguishes between buy volume (when the closing price is higher than the open) and sell volume (when the closing price is lower than the open). A progress bar highlights the ratio of buying vs. selling activity in percentage.
This is useful because volume confirms price action. For instance, if prices rise but sell volume dominates, it can signal weakness. New traders learning with this tool should focus on how volume often precedes price reversals and trends.
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4. RSI (Relative Strength Index)
RSI is a momentum oscillator that measures price strength on a scale from 0 to 100. The dashboard classifies RSI readings into overbought (>70), oversold (<30), or neutral zones and adds visual progress bars.
RSI helps learners understand momentum shifts. During training, one should notice how trending markets can keep RSI extended for longer periods (not immediate reversal signals), while range-bound markets react more sharply to RSI extremes. It is an excellent tool for practicing trend vs. range identification.
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5. MACD (Moving Average Convergence Divergence)
The MACD indicator involves a fast EMA, slow EMA, and signal line, with focus on crossovers. The dashboard shows whether a “bullish cross” (MACD above signal line) or “bearish cross” (MACD below signal line) has occurred.
MACD teaches traders to identify trend momentum shifts and divergence. During practice, traders can explore how MACD signals align with VWAP trends or RSI levels, which helps in building a structured multi-indicator analysis.
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6. Stochastic Oscillator
This indicator compares the current close relative to a range of highs and lows over a period. Displayed values oscillate between 0 and 100, marking zones of overbought (>80) and oversold (<20).
Stochastics are useful for students of trading to recognize short-term momentum changes. Unlike RSI, it reacts faster to price volatility, so false signals are common. Part of the training exercise can be to observe how stochastic “flips” can align with volume surges or daily range endpoints.
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7. Trend & Momentum Classification
The dashboard adds simple labels for trend (uptrend, downtrend, neutral) based on RSI thresholds. Additionally, it provides quick momentum classification (“bullish hold”, “bearish hold”, or neutral).
This is beneficial for beginners as it introduces structured thinking: differentiating long-term market bias (trend) from short-term directional momentum. By combining both, traders can practice filtering signals instead of trading randomly.
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8. Accumulation / Distribution Bias
Based on RSI levels, the script generates simplified tags such as “Accumulate Long”, “Accumulate Short”, or “Wait”.
This is purely an interpretive guide, helping learners think in terms of accumulation phases (when markets are low) and distribution phases (when markets are high). It reinforces the concept that trading is not only directional but also involves timing.
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9. Overall Market Status and Score
Finally, the dashboard compiles multiple indicators (VWAP position, RSI, MACD, Stochastics, and price vs. median levels) into a Market Score expressed as a percentage. It also labels the market as Overbought, Oversold, or Normal.
This scoring system isn’t a recommendation but a learning framework. Students can analyze how combining different indicators improves decision-making. The key training focus here is confluence: not depending on one indicator but observing when several conditions align.
Extended Study Material with Formulas
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1. Daily Reference Levels (High, Low, Open, Median, Range)
• Day High (H): Maximum price of the session.
DayHigh=max(Hightoday)DayHigh=max(Hightoday)
• Day Low (L): Minimum price of the session.
DayLow=min(Lowtoday)DayLow=min(Lowtoday)
• Day Open (O): Opening price of the session.
DayOpen=OpentodayDayOpen=Opentoday
• Day Range:
Range=DayHigh−DayLowRange=DayHigh−DayLow
• Median: Mid-point between high and low.
Median=DayHigh+DayLow2Median=2DayHigh+DayLow
These act as intraday guideposts for seeing how far the price has stretched from its key reference levels.
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2. VWAP (Volume Weighted Average Price)
VWAP considers both price and volume for a weighted average:
VWAPt=∑i=1t(Pricei×Volumei)∑i=1tVolumeiVWAPt=∑i=1tVolumei∑i=1t(Pricei×Volumei)
Here, Price_i can be the average price (High + Low + Close) ÷ 3, also known as hlc3.
• Interpretation: Price above VWAP = bullish bias; Price below = bearish bias.
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3. Volume Buy/Sell Analysis
The dashboard splits total volume into buy volume and sell volume based on candle type.
• Buy Volume:
BuyVol=Volumeif Close > Open, else 0BuyVol=Volumeif Close > Open, else 0
• Sell Volume:
SellVol=Volumeif Close < Open, else 0SellVol=Volumeif Close < Open, else 0
• Buy Ratio (%):
VolumeRatio=BuyVolBuyVol+SellVol×100VolumeRatio=BuyVol+SellVolBuyVol×100
This helps traders gauge who is in control during a session—buyers or sellers.
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4. RSI (Relative Strength Index)
RSI measures strength of momentum by comparing gains vs. losses.
Step 1: Compute average gains (AG) and losses (AL).
AG=Average of Upward Closes over N periodsAG=Average of Upward Closes over N periodsAL=Average of Downward Closes over N periodsAL=Average of Downward Closes over N periods
Step 2: Calculate relative strength (RS).
RS=AGALRS=ALAG
Step 3: RSI formula.
RSI=100−1001+RSRSI=100−1+RS100
• Used to detect overbought (>70), oversold (<30), or neutral momentum zones.
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5. MACD (Moving Average Convergence Divergence)
• Fast EMA:
EMAfast=EMA(Close,length=fast)EMAfast=EMA(Close,length=fast)
• Slow EMA:
EMAslow=EMA(Close,length=slow)EMAslow=EMA(Close,length=slow)
• MACD Line:
MACD=EMAfast−EMAslowMACD=EMAfast−EMAslow
• Signal Line:
Signal=EMA(MACD,length=signal)Signal=EMA(MACD,length=signal)
• Histogram:
Histogram=MACD−SignalHistogram=MACD−Signal
Crossovers between MACD and Signal are used in studying bullish/bearish phases.
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6. Stochastic Oscillator
Stochastic compares the current close against a range of highs and lows.
%K=Close−LowestLowHighestHigh−LowestLow×100%K=HighestHigh−LowestLowClose−LowestLow×100
Where LowestLow and HighestHigh are the lowest and highest values over N periods.
The %D line is a smooth version of %K (using a moving average).
%D=SMA(%K,smooth)%D=SMA(%K,smooth)
• Values above 80 = overbought; below 20 = oversold.
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7. Trend and Momentum Classification
This dashboard generates simplified trend/momentum logic using RSI.
• Trend:
• RSI < 40 → Downtrend
• RSI > 60 → Uptrend
• In Between → Neutral
• Momentum Bias:
• RSI > 70 → Bullish Hold
• RSI < 30 → Bearish Hold
• Otherwise Neutral
This is not predictive, only a classification framework for educational use.
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8. Accumulation/Distribution Bias
Based on extreme RSI values:
• RSI < 25 → Accumulate Long Bias
• RSI > 80 → Accumulate Short Bias
• Else → Wait/No Action
This helps learners understand the idea of accumulation at lows (strength building) and distribution at highs (profit booking).
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9. Overall Market Status and Score
The tool adds up 5 bullish conditions:
1. Price above VWAP
2. RSI > 50
3. MACD > Signal
4. Stochastic > 50
5. Price above Daily Median
BullishScore=ConditionsMet5×100BullishScore=5ConditionsMet×100
Then it categorizes the market:
• RSI > 70 or Stoch > 80 → Overbought
• RSI < 30 or Stoch < 20 → Oversold
• Else → Normal
This encourages learners to think in terms of probabilistic conditions instead of single-indicator signals.
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⚠️ Warning:
• Trading financial markets involves substantial risk.
• You can lose more money than you invest.
• Past performance of indicators does not guarantee future results.
• This script must not be copied, resold, or republished without authorization from aiTrendview.
By using this material or the code, you agree to take full responsibility for your trading decisions and acknowledge that this is not financial advice.
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⚠️ Disclaimer and Warning (From aiTrendview)
This Dynamic Trading Dashboard is created strictly for educational and research purposes on the TradingView platform. It does not provide financial advice, buy/sell recommendations, or guaranteed returns. Any use of this tool in live trading is completely at the user’s own risk. Markets are inherently risky; losses can exceed initial investment.
The intellectual property of this script and its methodology belongs to aiTrendview. Unauthorized reproduction, modification, or redistribution of this code is strictly prohibited. By using this study material or the script, you acknowledge personal responsibility for any trading outcomes. Always consult professional financial advisors before making investment decisions.
VWAP Executor — v6 (VWAP fix)tarek helishPractical scalping plan with high-rate (sometimes reaching 70–85% in a quiet market)
Concept: “VWAP bounce with a clear trend.”
Tools: 1–3-minute chart for entry, 5-minute trend filter, VWAP, EMA(50) on 5M, ATR(14) on 1M, volume.
When to trade: London session or early New York session; avoid 10–15 minutes before/after high-impact news.
Entry rules (buy for example):
Trend: Price is above the EMA(50) on 5M and has an upward trend.
Entry zone: First bounce to VWAP (or a ±1 standard deviation channel around it).
Signal: Bullish rejection/engulfing candle on 1M with increasing volume, and RSI(2) has exited oversold territory (optional).
Order: Entry after the confirmation candle closes or a limit close to VWAP.
Trade Management:
Stop: Below the bounce low or 0.6xATR(1M) (strongest).
Target: 0.4–0.7xATR(1M) or the previous micro-high (small return to increase success rate).
Trigger: Move the stop to breakeven after +0.25R; close manually if the 1M candle closes strongly against you.
Filter: Do not trade if the spread widens, or the price "saws" around VWAP without a trend.
Sell against the rules in a downtrend.
Why this plan raises the heat-rate? You buy a "small discount" within an existing trend and near the institutional average price (VWAP), with a small target price.
مواقعي شركة الماسة للخدمات المنزلية
شركة تنظيف بالرياض
نقل عفش بالرياض
Candlestick Patterns Dashboard Pro+ [ULTIMATE]Unleash the power of automated candlestick analysis with the most comprehensive and customizable pattern detection tool on TradingView. This is not just another pattern scanner; it's a complete trading dashboard designed to identify, score, and confirm high-probability setups, saving you hours of manual chart analysis.
Built with performance and reliability in mind, this script goes beyond simple detection by introducing a unique reliability score for every pattern, advanced confirmation filters, and a powerful on-screen dashboard to keep you informed.
Key Features
📈 Comprehensive Pattern Detection: Automatically identifies 13 of the most effective candlestick patterns, including Bullish/Bearish Engulfing, Hammer, Shooting Star, Doji, Morning/Evening Star, and more.
🔟 Dynamic Reliability Scoring: Every pattern is assigned a score from 1-10 based on its confirmation strength. Factors include candle body size, volume confirmation, trend alignment, and higher-timeframe confluence, giving you a quantifiable measure of a pattern's potential.
📊 The Ultimate Dashboard: Your at-a-glance command center. The on-screen dashboard provides a complete summary of all active patterns, showing you exactly when they last occurred and highlighting the most recent signals. It also includes an "Overall Bias" meter for a quick sentiment check.
🛡️ Trade Smarter with Advanced Confirmation Filters: Eliminate low-quality signals and focus on what matters.
Trend Alignment: Use SMA(50) and SMA(200) to only show patterns that agree with the dominant market trend.
Volume Confirmation: Validate patterns by requiring a surge in volume.
Non-Repainting HTF Confirmation: Ensure your patterns align with the trend on a higher timeframe (e.g., Daily trend for a 4H signal) using a reliable, non-repainting method.
Market Condition Filter: Isolate patterns that occur only in "Trending" or "Ranging" markets.
Time Filter: Restrict pattern detection to specific trading sessions.
🔧 ‘Fuzzy Logic’ for Real-World Trading: Textbook patterns are rare. Use the "Fuzzy Logic" settings to adjust the criteria for patterns like the Hammer, Piercing Line, and Doji, allowing you to catch imperfect but still valid real-world formations.
⚙️ Fully Customizable Scoring: You decide what's important! Adjust the bonus scores for volume, trend, and other factors to create a scoring system that perfectly aligns with your trading strategy.
🚨 Powerful & Customizable Alerts: Never miss an opportunity.
Create alerts for any individual pattern.
Get notified of "Pattern Clusters" when multiple bullish or bearish signals appear in close succession.
Customize the alert messages to be compatible with your favorite trading automation services.
🚀 Performance Optimized: A "Max Bars Back" setting ensures the script runs smoothly and efficiently, even on lower-end devices or extensive historical data.
How To Use This Indicator
For Confirmation: The primary strength of this tool is for confirmation. Do not trade based on patterns alone. Use the detected signals to confirm your own analysis, such as a pattern appearing at a key support/resistance level, a trendline, or a Fibonacci retracement. A Bullish Engulfing pattern at a major support level is a much stronger signal than one appearing in the middle of a range.
For Discovery: Use the Dashboard to quickly scan through your favorite assets. A dashboard full of recent bullish signals on one asset, and bearish on another, can instantly help you focus your attention for the day.
Customizing for Your Style:
Start with the Market Presets ("Forex," "Stocks," "Crypto") for a solid baseline.
Dive into the Scoring Weights to tell the indicator what you value most. A pure volume trader might increase the Volume Bonus score.
Adjust the Fuzzy Logic settings based on your market's volatility. A volatile crypto market might require a more lenient Doji definition than a stable blue-chip stock.
Setting Up Alerts:
Add the indicator to your chart.
Click the "Alert" button in the TradingView toolbar.
Set the "Condition" to "Candlestick Patterns Dashboard Pro+ ".
Choose the specific alert you want from the dropdown (e.g., "Bullish Pattern Detected," "Bearish Pattern Cluster").
Customize the message if needed and click "Create."
A Note of Thanks
This script began as a personal project and has evolved into this ultimate version thanks to invaluable community feedback, bug reports, and suggestions. A special thank you to the users who helped identify and fix critical bugs related to syntax and variable scope. This collaborative effort has made the indicator more robust and reliable for everyone.
Disclaimer: This tool is for educational and analytical purposes only. All trading involves substantial risk. Past performance is not indicative of future results. Please trade responsibly.
ST-Stochastic DashboardST-Stochastic Dashboard: User Manual & Functionality
1. Introduction
The ST-Stochastic Dashboard is a comprehensive tool designed for traders who utilize the Stochastic Oscillator. It combines two key features into a single indicator:
A standard, fully customizable Stochastic Oscillator plotted directly on your chart.
A powerful Multi-Timeframe (MTF) Dashboard that shows the status of the Stochastic %K value across three different timeframes of your choice.
This allows you to analyze momentum on your current timeframe while simultaneously monitoring for confluence or divergence on higher or lower timeframes, all without leaving your chart.
Disclaimer: In accordance with TradingView's House Rules, this document describes the technical functionality of the indicator. It is not financial advice. The indicator provides data based on user-defined parameters; all trading decisions are the sole responsibility of the user. Past performance is not indicative of future results.
2. How It Works (Functionality)
The indicator is divided into two main components:
A. The Main Stochastic Indicator (Chart Pane)
This is the visual representation of the Stochastic Oscillator for the chart's current timeframe.
%K Line (Blue): This is the main line of the oscillator. It shows the current closing price in relation to the high-low range over a user-defined period. A high value means the price is closing near the top of its recent range; a low value means it's closing near the bottom.
%D Line (Black): This is the signal line, which is a moving average of the %K line. It is used to smooth out the %K line and generate trading signals.
Overbought Zone (Red Area): By default, this zone is above the 75 level. When the Stochastic lines are in this area, it indicates that the asset may be "overbought," meaning the price is trading near the peak of its recent price range.
Oversold Zone (Blue Area): By default, this zone is below the 25 level. When the Stochastic lines are in this area, it indicates that the asset may be "oversold," meaning the price is trading near the bottom of its recent price range.
Crossover Signals:
Buy Signal (Blue Up Triangle): A blue triangle appears below the candles when the %K line crosses above the Oversold line (e.g., from 24 to 26). This suggests a potential shift from bearish to bullish momentum.
Sell Signal (Red Down Triangle): A red triangle appears above the candles when the %K line crosses below the Overbought line (e.g., from 76 to 74). This suggests a potential shift from bullish to bearish momentum.
B. The Multi-Timeframe Dashboard (Table on Chart)
This is the informational table that appears on your chart. Its purpose is to give you a quick, at-a-glance summary of the Stochastic's condition on other timeframes.
Function: The script uses TradingView's request.security() function to pull the %K value from three other timeframes that you specify in the settings.
Efficiency: The table is designed to update only on the last (most recent) bar (barstate.islast) to ensure the script runs efficiently and does not slow down your chart.
Columns:
Timeframe: Displays the timeframe you have selected (e.g., '5', '15', '60').
Stoch %K: Shows the current numerical value of the %K line for that specific timeframe, rounded to two decimal places.
Status: Interprets the %K value and displays a clear status:
OVERBOUGHT (Red Background): The %K value is above the "Upper Line" setting.
OVERSOLD (Blue Background): The %K value is below the "Lower Line" setting.
NEUTRAL (Black/Dark Background): The %K value is between the Overbought and Oversold levels.
3. Settings / Parameters in Detail
You can access these settings by clicking the "Settings" (cogwheel) icon on the indicator name.
Stochastic Settings
This group controls the behavior and appearance of the main Stochastic indicator plotted in the pane.
Stochastic Period (length)
Description: This is the lookback period used to calculate the Stochastic Oscillator. It defines the number of past bars to consider for the high-low range.
Default: 9
%K Smoothing (smoothK)
Description: This is the moving average period used to smooth the raw Stochastic value, creating the %K line. A higher value results in a smoother, less sensitive line.
Default: 3
%D Smoothing (smoothD)
Description: This is the moving average period applied to the %K line to create the %D (signal) line. A higher value creates a smoother signal line that lags further behind the %K line.
Default: 6
Lower Line (Oversold) (ul)
Description: This sets the threshold for the oversold condition. When the %K line is below this value, the dashboard will show "OVERSOLD". It is also the level the %K line must cross above to trigger a Buy Signal triangle.
Default: 25
Upper Line (Overbought) (ll)
Description: This sets the threshold for the overbought condition. When the %K line is above this value, the dashboard will show "OVERBOUGHT". It is also the level the %K line must cross below to trigger a Sell Signal triangle.
Default: 75
Dashboard Settings
This group controls the data and appearance of the multi-timeframe table.
Timeframe 1 (tf1)
Description: The first timeframe to be displayed in the dashboard.
Default: 5 (5 minutes)
Timeframe 2 (tf2)
Description: The second timeframe to be displayed in the dashboard.
Default: 15 (15 minutes)
Timeframe 3 (tf3)
Description: The third timeframe to be displayed in the dashboard.
Default: 60 (1 hour)
Dashboard Position (table_pos)
Description: Allows you to select where the dashboard table will appear on your chart.
Options: top_right, top_left, bottom_right, bottom_left
Default: bottom_right
4. How to Use & Interpret
Configuration: Adjust the Stochastic Settings to match your trading strategy. The default values (9, 3, 6) are common, but feel free to experiment. Set the Dashboard Settings to the timeframes that are most relevant to your analysis (e.g., your entry timeframe, a medium-term timeframe, and a long-term trend timeframe).
Analysis with the Dashboard: The primary strength of this tool is confluence. Look for situations where multiple timeframes align. For example:
If the dashboard shows OVERSOLD on the 15-minute, 60-minute, and your current 5-minute chart, a subsequent Buy Signal on your 5-minute chart may carry more weight.
Conversely, if your 5-minute chart shows OVERSOLD but the 60-minute chart is strongly OVERBOUGHT, it could indicate that you are looking at a minor pullback in a larger downtrend.
Interpreting States:
Overbought is not an automatic "sell" signal. It simply means momentum has been strong to the upside, and the price is near its recent peak. It could signal a potential reversal, but the price can also remain overbought for extended periods in a strong uptrend.
Oversold is not an automatic "buy" signal. It means momentum has been strong to the downside. While it can signal a potential bounce, prices can remain oversold for a long time in a strong downtrend.
Use the signals and dashboard states as a source of information to complement your overall trading strategy, which should include other forms of analysis such as price action, support/resistance levels, or other indicators.
CVD Polarity Indicator (With Rolling Smoothed)📊 CVD Polarity Indicator (with Rolling Smoothing)
Purpose
The CVD Polarity Indicator combines Cumulative Volume Delta (CVD) with price bar direction to measure whether buying or selling pressure is in agreement with price action. It then smooths that signal over time, making it easier to see underlying volume-driven market trends.
This indicator is essentially a volume–price agreement oscillator:
- It compares price direction with volume delta (CVD).
- Translates that into per-bar polarity.
- Smooths it into a rolling sum for clarity.
- Adds a short EMA to highlight turning points.
The end result: a tool that helps you see when price action is backed by real volume flows versus when it’s running on weak participation.
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1. Cumulative Volume Delta (CVD)
What it is:
CVD is the cumulative sum of buying vs. selling pressure measured by volume.
- If a bar closes higher than it opens → that bar’s volume is treated as buying pressure (+volume).
- If a bar closes lower than it opens → that bar’s volume is treated as selling pressure (–volume).
Rolling version:
Instead of accumulating indefinitely (which just creates a line that trends forever), this indicator uses a rolling sum over a user-defined number of bars (cumulation_length, default 14).
- This shows the net delta in recent bars, making the CVD more responsive and localized.
2. Bar Direction vs. CVD Change
Each bar has two pieces of directional information:
1. Bar direction: Whether the candle closed above or below its open (close - open).
2. CVD change: Whether cumulative delta increased or decreased from the prior bar (cvd - cvd ).
By comparing these two:
- Agreement (both up or both down):
→ Polarity = +volume (if bullish) or –volume (if bearish).
- Disagreement (bar up but CVD down, or bar down but CVD up):
→ Polarity flips sign, signaling divergence between price and volume.
Thus, raw polarity = a per-bar measure of whether price action and volume delta are in sync.
3. Polarity Smoothing (Rolling Polarity)
- Problem with raw polarity:
It flips bar-to-bar and looks very jagged — not great for seeing trends.
- Solution:
The indicator applies a rolling sum over the past polarity_length bars (default 14).
- This creates a smoother curve, representing the net polarity over time.
- Positive values = net bullish alignment (buyers stronger).
- Negative values = net bearish alignment (sellers stronger).
Think of it like an oscillator showing whether buyers or sellers have had control recently.
4. EMA Smoothing
Finally, a 10-period EMA is applied on top of the rolling polarity line:
- This further reduces noise.
- It helps highlight shifts in the underlying polarity trend.
- Crossovers of the polarity line and its EMA can serve as trade signals (bullish/bearish inflection points).
________________________________________________________________________________
How to Read It
1. Polarity above zero → Recent bars show more bullish agreement between price and volume.
2. Polarity below zero → Recent bars show more bearish agreement.
3. Polarity diverging from price → If price goes up but polarity trends down, it signals weakening buying pressure (potential reversal).
4. EMA crossovers →
- Polarity crossing above its EMA = bullish momentum shift.
- Polarity crossing below its EMA = bearish momentum shift.
Practical Use Cases
- Trend Confirmation
Use polarity to confirm whether a price move is supported by volume. If price rallies but
polarity stays negative, the move is weak.
- Divergence Signals
Watch for divergences between price trend and polarity trend (e.g., higher highs in price but
lower highs in polarity).
- Momentum Shifts
Use EMA crossovers as signals that the underlying balance of buying/selling has flipped.
Fractals + FVG [Combined]Звісно, ось варіант опису англійською, який можна використати для публікації індикатора в TradingView.
Description
This script combines two powerful and widely-used trading concepts into a single, comprehensive indicator: Bill Williams Fractals with dynamic support/resistance lines and Fair Value Gaps (FVG) based on the popular logic from LuxAlgo.
The goal is to provide a cleaner chart by merging two essential tools, allowing traders to analyze market structure and imbalances simultaneously.
Features
1. Williams Fractals with Invalidation Lines
This part of the indicator identifies classic Bill Williams fractals and enhances them with a unique visualization feature.
Fractal Detection: Automatically identifies both bullish (bottom) and bearish (top) fractals. You can choose between a 3-bar or 5-bar pattern in the settings.
Dynamic S/R Lines: A horizontal line is automatically drawn from every confirmed fractal, acting as a potential support or resistance level.
Automatic Invalidation: A line is considered "invalidated" or breached when the body of a candle closes past it. When this happens, the line stops extending, changes its color to the "invalidated" color, and remains on the chart as a historical reference. This provides a clear, objective signal that a level has been broken.
Customization: You can fully customize the colors for the support, resistance, and invalidated lines to match your chart theme.
2. Fair Value Gaps (FVG) / Imbalance
This module incorporates the robust FVG detection logic from LuxAlgo to automatically identify and display market imbalances.
FVG Detection: Highlights bullish and bearish Fair Value Gaps on the chart with colored boxes, representing inefficiencies in price delivery.
Automatic Mitigation: The FVG boxes are automatically removed from the chart once the price has "mitigated" or filled the gap, keeping your workspace clean and focused on active imbalances.
Multi-Timeframe (MTF): You can set the indicator to find and display FVGs from a higher timeframe directly on your current chart.
Dashboard: An optional on-screen dashboard provides a quick summary of the total count of bullish/bearish FVGs and the percentage that have been mitigated.
Full Customization: Control the colors of FVG boxes, extend their length, and configure other visual style settings.
How to Use
Fractal Lines: Use the active support and resistance lines as key levels for potential bounces or breaks. A line's invalidation can serve as confirmation of a shift in market structure.
FVG Zones: Fair Value Gaps often act as "magnets" for price. Use these zones as potential targets for your trades or as areas of interest for entries when price retraces to fill the imbalance.
Combined Strategy: The true power of this indicator comes from combining both concepts. For example, a bullish FVG forming near a key fractal support level can create a high-probability confluence zone for a long entry. Similarly, a break and invalidation of a fractal resistance line might signal that price is heading towards the next bearish FVG above.
This indicator is a tool for analysis and should be used in conjunction with your own trading strategy and risk management rules.
