trader_yang_001_v1📈 指標簡介
歡迎使用這個指標！
我是 Yang，致力於打造簡單直覺、實用的交易工具，幫助交易者快速上手。
⚙️ 使用前注意事項
1.可以調整【靈敏度】參數：
請依據你的「交易標的」與「時間級別」進行回測與調整，找到最適合你的數值。
2.此指標支援快訊通知，但請注意：
有時快訊可能會在當前 K 棒尚未收盤前觸發。
理論上程式應該要在 K 棒收盤後才確認訊號，但此限制目前無法完全避免。
因此不建議直接連結 API 進行自動交易。
收到快訊時，請等 K 棒收盤並確認訊號後再進場。
💬 回饋與更新
歡迎追蹤我的 Instagram (ID：traderyang)，了解更新、版本改良與交易心得。
你的回饋對我非常重要，我會在下一個版本持續改進此工具。
🧾 版本資訊
公開版本 v1.0
© 2025 Yang — 保留所有權利
📈 About This Indicator
Welcome to this indicator!
I'm Yang, a developer focused on creating simple, intuitive, and effective tools for traders.
⚙️ Before You Start
1.You can adjust the Sensitivity parameter.
Please backtest and fine-tune it according to your trading instrument and timeframe to find the most suitable value for your setup.
2.This indicator supports alert notifications, but please note:
Alerts may occasionally trigger before the current candle fully closes.
Ideally, the script should only confirm signals after the candle close, but this limitation currently cannot be fully avoided.
Therefore, it’s not recommended to link alerts directly to an API for automated trading.
When you receive an alert, wait for the candle to close and verify the signal before taking any position.
💬 Feedback & Updates
Follow me on Instagram (ID：traderyang) for updates, new releases, and trading insights.
Your feedback is always welcome — I’ll continue improving this tool in future versions.
🧾 Version
Public Release v1.0
© 2025 Yang — All rights reserved.
지표 및 전략
REMS Synergy OverlayThis 3rd generation REMS indicator builds upon the foundations assessing the relationships between RSI, EMAs, MACDs, and Stochastic RSI across multiple timeframes. Designed to help traders identify less frequent, but high probability entries across 2 time frames. Uses 3 levels of confluence indicators for both long and short moves.
Confluence Level 1 (Highest Conviction):
Evaluates selected criteria across both timeframes. All selected criteria must be in confluence to trigger signal.
Confluence Level 2 (Moderate Conviction):
Selected criteria can be selected by each timeframe individually. All selected criteria must be in confluence to trigger signal.
Confluence Level 3 (Lower/supportive confluence):
Of the selected criteria, this level can evaluate a set number of conditions that must be met. Number of conditions is user-defined.
Includes VWAP and 4 EMAs as optional visual representations.
Includes 'Enhanced Candles' than can colour code candlesticks for better visual identification. (off by default)
Originally designed with 5 minute and 2 minute timeframes in mind, and pairs well with REMS First Strike and/or REMS Snap Shot indicators.
Values coded below:
RSI
-Primary: Length = 14, Smoothing = 20 (via SMA)
-Secondary: Length = 7, Smoothing = 20 (via SMA)
Stochastic RSI
Primary:
-RSI Length = 14
-Stochastic Length = 8
-%K = 3, %D = 3
Secondary:
-RSI Length = 7
-Stochastic Length = 7
-%K = 3, %D = 2
MACD - applied to both timeframes
-Fast = 12, Slow = 26, Signal = 9
Yuki Leverage RR Calculator**YUKI LEVERAGE RR CALCULATOR**
A professional-grade risk/reward calculator for leveraged crypto or forex trades.
Instantly visualizes entry, stop loss, targets, leverage, and risk-to-reward ratios — helping you plan precise positions with confidence.
──────────────────────────────
**WHAT IT DOES**
Calculates position value, quantity, stop-loss price, liquidation estimate, and per-target profit.
Displays everything in an on-chart table with optional price tags and alerts.
──────────────────────────────
**KEY FEATURES**
• Long / Short toggle (only one active at a time)
• Leverage-aware position sizing based on Position Cost ($) and Leverage
• Dynamic Stop Loss: input % → auto price + $ risk
• Up to 3 Take-Profit Targets with scaling logic
• Instant R:R ratios per target
• Liquidation estimate (approximation only)
• ENTRY / SL / T1 / T2 / T3 / LIQ visual tags
• Dark/Light mode, adjustable table and tag size
• Built-in alerts for Targets and Stop Loss
──────────────────────────────
**INPUTS**
• Long or Short selection
• Entry Price, Stop Loss %
• Target 1 / Target 2 / Target 3 + Take Profit %
• Position Cost ($), Leverage
• Visual preferences: show/hide table, table corner, font size, tag offset, text size
──────────────────────────────
**TABLE OUTPUTS**
Position Info: Type, Entry, Position Cost, Leverage, Value
Risk Section: Stop Loss %, Stop Loss Price, Total Risk ($), Liquidation % & Price
Targets 1–3: Profit ($), R:R, Take Profit ($), Runner % or PnL
──────────────────────────────
**ALERTS**
• Target 1 Hit – when price crosses T1
• Target 2 Hit – when price crosses T2
• Target 3 Hit – when price crosses T3
• Stop Loss Hit – triggers based on direction
(Use TradingView Alerts → Condition → Indicator → select desired alert)
──────────────────────────────
**HOW TO USE**
1. Choose Long or Short
2. Enter Entry Price, Stop Loss %, Position Cost, and Leverage
3. Add Targets 1–3 with optional Take Profit %
4. Adjust visuals as desired
5. Monitor table + alerts for live trade planning
──────────────────────────────
**NOTES**
• Liquidation values are estimates only
• Fees, slippage, and funding not included
• Designed for educational and planning purposes
──────────────────────────────
⚠️ **DISCLAIMER**
For educational use only — not financial advice.
Trading leveraged products involves high risk of loss.
Always confirm calculations with your exchange and trade responsibly.
True Single Line Fusion [by TitikSona]🧠 Full Description
True Single Line Fusion by TitikSona is an open-source oscillator that unifies Fast Stochastic, Slow Stochastic, and RSI into a single smooth momentum line.
It simplifies multi-oscillator analysis into one clear visual — helping traders recognize potential momentum shifts, exhaustion, and reversal zones.
⚙️ Core Logic
The indicator calculates:
Fast Stochastic (12,3,3) → short-term swing sensitivity
Slow Stochastic (100,8,8) → broad trend context
RSI (26) → overall strength and directional bias
All three are normalized (0–100) and averaged to form the Fusion Line, creating a single unified momentum curve.
A Signal Line (SMA-9) and Histogram are added to highlight short-term acceleration or deceleration.
Formula: Fusion = (FastK + SlowK + RSI) / 3
🔍 Interpretation
Fusion Line rising → momentum strengthening upward
Fusion Line falling → momentum weakening
Histogram color (green/red) shows the direction and intensity of the move
Background highlights identify potential extremes:
🟩 Green = potential oversold region
🟥 Red = potential overbought region
💡 How to Use
Works on any symbol and timeframe.
Use the Fusion Line’s direction and slope as momentum context, not as direct buy/sell signals.
Combine with price structure, support/resistance, or volume analysis to confirm potential reversals.
Example:
Fusion Line turning upward from green zone → possible bullish momentum shift
Fusion Line turning downward from red zone → possible bearish exhaustion
📘 Notes
Ideal for identifying turning points in ranging or consolidating markets.
Does not generate automated signals or predictions.
Open-source for learning, modification, and educational use.
Designed for clarity, low lag, and clean visualization.
🧩 Developed and shared by TitikSona — made to unify oscillators into one adaptive momentum tool.
MORE - MTF Open Retest Extensions [Pro]Overview
MORE- MTF Open Retest Extensions highlights what price typically does after a higher-timeframe structure break (taking out the previous candle’s high or low) and before a potential retest of the current open.
It plots percentile extension levels (above/below the broken side) that quantify how far price has historically moved prior to an open retest if a retest occurs, giving traders objective context for stretch vs. common movement around structural breaks.
Key features
• Break-aware logic: MORE activates only after the current timeframe has broken the prior candle’s high/low. No break → no extensions.
• Open-retest probabilities: Displays the empirical likelihood of retesting the current open following a break, with sensitivity to when in the interval the break occurred (early/late breaks can behave differently).
• Pre-retest extension percentiles: Five percentile bands (e.g., 25/50/75/85/95) show how far price typically extends before any open retest on the broken side.
• Multi-timeframe dashboard: Monitor multiple reference timeframes (e.g., 1h → 12h) while viewing any chart timeframe. See which breaks are active and the highest percentile reached this interval.
• Filtering & display controls: Toggle historical zones, choose zones vs. lines (or both).
• Filtering with a threshold: User can enter a threshold for the historical probability so that the open, zones, levels and dashboard only show for timeframes above this user defined input. e.g. input of 70%, zone and levels will only be drawn when the historical data was greater than or equal to this level.
• Show selected timeframe or all untested opens the dashboard is showing as "Active"
• 2 Alert types: Set for a specific timeframe to alert an activate open for retest or set a percentile level to be crossed and alert on cross.
No signals, just context: MORE is a descriptive tool for structure and stretch—use it alongside your own strategy and risk framework.
Methodology (transparency)
• MORE uses embedded statistical datasets constructed from extensive historical price behavior across multiple timeframes.
• Each dataset represents conditional empirical outcomes —specifically, how far price extended beyond a prior candle’s high/low before retesting its open on the same timeframe.
• Percentiles and probabilities are calculated from these internal data arrays, ensuring the indicator runs deterministically on TradingView with no external data connections .
• The proprietary component lies in:
The way volatility and structure are normalized across timeframes;
How conditional breaks and open-retest windows are segmented; and
How percentile extension zones are blended into continuous statistical envelopes.
• These methods and datasets are unique to LevelLogic Indicators and are not replicated from any public or open-source scripts.
• Outputs summarize historical tendencies for educational context only — they are not predictive signals .
How to use
• Pick the reference timeframe (e.g., 1H, 2H, 4H, … 12H).
• Wait for a break of the prior candle’s high/low on that timeframe—MORE then plots the pre-retest extension percentiles on the broken side.
• Use the open-retest probability as context only; combine with your own entry/management rules.
• Optionally toggle historical view to study prior intervals and how far price usually stretched before any open retest.
• Consider alerts on percentile crosses if you want notifications when price enters statistically stretched areas.
Notes
Educational/analytical tool — no signals, no performance or outcome promises.
Historical tendencies change with regime; treat outputs as context, not advice.
Non-standard bars (e.g., Heikin Ashi/Renko) are for display only.
Credits
Developed by LevelLogic Indicators to provide clear, empirical context around breaks and open-retest behavior across multiple timeframes.
Invite-only script
Only users approved by the author can access this script. Request permission per the author’s instructions.
VWAP + Multi-Condition RSI Signals + FibonacciPlatform / System
Platform: TradingView
Language: Pine Script® v6
Purpose: This script is an overlay indicator for technical analysis on charts. It combines multiple tools: VWAP, RSI signals, and Fibonacci levels.
1️⃣ VWAP (Volume Weighted Average Price)
What it does:
Plots the VWAP line on the chart, which is a weighted average price based on volume.
Can be anchored to different periods: Session, Week, Month, Quarter, Year, Decade, Century, or corporate events like Earnings, Dividends, Splits.
Optionally plots bands above and below VWAP based on standard deviation or a percentage.
Supports up to 3 bands with customizable multipliers.
Will not display if the timeframe is daily or higher and the hideonDWM option is enabled.
Visual on chart: A main VWAP line with optional shaded bands.
2️⃣ RSI (Relative Strength Index) Signals
What it does:
Calculates RSI with a configurable period.
Identifies overbought and oversold zones using user-defined levels.
Generates buy/sell signals based on:
RSI crossing above oversold → Buy
RSI crossing below overbought → Sell
Detects strong signals using divergences:
Bullish divergence: Price makes lower low, RSI makes higher low → Strong Buy
Bearish divergence: Price makes higher high, RSI makes lower high → Strong Sell
Optional momentum signals when RSI crosses 50 after recent overbought/oversold conditions.
Visual on chart:
Triangles for buy/sell
Different color triangles/circles for strong and momentum signals
Background shading in RSI overbought/oversold zones
Alerts: The script can trigger alerts when any of these signals occur.
3️⃣ Fibonacci Levels
What it does:
Calculates Fibonacci retracement and extension levels based on the highest high and lowest low over a configurable lookback period.
Plots standard Fibonacci levels: 0.146, 0.236, 0.382, 0.5, 0.618, 0.786, 1.0
Plots extension levels: 1.272, 1.618, 2.0, 2.618
Helps identify potential support/resistance zones.
Visual on chart: Horizontal lines at each Fibonacci level, shaded with different transparencies.
Summary
This script is essentially a multi-tool trading indicator that combines:
VWAP with dynamic bands for trend analysis and price positioning
RSI signals with divergences for entry/exit points
Fibonacci retracement and extension levels for support/resistance
It is interactive and visual, providing both chart overlays and alert functionality for active trading strategies.
This code is provided for training and educational purposes only. It is not financial advice and should not be used for live trading without proper testing and professional guidance.
CUBE's V17CUBE’s V15.1 — Sparkles ⚡ + Cubes 🟨 + Smart/LC 🟫 + Golden ✨ (multi-signal scalper & trend helper)
CUBE’s V15.1 is a multi-module toolkit for intraday momentum and quick-scalp decision making. It blends a trend engine, VWAP/EMA50 band logic, CRT + Volume pair detection, weighted divergence, OBV-MACD regime flips, and “Sparkles” presets—then fuses them into readable Cube labels and higher-conviction Golden combos.
What it prints (signal taxonomy)
🟨 Cube ++ Incoming — pre-signal when price enters VWAP/EMA50 “yellow” bands with trend alignment.
🟨 Cube’s Buy ++ / Sell ++ — the “plus-plus” confirmations after CRT context; gated to avoid spam.
🟫 Last Chance → 🟫 Last Chance ++ — RSI + divergence-weighted follow-through (waits for a tiny UT flip).
🟪 Smart Cube — post-Cube, waits for KC(1.2) location + OBV presence + divergence stack (more selective).
✨ Golden (Sparkles + Cube) — objective confluence labels that require Sparkles (preset wins) plus a Cube event inside a short window. Comes in Golden-2 (2+ sparkles in 3 bars) and Golden-1 (tight 0–1 bar proximity).
Each label automatically shows “(Quick Scalp)” when price is inside the careful bands, so you know when to downshift risk.
The engines (under the hood)
Trend: Pivot-Point SuperTrend (PPST 2/10/3) drives bullish/bearish context (invertible).
Bands: 5-minute VWAP + EMA50 zones with symbol-aware tolerances (majors/ETFs/crypto/megacaps tuned).
CRT + Volume Spike Pair: detects recent hammer/shooter + volume conditions and uses them to gate higher tiers.
Weighted Divergence: RSI / Stoch (weighted) / CCI / MOM / OBV (weighted) / CMF / MFI (and more) with CRT-recency gates to keep it relevant.
UT micro-flips: tiny ATR trail crosses used to “arm” Last Chance ++ entries.
OBV-MACD regime: structural flips for the Super7 and Smart Cube filters.
Super7 Sparkles: five presets (4/8/15/24/40 bars) that score 9 modules; you can show compact ✨ icons or 9/9 text.
Quick start (60 seconds)
Add to a 1–5m chart of your instrument.
Leave defaults on; optionally toggle “Sparkle Settings” (the presets are already on).
Watch for:
✨ Golden Buy/Sell → higher-quality scalp setups.
🟨 Cube’s Buy/Sell ++ → momentum continuation outside the yellow bands.
🟪 Smart Cube → selective continuation after a Cube with KC/OBV/div confluence.
Use the built-in alerts (see list below) to automate.
Inputs & customization highlights
Invert Trend Logic — flips bull/bear interpretation (useful in range regimes).
Reference TF label anchoring — place labels using a reference timeframe; optional “(tf)” tag.
Careful (Quick-Scalp) palettes — swap label colors when inside bands; hide/show quick-scalp labels per mode.
Duplicate filters — suppress Cube repeats within a window.
Session tools — optional 6:00 PM 5m “reset” box (purple) and 9:30 AM 1m NY Open box (yellow).
Backgrounds — optional ST(10,1) 0.5–0.7 ATR ribbons for context.
Presets — five Sparkle presets with per-side alternation and wipe logic.
Alerts (names as they appear in TradingView)
⬜ Cube’s Buy / Sell (or 🟨 Incoming if trend is inverted)
🟨 CUBE’S BUY ++ / CUBE’S SELL ++ (or “Cube’s … ++” if inverted)
🟫 Buy Last Chance / 🟫 Incoming (Sell Last Chance)
🟫 Cube’s Last Chance Buy ++ / Cube’s Last Chance Sell
🟪 Smart Cube’s Buy / Smart Cube’s Sell
🔔 ALL Cube Alerts (one catch-all)
✨ G✨lden Buy/Sell (Sparkles+Cube) and G✨lden-1/2 variants
Tip: Set close-bar alerts for most signals; if you want early heads-up, allow “once per bar” but expect more noise.
Reading the labels
“(Quick Scalp)” suffix = price inside the VWAP/EMA50 careful bands; tighten targets/size.
Some labels include indicator names + a weighted count (e.g., “Hist RSI MOM 3”) to hint at divergence depth.
Star ⭐ near a label means a CRT+VOL pair was detected within the recent window.
Golden text shows the most recent cube subtype (“Cube ++”, “Smart Cube”, etc.) that satisfied the window rule.
Recommended markets & timeframes
Built-in tuning for: NQ/ES/RTY/YM, GC/CL, XAU/XAG, FX majors, BTC/ETH/SOL, SPY/QQQ/IWM/DIA, and mega-caps (AAPL, MSFT, NVDA, etc.).
Best experience on 1m–5m for intraday. Works on higher TFs but is designed around the 5-minute VWAP/EMA50 backbone.
Best practices
Confluence over single prints: Use ✨ Golden or 🟪 Smart Cube + trend + structure.
Location matters: Prefer signals near session boxes, prior day H/L, and liquidity pools.
Risk first: Size down in (Quick Scalp) zones and during lunch hours/illiquid sessions.
Avoid double-counting: The script already suppresses blatant duplicates—don’t force extra alerts.
Repainting & transparency
Core signals evaluate on confirmed bars; major request.security calls use lookahead_off.
The 1m open/6pm boxes use alignment tricks for placement; they don’t feed signal logic.
As with any multi-TF logic, real-time bars can update intra-bar—use “on close” alerts for strict confirmation.
Disclaimer
This script is for educational purposes. It’s not financial advice and does not guarantee results. Markets carry risk—always test on replay/paper first, know your instrument’s tick/fee structure, and use hard stops.
Session VWAP & ATR H/L ZonesThis script is a comprehensive tool for day traders, designed to visualize key price levels and zones based on volume and volatility within a specific trading session.
Traders would use your script to identify potential areas of support and resistance, gauge the session's trend, and spot opportunities for mean reversion or breakout trades.
Core Concepts Explained
Your script plots three main types of information on the chart, each serving a different purpose for a trader.
1. Session VWAP (Volume-Weighted Average Price) 📈
What it is: The yellow line is the VWAP, which is the average price of an asset for the current trading session, weighted by the volume traded at each price level. It essentially shows the "fair" price for the day according to the market's activity.
How it's used:
Trend Gauge: If the price is consistently trading above the VWAP, it's generally considered a bullish intraday trend. If it's below, the trend is bearish.
Dynamic Support/Resistance: During a trend, traders often look for the price to pull back to the VWAP to find an entry point (e.g., buying a dip to the VWAP in an uptrend).
VWAP Bands: The optional gray, red, and green bands are standard deviations from the VWAP. They measure how far the price has strayed from its "fair value."
2. ATR High/Low Zones (Support & Resistance) 🎯
What they are: These are the shaded green and red areas at the top and bottom of the session's price range.
The red zone (resistance) is calculated by taking the session's current high and subtracting a value based on the Average True Range (ATR), which is a measure of recent volatility.
The green zone (support) is calculated by taking the session's current low and adding the ATR-based value.
How they're used: These are not just lines; they are zones of interest.
Profit-Taking Areas: A trader who is long might consider taking profits when the price enters the red resistance zone.
Reversal Signals: When the price enters one of these zones and shows signs of stalling (e.g., with specific candlestick patterns), it could signal a potential reversal.
3. Previous Session High & Low 📊
What they are: The script plots the high and low from the previous trading session as straight horizontal lines (teal and fuchsia by default).
How they're used: These are extremely significant static levels that many traders watch.
Price Magnets: Price is often drawn to these levels.
Key Inflection Points: A decisive break above the previous day's high can signal strong bullish momentum. Conversely, a failure to break it can indicate weakness. These levels frequently act as strong support or resistance.
Z-Score Momentum | MisinkoMasterThe Z-Score Momentum is a new trend analysis indicator designed to catch reversals, and shifts in trends by comparing the "positive" and "negative" momentum by using the Z-Score.
This approach helps traders and investors get unique insight into the market of not just Crypto, but any market.
A deeper dive into the indicator
First, I want to cover the "Why?", as I believe it will ease of the part of the calculation to make it easier to understand, as by then you will understand how it fits the puzzle.
I had an attempt to create a momentum oscillator that would catch reversals and provide high tier accuracy while maintaining the main part => the speed.
I thought back to many concepts, divergences between averages?
- Did not work
Maybe a MACD rework?
- Did not work with what I tried :(
So I thought about statistics, Standard Deviation, Z-Score, Sharpe/Sortino/Omega ratio...
Wait, was that the Z-Score? I only tried the For Loop version of it :O
So on my way back from school I formulated a concept (originaly not like this but to that later) that would attempt to use the Z-Score as an accurate momentum oscillator.
Many ideas were falling out of the blue, but not many worked.
After almost giving up on this, and going to go back to developing my strategies, I tried one last thing:
What if we use divergences in the average, formulated like a Z-score?
Surprise-surprise, it worked!
Now to explain what I have been so passionately yapping about, and to connect the pieces of the puzzle once and for all:
The indicator compares the "strength" of the bullish/bearish factors (could be said differently, but this is my "speach bubble", and I think this describes it the best)
What could we use for the "bullish/bearish" factors?
How about high & low?
I mean, these are by definitions the highest and lowest points in price, which I decided to interpret as: The highest the bull & bear "factors" achieved that bar.
The problem here is comparison, I mean high will ALWAYS > low, unless the asset decided to unplug itself and stop moving, but otherwise that would be unfair.
Now if I use my Z-score, it will get higher while low is going up, which is the opposite of what I want, the bearish "factor" is weaker while we go up!
So I sat on my ret*rded a*s for 25 minutes, completly ignoring the fact the number "-1" exists.
Surprise surprise, multiplying the Z-Score of the low by -1 did what I wanted!
Now it reversed itself (magically). Now while the low keeps going down, the bear factor increases, and while it goes up the bear factor lowers.
This was btw still too noisy, so instead of the classic formula:
a = current value
b = average value
c = standard deviation of a
Z = (a-b)/c
I used:
a = average value over n/2 period
b = average value over n period
c = standard deviation of a
Z = (a-b)/c
And then compared the Z-Score of High to the Z-Score of Low by basic subtraction, which gives us final result and shows us the strength of trend, the direction of the trend, and possibly more, which I may have not found.
As always, this script is open source, so make sure to play around with it, you may uncover the treasure that I did not :)
Enjoy Gs!
Volatilidad Multi-TF📊 Multi-Timeframe Volatility (ATR%)
Description
Indicator that displays the current asset's volatility across multiple timeframes simultaneously. It uses the ATR (Average True Range) normalized as a percentage of price, allowing for objective volatility comparison across different timeframes.
✨ Key Features
- Multi-Timeframe Analysis: Visualize volatility across 5 different timeframes (1H, 4H, D, W, M)
- Normalized Volatility: ATR expressed as a percentage of price for accurate comparison
- Compact Table: Clean and easy-to-read interface in the corner of your chart
- Auto-Update: Automatically adapts to the asset you're viewing
- No Additional Plots: Only displays essential information in table format
🎯 How to Use
1. Add the indicator to your chart
2. The table will automatically display the current asset's volatility
3. Percentage values allow you to quickly identify:
- Which timeframe has higher/lower volatility
- Divergences between timeframes
- High or low volatility zones to adjust your strategies
⚙️ Configurable Parameters
- ATR Period: Default 14, adjust according to your strategy
📈 Practical Applications
- Risk Management: Adjust position sizing based on current volatility
- Asset Selection: Identify assets with suitable volatility for your profile
- Entry Timing: Detect volatility expansions/contractions
- Timeframe Analysis: Compare volatility across different time periods
💡 Technical Notes
- Normalized ATR allows volatility comparison between assets with different prices
- Useful for both intraday trading (1H, 4H) and swing/positional trading (D, W, M)
- Compatible with any market: cryptocurrencies, forex, stocks, indices
⚠️ Disclaimer
This indicator is a technical analysis tool. It does not constitute financial advice. Conduct your own analysis and risk management before trading.
Squeeze Momentum IndicatorThis indicator identifies periods of low market volatility—commonly referred to as a "squeeze"—by comparing Bollinger Bands and Keltner Channels. When volatility compresses, price often prepares for a directional breakout. The histogram visualizes momentum strength and direction once the squeeze ends.
**How it works:**
- **Squeeze detection**: A squeeze is active when Bollinger Bands are fully contained within Keltner Channels. This appears as black crosses on the zero line.
- **Volatility expansion**: When Bollinger Bands move outside Keltner Channels, volatility is increasing. This state is marked with blue crosses.
- **Momentum histogram**: The core signal is a linear regression of price relative to a dynamic baseline (average of the highest high, lowest low, and SMA over the lookback period).
- **Aqua**: Positive momentum that is accelerating.
- **Bright blue**: Positive momentum that is decelerating.
- **Yellow**: Negative momentum that is accelerating downward.
- **Orange**: Negative momentum that is decelerating (potential reversal zone).
**Usage notes:**
Traders often monitor the transition from squeeze (black) to expansion (blue) combined with a strong histogram move away from zero as a potential entry signal. Color changes in the histogram help assess momentum shifts before price makes large moves.
This script is designed for educational and analytical purposes. It does not constitute investment advice. Always test strategies in a simulated environment before applying them to live trading.
Binary Options Fast Scalping [TradingFinder] M1 & M5 Signals🔵 Introduction
In the structure of financial markets, spiky moments and sudden price movements play a key role in Liquidity Grabs and Market Structure Resets. These movements usually occur after the accumulation of orders in Buy Side or Sell Side Liquidity zones and are accompanied by rapid breaks in the form of Break of Structure (BoS) or Change of Character (CHoCH).
At this stage, the market temporarily moves in the direction of liquidity to trigger counter orders and then enters a Retracement or Pullback phase, a point where professional traders using the Smart Money Concept (SMC) look for candle confirmation to enter with precision.
This strategy is built upon the same logic : an initial spiky move as a signal of institutional or liquidity driven algorithms, followed by a controlled pullback toward areas such as the Order Block, Fair Value Gap (FVG), or Imbalance Zone, and finally an entry based on a strong confirmation candle (Engulf, Rejection, Breaker) that defines the true direction of order flow.
This combination of price behavior, especially on lower timeframes such as M1 or M5, provides an ideal setup for fast Scalping, Micro Structure Trading, and even short term directional prediction in Binary Options Trading.
Since the main focus of this method is on identifying liquidity phases, structural confirmations, and momentum confirmation candles, the trader can design entries with high probability and logical stop loss placement using the concepts of Fractal Market Structure and Multi Timeframe Confirmation.
In the scalping version, the main objective is to capture the move toward the next liquidity pool or opposite demand and supply zone, while in the binary version, only the prediction of the next candle’s direction matters. This strategy inherently operates based on Smart Money Behavior, Liquidity Engineering, and Order Flow Dynamics, allowing the extraction of fast and profitable moves from the internal logic of market structure.
🔵 How to Use
The operational logic of this strategy is based on Liquidity Sweep, Pullback, and Confirmation Candle. The trader should first identify the initial Impulse Move, which is often accompanied by liquidity absorption around Buy Side or Sell Side Liquidity areas. After that, the market enters the Retracement phase and returns to structural zones such as the Order Block or the Fair Value Gap (FVG).
At this point, a position is taken only when a confirmation candle (Engulf, Breaker, or Rejection Candle) closes in the direction of continuation and aligns with the new structure (BOS or CHoCH). Applying this model on lower timeframes offers the highest precision for fast Scalping or for predicting the next candle’s direction in Binary Option trading.
🟣 Bullish Setup
In the bullish setup, the market first forms a spiky upward move with a sudden increase in momentum, indicating the activation of liquidity flow in the Buy Side Liquidity zone. This movement is usually accompanied by a Break of Structure (BOS) to the upside and marks the beginning of the Impulse Move phase. After this move, the price enters the Pullback phase and returns to structural areas such as the Bullish Order Block, Fair Value Gap (FVG), or Mitigation zone.
At this stage, the trader waits for a bullish confirmation candle (Bullish Engulf or Breaker Candle) to validate the end of the retracement. Entry is made at the close of the confirmation candle or on a minor pullback, with the stop loss placed below the Swing Low or below the pullback zone. The target is set at the next Buy Side Liquidity or Equal Highs. In the binary version, only the direction of the next candle matters and the entry takes place immediately after the confirmation candle.
🟣 Bearish Setup
In the bearish setup, the market first forms a spiky downward move, signaling increased selling pressure and liquidity absorption at the Sell Side Liquidity zone. This movement is accompanied by a Break of Structure (BOS) to the downside and represents the beginning of a bearish momentum phase. After the spike, the price enters the Retracement phase and returns to the Bearish Order Block or bearish Fair Value Gap zone. Within these areas, the formation of a bearish confirmation candle (Bearish Engulf, Breaker, or Rejection Candle) validates the continuation of the downtrend.
The entry is taken at the close of the confirmation candle, with the stop loss placed above the Swing High or above the pullback zone, and the target set toward the next Sell Side Liquidity or Equal Lows. In binary applications, only the direction of the next candle is considered and the confirmation candle serves as the entry trigger.
🔵 Conclusion
This strategy, by combining the principles of the Smart Money Concept, Liquidity Dynamics, and Candle Confirmation Logic, offers a precise and multi functional approach to market entry. Its core structure, identifying the initial spiky movement, waiting for a structural pullback, and entering based on a confirmation candle allows quick interpretation of institutional liquidity behavior and provides trading opportunities with high accuracy and controlled risk.
On lower timeframes, this logic becomes a powerful tool for Scalping and Micro Structure Trading, while in binary markets it delivers high success rates due to its focus on predicting the next candle’s direction. Built upon the foundations of Order Flow, Market Structure, and Fractal Liquidity Behavior, this strategy demonstrates that even in the fastest and noisiest market conditions, the order of Smart Money remains observable and exploitable.
TFPV — FULL Radial Kernel MA (Short/Long, Time Folding, Colored)TFPV is a pair of adaptive moving averages built with a radial kernel (Gaussian/Laplacian/Cauchy) on a joint metric of time, price, and volume. It can “fold” time along the market’s dominant cycle so that bars separated by entire cycles still contribute as if they were near each other—helpful for cyclical or range-bound markets. The short/long lines auto-color by regime and include cross alerts.
What it does
Radial-kernel averaging: Weights past bars by their distance from the current bar in a 3-axis space:
Time (αₜ): linear distance or cycle-aware phase distance
Price (αₚ): normalized by robust price scale
Volume (αᵥ): normalized by (log) volume scale
Time folding: Choose Linear (standard) or Circular using:
Homodyne (Hilbert) dominant period, or
ACF (autocorrelation) dominant period
This compresses distances for bars that are one or more full cycles apart, improving smoothing without lagging trends.
Adaptive scales: Price/volume bandwidths use Robust MAD, Stdev, or ATR. Optional Super Smoother center reduces noise before measuring distances.
Visual regime coloring: Short above Long → teal (bullish). Short below Long → orange (bearish). Optional fill highlights the spread.
How to read it
Trend filter: Trade in the direction of the color (teal bullish, orange bearish).
Crossovers: Short crossing above Long often marks early trend continuation after pullbacks; crossing below can warn of weakening momentum.
Spread width: A widening gap suggests strengthening trend; a shrinking gap hints at consolidation or a possible regime change.
Key settings
Lengths
Short/Long window: Lookback for each radial MA. Short reacts faster; Long stabilizes the regime.
Kernel & Metric
Kernel: Gaussian, Laplacian, or Cauchy (default). Cauchy is heavier-tailed (keeps more outliers), Gaussian is tighter.
Axis weights (αₜ, αₚ, αᵥ): Importance of time/price/volume distances. Increase a weight to make that axis matter more.
Ignore weights below: Hard cutoff for tiny kernel weights to speed up/clean contributions.
Time Folding
Topology: Linear (standard MA behavior) or Circular (Homodyne/ACF) (cycle-aware).
Cycle floor/ceil: Bounds for the dominant period search.
σₜ mode: Auto sets time bandwidth from the detected period (or length in Linear mode) × multiplier; Manual fixes σₜ in bars.
Price/Volume Scaling
Price scale: Robust MAD (outlier-resistant), Stdev, or ATR (trend-aware).
σₚ/σᵥ multipliers: Bandwidths for price/volume axes. Larger values = looser matching (smoother, more lag).
Use log(volume): Stabilizes volume’s scale across regimes; recommended.
Kernel Center
Price center: Raw (close) or Super Smoother to reduce noise before measuring price distance.
Plotting
Plot source: Show/hide the input source.
Fill between lines: Visual emphasis of the short/long spread.
Tips
Start with defaults: Cauchy, Circular (Homodyne), Robust MAD, log-volume on.
For choppy/cyclical symbols, Circular time folding often reduces false flips.
If signals feel too twitchy, either increase Short/Long lengths or raise σₚ/σᵥ multipliers (looser kernel).
For strong trends with regime shifts, try ATR price scaling.
Friday & Monday HighlighterFriday & Monday Institutional Range Marker — Know Where Big Firms Set the Trap!
🧠 Description
This indicator automatically highlights Friday and Monday sessions on your chart — days when institutional players and algorithmic firms (like Citadel, Jane Street, or Tower Research) quietly shape the upcoming week’s price structure.
🔍 Why Friday & Monday matter
Friday : Large institutions often book profits or hedge into the weekend. Their final-hour moves reveal the next week’s bias.
Monday : Big players rebuild positions, absorbing liquidity left behind by retail traders.
Together, these two days define the range traps and breakout zones that often control price action until midweek.
> In short, the Friday–Monday high and low often act as invisible walls — guiding scalpers, option sellers, and swing traders alike.
🧩 What this tool does
✅ Highlights Friday (red) and Monday (green) sessions
✅ Adds optional day labels above bars
✅ Works across all timeframes (best on 15min to 1hr charts)
✅ Helps you visually identify where institutions likely built their positions
Use it to quickly spot:
* Range boundaries that trap traders
* Gap zones likely to get filled
* High–low sweeps before reversals
⚙️ Recommended Use
1. Mark Friday’s high–low → Watch for liquidity sweeps on Monday.
2. When Monday holds above Friday’s high , breakout continuation is likely.
3. When Monday fails below Friday’s low , expect a reversal or trap.
4. Combine this with OI shifts, IV crush, and FII–DII flow data for confirmation.
⚠️ Disclaimer
This indicator is for **educational and analytical purposes only**.
It does **not constitute financial advice** or a trading signal.
Markets are dynamic — always perform your own research before trading or investing.
IB range + Breakout fibsThe IB High / Low + Auto-Fib indicator automatically plots the Initial Balance range and a Fibonacci projection for each trading day.
Define your IB start and end times (e.g., 09:30–10:30).
The indicator marks the IB High and IB Low from that session and extends them to the session close.
It keeps the last N days visible for context.
When price breaks outside the IB range, it automatically plots a Fibonacci retracement/extension from the opposite IB side to the breakout, using levels 0, 0.236, 0.382, 0.5, 0.618, 0.88, 1.
The Fib updates dynamically as the breakout extends, and labels are neatly aligned on the right side of the chart for clarity.
Ideal for traders who monitor Initial Balance breaks, range expansions, and Fibonacci reaction levels throughout the trading session.
Kalman Exponentialy Weighted Moving Average | MisinkoMasterThe Kalman Exponentialy Weighted Moving Average is a technical analysis tool providing users with more responsive and smoother signals, providing crystal-clear signals and giving investors valuable insights on market trends, however it could be used in many cases.
A deeper dive into the indicator:
When going through my creation of strategies, I had stumbled on an indicator called "EWMA", which worked decently, but it was far too simple in my opinion so I decided to combine the EMA & WMA, but with a little more complexity, and it has worked .
I began by learning how both MAs work, I already knew how WMA works, but EMA I did not.
After learning both I found out they were quite simple in principle and that there was a way to combine them in such way that you would get really good signals, however it was way too noisy.
While it could avoid major dumps that were not avoided by most indicators, it would lose that edge because of being too noisy.
After testing out many conditions, combinations & more, the best working one was this one:
WMA > KEWMA = long
WMA < KEWMA = short
I will explain this later, but this gave fast signals, and while it still was noisy it was better then before.
To smooth it out, I started testing price filters => Gaussian Filter and many more were tested out, but they either slowed it down to the point it was no longer of much use, or did not smooth it at all.
After testing the Kalman filter on this thing, I was shocked.
It was just right and made the indicator a lot better, smoothed it and kept most of the responsivness it had.
Now to the big question: "How is it calculated?"
Now first it needs to calculate the Kalman source, which smooths the source which will be used.
After that, we calculate the Weighted Moving Average for " n " period on the Kalman source.
Now that we have our WMA values, we need to calculate " a ".
a is calculated in the following formula:
a = 2/(1+ n )
where n is the user defined length
Now for the last part:
KEWMA = WMAyesterday * (1-a) + WMAtoday * a
This creates a very accurate and reactive indicator, that can prove useful in many uses, beyond those I will and did talk about.
For the trend logic as mentioned before:
Long = WMA > KEWMA
Short = WMA < KEWMA
This worked best, but you might find better ways of using it.
I think that is all I have to say about it, I left it open source so you can all code it in your strategies and play around with it.
Enjoy Gs!
3D Candles (Zeiierman)█ Overview
3D Candles (Zeiierman) is a unique 3D take on classic candlesticks, offering a fresh, high-clarity way to visualize price action directly on your chart. Visualizing price in alternative ways can help traders interpret the same data differently and potentially gain a new perspective.
█ How It Works
⚪ 3D Body Construction
For each bar, the script computes the candle body (open/close bounds), then projects a top face offset by a depth amount. The depth is proportional to that candle’s high–low range, so it looks consistent across symbols with different prices/precisions.
rng = math.max(1e-10, high - low ) // candle range
depthMag = rng * depthPct * factorMag // % of range, shaped by tilt amount
depth = depthMag * factorSign // direction from dev (up/down)
depthPct → how “thick” the 3D effect is, as a % of each candle’s own range.
factorMag → scales the effect based on your tilt input (dev), with a smooth curve so small tilts still show.
factorSign → applies the direction of the tilt (up or down).
⚪ Tilt & Perspective
Tilt is controlled by dev and translated into a gentle perspective factor:
slope = (4.0 * math.abs(dev)) / width
factorMag = math.pow(math.min(1.0, slope), 0.5) // sqrt softens response
factorSign = dev == 0 ? 0.0 : math.sign(dev) // direction (up/down)
Larger dev → stronger 3D presence (up to a cap).
The square-root curve makes small dev values noticeable without overdoing it.
█ How to Use
Traders can use 3D Candles just like regular candlesticks. The difference is the 3D visualization, which can broaden your view and help you notice price behavior from a fresh perspective.
⚪ Quick setup (dual-view):
Split your TradingView layout into two synchronized charts.
Right pane: keep your standard candlestick or bar chart for live execution.
Left pane: add 3D Candles (Zeiierman) to compare the same symbol/timeframe.
Observe differences: the 3D rendering can make expansion/contraction and body emphasis easier to spot at a glance.
█ Go Full 3D
Take the experience further by pairing 3D Candles (Zeiierman) with Volume Profile 3D (Zeiierman) , a perfect complement that shows where activity is concentrated, while your 3D candles show how the price unfolded.
█ Settings
Candles — How many 3D candles to draw. Higher values draw more shapes and may impact performance on slower machines.
Block Width (bars) — Visual thickness of each 3D candle along the x-axis. Larger values look chunkier but can overlap more.
Up/Down — Controls the tilt and strength of the 3D top face.
3D depth (% of range) — Thickness of the 3D effect as a percentage of each candle’s own high–low range. Larger values exaggerate the depth.
-----------------
Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
Dobrusky Volume PulseWhat it does & who it’s for
Volume Pulse is a lightweight, customizable volume profile overlay that shows traders how volume is distributed across price levels over a chosen lookback window. Unlike standard profiles, it also maps cumulative buy/sell pressure at each level, so you see not just where volume clustered, but which side dominated.
Core ideas
Cumulative volume by price: Builds a horizontal profile of traded volume at each level, based on user-defined depth and resolution.
Directional pressure mapping: At every price level, the script accumulates bullish vs. bearish volume based on candle closes vs. opens, providing a directional read on whether buyers or sellers had the upper hand.
POC: Automatically highlights the Point of Control (POC) — the level with the most activity.
Customizable presentation: Adjustable profile resolution, bar width, offset, colors, and whether to show cumulative, directional, or both.
How the components work together
The profile provides the “where,” while the buy/sell mapping adds the “who.” By combining these, traders can see whether a high-volume node was buyer-driven absorption or seller-driven distribution — a distinction classic profiles don’t reveal. This directional overlay reduces the guesswork of interpreting raw volume clusters.
How to use
Apply the overlay to your chart.
Watch the POC and areas of significant increase or decrease in volume (and pressure) as natural magnets or rejection areas.
When trading intraday, I've found that higher timeframe volume levels act as strong magnets. In the chart, you can see the volume levels I've drawn on the SPY daily chart. These levels are targets I use when trading the 5-minute chart.
Pay attention to color dominance at those zones — green-heavy nodes suggest buyer control; red-heavy nodes suggest seller control.
Combine with time-based volume tools and price-action for a more comprehensive trade plan.
Settings overview
Lookback depth: Number of bars used for profile calculation.
Profile resolution: Number of horizontal bars to split volume across price.
Bar style: Width, offset, and multiplier for scaling.
Toggle layers: Choose cumulative, directional, or both.
POC display: Optional highlight of the most traded level.
Limitations & best practices
This is a contextual overlay, not a trade-signal system.
Works best on liquid instruments (indices, futures, major stocks, liquid crypto) where volume distribution is meaningful.
Directional mapping uses candle body bias (close vs. open), not raw order flow. For full tape analysis, pair with actual order flow data.
Originality justification
Dual profile: combines cumulative volume-by-price and buyer/seller pressure per bin (close vs. open) — not a standard VP clone.
From-scratch binning + POC in a single pass for speed; no reused libraries.
Flexible display (cumulative / directional / both) with independent resolution, width, and offset for intraday or HTF use.
Clear visuals (optional POC, balanced node coloring) and open-source code so traders can audit and extend.
RSI Divergence Screener [Pineify]RSI Divergence Screener
Key Features
Multi-symbol and multi-timeframe support for advanced market screening.
Real-time detection and visualization of bullish and bearish RSI divergences.
Seamless integration with core technical indicators and custom divergences.
Highly customizable parameters for precise adaptation to personal trading strategies.
Comprehensive screener table for swift asset comparison and analysis.
How It Works
The RSI Divergence Screener leverages the power of Relative Strength Index (RSI) to systematically track momentum shifts across cryptocurrencies and their respective timeframes. By monitoring both fast and slow RSI calculations, the screener isolates divergence signals—key reversal points that often precede major price moves.
The indicator calculates two RSI values for each selected asset: one with a short lookback (Fast RSI) and another with a longer period (Slow RSI).
It runs a comparative algorithm to find divergences—whenever Fast RSI deviates significantly from Slow RSI, it flags the signal as bullish or bearish.
All detected divergences are dynamically presented in a table view, allowing traders to scan symbols and timeframes for optimal trading setups.
Trading Ideas and Insights
Spot early momentum reversals and preempt major price swings via divergence signals.
Combine multiple symbols and timeframes for cross-market trending opportunities.
Identify high-probability scalping and swing trading setups informed by RSI divergence logic.
Quickly compare crypto asset strength and trend exhaustion across short and long-term horizons.
How Multiple Indicators Work Together
This screener’s edge lies in its synergistic use of multi-setting RSI calculations and customizable input groups.
The dual-RSI approach (Fast vs. Slow) isolates subtle trend shifts missed by traditional single-period RSI.
Safe and reliable divergences arise only when the mathematical difference between Fast RSI and Slow RSI meets predefined thresholds, minimizing false positives.
Divergences are contextualized using tailored color codes and backgrounds, rendering insights immediately actionable.
You can expand analysis with additional moving average filters or overlays for further confirmation.
Unique Aspects
First-of-its-kind screener dedicated solely to RSI divergence, designed especially for crypto volatility.
Efficient screening of up to eight assets and multiple timeframes in one compact dashboard.
Intuitive iconography, color logic, and table layouts optimized for rapid decision-making.
Advanced input group design for fine-tuning indicator settings per symbol, timeframe, and source.
How to Use
Select up to eight cryptocurrency symbols to screen for divergence signals.
Assign individual timeframes and source prices for each asset to customize analysis.
Set Fast RSI and Slow RSI lengths according to your preferred strategy (e.g., scalping, swing, or trend following).
Review the screener table: colored cells highlight actionable bullish (green) and bearish (red) divergences.
Confirm trade setups with additional indicators or price action for robust risk management.
Customization
Symbols: Choose any crypto pair or ticker for dynamic divergence tracking.
Timeframes: Scan across 1m, 5m, 10m, 30m, and more for full market coverage.
RSI lengths: Configure Fast and Slow RSI periods based on volatility and trading style.
Visuals: Tailor table colors, fonts, and alert backgrounds per your preference.
Conclusion
The RSI Divergence Screener is a versatile, original TradingView indicator that empowers traders to scan, compare, and act on divergence signals with speed and precision. Its multi-symbol design, robust logic, and extensive customization options set a new standard for market screening tools. Integrate it into your crypto trading process to capture actionable opportunities ahead of the crowd and optimize your technical analysis workflow.
Intrinsic Value AnalyzerThe Intrinsic Value Analyzer is an all-in-one valuation tool that automatically calculates the fair value of a stock using industry-standard valuation techniques. It estimates intrinsic value through Discounted Cash Flow (DCF), Enterprise Value to Revenue (EV/REV), Enterprise Value to EBITDA (EV/EBITDA), and Price to Earnings (P/EPS). The model features adjustable parameters and a built-in alert system that notifies investors in real time when valuation multiples reach predefined thresholds. It also includes a comprehensive, color-coded table that compares the company’s historical average growth rates, valuation multiples, and financial ratios with the most recent values, helping investors quickly assess how current values align with historical averages.
The model calculates the historical Compounded Annual Growth Rates (CAGR) and average valuation multiples over the selected Lookback Period. It then projects Revenue, Earnings Before Interest, Taxes, Depreciation, and Amortization (EBITDA), Earnings per Share (EPS), and Free Cash Flow (FCF) for the selected Forecast Period and discounts their future values back to the present using the Weighted Average Cost of Capital (WACC) or the Cost of Equity. By default, the model automatically applies the historical averages displayed in the table as the growth forecasts and target multiples. These assumptions can be modified in the menu by entering custom REV-G, EBITDA-G, EPS-G, and FCF-G growth forecasts, as well as EV/REV, EV/EBITDA, and P/EPS target multiples. When new input values are entered, the model recalculates the fair value in real time, allowing users to see how changes in these assumptions affect the company’s fair value.
DCF = (Sum of (FCF × (1 + FCF-G) ^ t ÷ (1 + WACC) ^ t) for each year t until Forecast Period + ((FCF × (1 + FCF-G) ^ Forecast Period × (1 + LT Growth)) ÷ ((WACC - LT Growth) × (1 + WACC) ^ Forecast Period)) + Cash - Debt - Preferred Equity - Minority Interest) ÷ Shares Outstanding
EV/REV = ((Revenue × (1 + REV-G) ^ Forecast Period × EV/REV Target) ÷ (1 + WACC) ^ Forecast Period + Cash - Debt - Preferred Equity - Minority Interest) ÷ Shares Outstanding
EV/EBITDA = ((EBITDA × (1 + EBITDA-G) ^ Forecast Period × EV/EBITDA Target) ÷ (1 + WACC) ^ Forecast Period + Cash - Debt - Preferred Equity - Minority Interest) ÷ Shares Outstanding
P/EPS = (EPS × (1 + EPS-G) ^ Forecast Period × P/EPS Target) ÷ (1 + Cost of Equity) ^ Forecast Period
The discounted one-year average analyst price target (1Y PT) is also displayed alongside the valuation labels to provide an overview of consensus estimates. For the DCF model, the terminal long-term FCF growth rate (LT Growth) is based on the selected country to reflect expected long-term nominal GDP growth and can be modified in the menu. For metrics involving FCF, users can choose between reported FCF, calculated as Cash From Operations (CFO) - Capital Expenditures (CAPEX), or standardized FCF, calculated as Earnings Before Interest and Taxes (EBIT) × (1 - Average Tax Rate) + Depreciation and Amortization - Change in Net Working Capital - CAPEX. Historical average values displayed in the left column of the table are based on Fiscal Year (FY) data, while the latest values in the right column use the most recent Trailing Twelve Month (TTM) or Fiscal Quarter (FQ) data. The indicator displays color-coded price labels for each fair value estimate, showing the percentage upside or downside from the current price. Green indicates undervaluation, while red indicates overvaluation. The table follows a separate color logic:
REV-G, EBITDA-G, EPS-G, FCF-G = Green indicates positive annual growth when the CAGR is positive. Red indicates negative annual growth when the CAGR is negative.
EV/REV = Green indicates undervaluation when EV/REV ÷ REV-G is below 1. Red indicates overvaluation when EV/REV ÷ REV-G is above 2. Gray indicates fair value.
EV/EBITDA = Green indicates undervaluation when EV/EBITDA ÷ EBITDA-G is below 1. Red indicates overvaluation when EV/EBITDA ÷ EBITDA-G is above 2. Gray indicates fair value.
P/EPS = Green indicates undervaluation when P/EPS ÷ EPS-G is below 1. Red indicates overvaluation when P/EPS ÷ EPS-G is above 2. Gray indicates fair value.
EBITDA% = Green indicates profitable operations when the EBITDA margin is positive. Red indicates unprofitable operations when the EBITDA margin is negative.
FCF% = Green indicates strong cash conversion when FCF/EBITDA > 50%. Red indicates unsustainable FCF when FCF/EBITDA is negative. Gray indicates normal cash conversion.
ROIC = Green indicates value creation when ROIC > WACC. Red indicates value destruction when ROIC is negative. Gray indicates positive but insufficient returns.
ND/EBITDA = Green indicates low leverage when ND/EBITDA is below 1. Red indicates high leverage when ND/EBITDA is above 3. Gray indicates moderate leverage.
YIELD = Green indicates positive shareholder return when Shareholder Yield > 1%. Red indicates negative shareholder return when Shareholder Yield < -1%.
The Return on Invested Capital (ROIC) is calculated as EBIT × (1 - Average Tax Rate) ÷ (Average Debt + Average Equity - Average Cash). Shareholder Yield (YIELD) is calculated as the CAGR of Dividend Yield - Change in Shares Outstanding. The Weighted Average Cost of Capital (WACC) is displayed at the top left of the table and is derived from the current Market Cap (MC), Debt, Cost of Equity, and Cost of Debt. The Cost of Equity is calculated using the Equity Beta, Index Return, and Risk-Free Rate, which are based on the selected country. The Equity Beta (β) is calculated as the 5-year Blume-adjusted beta between the weekly logarithmic returns of the underlying stock and the selected country’s stock market index. For accurate calculations, it is recommended to use the stock ticker listed on the primary exchange corresponding to the company’s main index.
Cost of Debt = (Interest Expense on Debt ÷ Average Debt) × (1 - Average Tax Rate)
Cost of Equity = Risk-Free Rate + Equity Beta (β) × (Index Return - Risk-Free Rate)
WACC = (MC ÷ (MC + Debt)) × Cost of Equity + (Debt ÷ (MC + Debt)) × Cost of Debt
This indicator works best for operationally stable and profitable companies that are primarily valued based on fundamentals rather than speculative growth, such as those in the industrial, consumer, technology, and healthcare sectors. It is less suitable for early-stage, unprofitable, or highly cyclical companies, including energy, real estate, and financial institutions, as these often have irregular cash flows or distorted balance sheets. It is also worth noting that TradingView’s financial data provider, FactSet, standardizes financial data from official company filings to align with a consistent accounting framework. While this improves comparability across companies, industries, and countries, it may also result in differences from officially reported figures.
In summary, the Intrinsic Value Analyzer is a comprehensive valuation tool designed to help long-term investors estimate a company’s fair value while comparing historical averages with the latest values. Fair value estimates are driven by growth forecasts, target multiples, and discount rates, and should always be interpreted within the context of the underlying assumptions. By default, the model applies historical averages and current discount rates, which may not accurately reflect future conditions. Investors are therefore encouraged to adjust inputs in the menu to better understand how changes in these key assumptions influence the company’s fair value.
Seasonality Heatmap [QuantAlgo]🟢 Overview
The Seasonality Heatmap analyzes years of historical data to reveal which months and weekdays have consistently produced gains or losses, displaying results through color-coded tables with statistical metrics like consistency scores (1-10 rating) and positive occurrence rates. By calculating average returns for each calendar month and day-of-week combination, it identifies recognizable seasonal patterns (such as which months or weekdays tend to rally versus decline) and synthesizes this into actionable buy low/sell high timing possibilities for strategic entries and exits. This helps traders and investors spot high-probability seasonal windows where assets have historically shown strength or weakness, enabling them to align positions with recurring bull and bear market patterns.
🟢 How It Works
1. Monthly Heatmap
How % Return is Calculated:
The indicator fetches monthly closing prices (or Open/High/Low based on user selection) and calculates the percentage change from the previous month:
(Current Month Price - Previous Month Price) / Previous Month Price × 100
Each cell in the heatmap represents one month's return in a specific year, creating a multi-year historical view
Colors indicate performance intensity: greener/brighter shades for higher positive returns, redder/brighter shades for larger negative returns
What Averages Mean:
The "Avg %" row displays the arithmetic mean of all historical returns for each calendar month (e.g., averaging all Januaries together, all Februaries together, etc.)
This metric identifies historically recurring patterns by showing which months have tended to rise or fall on average
Positive averages indicate months that have typically trended upward; negative averages indicate historically weaker months
Example: If April shows +18.56% average, it means April has averaged a 18.56% gain across all years analyzed
What Months Up % Mean:
Shows the percentage of historical occurrences where that month had a positive return (closed higher than the previous month)
Calculated as:
(Number of Months with Positive Returns / Total Months) × 100
Values above 50% indicate the month has been positive more often than negative; below 50% indicates more frequent negative months
Example: If October shows "64%", then 64% of all historical Octobers had positive returns
What Consistency Score Means:
A 1-10 rating that measures how predictable and stable a month's returns have been
Calculated using the coefficient of variation (standard deviation / mean) - lower variation = higher consistency
High scores (8-10, green): The month has shown relatively stable behavior with similar outcomes year-to-year
Medium scores (5-7, gray): Moderate consistency with some variability
Low scores (1-4, red): High variability with unpredictable behavior across different years
Example: A consistency score of 8/10 indicates the month has exhibited recognizable patterns with relatively low deviation
What Best Means:
Shows the highest percentage return achieved for that specific month, along with the year it occurred
Reveals the maximum observed upside and identifies outlier years with exceptional performance
Useful for understanding the range of possible outcomes beyond the average
Example: "Best: 2016: +131.90%" means the strongest January in the dataset was in 2016 with an 131.90% gain
What Worst Means:
Shows the most negative percentage return for that specific month, along with the year it occurred
Reveals maximum observed downside and helps understand the range of historical outcomes
Important for risk assessment even in months with positive averages
Example: "Worst: 2022: -26.86%" means the weakest January in the dataset was in 2022 with a 26.86% loss
2. Day-of-Week Heatmap
How % Return is Calculated:
Calculates the percentage change from the previous day's close to the current day's price (based on user's price source selection)
Returns are aggregated by day of the week within each calendar month (e.g., all Mondays in January, all Tuesdays in January, etc.)
Each cell shows the average performance for that specific day-month combination across all historical data
Formula:
(Current Day Price - Previous Day Close) / Previous Day Close × 100
What Averages Mean:
The "Avg %" row at the bottom aggregates all months together to show the overall average return for each weekday
Identifies broad weekly patterns across the entire dataset
Calculated by summing all daily returns for that weekday across all months and dividing by total observations
Example: If Monday shows +0.04%, Mondays have averaged a 0.04% change across all months in the dataset
What Days Up % Mean:
Shows the percentage of historical occurrences where that weekday had a positive return
Calculated as:
(Number of Positive Days / Total Days Observed) × 100
Values above 50% indicate the day has been positive more often than negative; below 50% indicates more frequent negative days
Example: If Fridays show "54%", then 54% of all Fridays in the dataset had positive returns
What Consistency Score Means:
A 1-10 rating measuring how stable that weekday's performance has been across different months
Based on the coefficient of variation of daily returns for that weekday across all 12 months
High scores (8-10, green): The weekday has shown relatively consistent behavior month-to-month
Medium scores (5-7, gray): Moderate consistency with some month-to-month variation
Low scores (1-4, red): High variability across months, with behavior differing significantly by calendar month
Example: A consistency score of 7/10 for Wednesdays means they have performed with moderate consistency throughout the year
What Best Means:
Shows which calendar month had the strongest average performance for that specific weekday
Identifies favorable day-month combinations based on historical data
Format shows the month abbreviation and the average return achieved
Example: "Best: Oct: +0.20%" means Mondays averaged +0.20% during October months in the dataset
What Worst Means:
Shows which calendar month had the weakest average performance for that specific weekday
Identifies historically challenging day-month combinations
Useful for understanding which month-weekday pairings have shown weaker performance
Example: "Worst: Sep: -0.35%" means Tuesdays averaged -0.35% during September months in the dataset
3. Optimal Timing Table/Summary Table
→ Best Month to BUY: Identifies the month with the lowest average return (most negative or least positive historically), representing periods where prices have historically been relatively lower
Based on the observation that buying during historically weaker months may position for subsequent recovery
Shows the month name, its average return, and color-coded performance
Example: If May shows -0.86% as "Best Month to BUY", it means May has historically averaged -0.86% in the analyzed period
→ Best Month to SELL: Identifies the month with the highest average return (most positive historically), representing periods where prices have historically been relatively higher
Based on historical strength patterns in that month
Example: If July shows +1.42% as "Best Month to SELL", it means July has historically averaged +1.42% gains
→ 2nd Best Month to BUY: The second-lowest performing month based on average returns
Provides an alternative timing option based on historical patterns
Offers flexibility for staged entries or when the primary month doesn't align with strategy
Example: Identifies the next-most favorable historical buying period
→ 2nd Best Month to SELL: The second-highest performing month based on average returns
Provides an alternative exit timing based on historical data
Useful for staged profit-taking or multiple exit opportunities
Identifies the secondary historical strength period
Note: The same logic applies to "Best Day to BUY/SELL" and "2nd Best Day to BUY/SELL" rows, which identify weekdays based on average daily performance across all months. Days with lowest averages are marked as buying opportunities (historically weaker days), while days with highest averages are marked for selling (historically stronger days).
🟢 Examples
Example 1: NVIDIA NASDAQ:NVDA - Strong May Pattern with High Consistency
Analyzing NVIDIA from 2015 onwards, the Monthly Heatmap reveals May averaging +15.84% with 82% of months being positive and a consistency score of 8/10 (green). December shows -1.69% average with only 40% of months positive and a low 1/10 consistency score (red). The Optimal Timing table identifies December as "Best Month to BUY" and May as "Best Month to SELL." A trader recognizes this high-probability May strength pattern and considers entering positions in late December when prices have historically been weaker, then taking profits in May when the seasonal tailwind typically peaks. The high consistency score in May (8/10) provides additional confidence that this pattern has been relatively stable year-over-year.
Example 2: Crypto Market Cap CRYPTOCAP:TOTALES - October Rally Pattern
An investor examining total crypto market capitalization notices September averaging -2.42% with 45% of months positive and 5/10 consistency, while October shows a dramatic shift with +16.69% average, 90% of months positive, and an exceptional 9/10 consistency score (blue). The Day-of-Week heatmap reveals Mondays averaging +0.40% with 54% positive days and 9/10 consistency (blue), while Thursdays show only +0.08% with 1/10 consistency (yellow). The investor uses this multi-layered analysis to develop a strategy: enter crypto positions on Thursdays during late September (combining the historically weak month with the less consistent weekday), then hold through October's historically strong period, considering exits on Mondays when intraweek strength has been most consistent.
Example 3: Solana BINANCE:SOLUSDT - Extreme January Seasonality
A cryptocurrency trader analyzing Solana observes an extraordinary January pattern: +59.57% average return with 60% of months positive and 8/10 consistency (teal), while May shows -9.75% average with only 33% of months positive and 6/10 consistency. August also displays strength at +59.50% average with 7/10 consistency. The Optimal Timing table confirms May as "Best Month to BUY" and January as "Best Month to SELL." The Day-of-Week data shows Sundays averaging +0.77% with 8/10 consistency (teal). The trader develops a seasonal rotation strategy: accumulate SOL positions during May weakness, hold through the historically strong January period (which has shown this extreme pattern with reasonable consistency), and specifically target Sunday exits when the weekday data shows the most recognizable strength pattern.
X Feigenbaumplots forward “projection zones” derived from a user-defined Feigenbaum Deterministic Range (FDR). Starting from two anchor prices (p01a, p01b) that define the initial condition, the tool computes successive expansion zones above and below that range using fixed scale factors. Each zone is rendered as a shaded box with optional edge outlines, an auto-midline, and an optional label—giving you an at-a-glance map of where price may propagate next.
This indicator is a visual framework, not a signal generator. It’s meant to be combined with your existing structure/flow reads (order flow, VWAPs, ORs, HTF levels, etc.) to plan scenarios, targets, and invalidation.
Key ideas (context)
Initial condition → expansions: You define a deterministic base range (FDR) from which the script projects outward “echoes.”
Bidirectional mapping: Zones are drawn symmetrically as +1, +2, +3, +4 (above) and −1, −2, −3, −4 (below) to reflect potential propagation in either direction.
Diminishing confidence with distance: Farther zones are for scenario planning/targets; nearer zones are more actionable for risk placement and management.
How the levels are built
Feigenbaum Deterministic Range (FDR):
Inputs p01a and p01b define the initial range (FDR = p01a − p01b).
Category “F Range” draws that base box.
Projection Zones:
The script computes zone pairs by offsetting from the initial range using fixed multipliers of FDR. In code, these are the pre-set coefficients:
±1: 0.6714 and 1.5029
±2: 2.5699 and 3.6692
±3: 6.1398 and 8.3384
±4: 13.2796 and 17.6768
Each zone is two prices (a, b) forming a band; the same logic mirrors below the range for the negative side.
Rendering & midlines:
Each enabled category draws a filled box from the anchor bar to the right edge (current bar + extend_len).
Optional outlines (solid/dashed/dotted) for top/bottom/left/right edges.
Optional midline (always dashed) bisects each zone for quick reference.
Anchoring & timeframe logic
Anchor refresh: interval1 sets an HTF “clock” (e.g., Daily). On each new HTF bar, all categories re-anchor at that bar’s index so new projections start cleanly with the fresh session/period.
Extend control: extend_len nudges the right boundary beyond the latest bar for label/edge clarity.
Inputs & styling
Settings group:
Anchor 1 Timeframe (e.g., D) defines the refresh cadence.
Label toggles: show/hide, size, text color, and background.
Feigenbaum DR group:
Enable the base F range, set p01a/p01b, choose fill/line colors, outline style, and the mid toggle.
Ranger Factors groups (Zones ±1…±4):
Each zone can be enabled/disabled, inherits its computed prices, and has independent fill/line color, outline style, and mid toggle.
Practical usage
Scenario mapping: Use +/−1 zones for near-term impulse tracking and intraday targets; treat +/−3 and +/−4 as stretch objectives or “if trend persists” waypoints.
Confluence first: Prioritize trades when a Feigenbaum zone aligns with a known liquidity pool, session level (e.g., OR, ETH/RTH AVWAP), HTF pivot, or key option-derived levels.
Risk & invalidation: The base FDR and nearest zone edges provide clean invalidation references and partial-take structures.
Notes & limitations
The coefficients are fixed in this version (you can expose them as inputs if you want to calibrate per market).
Projections are descriptive, not predictive; treat farther zones as lower-confidence context.
Because anchors reset on the selected HTF, choose interval1 consistent with your playbook (e.g., Daily for RTH framing, Weekly for swing maps).
Output summary
Boxes: FDR (base), Zones +1/−1, +2/−2, +3/−3, +4/−4
Edges: Optional top/bottom/left/right per zone (styleable)
Midlines: Optional dashed mid per zone
Labels: Optional, style-controlled, positioned just beyond the right edge
ICT Anchored Market Structures with Validation [LuxAlgo]The ICT Anchored Market Structures with Validation indicator is an advanced iteration of the original Pure-Price-Action-Structures tool, designed for price action traders.
It systematically tracks and validates key price action structures, distinguishing between true structural shifts/breaks and short-term sweeps to enhance trend and reversal analysis. The indicator automatically highlights structural points, confirms breakouts, identifies sweeps, and provides clear visual cues for short-term, intermediate-term, and long-term market structures.
A distinctive feature of this indicator is its exclusive reliance on price patterns. It does not depend on any user-defined input, ensuring that its analysis remains robust, objective, and uninfluenced by user bias, making it an effective tool for understanding market dynamics.
🔶 USAGE
Market structure is a cornerstone of price action analysis. This script automatically detects real-time market structures across short-term, intermediate-term, and long-term levels, simplifying trend analysis for traders. It assists in identifying both trend reversals and continuations with greater clarity.
Market structure shifts and breaks help traders identify changes in trend direction. A shift signals a potential reversal, often occurring when a swing high or low is breached, suggesting a transition in trend. A break, on the other hand, confirms the continuation of an established trend, reinforcing the current direction. Recognizing these shifts and breaks allows traders to anticipate price movement with greater accuracy.
It’s important to note that while a CHoCH may signal a potential trend reversal and a BoS suggests a continuation of the prevailing trend, neither guarantees a complete reversal or continuation. In some cases, CHoCH and BoS levels may act as liquidity zones or areas of consolidation rather than indicating a clear shift or continuation in market direction. The indicator’s validation component helps confirm whether the detected CHoCH and BoS are true breakouts or merely liquidity sweeps.
🔶 DETAILS
🔹 Market Structures
Market structures are derived from price action analysis, focusing on identifying key levels and patterns in the market. Swing point detection, a fundamental concept in ICT trading methodologies and teachings, plays a central role in this approach.
Swing points are automatically identified based exclusively on market movements, without requiring any user-defined input.
🔹 Utilizing Swing Points
Swing points are not identified in real-time as they form. Short-term swing points may appear with a delay of up to one bar, while the identification of intermediate and long-term swing points is entirely dependent on subsequent market movements. Importantly, this detection process is not influenced by any user-defined input, relying solely on pure price action. As a result, swing points are generally not intended for real-time trading scenarios.
Instead, traders often analyze historical swing points to understand market trends and identify potential entry and exit opportunities. By examining swing highs and lows, traders can:
Recognize Trends: Swing highs and lows provide insight into trend direction. Higher swing highs and higher swing lows signify an uptrend, while lower swing highs and lower swing lows indicate a downtrend.
Identify Support and Resistance Levels: Swing highs often act as resistance levels, referred to as Buyside Liquidity Levels in ICT terminology, while swing lows function as support levels, also known as Sellside Liquidity Levels. Traders can leverage these levels to plan their trade entries and exits.
Spot Reversal Patterns: Swing points can form key reversal patterns, such as double tops or bottoms, head and shoulders, and triangles. Recognizing these patterns can indicate potential trend reversals, enabling traders to adjust their strategies effectively.
Set Stop Loss and Take Profit Levels: In ICT teachings, swing levels represent price points with expected clusters of buy or sell orders. Traders can target these liquidity levels/pools for position accumulation or distribution, using swing points to define stop loss and take profit levels in their trades.
Overall, swing points provide valuable information about market dynamics and can assist traders in making more informed trading decisions.
🔹 Logic of Validation
The validation process in this script determines whether a detected market structure shift or break represents a confirmed breakout or a sweep.
The breakout is confirmed when the close price is significantly outside the deviation range of the last detected structural price. This deviation range is defined by the 17-period Average True Range (ATR), which creates a buffer around the detected market structure shift or break.
A sweep occurs when the price breaches the structural level within the deviation range but does not confirm a breakout. In this case, the label is updated to 'SWEEP.'
A visual box is created to represent the price range where the breakout or sweep occurs. If the validation process continues, the box is updated. This box visually highlights the price range involved in a sweep, helping traders identify liquidity events on the chart.
🔶 SETTINGS
The settings for Short-Term, Intermediate-Term, and Long-Term Structures are organized into groups, allowing users to customize swing points, market structures, and visual styles for each.
🔹 Structures
Swings and Size: Enables or disables the display of swing highs and lows, assigns icons to represent the structures, and adjusts the size of the icons.
Market Structures: Toggles the visibility of market structure lines.
Market Structure Validation: Enable or disable validation to distinguish true breakouts from liquidity sweeps.
Market Structure Labels: Displays or hides labels indicating the type of market structure.
Line Style and Width: Allows customization of the style and width of the lines representing market structures.
Swing and Line Colors: Provides options to adjust the colors of swing icons, market structure lines, and labels for better visualization.
🔶 RELATED SCRIPTS
Pure-Price-Action-Structures.
Market-Structures-(Intrabar).
